WorldWideScience

Sample records for automated demand response

  1. Home Network Technologies and Automating Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    McParland, Charles

    2009-12-01

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively

  2. Open Automated Demand Response Communications Specification (Version 1.0)

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

    2009-02-28

    The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

  3. Opportunities for Automated Demand Response in California Agricultural Irrigation

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-01

    Pumping water for agricultural irrigation represents a significant share of California’s annual electricity use and peak demand. It also represents a large source of potential flexibility, as farms possess a form of storage in their wetted soil. By carefully modifying their irrigation schedules, growers can participate in demand response without adverse effects on their crops. This report describes the potential for participation in demand response and automated demand response by agricultural irrigators in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use in California. Typical on-­farm controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Case studies of demand response programs in California and across the country are reviewed, and their results along with overall California demand estimates are used to estimate statewide demand response potential. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  4. Opportunities for Automated Demand Response in California Wastewater Treatment Facilities

    Energy Technology Data Exchange (ETDEWEB)

    Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wray, Craig [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-30

    Previous research over a period of six years has identified wastewater treatment facilities as good candidates for demand response (DR), automated demand response (Auto-­DR), and Energy Efficiency (EE) measures. This report summarizes that work, including the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy used and demand, as well as details of the wastewater treatment process. It also discusses control systems and automated demand response opportunities. Furthermore, this report summarizes the DR potential of three wastewater treatment facilities. In particular, Lawrence Berkeley National Laboratory (LBNL) has collected data at these facilities from control systems, submetered process equipment, utility electricity demand records, and governmental weather stations. The collected data were then used to generate a summary of wastewater power demand, factors affecting that demand, and demand response capabilities. These case studies show that facilities that have implemented energy efficiency measures and that have centralized control systems are well suited to shed or shift electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. In summary, municipal wastewater treatment energy demand in California is large, and energy-­intensive equipment offers significant potential for automated demand response. In particular, large load reductions were achieved by targeting effluent pumps and centrifuges. One of the limiting factors to implementing demand response is the reaction of effluent turbidity to reduced aeration at an earlier stage of the process. Another limiting factor is that cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities, limit a facility’s potential to participate in other DR activities.

  5. Enabling Automated Dynamic Demand Response: From Theory to Practice

    Energy Technology Data Exchange (ETDEWEB)

    Frincu, Marc; Chelmis, Charalampos; Aman, Saima; Saeed, Rizwan; Zois, Vasileios; Prasanna, Viktor

    2015-07-14

    Demand response (DR) is a technique used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In this paper we propose a system for achieving automated controlled DR in a heterogeneous environment. We present some of the main issues arising in building such a system, including privacy, customer satisfiability, reliability, and fast decision turnaround, with emphasis on the solutions we proposed. Based on the lessons we learned from empirical results we describe an integrated automated system for controlled DR on the USC microgrid. Results show that while on a per building per event basis the accuracy of our prediction and customer selection techniques varies, it performs well on average when considering several events and buildings.

  6. Open Automated Demand Response for Small Commerical Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  7. Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish; Koch, Ed; Hennage, Dan; Hernandez, John; Chiu, Albert; Sezgen, Osman; Goodin, John

    2009-11-06

    The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office building, and a bakery, are recruited into the pilot program. For each facility, hourly demand, and load curtailment potential are forecasted two days ahead and submitted to the CAISO the day before the operation as an available resource. These DR resources are optimized against all other generation resources in the CAISO ancillary service. Each facility is equipped with four-second real time telemetry equipment to ensure resource accountability and visibility to CAISO operators. When CAISO requests DR resources, PG&E's OpenADR (Open Automated DR) communications infrastructure is utilized to deliver DR signals to the facilities energy management and control systems (EMCS). The pre-programmed DR strategies are triggered without a human in the loop. This paper describes the automated system architecture and the flow of information to trigger and monitor the performance of the DR events. We outline the DR strategies at each of the participating facilities. At one site a real time electric measurement feedback loop is implemented to assure the delivery of CAISO dispatched demand reductions. Finally, we present results from each of the facilities and discuss findings.

  8. Northwest Open Automated Demand Response Technology Demonstration Project

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

    2010-03-17

    The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also

  9. A Distributed Intelligent Automated Demand Response Building Management System

    Energy Technology Data Exchange (ETDEWEB)

    Auslander, David [Univ. of California, Berkeley, CA (United States); Culler, David [Univ. of California, Berkeley, CA (United States); Wright, Paul [Univ. of California, Berkeley, CA (United States); Lu, Yan [Siemens Corporate Research Inc., Princeton, NJ (United States); Piette, Mary [Univ. of California, Berkeley, CA (United States)

    2013-03-31

    The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Response (openADR), Auto-­Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­to-­building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­ March) and a steam absorption chiller for use in the warm months (April-­October). Lighting in the open office areas is provided by direct-­indirect luminaries with Building Management System-­based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load

  10. Automated Dynamic Demand Response Implementation on a Micro-grid

    Energy Technology Data Exchange (ETDEWEB)

    Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos; Prasanna, Viktor K.

    2016-11-16

    In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability to dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.

  11. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2010-08-02

    This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

  12. Integrated Platform for Automated Sustainable Demand Response in Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Zois, Vassilis [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Computer Science; Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering; Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering

    2014-10-08

    Demand Response(DR) is a common practice used by utility providers to regulate energy demand. It is used at periods of high demand to minimize the peak to average consumption ratio. Several methods have been Demand Response(DR) is a common praon using information about the baseline consumption and the consumption during DR. Our goal is to provide a sustainable reduction to ensure the elimination of peaks in demand. The proposed system includes an adaptation mechanism for when the provided solution does not meet the DR requirements. We conducted a series of experiments using consumption data from a real life micro grid to evaluate the efficiency as well as the robustness of our solution.

  13. Opportunities for Automated Demand Response in California’s Dairy Processing Industry

    Energy Technology Data Exchange (ETDEWEB)

    Homan, Gregory K. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-30

    During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception that the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  14. Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards

    OpenAIRE

    Ghatikar, Girish

    2014-01-01

    This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California?s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated Demand Response (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard ...

  15. Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

    2009-05-11

    This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

  16. Evaluation of automated residential demand response with flat and dynamic pricing

    International Nuclear Information System (INIS)

    Swisher, Joel; Wang, Kitty; Stewart, Stewart

    2005-01-01

    This paper reviews the performance of two recent automated load management programs for residential customers of electric utilities in two American states. Both pilot programs have been run with about 200 participant houses each, and both programs have control populations of similar customers without the technology or program treatment. In both cases, the technology used in the pilot is GoodWatts, an advanced, two-way, real-time, comprehensive home energy management system. The purpose of each pilot is to determine the household kW reduction in coincident peak electric load from the energy management technology. Nevada Power has conducted a pilot program for Air-Conditioning Load Management (ACLM), in which customers are sent an electronic curtailment signal for three-hour intervals during times of maximum peak demand. The participating customers receive an annual incentive payment, but otherwise they are on a conventional utility tariff. In California, three major utilities are jointly conducting a pilot demonstration of an Automated Demand Response System (ADRS). Customers are on a time-of-use (ToU) tariff, which includes a critical peak pricing (CPP) element. During times of maximum peak demand, customers are sent an electronic price signal that is three times higher than the normal on-peak price. Houses with the automated GoodWatts technology reduced their demand in both the ACLM and the ADRS programs by about 50% consistently across the summer curtailment or super peak events, relative to homes without the technology or any load management program or tariff in place. The absolute savings were greater in the ACLM program, due to the higher baseline air conditioning loads in the hotter Las Vegas climate. The results suggest that either automated technology or dynamic pricing can deliver significant demand response in low-consumption houses. However, for high-consumption houses, automated technology can reduce load by a greater absolute kWh difference. Targeting

  17. Development and evaluation of fully automated demand response in large facilities

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

    2004-03-30

    This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing

  18. Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Mathieu, Johanna; Parrish, Kristen

    2010-05-14

    California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.

  19. Costs to Automate Demand Response - Taxonomy and Results from Field Studies and Programs

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schetrit, Oren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cheung, Iris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Li, Becky Z [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2017-07-31

    During the past decade, the technology to automate demand response (DR) in buildings and industrial facilities has advanced significantly. Automation allows rapid, repeatable, reliable operation. This study focuses on costs for DR automation in commercial buildings with some discussion on residential buildings and industrial facilities. DR automation technology relies on numerous components, including communication systems, hardware and software gateways, standards-based messaging protocols, controls and integration platforms, and measurement and telemetry systems. This report compares cost data from several DR automation programs and pilot projects, evaluates trends in the cost per unit of DR and kilowatts (kW) available from automated systems, and applies a standard naming convention and classification or taxonomy for system elements. Median costs for the 56 installed automated DR systems studied here are about $200/kW. The deviation around this median is large with costs in some cases being an order of magnitude great or less than the median. This wide range is a result of variations in system age, size of load reduction, sophistication, and type of equipment included in cost analysis. The costs to automate fast DR systems for ancillary services are not fully analyzed in this report because additional research is needed to determine the total cost to install, operate, and maintain these systems. However, recent research suggests that they could be developed at costs similar to those of existing hot-summer DR automation systems. This report considers installation and configuration costs and does include the costs of owning and operating DR automation systems. Future analysis of the latter costs should include the costs to the building or facility manager costs as well as utility or third party program manager cost.

  20. Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Kiliccote, Sila

    2010-06-02

    We present an Open Automated Demand Response Communications Specifications (OpenADR) data model capable of communicating real-time prices to electricity customers. We also show how the same data model could be used to for other types of dynamic pricing tariffs (including peak pricing tariffs, which are common throughout the United States). Customers participating in automated demand response programs with building control systems can respond to dynamic prices by using the actual prices as inputs to their control systems. Alternatively, prices can be mapped into"building operation modes," which can act as inputs to control systems. We present several different strategies customers could use to map prices to operation modes. Our results show that OpenADR can be used to communicate dynamic pricing within the Smart Grid and that OpenADR allows for interoperability with existing and future systems, technologies, and electricity markets.

  1. Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings in the Pacific Northwest

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Kiliccote, Sila; Dudley, Junqiao H.

    2011-11-11

    There are growing strains on the electric grid as cooling peaks grow and equipment ages. Increased penetration of renewables on the grid is also straining electricity supply systems and the need for flexible demand is growing. This paper summarizes results of a series of field test of automated demand response systems in large buildings in the Pacific Northwest. The objective of the research was two fold. One objective was to evaluate the use demand response automation technologies. A second objective was to evaluate control strategies that could change the electric load shape in both winter and summer conditions. Winter conditions focused on cold winter mornings, a time when the electric grid is often stressed. The summer test evaluated DR strategies in the afternoon. We found that we could automate both winter and summer control strategies with the open automated demand response communication standard. The buildings were able to provide significant demand response in both winter and summer events.

  2. Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Riess, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-01-02

    This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California's investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated Demand Response (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard and its many benefits. This study focused on OpenADR deployments and systems used by the California IOUs and included a summary of the OpenADR deployment from the U.S. Department of Energy-funded demonstration conducted by the Sacramento Municipal Utility District (SMUD). Lawrence Berkeley National Laboratory collected and analyzed data about OpenADR 1.0 deployments, categorized architectures, developed a data model mapping to understand the technical compatibility of each version, and compared the capabilities and features of the two specifications. The findings, for the first time, provided evidence of the total enabled load shed and average first cost for system enablement in the IOU and SMUD service territories. The OpenADR 2.0a profile specification semantically supports AutoDR system architectures and data propagation with a testing and certification program that promotes interoperability, scaled deployments by multiple vendors, and provides additional features that support future services.

  3. Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Page, Janie; Kiliccote, Sila; Dudley, Junqiao Han; Piette, Mary Ann; Chiu, Albert K.; Kellow, Bashar; Koch, Ed; Lipkin, Paul

    2011-07-01

    Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated Demand Response (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demand response for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

  4. Automated Demand Response: The Missing Link in the Electricity Value Chain

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

    2009-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies

  5. Automated Demand Response: The Missing Link in the Electricity Value Chain

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee; Rhyne, Ivin; Piette, Mary Ann; Thompson, Lisa; Lekov, Alex

    2008-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to Open

  6. Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report

    Energy Technology Data Exchange (ETDEWEB)

    Lekov, Alex; Thompson, Lisa; McKane, Aimee; Song, Katherine; Piette, Mary Ann

    2009-04-01

    This report summarizes the Lawrence Berkeley National Laboratory?s research to date in characterizing energy efficiency and automated demand response opportunities for wastewater treatment facilities in California. The report describes the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy use and demand, as well as details of the wastewater treatment process. It also discusses control systems and energy efficiency and automated demand response opportunities. In addition, several energy efficiency and load management case studies are provided for wastewater treatment facilities.This study shows that wastewater treatment facilities can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for automated demand response at little additional cost. These improved controls may prepare facilities to be more receptive to open automated demand response due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

  7. Effects of Granular Control on Customers’ Perspective and Behavior with Automated Demand Response Systems

    Energy Technology Data Exchange (ETDEWEB)

    Schetrit, Oren; Kim, Joyce; Yin, Rongxin; Kiliccote, Sila

    2014-08-01

    Automated demand response (Auto-DR) is expected to close the loop between buildings and the grid by providing machine-to-machine communications to curtail loads without the need for human intervention. Hence, it can offer more reliable and repeatable demand response results to the grid than the manual approach and make demand response participation a hassle-free experience for customers. However, many building operators misunderstand Auto-DR and are afraid of losing control over their building operation. To ease the transition from manual to Auto-DR, we designed and implemented granular control of Auto-DR systems so that building operators could modify or opt out of individual load-shed strategies whenever they wanted. This paper reports the research findings from this effort demonstrated through a field study in large commercial buildings located in New York City. We focused on (1) understanding how providing granular control affects building operators’ perspective on Auto-DR, and (2) evaluating the usefulness of granular control by examining their interaction with the Auto-DR user interface during test events. Through trend log analysis, interviews, and surveys, we found that: (1) the opt-out capability during Auto-DR events can remove the feeling of being forced into load curtailments and increase their willingness to adopt Auto-DR; (2) being able to modify individual load-shed strategies allows flexible Auto-DR participation that meets the building’s changing operational requirements; (3) a clear display of automation strategies helps building operators easily identify how Auto-DR is functioning and can build trust in Auto-DR systems.

  8. Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila

    2013-10-01

    Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

  9. Development and Demonstration of the Open Automated Demand Response Standard for the Residential Sector

    Energy Technology Data Exchange (ETDEWEB)

    Herter, Karen; Rasin, Josh; Perry, Tim

    2009-11-30

    The goal of this study was to demonstrate a demand response system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated Demand Response (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricing information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.

  10. OPPORTUNITIES FOR AUTOMATED DEMAND RESPONSE IN CALIFORNIA’S DAIRY PROCESSING INDUSTRY:

    OpenAIRE

    Homan, Gregory K.; Aghajanzadeh, Arian; McKane, Aimee

    2015-01-01

    During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industri...

  11. Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Faulkner, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-12-20

    This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities The average baseline demand at the Southeast facility was approximately 4 MW. During the rainy season (October-March) the facility treated 40% more wastewater than the dry season, but demand only increased by 4%. Submetering of the facility's lift pumps and centrifuges predicted load shifts capabilities of 154 kW and 86 kW, respectively, with large lift pump shifts in the rainy season. Analysis of demand data during maintenance events confirmed the magnitude of these possible load shifts, and indicated other areas of the facility with demand response potential. Load sheds were seen to be possible by shutting down a portion of the facility's aeration trains (average shed of 132 kW). Load shifts were seen to be possible by shifting operation of centrifuges, the gravity belt thickener, lift pumps, and external pump stations These load shifts were made possible by the storage capabilities of the facility and of the city's sewer system. Large load reductions (an average of 2,065 kW) were seen from operating the cogeneration unit, but normal practice is continuous operation, precluding its use for demand response. The study also identified potential demand response opportunities that warrant further study: modulating variable-demand aeration loads, shifting

  12. Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment

    Science.gov (United States)

    Adika, Christopher Otieno

    The advancement of renewable energy technologies and the deregulation of the electricity market have seen the emergence of Demand response (DR) programs. Demand response is a cost-effective load management strategy which enables the electricity suppliers to maintain the integrity of the power grid during high peak periods, when the customers' electrical load is high. DR programs are designed to influence electricity users to alter their normal consumption patterns by offering them financial incentives. A well designed incentive-based DR scheme that offer competitive electricity pricing structure can result in numerous benefits to all the players in the electricity market. Lower power consumption during peak periods will significantly enhance the robustness of constrained networks by reducing the level of power of generation and transmission infrastructure needed to provide electric service. Therefore, this will ease the pressure of building new power networks as we avoiding costly energy procurements thereby translating into huge financial savings for the power suppliers. Peak load reduction will also reduce the inconveniences suffered by end users as a result of brownouts or blackouts. Demand response will also drastically lower the price peaks associated with wholesale markets. This will in turn reduce the electricity costs and risks for all the players in the energy market. Additionally, DR is environmentally friendly since it enhances the flexibility of the power grid through accommodation of renewable energy resources. Despite its many benefits, DR has not been embraced by most electricity networks. This can be attributed to the fact that the existing programs do not provide enough incentives to the end users and, therefore, most electricity users are not willing to participate in them. To overcome these challenges, most utilities are coming up with innovative strategies that will be more attractive to their customers. Thus, this dissertation presents various

  13. Optimized Energy Management of a Single-House Residential Micro-Grid With Automated Demand Response

    DEFF Research Database (Denmark)

    Anvari-Moghaddam, Amjad; Monsef, Hassan; Rahimi-Kian, Ashkan

    2015-01-01

    In this paper, an intelligent multi-objective energy management system (MOEMS) is proposed for applications in residential LVAC micro-grids where households are equipped with smart appliances, such as washing machine, dishwasher, tumble dryer and electric heating and they have the capability to t...... to reduce residential energy use and improve the user’s satisfaction degree by optimal management of demand/generation sides.......In this paper, an intelligent multi-objective energy management system (MOEMS) is proposed for applications in residential LVAC micro-grids where households are equipped with smart appliances, such as washing machine, dishwasher, tumble dryer and electric heating and they have the capability...... to take part in demand response (DR) programs. The superior performance and efficiency of the proposed system is studied through several scenarios and case studies and validated in comparison with the conventional models. The simulation results demonstrate that the proposed MOEMS has the capability...

  14. Automation of energy demand forecasting

    Science.gov (United States)

    Siddique, Sanzad

    Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

  15. Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Lisa; Lekov, Alex; McKane, Aimee; Piette, Mary Ann

    2010-08-20

    This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions of 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities.

  16. Research on Simulation Requirements and Business Architecture of Automated Demand Response in Power Sales Side Market Liberalization

    Science.gov (United States)

    Liu, Yiqun; Zhou, Pengcheng; Zeng, Ming; Chen, Songsong

    2018-01-01

    With the gradual reform of the electricity market, the power sale side liberalization has become the focus of attention as the key task of reform. The open power market provides a good environment for DR (Demand Response). It is of great significance to research the simulation requirements and business architecture of ADR (Automatic Demand Response) in power sale side market liberalization. Firstly, this paper analyzes the simulation requirements of ADR. Secondly, it analyzes the influence factors that the business development of ADR from five aspects after power sale side market liberalization. Finally, Based on ADR technology support system, the business architecture of ADR after power sale side market liberalization is constructed.

  17. Market transformation lessons learned from an automated demand response test in the Summer and Fall of 2003

    Energy Technology Data Exchange (ETDEWEB)

    Shockman, Christine; Piette, Mary Ann; ten Hope, Laurie

    2004-08-01

    A recent pilot test to enable an Automatic Demand Response system in California has revealed several lessons that are important to consider for a wider application of a regional or statewide Demand Response Program. The six facilities involved in the site testing were from diverse areas of our economy. The test subjects included a major retail food marketer and one of their retail grocery stores, financial services buildings for a major bank, a postal services facility, a federal government office building, a state university site, and ancillary buildings to a pharmaceutical research company. Although these organizations are all serving diverse purposes and customers, they share some underlying common characteristics that make their simultaneous study worthwhile from a market transformation perspective. These are large organizations. Energy efficiency is neither their core business nor are the decision makers who will enable this technology powerful players in their organizations. The management of buildings is perceived to be a small issue for top management and unless something goes wrong, little attention is paid to the building manager's problems. All of these organizations contract out a major part of their technical building operating systems. Control systems and energy management systems are proprietary. Their systems do not easily interact with one another. Management is, with the exception of one site, not electronically or computer literate enough to understand the full dimensions of the technology they have purchased. Despite the research team's development of a simple, straightforward method of informing them about the features of the demand response program, they had significant difficulty enabling their systems to meet the needs of the research. The research team had to step in and work directly with their vendors and contractors at all but one location. All of the participants have volunteered to participate in the study for altruistic

  18. Ontario demand response scenarios

    International Nuclear Information System (INIS)

    Rowlands, I.H.

    2005-09-01

    Strategies for demand management in Ontario were examined via 2 scenarios for a commercial/institutional building with a normal summertime peak load of 300 kW between 14:00 and 18:00 during a period of high electricity demand and high electricity prices. The first scenario involved the deployment of a 150 kW on-site generator fuelled by either diesel or natural gas. The second scenario involved curtailing load by 60 kW during the same periods. Costs and benefits of both scenarios were evaluated for 3 groups: consumers, system operators and society. Benefits included electricity cost savings, deferred transmission capacity development, lower system prices for electricity, as well as environmental changes, economic development, and a greater sense of corporate social responsibility. It was noted that while significant benefits were observed for all 3 groups, they were not substantial enough to encourage action, as the savings arising from deferred generation capacity development do not accrue to individual players. The largest potential benefit was identified as lower prices, spread across all users of electricity in Ontario. It was recommended that representative bodies cooperate so that the system-wide benefits can be reaped. It was noted that if 10 municipal utilities were able to have 250 commercial or institutional customers engaged in distributed response, then a total peak demand reduction of 375 MW could be achieved, representing more than 25 per cent of Ontario's target for energy conservation. It was concluded that demand response often involves the investment of capital and new on-site procedures, which may affect reactions to various incentives. 78 refs., 10 tabs., 5 figs

  19. Demand response in energy markets

    International Nuclear Information System (INIS)

    Skytte, K.; Birk Mortensen, J.

    2004-11-01

    Improving the ability of energy demand to respond to wholesale prices during critical periods of the spot market can reduce the total costs of reliably meeting demand, and the level and volatility of the prices. This fact has lead to a growing interest in the short-run demand response. There has especially been a growing interest in the electricity market where peak-load periods with high spot prices and occasional local blackouts have recently been seen. Market concentration at the supply side can result in even higher peak-load prices. Demand response by shifting demand from peak to base-load periods can counteract the market power in the peak-load. However, demand response has so far been modest since the current short-term price elasticity seems to be small. This is also the case for related markets, for example, green certificates where the demand is determined as a percentage of the power demand, or for heat and natural gas markets. This raises a number of interesting research issues: 1) Demand response in different energy markets, 2) Estimation of price elasticity and flexibility, 3) Stimulation of demand response, 4) Regulation, policy and modelling aspects, 5) Demand response and market power at the supply side, 6) Energy security of supply, 7) Demand response in forward, spot, ancillary service, balance and capacity markets, 8) Demand response in deviated markets, e.g., emission, futures, and green certificate markets, 9) Value of increased demand response, 10) Flexible households. (BA)

  20. Strategies for Demand Response in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-06-20

    This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

  1. Voltage Controlled Dynamic Demand Response

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Mahat, Pukar

    2013-01-01

    Future power system is expected to be characterized by increased penetration of intermittent sources. Random and rapid fluctuations in demands together with intermittency in generation impose new challenges for power balancing in the existing system. Conventional techniques of balancing by large...... central or dispersed generations might not be sufficient for future scenario. One of the effective methods to cope with this scenario is to enable demand response. This paper proposes a dynamic voltage regulation based demand response technique to be applied in low voltage (LV) distribution feeders....... An adaptive dynamic model has been developed to determine composite voltage dependency of an aggregated load on feeder level. Following the demand dispatch or control signal, optimum voltage setting at the LV substation is determined based on the voltage dependency of the load. Furthermore, a new technique...

  2. Demand Response Spinning Reserve Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

    2007-05-01

    The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

  3. Demand Response Resource Quantification with Detailed Building Energy Models

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Elaine; Horsey, Henry; Merket, Noel; Stoll, Brady; Nag, Ambarish

    2017-04-03

    Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.

  4. Demand Response in Smart Grids

    DEFF Research Database (Denmark)

    Hansen, Jacob; Knudsen, Jesper Viese; Annaswamy, Anuradha M.

    2014-01-01

    In recent decades, moves toward higher integration of Renewable Energy Resources have called for fundamental changes in both the planning and operation of the overall power grid. One such change is the incorporation of Demand Response (DR), the process by which consumers can adjust their demand...... in a flexible manner. This paper presents a survey of various aspects of DR including the different types of participants, as well as the underlying challenges and the overall potential of DR when it comes to large-scale implementations. Benefits of DR as reported in the literature for performance metrics...

  5. Demand Response Valuation Frameworks Paper

    Energy Technology Data Exchange (ETDEWEB)

    Heffner, Grayson

    2009-02-01

    While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

  6. Progress toward Producing Demand-Response-Ready Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Hammerstrom, Donald J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sastry, Chellury [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2009-12-01

    This report summarizes several historical and ongoing efforts to make small electrical demand-side devices like home appliances more responsive to the dynamic needs of electric power grids. Whereas the utility community often reserves the word demand response for infrequent 2 to 6 hour curtailments that reduce total electrical system peak load, other beneficial responses and ancillary services that may be provided by responsive electrical demand are of interest. Historically, demand responses from the demand side have been obtained by applying external, retrofitted, controlled switches to existing electrical demand. This report is directed instead toward those manufactured products, including appliances, that are able to provide demand responses as soon as they are purchased and that require few, or no, after-market modifications to make them responsive to needs of power grids. Efforts to be summarized include Open Automated Demand Response, the Association of Home Appliance Manufacturer standard CHA 1, a simple interface being developed by the U-SNAP Alliance, various emerging autonomous responses, and the recent PinBus interface that was developed at Pacific Northwest National Laboratory.

  7. Real-Time Implementation of Demand Response Programs Based on Open ADR Technology

    OpenAIRE

    Omid Abrishambaf; Pedro Faria; Zita Vale

    2017-01-01

    In the Demand Response (DR) concepts, we witness several barriers that need to be addressed such as, data transferring from promoting entities to demand side. The Open Automated Demand Response (Open ADR) standard specification is a solution for overcoming these barriers. This PhD work proposes a real business model for DR implementation based on Open ADR technology.

  8. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  9. Evaluation of Representative Smart Grid Investment Project Technologies: Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Jason C.; Prakash Kumar, Nirupama; Bonebrake, Christopher A.

    2012-02-14

    This document is one of a series of reports estimating the benefits of deploying technologies similar to those implemented on the Smart Grid Investment Grant (SGIG) projects. Four technical reports cover the various types of technologies deployed in the SGIG projects, distribution automation, demand response, energy storage, and renewables integration. A fifth report in the series examines the benefits of deploying these technologies on a national level. This technical report examines the impacts of a limited number of demand response technologies and implementations deployed in the SGIG projects.

  10. Demand Response on domestic thermostatically controlled loads

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam

    Electricity has become an inevitable part of human life in present day world. In the past two centuries, the electric power system has undergone a lot of changes. Due to the awareness about the adverse impact of the fossil fuels, the power industry is adopting green and sustainable energy sources...... with renewable energy sources, the production cannot be adjusted to match the demand due to the fluctuating nature of the renewable energy sources. Therefore, the demand has to be adjusted to match the power production. The concept of adjusting the demand to match the production is called demand response...... prediction strategy is developed to predict the refrigerator temperature and to estimate the flexibility available for demand response activation. A field experiment with refrigerators is conducted to study secondary frequency control using demand response activation on TCLs. The response time and the ramp...

  11. Lighting Systems Control for Demand Response

    NARCIS (Netherlands)

    Husen, S.A.; Pandharipande, A.; Tolhuizen, L.M.G.; Wang, Y.; Zhao, M.

    2012-01-01

    Lighting is a major part of energy consumption in buildings. Lighting systems will thus be one of the important component systems of a smart grid for dynamic load management services like demand response.In the scenario considered in this paper, under a demand response request, lighting systems in a

  12. Addressing Energy Demand through Demand Response. International Experiences and Practices

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Bo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ni, Chun Chun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Martin, Phil [Enernoc, Inc., Boston, MA (United States); Wikler, Greg

    2012-06-01

    Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

  13. Autonomous Demand Response for Primary Frequency Regulation

    Energy Technology Data Exchange (ETDEWEB)

    Donnelly, Matt [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Trudnowski, Daniel J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mattix, S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Dagle, Jeffery E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-01-01

    The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology.

  14. The alchemy of demand response: turning demand into supply

    Energy Technology Data Exchange (ETDEWEB)

    Rochlin, Cliff

    2009-11-15

    Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

  15. Option value of electricity demand response

    Energy Technology Data Exchange (ETDEWEB)

    Sezgen, Osman; Goldman, C.A. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720 (United States); Krishnarao, P. [Citigroup Energy Inc., 1301 Fannin St, Houston, TX 77002 (United States)

    2007-02-15

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  16. Option value of electricity demand response

    International Nuclear Information System (INIS)

    Sezgen, Osman; Goldman, C.A.; Krishnarao, P.

    2007-01-01

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  17. Automated Demand Response for Energy Sustainability

    Science.gov (United States)

    2015-05-01

    electric loads for use in DR programs include HVAC equipment, lighting, water pumping, and other miscellaneous motor loads. Figure 5 shows a high...100 Appendix L: Comparative Analysis: Bldg 254/271 HVAC Controls Project ............................ 102 Appendix M: Comparative...Security Technology Certification Program FEMP Federal Energy Management Program FERC Federal Energy Regulatory Commission HVAC Heating, ventilation

  18. Coordination of Energy Efficiency and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  19. A Novel Technique to Enhance Demand Responsiveness

    DEFF Research Database (Denmark)

    Farashbashi-Astaneh, Seyed-Mostafa; Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte

    2015-01-01

    In this study, a new pricing approach is proposed to increase demand responsiveness. The proposed approach considers two well-known demand side management techniques, namely peak shaving and valley filling. This is done by incentivising consumers by magnifying price difference between peak and off...

  20. Resilience Evaluation of Demand Response as Spinning Reserve under Cyber-Physical Threats

    Directory of Open Access Journals (Sweden)

    Anas AlMajali

    2016-12-01

    Full Text Available In the future, automated demand response mechanisms will be used as spinning reserve. Demand response in the smart grid must be resilient to cyber-physical threats. In this paper, we evaluate the resilience of demand response when used as spinning reserve in the presence of cyber-physical threats. We quantify this evaluation by correlating the stability of the system in the presence of attacks measured by system frequency (Hz and attack level measured by the amount of load (MW that responds to the demand response event. The results demonstrate the importance of anticipating the dependability of demand response before it can be relied upon as spinning reserve.

  1. Market design for rapid demand response

    DEFF Research Database (Denmark)

    Nielsen, Kurt; Tamirat, Tseganesh Wubale

    it simple to involve the endusers in advance and to activate demand response immediately. The collective solution is analyzed and economic simulations are conducted for the case of Kenya. Kenya has been su ering from unreliable electricity supply for many years and companies and households have learned......We suggest a market design for rapid demand response in electricity markets. The solution consists of remotely controlled switches, meters, forecasting models as well as a flexible auction market to set prices and select endusers job by job. The auction market motivates truth-telling and makes...... to adjust by investments in backup generators. We focus on turning the many private backup generators into a demand response system. The economic simulation focuses on possible distortion introduced by various ways of splitting the generated surplus from the demand response system. An auction run instantly...

  2. Hawaiian Electric Company Demand Response Roadmap Project

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-12

    The objective of this project was to develop a “roadmap” to guide the Hawaiian Electric Company (HECO) demand response (DR) planning and implementation in support of the Hawaii Clean Energy Initiative (HCEI) 70% clean energy goal by 2030.

  3. Demand Response and Energy Storage Integration Study

    Energy Technology Data Exchange (ETDEWEB)

    Ookie Ma, Kerry Cheung

    2016-03-01

    Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational value in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.

  4. Does responsive pricing smooth demand shocks?

    OpenAIRE

    Pascal, Courty; Mario, Pagliero

    2011-01-01

    Using data from a unique pricing experiment, we investigate Vickrey’s conjecture that responsive pricing can be used to smooth both predictable and unpredictable demand shocks. Our evidence shows that increasing the responsiveness of price to demand conditions reduces the magnitude of deviations in capacity utilization rates from a pre-determined target level. A 10 percent increase in price variability leads to a decrease in the variability of capacity utilization rates between...

  5. Opportunities, Barriers and Actions for Industrial Demand Response in California

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

    2008-01-31

    In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated

  6. Demand response in a market environment

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler

    This thesis addresses the design, deployment and benefits of demand response in a market environment. Demand response is consumption that can be controlled by an external stimulus in the power system. Flexible consumption is a useful tool for absorbing volatile power from renewable sources like...... wind power and photovoltaics, and dealing with decentralised activity like electric vehicle charging. Without flexible consumption or other new technologies like storage, there will be several occasions of surplus or deficit of generation to meet the demand of the future, sometimes expected...... and sometimes not, that will lead to power system failure. The type of demand response investigated is consumption controlled by indirect means, like an electricity price. Initially, algorithms responding to real-time electricity prices are researched and benchmarked according to comfort and cost. After...

  7. Refrigerated Warehouse Demand Response Strategy Guide

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Doug [VaCom Technologies, San Luis Obispo, CA (United States); Castillo, Rafael [VaCom Technologies, San Luis Obispo, CA (United States); Larson, Kyle [VaCom Technologies, San Luis Obispo, CA (United States); Dobbs, Brian [VaCom Technologies, San Luis Obispo, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-11-01

    This guide summarizes demand response measures that can be implemented in refrigerated warehouses. In an appendix, it also addresses related energy efficiency opportunities. Reducing overall grid demand during peak periods and energy consumption has benefits for facility operators, grid operators, utility companies, and society. State wide demand response potential for the refrigerated warehouse sector in California is estimated to be over 22.1 Megawatts. Two categories of demand response strategies are described in this guide: load shifting and load shedding. Load shifting can be accomplished via pre-cooling, capacity limiting, and battery charger load management. Load shedding can be achieved by lighting reduction, demand defrost and defrost termination, infiltration reduction, and shutting down miscellaneous equipment. Estimation of the costs and benefits of demand response participation yields simple payback periods of 2-4 years. To improve demand response performance, it’s suggested to install air curtains and another form of infiltration barrier, such as a rollup door, for the passageways. Further modifications to increase efficiency of the refrigeration unit are also analyzed. A larger condenser can maintain the minimum saturated condensing temperature (SCT) for more hours of the day. Lowering the SCT reduces the compressor lift, which results in an overall increase in refrigeration system capacity and energy efficiency. Another way of saving energy in refrigerated warehouses is eliminating the use of under-floor resistance heaters. A more energy efficient alternative to resistance heaters is to utilize the heat that is being rejected from the condenser through a heat exchanger. These energy efficiency measures improve efficiency either by reducing the required electric energy input for the refrigeration system, by helping to curtail the refrigeration load on the system, or by reducing both the load and required energy input.

  8. Demand Response as a System Reliability Resource

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joseph H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Lewis, Nancy Jo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Watson, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Auslander, David [Univ. of California, Berkeley, CA (United States); Paprotny, Igor [Univ. of California, Berkeley, CA (United States); Makarov, Yuri [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-12-31

    The Demand Response as a System Reliability Resource project consists of six technical tasks: • Task 2.1. Test Plan and Conduct Tests: Contingency Reserves Demand Response (DR) Demonstration—a pioneering demonstration of how existing utility load-management assets can provide an important electricity system reliability resource known as contingency reserve. • Task 2.2. Participation in Electric Power Research Institute (EPRI) IntelliGrid—technical assistance to the EPRI IntelliGrid team in developing use cases and other high-level requirements for the architecture. • Task 2.3. Research, Development, and Demonstration (RD&D) Planning for Demand Response Technology Development—technical support to the Public Interest Energy Research (PIER) Program on five topics: Sub-task 1. PIER Smart Grid RD&D Planning Document; Sub-task 2. System Dynamics of Programmable Controllable Thermostats; Sub-task 3. California Independent System Operator (California ISO) DR Use Cases; Sub-task 4. California ISO Telemetry Requirements; and Sub-task 5. Design of a Building Load Data Storage Platform. • Task 2.4. Time Value of Demand Response—research that will enable California ISO to take better account of the speed of the resources that it deploys to ensure compliance with reliability rules for frequency control. • Task 2.5. System Integration and Market Research: Southern California Edison (SCE)—research and technical support for efforts led by SCE to conduct demand response pilot demonstrations to provide a contingency reserve service (known as non-spinning reserve) through a targeted sub-population of aggregated residential and small commercial customers enrolled in SCE’s traditional air conditioning (AC) load cycling program, the Summer Discount Plan. • Task 2.6. Demonstrate Demand Response Technologies: Pacific Gas and Electric (PG&E)—research and technical support for efforts led by PG&E to conduct a demand response pilot demonstration to provide non

  9. Modelling of demand response and market power

    International Nuclear Information System (INIS)

    Kristoffersen, B.B.; Donslund, B.; Boerre Eriksen, P.

    2004-01-01

    Demand-side flexibility and demand response to high prices are prerequisites for the proper functioning of the Nordic power market. If the consumers are unwilling to respond to high prices, the market may fail the clearing, and this may result in unwanted forced demand disconnections. Being the TSO of Western Denmark, Eltra is responsible of both security of supply and the design of the power market within its area. On this basis, Eltra has developed a new mathematical model tool for analysing the Nordic wholesale market. The model is named MARS (MARket Simulation). The model is able to handle hydropower and thermal production, nuclear power and wind power. Production, demand and exchanges modelled on an hourly basis are new important features of the model. The model uses the same principles as Nord Pool (The Nordic Power Exchange), including the division of the Nordic countries into price areas. On the demand side, price elasticity is taken into account and described by a Cobb-Douglas function. Apart from simulating perfect competition markets, particular attention has been given to modelling imperfect market conditions, i.e. exercise of market power on the supply side. Market power is simulated by using game theory, including the Nash equilibrium concept. The paper gives a short description of the MARS model. Besides, focus is on the application of the model in order to illustrate the importance of demand response in the Nordic market. Simulations with different values of demand elasticity are compared. Calculations are carried out for perfect competition and for the situation in which market power is exercised by the large power producers in the Nordic countries (oligopoly). (au)

  10. Analyses of demand response in Denmark

    International Nuclear Information System (INIS)

    Moeller Andersen, F.; Grenaa Jensen, S.; Larsen, Helge V.; Meibom, P.; Ravn, H.; Skytte, K.; Togeby, M.

    2006-10-01

    Due to characteristics of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many consumers do not experience corresponding variations in the price they pay for consuming electricity. The topic of this report is: are consumers willing and able to respond to short-term variations in electricity prices, and if so, what is the social benefit of consumers doing so? Taking Denmark and the Nord Pool market as a case, the report focuses on what is known as short-term consumer flexibility or demand response in the electricity market. With focus on market efficiency, efficient allocation of resources and security of supply, the report describes demand response from a micro-economic perspective and provides empirical observations and case studies. The report aims at evaluating benefits from demand response. However, only elements contributing to an overall value are presented. In addition, the analyses are limited to benefits for society, and costs of obtaining demand response are not considered. (au)

  11. Use of demand response in electricity markets

    DEFF Research Database (Denmark)

    Singh, Sri Niwas; Østergaard, Jacob

    2010-01-01

    Demand response (DR) can provide sufficient measure, if implemented successfully, to provide economic, secure and stable supply to the customers even under the variability of the generated output from renewable energy source such as wind and solar. However, there are several issues to be analyzed...

  12. Demand Responsive Lighting: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03

    The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts

  13. Estimating Reduced Consumption for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States); Saeed, Muhammad Rizwan [Univ. of Southern California, Los Angeles, CA (United States); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-01-30

    Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in response to a request sent from the utility whenever it anticipates a peak in demand. To successfully plan and implement demand response, the utility requires reliable estimate of reduced consumption during DR. This also helps in optimal selection of consumers and curtailment strategies during DR. While much work has been done on predicting normal consumption, reduced consumption prediction is an open problem that is under-studied. In this paper, we introduce and formalize the problem of reduced consumption prediction, and discuss the challenges associated with it. We also describe computational methods that use historical DR data as well as pre-DR conditions to make such predictions. Our experiments are conducted in the real-world setting of a university campus microgrid, and our preliminary results set the foundation for more detailed modeling.

  14. Social implications of residential demand response in cool temperate climates

    International Nuclear Information System (INIS)

    Darby, Sarah J.; McKenna, Eoghan

    2012-01-01

    Residential electrical demand response (DR) offers the prospect of reducing the environmental impact of electricity use, and also the supply costs. However, the relatively small loads and numerous actors imply a large effort: response ratio. Residential DR may be an essential part of future smart grids, but how viable is it in the short to medium term? This paper reviews some DR concepts, then evaluates the propositions that households in cool temperate climates will be in a position to contribute to grid flexibility within the next decade, and that that they will allow some automated load control. Examples of demand response from around the world are discussed in order to assess the main considerations for cool climates. Different tariff types and forms of control are assessed in terms of what is being asked of electricity users, with a focus on real-time pricing and direct load control in energy systems with increasingly distributed resources. The literature points to the significance of thermal loads, supply mix, demand-side infrastructure, market regulation, and the framing of risks and opportunities associated with DR. In concentrating on social aspects of residential demand response, the paper complements the body of work on technical and economic potential. - Highlights: ► Demand response implies major change in governance of electricity systems. ► Households in cool temperate climates can be flexible, mainly with thermal loads. ► DR requires simple tariffs, appropriate enabling technology, education, and feedback. ► Need to test consumer acceptance of DR in specific conditions. ► Introduce tariffs with technologies e.g., TOU tariff plus DLC with electric vehicles.

  15. Using automated planning for sensorweb response

    Science.gov (United States)

    Chien, Steve; Davies, Ashley; Tran, Daniel; Cichy, Benjamin; Rabideau, Gregg; Castano, Rebecca; Sherwood, Rob; Jones, Jeremy; Grosvenor, Sandy; Mandl, Dan; hide

    2004-01-01

    This paper describes efforts to link these science event detection systems with an automated response system to retarget remote sensing assets to observe these important but transient science events. Of course, automated mission planning is a key element of the overall tracking and response system. We describe the current prototype system which utilizes the Earth Observing One spacecraft, MODIS flying on Terra and Aqua, QuickSCAT, GOES, and AVHRR platforms as well as future plans for expansion.

  16. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank; McKane, Aimee; Olsen, Daniel

    2011-06-14

    Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

  17. Laboratory Testing of Demand-Response Enabled Household Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  18. Laboratory Testing of Demand-Response Enabled Household Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jin, X. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Earle, L. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  19. Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

    Energy Technology Data Exchange (ETDEWEB)

    Hummon, Marissa [National Renewable Energy Lab. (NREL), Golden, CO (United States); Palchak, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olsen, Daniel J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Matson, Nance [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rose, Cody [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ma, Ookie [U.S. Dept. of Energy, Washington, DC (United States)

    2013-12-01

    This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multi-national-laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associatedmarkets and institutions. This report implements DR resources in the commercial production cost model PLEXOS.

  20. Smart Demand Response Based on Smart Homes

    Directory of Open Access Journals (Sweden)

    Jingang Lai

    2015-01-01

    Full Text Available Smart homes (SHs are crucial parts for demand response management (DRM of smart grid (SG. The aim of SHs based demand response (DR is to provide a flexible two-way energy feedback whilst (or shortly after the consumption occurs. It can potentially persuade end-users to achieve energy saving and cooperate with the electricity producer or supplier to maintain balance between the electricity supply and demand through the method of peak shaving and valley filling. However, existing solutions are challenged by the lack of consideration between the wide application of fiber power cable to the home (FPCTTH and related users’ behaviors. Based on the new network infrastructure, the design and development of smart DR systems based on SHs are related with not only functionalities as security, convenience, and comfort, but also energy savings. A new multirouting protocol based on Kruskal’s algorithm is designed for the reliability and safety of the SHs distribution network. The benefits of FPCTTH-based SHs are summarized at the end of the paper.

  1. Automated leak localization performance without detailed demand distribution data

    NARCIS (Netherlands)

    Moors, Janneke; Scholten, L.; van der Hoek, J.P.; den Besten, J.

    2018-01-01

    Automatic leak localization has been suggested to reduce the time and personnel efforts needed to localize
    (small) leaks. Yet, the available methods require a detailed demand distribution model for successful
    calibration and good leak localization performance. The main aim of this work was

  2. Demand response in Indian electricity market

    International Nuclear Information System (INIS)

    Siddiqui, Md Zakaria; Maere d'Aertrycke, Gauthier de; Smeers, Yves

    2012-01-01

    This paper outlines a methodology for implementing cost of service regulation in retail market for electricity in India when wholesale market is liberalised and operates through an hourly spot market. As in a developing country context political considerations make tariff levels more important than supply security, satisfying the earmarked level of demand takes a back seat. Retail market regulators are often forced by politicians to keep the retail tariff at suboptimal level. This imposes budget constraint on distribution companies to procure electricity that it requires to meet the earmarked level of demand. This is the way demand response is introduced in the system and has its impact on spot market prices. We model such a situation of not being able to serve the earmarked demand as disutility to the regulator which has to be minimised and we compute associated equilibrium. This results in systematic mechanism for cutting loads. We find that even a small cut in ability of the distribution companies to procure electricity from the spot market has profound impact on the prices in the spot market. - Highlights: ► Modelling the impact of retail tariff in different states on spot prices of electricity in India. ► Retail tariffs are usually fixed below appropriate levels by states due to political reasons. ► Due to revenue constraint distribution utility withdraws demand from spot market in peak hours. ► This adversely affects the scarcity rent of generators and subsequently future investment. ► We show possibility of strategic behaviour among state level regulators in setting retail tariff.

  3. Assessing the Control Systems Capacity for Demand Response in California Industries

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; McKane, Aimee; Goli, Sasank; Therkelsen, Peter; Olsen, Daniel

    2012-01-18

    California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This,study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with

  4. Retail Demand Response in Southwest Power Pool

    Energy Technology Data Exchange (ETDEWEB)

    Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

    2009-01-30

    In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region. LBNL conducted a detailed survey of existing DR programs and dynamic pricing tariffs administered by SPP's member utilities. Survey respondents were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g. seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. Nearly all of the 30 load-serving entities in SPP responded to the survey. Of this group, fourteen SPP member utilities administer 36 DR programs, five dynamic pricing tariffs, and six voluntary customer response initiatives. These existing DR programs and dynamic pricing tariffs have a peak demand reduction potential of 1,552 MW. Other major findings of this study are: o About 81percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;14percent. o Arkansas accounts for ~;;50percent of the DR resources in the SPP footprint; these DR resources are primarily managed by cooperatives. o Publicly-owned cooperatives accounted for 54percent of the existing DR resources

  5. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-11-30

    Demand-side frequency control can complement traditional generator controls to maintain the stability of large electric systems in the face of rising uncertainty and variability associated with renewable energy resources. This report presents a hierarchical frequency-based load control strategy that uses a supervisor to flexibly adjust control gains that a population of end-use loads respond to in a decentralized manner to help meet the NERC BAL-003-1 frequency response standard at both the area level and interconnection level. The load model is calibrated and used to model populations of frequency-responsive water heaters in a PowerWorld simulation of the U.S. Western Interconnection (WECC). The proposed design is implemented and demonstrated on physical water heaters in a laboratory setting. A significant fraction of the required frequency response in the WECC could be supplied by electric water heaters alone at penetration levels of less than 15%, while contributing to NERC requirements at the interconnection and area levels.

  6. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hansen, Jacob [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fuller, Jason C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sun, Yannan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-12-01

    Current power grid operation predominantly relies on scheduling and regulating generation resources to supply loads and balance load changes. Due to the inherent intermittency of renewable energy, more flexible and fast ramping capacity is required to compensate for the uncertainty and variability introduced by renewable energy resources. With the advancement of information technologies, power system end-use loads are becoming more agile and can participate in provision of balancing energy and other grid services. The use of demand response can greatly reduce the required generation reserve in a clean and environmentally friendly way. In this report, a new frequency responsive load (FRL) controller was proposed based on the GFA controller, which can respond to both over and under-frequency events. A supervisory control was introduced to coordinate the autonomous response from FRLs in order to overcome the issues of excessive system response due to high penetration of FRLs. The effectiveness of the proposed FRL controller was demonstrated by large-scale simulation studies on the WECC system. Specifically, the FRLs were deployed in the WECC system at different penetration levels to analyze the performance of the proposed strategy both with and without supervisory level control. While both methods have their own advantages, the case without supervisory control could lead to system-wide instability depending on the size of the contingency and the number of FRLs deployed in the system. In addition, the voltage impacts of this controller on distribution system were also carefully investigated. Finally, a preliminary measurement and verification approach was also developed.

  7. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhang, Wei [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moya, Christian [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-10-08

    Frequency control plays an important role in preserving the power balance of a multi-machine power system. Generators modify their power output when a non-zero frequency deviation is presented in order to restore power balance across the network. However, with plans for large-scale penetration of renewable energy resources, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive, but also technically difficult. Frequency control from the demand side or load control presents a novel and viable way for providing the desired frequency response. Loads can measure frequency locally and change their power consumption after a non-zero frequency deviation is presented in order to achieve power balance between generation and consumption. The specific objectives of this project are to: •Provide a framework to facilitate large-scale deployment of frequency responsive end-use devices •Systematically design decentralized frequency-based load control strategies for enhanced stability performance •Ensure applicability over wide range of operating conditions while accounting for unpredictable end-use behavior and physical device constraints •Test and validate control strategy using large-scale simulations and field demonstrations •Create a level-playing field for smart grid assets with conventional generators

  8. Benefits and challenges of electrical demand response: A critical review

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    Advances in IT, control and forecasting capabilities have made demand response a viable, and potentially attractive, option to increase power system flexibility. This paper presents a critical review of the literature in the field of demand response, providing an overview of the benefits...... and challenges of demand response. These benefits include the ability to balance fluctuations in renewable generation and consequently facilitate higher penetrations of renewable resources on the power system, an increase in economic efficiency through the implementation of real-time pricing, and a reduction...... in generation capacity requirements. Nevertheless, demand response is not without its challenges. The key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally. One of the greatest challenges...

  9. An analytical approach to activating demand elasticity with a demand response mechanism

    International Nuclear Information System (INIS)

    Clastres, Cedric; Khalfallah, Haikel

    2015-01-01

    The aim of this work is to demonstrate analytically the conditions under which activating the elasticity of consumer demand could benefit social welfare. We have developed an analytical equilibrium model to quantify the effect of deploying demand response on social welfare and energy trade. The novelty of this research is that it demonstrates the existence of an optimal area for the price signal in which demand response enhances social welfare. This optimal area is negatively correlated to the degree of competitiveness of generation technologies and the market size of the system. In particular, it should be noted that the value of un-served energy or energy reduction which the producers could lose from such a demand response scheme would limit its effectiveness. This constraint is even greater if energy trade between countries is limited. Finally, we have demonstrated scope for more aggressive demand response, when only considering the impact in terms of consumer surplus. (authors)

  10. Does Knowledge Contribute to the Acceptance of Demand Response?

    Directory of Open Access Journals (Sweden)

    Salla Annala

    2014-03-01

    Full Text Available More flexible demand side would benefit the electricity markets, networks and sustainable power generation in many ways. The success of demand response programs, however, relies on consumer acceptance. This paper reviews previous studies about acceptability of different kinds of residential demand response programs. Furthermore, it discusses whether consumers who are more aware of the principles and benefits of demand response have more positive attitudes towards demand response programs. The results of the literature review and two survey studies suggest that price and security of supply are currently bigger motives to change consumption behaviour than environmental issues and that the savings expected to trigger any action (and to lead to lasting change in behaviour may be relatively high. Therefore, the framing of demand response programs goals may affect the acceptance. Additionally, consumers seem to prefer simple price structures that remain constant for a long time to more dynamic options.

  11. Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

    International Nuclear Information System (INIS)

    Gyamfi, Samuel; Krumdieck, Susan

    2011-01-01

    Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers' network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. - Highlights: → Multiple-factor behaviour intervention is necessarily for effective residential demand response. → Security signals can achieve result comparable to price. → The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. → New Zealand's energy policy should include innovation and development of VDR programmes and technologies.

  12. Interoperability of Demand Response Resources Demonstration in NY

    Energy Technology Data Exchange (ETDEWEB)

    Wellington, Andre

    2014-03-31

    The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

  13. Targeting Customers for Demand Response Based on Big Data

    OpenAIRE

    Kwac, Jungsuk; Rajagopal, Ram

    2014-01-01

    Selecting customers for demand response programs is challenging and existing methodologies are hard to scale and poor in performance. The existing methods were limited by lack of temporal consumption information at the individual customer level. We propose a scalable methodology for demand response targeting utilizing novel data available from smart meters. The approach relies on formulating the problem as a stochastic integer program involving predicted customer responses. A novel approximat...

  14. Assessment of Industrial Load for Demand Response across Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL; Ma, Ookie [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)

    2013-11-01

    Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

  15. Role of Storage and Demand Response, Greening the Grid

    Energy Technology Data Exchange (ETDEWEB)

    2015-09-01

    Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. This document, part of a Greening the Grid toolkit, examines storage and demand response as means to match renewable energy supply with demand.

  16. The Role of Demand Response in Default Service Pricing

    International Nuclear Information System (INIS)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2006-01-01

    In designing default service for competitive retail markets, demand response has been an afterthought at best. But that may be changing, as states that initiated customer choice in the past five to seven years reach an important juncture in retail market design and consider an RTP-type default service for large commercial and industrial customers. The authors describe the experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price-responsive demand. (author)

  17. Demonstrating demand response from water distribution system through pump scheduling

    International Nuclear Information System (INIS)

    Menke, Ruben; Abraham, Edo; Parpas, Panos; Stoianov, Ivan

    2016-01-01

    Highlights: • Water distribution systems can profitably provide demand response energy. • STOR and FFR are financially viable under a wide range of operating conditions. • Viability depends on the pump utilisation and peak price of the electricity tariff. • Total GHG emissions caused by the provision of reserve energy are <300 gCO 2 /kW h. • These are lower than those from the major reserve energy provision technologies. - Abstract: Significant changes in the power generation mix are posing new challenges for the balancing systems of the grid. Many of these challenges are in the secondary electricity grid regulation services and could be met through demand response (DR) services. We explore the opportunities for a water distribution system (WDS) to provide balancing services with demand response through pump scheduling and evaluate the associated benefits. Using a benchmark network and demand response mechanisms available in the UK, these benefits are assessed in terms of reduced green house gas (GHG) emissions from the grid due to the displacement of more polluting power sources and additional revenues for water utilities. The optimal pump scheduling problem is formulated as a mixed-integer optimisation problem and solved using a branch and bound algorithm. This new formulation finds the optimal level of power capacity to commit to the provision of demand response for a range of reserve energy provision and frequency response schemes offered in the UK. For the first time we show that DR from WDS can offer financial benefits to WDS operators while providing response energy to the grid with less greenhouse gas emissions than competing reserve energy technologies. Using a Monte Carlo simulation based on data from 2014, we demonstrate that the cost of providing the storage energy is less than the financial compensation available for the equivalent energy supply. The GHG emissions from the demand response provision from a WDS are also shown to be smaller than

  18. Personality predicts brain responses to cognitive demands.

    Science.gov (United States)

    Kumari, Veena; ffytche, Dominic H; Williams, Steven C R; Gray, Jeffrey A

    2004-11-24

    Eysenck (1981) proposed that the personality dimension of introversion- extraversion (E) reflects individual differences in a cortical arousal system modulated by reticulothalamic- cortical pathways: it is chronically more active in introverts relative to extraverts and influences cognitive performance in interaction with task parameters. A circuit with connections to this system, including the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate (AC) cortex, has been identified in studies applying functional magnetic resonance imaging (fMRI) to a broad range of cognitive tasks. We examined the influence of E, assessed with the Eysenck Personality Questionnaire-Revised (Eysenck and Eysenck, 1991), in fMRI activity during an "n-back" task involving four memory loads (0-, 1-, 2-, and 3-back) and a rest condition in healthy men. To confirm the specificity of E effects, we also examined the effects of neuroticism and psychoticism (P) scores. We observed that, as predicted by Eysenck's model, the higher the E score, the greater the change in fMRI signal from rest to the 3-back condition in the DLPFC and AC. In addition, E scores were negatively associated with resting fMRI signals in the thalamus and Broca's area extending to Wernicke's area, supporting the hypothesized (negative) relationship between E and resting arousal. P scores negatively correlated with resting fMRI signal in the globus pallidus-putamen, extending previous findings of a negative relationship of schizotypy to striatal activity seen with older neuroimaging modalities to fMRI. These observations suggest that individual differences affect brain responses during cognitive activity and at rest and provide evidence for the hypothesized neurobiological basis of personality.

  19. Price elasticity matrix of demand in power system considering demand response programs

    Science.gov (United States)

    Qu, Xinyao; Hui, Hongxun; Yang, Shengchun; Li, Yaping; Ding, Yi

    2018-02-01

    The increasing renewable energy power generations have brought more intermittency and volatility to the electric power system. Demand-side resources can improve the consumption of renewable energy by demand response (DR), which becomes one of the important means to improve the reliability of power system. In price-based DR, the sensitivity analysis of customer’s power demand to the changing electricity prices is pivotal for setting reasonable prices and forecasting loads of power system. This paper studies the price elasticity matrix of demand (PEMD). An improved PEMD model is proposed based on elasticity effect weight, which can unify the rigid loads and flexible loads. Moreover, the structure of PEMD, which is decided by price policies and load types, and the calculation method of PEMD are also proposed. Several cases are studied to prove the effectiveness of this method.

  20. Demonstration of automated price response in large customers in New York City using Auto-DR and OpenADR

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Joyce Jihyun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schetrit, Oren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yin, Rongxin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-05-01

    Demand response (DR) – allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern – continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. From October 2011 to December 2013, the Demand Response Research Center at Lawrence Berkeley National Laboratory, the New York State Energy Research and Development Authority, and partners Honeywell and Akuacom, have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR) communication protocols. In particular, this project focuses on demonstrating how the OpenADR platform, enabled by Akuacom, can automate and simplify interactions between buildings and various stakeholders in New York State and enable the automation of customers’ price response to yield bill savings under dynamic pricing. In this paper, the cost control opportunities under day-ahead hourly pricing and Auto-DR control strategies are presented for four demonstration buildings; present the breakdown of Auto-DR enablement costs; summarize the field test results and their load impact; and show potential bill savings by enabling automated price response under Consolidated Edison’s Mandatory Hourly Pricing (MHP) tariff. For one of the sites, the potential bill savings at the site’s current retail rate are shown. Facility managers were given granular equipment-level opt-out capability to ensure full control of the sites during the Auto-DR implementation. The expected bill savings ranged from 1.1% to 8.0% of the total MHP bill. The automation and enablement costs ranged from $70 to $725 per kW shed. The results show that OpenADR can facilitate the automation of price response, deliver savings to the customers and opt-out capability of the implementation retains control of the

  1. Providing frequency regulation reserve services using demand response scheduling

    International Nuclear Information System (INIS)

    Motalleb, Mahdi; Thornton, Matsu; Reihani, Ehsan; Ghorbani, Reza

    2016-01-01

    Highlights: • Proposing a market model for contingency reserve services using demand response. • Considering transient limitations of grid frequency for inverter-based generations. • Price-sensitive scheduling of residential batteries and water heaters using dynamic programming. • Calculating the profits of both generation companies and demand response aggregators. - Abstract: During power grid contingencies, frequency regulation is a primary concern. Historically, frequency regulation during contingency events has been the sole responsibility of the power utility. We present a practical method of using distributed demand response scheduling to provide frequency regulation during contingency events. This paper discusses the implementation of a control system model for the use of distributed energy storage systems such as battery banks and electric water heaters as a source of ancillary services. We present an algorithm which handles the optimization of demand response scheduling for normal operation and during contingency events. We use dynamic programming as an optimization tool. A price signal is developed using optimal power flow calculations to determine the locational marginal price of electricity, while sensor data for water usage is also collected. Using these inputs to dynamic programming, the optimal control signals are given as output. We assume a market model in which distributed demand response resources are sold as a commodity on the open market and profits from demand response aggregators as brokers of distributed demand response resources can be calculated. In considering control decisions for regulation of transient changes in frequency, we focus on IEEE standard 1547 in order to prevent the safety shut-off of inverter-based generation and further exacerbation of frequency droop. This method is applied to IEEE case 118 as a demonstration of the method in practice.

  2. Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand

    International Nuclear Information System (INIS)

    Adeyemi, Olutomi I.; Hunt, Lester C.

    2014-01-01

    This paper explores the way technical progress and improvements in energy efficiency are captured when modelling OECD industrial energy demand. The industrial sectors of the developed world involve a number of different practices and processes utilising a range of different technologies. Consequently, given the derived demand nature of energy, it is vital when modelling industrial energy demand that the impact of technical progress is appropriately captured. However, the energy economics literature does not give a clear guide on how this can be achieved; one strand suggests that technical progress is ‘endogenous’ via asymmetric price responses whereas another strand suggests that it is ‘exogenous’. More recently, it has been suggested that potentially there is a role for both ‘endogenous’ technical progress and ‘exogenous’ technical progress and consequently the general model should be specified accordingly. This paper therefore attempts to model OECD industrial energy demand using annual time series data over the period 1962–2010 for 15 OECD countries. Using the Structural Time Series Model framework, the general specifications allow for both asymmetric price responses (for technical progress to impact endogenously) and an underlying energy demand trend (for technical progress and other factors to impact exogenously, but in a non-linear way). The results show that almost all of the preferred models for OECD industrial energy demand incorporate both a stochastic underlying energy demand trend and asymmetric price responses. This gives estimated long-run income elasticities in the range of 0.34 to 0.96; estimated long-run price-maximum elasticities in the range of − 0.06 to − 1.22; estimated long-run price-recovery elasticities in the range of 0.00 to − 0.27; and estimated long-run price-cut elasticities in the range of 0.00 to − 0.18. Furthermore, the analysis suggests that when modelling industrial energy demand there is a place for

  3. An electricity generation planning model incorporating demand response

    International Nuclear Information System (INIS)

    Choi, Dong Gu; Thomas, Valerie M.

    2012-01-01

    Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

  4. Data-driven Demand Response Characterization and Quantification

    DEFF Research Database (Denmark)

    Le Ray, Guillaume; Pinson, Pierre; Larsen, Emil Mahler

    2017-01-01

    Analysis of load behavior in demand response (DR) schemes is important to evaluate the performance of participants. Very few real-world experiments have been carried out and quantification and characterization of the response is a difficult task. Nevertheless it will be a necessary tool...

  5. Improving demand response potential of a supermarket refrigeration system

    DEFF Research Database (Denmark)

    Pedersen, Rasmus; Schwensen, John; Biegel, Benjamin

    2017-01-01

    through tests on a full scale supermarket refrigeration system made available by Danfoss A/S. The conducted application test shows that feedback based on food temperature can increase the demand flexibility during a step by approx. 60 % the first 70 minutes and up to 100%over the first 150 minutes......In a smart grid the load shifting capabilities of demand-side devices such as supermarkets are of high interest. In supermarkets this potential is represented by the ability to store energy in the thermal mass of refrigerated foodstuff. To harness the full load shifting potential we propose...... - thereby strengthening the demand response potential of supermarket refrigeration systems....

  6. Automated Demand Response for Energy Sustainability Cost and Performance Report

    Science.gov (United States)

    2015-07-23

    heating, ventilation, and air conditioning ( HVAC ) equipment, lighting, water pumping, and other miscellaneous motor loads. A military installation can...ESTCP Environmental Security Technology Certification Program FEMP Federal Energy Management Program GHG greenhouse gas HVAC heating...lighting, etc.) as well as miscellaneous motor loads. Revenues received from participation in the electricity markets (through utility bill

  7. Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Michael R [ORNL; Kirby, Brendan J [ORNL; Kueck, John D [ORNL; Todd, Duane [Alcoa; Caulfield, Michael [Alcoa; Helms, Brian [Alcoa

    2009-02-01

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter

  8. A compact, portable, re-configurable, and automated system for on-demand pharmaceutical tablet manufacturing.

    Science.gov (United States)

    Azad, Mohammad A; Osorio, Juan G; Brancazio, David; Hammersmith, Gregory; Klee, David M; Rapp, Kersten; Myerson, Allan

    2018-03-25

    Due to the complex nature of the pharmaceutical supply chain, the industry faces several major challenges when it comes to ensuring an adequate supply of quality drug products. These challenges are not only the causes of supply chain disruptions and financial loss, but can also prevent underserved and remote areas from receiving life-saving drugs. As a preliminary demonstration to mitigate all these challenges, at MIT we have developed active pharmaceutical ingredients manufacturing in a miniature platform. However, manufacturing of final oral solid dosage as tablets from drug substances had not been demonstrated. In this study, a compact, portable, re-configurable, and automated tablet manufacturing system, roughly the size of a North American household oven, [72.4 cm (length) × 53.3 cm (width) × 134.6 cm (height)] was designed, built and demonstrated. This miniature system is able to manufacture on-demand tablets from drug crystals on a scale of hundreds to thousands per day. Ibuprofen and Diazepam, each having different drug loading, were manufactured using this miniature system and meet U.S. Pharmacopeia standards. We foresee this flexible, miniature, plug-and-play pharmaceutical solids dosage manufacturing system advancing on-demand ready-to-use pharmaceuticals enabling future treatment of human diseases at the point-of-care. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Embedded generation for industrial demand response in renewable energy markets

    International Nuclear Information System (INIS)

    Leanez, Frank J.; Drayton, Glenn

    2010-01-01

    Uncertainty in the electrical energy market is expected to increase with growth in the percentage of generation using renewable resources. Demand response can play a key role in giving stability to system operation. This paper discusses the embedded generation for industrial demand response in renewable energy markets. The methodology of the demand response is explained. It consists of long-term optimization and stochastic optimization. Wind energy, among all the renewable resources, is becoming increasingly popular. Volatility in the wind energy sector is high and this is explained using examples. Uncertainty in the wind market is shown using stochastic optimization. Alternative techniques for generation of wind energy were seen to be needed. Embedded generation techniques include co-generation (CHP) and pump storage among others. These techniques are analyzed and the results are presented. From these results, it is seen that investment in renewables is immediately required and that innovative generation technologies are also required over the long-term.

  10. Stimulation of demand response through evaluation and training

    International Nuclear Information System (INIS)

    Encinas, N.; Alfonso, D.; Alvarez, C.; Mendez, C.; Rodriguez, J.; Perez-Navarro, A.; Gabaldon, A.

    2004-01-01

    The objective of Demand Response is to enhance customer choice opportunities by means of price-responsive mechanisms in contrast to direct load control practices and associated revenues based on fixed incentives. In this way, the new approach complements the traditional concept of Demand Side Management by including the voluntary nature to customer participation. This voluntary feature implies a change in customers' traditional behaviour and therefore stimulation and training is needed to achieve an optimal participation. This paper presents a methodology developed to stimulate and train customers for Demand Response practices as well as to identify the suitable products for different customers. Finally, the paper includes an example of the methodology considering a university as a customer. (au)

  11. Economic Dispatch of Demand Response Balancing through Asymmetric Block Offers

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2015-01-01

    This paper proposes a method of describing the load shifting ability of flexible electrical loads in a manner suitable for existing power system dispatch frameworks. The concept of an asymmetric block offer for flexible loads is introduced. This offer structure describes the ability of a flexible...... load to provide a response to the power system and the subsequent need to recover. The conventional system dispatch algorithm is altered to facilitate the dispatch of demand response units alongside generating units using the proposed offer structure. The value of demand response is assessed through...... case studies that dispatch flexible supermarket refrigeration loads for the provision of regulating power. The demand resource is described by a set of asymmetric blocks, and a set of four blocks offers is shown to offer cost savings for the procurement of regulating power in excess of 20...

  12. Unlocking the potential for efficiency and demand response throughadvanced metering

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger; Herter, Karen; Wilson, John

    2004-06-30

    Reliance on the standard cumulative kilowatt-hour meter substantially compromises energy efficiency and demand response programs. Without advanced metering, utilities cannot support time-differentiated rates or collect the detailed customer usage information necessary to (1)educate the customer to the economic value of efficiency and demand response options, or (2) distribute load management incentives proportional to customer contribution. These deficiencies prevent the customer feedback mechanisms that would otherwise encourage economically sound demand-side investments and behaviors. Thus, the inability to collect or properly price electricity usage handicaps the success of almost all efficiency and demand response options. Historically, implementation of the advanced metering infrastructure (AMI) necessary for the successful efficiency and demand response programs has been prevented by inadequate cost-benefit analyses. A recent California effort has produced an expanded cost-effectiveness methodology for AMI that introduces previously excluded benefits. In addition to utility-centric costs and benefits, the new model includes qualitative and quantitative costs and benefits that accrue to both customers and society.

  13. Demand response. Intelligent load management for the German control power market; Demand Response. Intelligentes Lastmanagement fuer den deutschen Regelleistungsmarkt

    Energy Technology Data Exchange (ETDEWEB)

    Neubarth, Juergen [Entelios AG / e3 consult, Muenchen (Germany); Henle, Markus [SWM Services GmbH, Muenchen (Germany)

    2012-07-01

    With the expansion of electricity generation from wind and solar power the demand for flexible generation and storage capacities increases. While the development of highly flexible gas and storage power plants has been discussed intensively on a political level the already existing flexibility potential on the demand side has in many cases been disregarded so far. In a pilot project the Entelios AG and Stadtwerke Muenchen have shown that an intelligent load management could already contribute to system stability. However, in the long run a successful establishment of demand response in the German power and balancing market requires not only a clear definition of the new market role of demand response but in particular a further development of the regulatory framework in the course of the implementation of the EC energy efficiency directive. (orig.)

  14. Demand response scheme based on lottery-like rebates

    KAUST Repository

    Schwartz, Galina A.

    2014-08-24

    In this paper, we develop a novel mechanism for reducing volatility of residential demand for electricity. We construct a reward-based (rebate) mechanism that provides consumers with incentives to shift their demand to off-peak time. In contrast to most other mechanisms proposed in the literature, the key feature of our mechanism is its modest requirements on user preferences, i.e., it does not require exact knowledge of user responsiveness to rewards for shifting their demand from the peak to the off-peak time. Specifically, our mechanism utilizes a probabilistic reward structure for users who shift their demand to the off-peak time, and is robust to incomplete information about user demand and/or risk preferences. We approach the problem from the public good perspective, and demonstrate that the mechanism can be implemented via lottery-like schemes. Our mechanism permits to reduce the distribution losses, and thus improve efficiency of electricity distribution. Finally, the mechanism can be readily incorporated into the emerging demand response schemes (e.g., the time-of-day pricing, and critical peak pricing schemes), and has security and privacy-preserving properties.

  15. Control for large scale demand response of thermostatic loads

    DEFF Research Database (Denmark)

    Totu, Luminita Cristiana; Leth, John; Wisniewski, Rafal

    2013-01-01

    Demand response is an important Smart Grid concept that aims at facilitating the integration of volatile energy resources into the electricity grid. This paper considers a residential demand response scenario and specifically looks into the problem of managing a large number thermostatbased...... appliances with on/off operation. The objective is to reduce the consumption peak of a group of loads composed of both flexible and inflexible units. The power flexible units are the thermostat-based appliances. We discuss a centralized, model predictive approach and a distributed structure with a randomized...

  16. Modeling, Analysis, and Control of Demand Response Resources

    Energy Technology Data Exchange (ETDEWEB)

    Mathieu, Johanna L. [Univ. of California, Berkeley, CA (United States)

    2012-05-01

    While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real

  17. Demand Response an Alternative Solution to Prevent Load Shedding Triggering

    Directory of Open Access Journals (Sweden)

    K. Mollah

    2014-12-01

    Full Text Available This paper investigates an alternative solution to prevent Load Shedding (LS triggering during underfrequency and proposes a new technique to restore the frequency during emergency events. Demand response (DR is considered as one of the most promising Smart Grid concepts that can be used to support the peak demand, whereas, LS is an existing last resort method during emergency grid situations. Both schemes aim to balance the load and generation in real-time and restore the frequency very quickly. This paper incorporates integrating Incentive based Demand Response (IDR with spinning reserve for smaller underfrequency events to manage the system peak demand. It also introduces a new frequency band for an Emergency Demand Response (EDR as an alternative inexpensive solution that can replace costly spinning reserves and help to prevent LS. An energy index factor is used to identify the consumption pattern of consumers to enable them to participate in IDR. An illustrative example of the performance of the proposed scheme on a modified 15 bus test system is shown. Simulation results on different scenarios confirm that the proposed method is effective to improve the frequency restoration process along with enabling participation of new services.

  18. On the demand for prescription drugs: heterogeneity in price responses.

    Science.gov (United States)

    Skipper, Niels

    2013-07-01

    This paper estimates the price elasticity of demand for prescription drugs using an exogenous shift in consumer co-payment caused by a reform in the Danish subsidy scheme for the general public. Using purchasing records for the entire Danish population, I show that the average price response for the most commonly used drug yields demand elasticities in the range of -0.36 to -0.5. The reform is shown to affect women, the elderly, and immigrants the most. Furthermore, this paper shows significant heterogeneity in the price response over different types of antibiotics, suggesting that the price elasticity of demand varies considerably even across relatively similar drugs. Copyright © 2012 John Wiley & Sons, Ltd.

  19. Individual differences in response to automation: the five factor model of personality.

    Science.gov (United States)

    Szalma, James L; Taylor, Grant S

    2011-06-01

    This study examined the relationship of operator personality (Five Factor Model) and characteristics of the task and of adaptive automation (reliability and adaptiveness-whether the automation was well-matched to changes in task demand) to operator performance, workload, stress, and coping. This represents the first investigation of how the Five Factors relate to human response to automation. One-hundred-sixty-one college students experienced either 75% or 95% reliable automation provided with task loads of either two or four displays to be monitored. The task required threat detection in a simulated uninhabited ground vehicle (UGV) task. Task demand exerted the strongest influence on outcome variables. Automation characteristics did not directly impact workload or stress, but effects did emerge in the context of trait-task interactions that varied as a function of the dimension of workload and stress. The pattern of relationships of traits to dependent variables was generally moderated by at least one task factor. Neuroticism was related to poorer performance in some conditions, and all five traits were associated with at least one measure of workload and stress. Neuroticism generally predicted increased workload and stress and the other traits predicted decreased levels of these states. However, in the case of the relation of Extraversion and Agreeableness to Worry, Frustration, and avoidant coping, the direction of effects varied across task conditions. The results support incorporation of individual differences into automation design by identifying the relevant person characteristics and using the information to determine what functions to automate and the form and level of automation.

  20. Analyses of demand response in Denmark[Electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Moeller Andersen, F.; Grenaa Jensen, S.; Larsen, Helge V.; Meibom, P.; Ravn, H.; Skytte, K.; Togeby, M.

    2006-10-15

    Due to characteristics of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many consumers do not experience corresponding variations in the price they pay for consuming electricity. The topic of this report is: are consumers willing and able to respond to short-term variations in electricity prices, and if so, what is the social benefit of consumers doing so? Taking Denmark and the Nord Pool market as a case, the report focuses on what is known as short-term consumer flexibility or demand response in the electricity market. With focus on market efficiency, efficient allocation of resources and security of supply, the report describes demand response from a micro-economic perspective and provides empirical observations and case studies. The report aims at evaluating benefits from demand response. However, only elements contributing to an overall value are presented. In addition, the analyses are limited to benefits for society, and costs of obtaining demand response are not considered. (au)

  1. Opportunities and Challenges of Demand Response in Active Distribution Grids

    DEFF Research Database (Denmark)

    Ponnaganti, Pavani; Pillai, Jayakrishnan Radhakrishna; Bak-Jensen, Birgitte

    2018-01-01

    operator to shed the load in order to maintain security of the system. With the advent of advanced smart metering infrastructure, communication between system operator and end-use customers makes it possible to adjust/curtail/shift the demand with respect to the state of the system. The response...

  2. Hierarchical Control Architecture for Demand Response in Smart Grid Scenario

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Mahat, Pukar

    2013-01-01

    To compensate for intermittency of generation and consequent impacts of non-dispatchable generating sources, especially solar PV panels and wind turbines, demand response (DR) has been considered one of the most effective tools. In recent years, DR has received more attention as a potentially...

  3. Load Reduction, Demand Response and Energy Efficient Technologies and Strategies

    Energy Technology Data Exchange (ETDEWEB)

    Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

    2008-11-19

    The Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

  4. The Cobweb Effect in Balancing Markets with Demand Response

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler; Pinson, Pierre; Wang, Jianhui

    2015-01-01

    to control and integrate DR into the power system remains an open question. Integration into existing electricity markets is one option, but dynamic pricing with DR has been observed to be unstable, resulting in oscillations in supply and demand. This socalled Cobweb effect is presented here using the market......Integration of renewable energy sources (RES) like wind into the power system is a high priority in many countries, but it becomes increasingly difficult as renewables reach a significant share of generation. Demand response (DR) can potentially mitigate some of these difficulties, but the best way...

  5. The optimization of demand response programs in smart grids

    International Nuclear Information System (INIS)

    Derakhshan, Ghasem; Shayanfar, Heidar Ali; Kazemi, Ahad

    2016-01-01

    The potential to schedule portion of the electricity demand in smart energy systems is clear as a significant opportunity to enhance the efficiency of the grids. Demand response is one of the new developments in the field of electricity which is meant to engage consumers in improving the energy consumption pattern. We used Teaching & Learning based Optimization (TLBO) and Shuffled Frog Leaping (SFL) algorithms to propose an optimization model for consumption scheduling in smart grid when payment costs of different periods are reduced. This study conducted on four types residential consumers obtained in the summer for some residential houses located in the centre of Tehran city in Iran: first with time of use pricing, second with real-time pricing, third one with critical peak pricing, and the last consumer had no tariff for pricing. The results demonstrate that the adoption of demand response programs can reduce total payment costs and determine a more efficient use of optimization techniques. - Highlights: •An optimization model for the demand response program is made. •TLBO and SFL algorithms are applied to reduce payment costs in smart grid. •The optimal condition is provided for the maximization of the social welfare problem. •An application to some residential houses located in the centre of Tehran city in Iran is demonstrated.

  6. The power to choose. Demand response in liberalized electricity markets

    International Nuclear Information System (INIS)

    2003-01-01

    Highly volatile electricity prices are becoming a more frequent and unwanted characteristic of modern electricity wholesale markets. But low demand elasticity, mainly the result of a lack of incentives and consumers' inability to control demand, means that consumer behaviour is not reflected in the cost of energy. This study analyses the impact of price-responsive demand and shows how pricing, policy and technology can be used to inform consumer behaviour and choice. Informed choice and market-based valuation of electricity supply will ensure liberalized markets are competitive, efficient, less volatile and able to provide long term security of supply. Significant benefits will occur even if only 5% of customers become responsive to price-incentives and information. And customers will respond to well designed programs, thereby developing a role in ensuring efficient price formulation for electricity. This study analyses the economic, efficiency and security benefits and identifies the changes in electricity tariffs and the network infrastructure needed to achieve greater demand response

  7. Demand-side management and demand response in the Ontario energy sectors

    International Nuclear Information System (INIS)

    2003-01-01

    In June 2003, the Ontario Energy Board was asked by the Minister of Energy to identify and review options for the delivery of demand-side management (DSM) and demand response (DR) activities within the electricity sector, by consulting with stakeholders. The role of local distribution company (distributor) in such activities was also to be determined. The objective was to balance implementation costs with the benefits to consumers and the entire system. The preliminary research and ideas were presented in this discussion paper. Definitions of both DSM and DR were provided, followed by an overview of economic theory and competitive markets. The framework for discussion was presented, along with a list of issues and other considerations. A spectrum of potential approaches to a DSM and DR framework was included and jurisdictional examples provided. A brief overview of the concept of load aggregation was presented and the next steps for consultations were outlined. 30 refs., 7 tabs

  8. Analysis of the Effects of Connected–Automated Vehicle Technologies on Travel Demand

    Energy Technology Data Exchange (ETDEWEB)

    Auld, Joshua [Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439; Sokolov, Vadim [Department of Systems Engineering and Operations Research, Volgenau School of Engineering, George Mason University, MS 4A6, 4400 University Drive, Fairfax, VA 22030; Stephens, Thomas S. [Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439

    2017-01-01

    Connected–automated vehicle (CAV) technologies are likely to have significant effects not only on how vehicles operate in the transportation system, but also on how individuals behave and use their vehicles. While many CAV technologies—such as connected adaptive cruise control and ecosignals—have the potential to increase network throughput and efficiency, many of these same technologies have a secondary effect of reducing driver burden, which can drive changes in travel behavior. Such changes in travel behavior—in effect, lowering the cost of driving—have the potential to increase greatly the utilization of the transportation system with concurrent negative externalities, such as congestion, energy use, and emissions, working against the positive effects on the transportation system resulting from increased capacity. To date, few studies have analyzed the potential effects on CAV technologies from a systems perspective; studies often focus on gains and losses to an individual vehicle, at a single intersection, or along a corridor. However, travel demand and traffic flow constitute a complex, adaptive, nonlinear system. Therefore, in this study, an advanced transportation systems simulation model—POLARIS—was used. POLARIS includes cosimulation of travel behavior and traffic flow to study the potential effects of several CAV technologies at the regional level. Various technology penetration levels and changes in travel time sensitivity have been analyzed to determine a potential range of effects on vehicle miles traveled from various CAV technologies.

  9. How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

    Science.gov (United States)

    Kraut, Joshua M.; Mercer, Joey; Morey, Susan; Homola, Jeffrey; Gomez, Ashley; Prevot, Thomas

    2013-01-01

    In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

  10. Efficient Customer Selection for Sustainable Demand Response in Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Zois, Vasileios; Frincu, Marc; Chelmis, Charalambos; Saeed, Muhammad Rizwan; Prasanna, Viktor K.

    2014-11-03

    Regulating the power consumption to avoid peaks in demand is a common practice. Demand Response(DR) is being used by utility providers to minimize costs or ensure system reliability. Although it has been used extensively there is a shortage of solutions dealing with dynamic DR. Past attempts focus on minimizing the load demand without considering the sustainability of the reduced energy. In this paper an efficient algorithm is presented which solves the problem of dynamic DR scheduling. Data from the USC campus micro grid were used to evaluate the efficiency as well as the robustness of the proposed solution. The targeted energy reduction is achieved with a maximum average approximation error of ≈ 0.7%. Sustainability of the reduced energy is achieved with respect to the optimal available solution providing a maximum average error less than 0.6%. It is also shown that a solution is provided with a low computational cost fulfilling the requirements of dynamic DR.

  11. Market integration of flexible demand and DG-RES supply. A new approach for demand response

    International Nuclear Information System (INIS)

    Warmer, C.J.; Hommelberg, M.P.F.; Kamphuis, I.G.; Kok, J.K.

    2007-06-01

    In this paper we discuss the shortcomings of traditional Demand Response programs in an environment in which a large amount of distributed generation is available. An innovative approach is given in which true Customer Site Integration is obtained in the spirit of the liberalized electricity market, by making use of the load flexibility of underlying processes of production and consumption devices. The approach is based on distributed control mechanisms and incorporates new market models for distribution and aggregation costs, load losses, and network constraints

  12. Effects of Demand Response on Retail and Wholesale Power Markets

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Kalsi, Karanjit

    2012-07-26

    Demand response has grown to be a part of the repertoire of resources used by utilities to manage the balance between generation and load. In recent years, advances in communications and control technology have enabled utilities to consider continuously controlling demand response to meet generation, rather than the other way around. This paper discusses the economic applications of a general method for load resource analysis that parallels the approach used to analyze generation resources and uses the method to examine the results of the US Department of Energy’s Olympic Peninsula Demonstration Testbed. A market-based closed-loop system of controllable assets is discussed with necessary and sufficient conditions on system controllability, observability and stability derived.

  13. Influence Of Corporate Social Responsibility On Hotel Demand

    OpenAIRE

    Claudia Sevilla-Sevilla; Maria Dolores Reina-Paz; Ainhoa Rodriguez-Oromendia

    2014-01-01

    The embrace of corporate social responsibility (CSR) by the Spanish hospitality industry is still in the early stages. Few hotel companies publish sustainability reports, although the number of tourism and distribution channel organizations (tour operators, online travel agencies, etc.) incorporating specific aspects of CSR is growing each year. In this paper, the authors analyze whether CSR has a direct effect on end-consumer demand in Spain, identifying those aspects that customers evaluate...

  14. Demand-side management and demand response in the Ontario energy sectors

    International Nuclear Information System (INIS)

    2004-01-01

    A directive from the former Minister of Energy was received by the Ontario Energy Board (OEB), directing the Board to consult with stakeholders on options for the delivery of demand-side management (DSM) and demand response (DR) activities within the electricity sector, including the role of local distribution companies in such activities. The implementation costs were to be balanced with the benefits to both consumers and the entire system. The scope of the review was expanded by the Board to include the role of gas distribution companies in DSM. A consultation process was implemented and stakeholders were invited to participate. A series of recommendations was made, including: (1) a hybrid framework utilizing market-based and public-policy approaches should deliver DSM and DR activities in Ontario's energy markets, (2) DSM and DR activities should come under the responsibility of a central agency, (3) DSM and DR activities should be coordinated through cooperation between the Ministry of Energy, the Independent Electricity Market Operator (IMO) and the Ontario Energy Board, (4) regulatory mechanisms to induce gas distributors, electricity transmitters and electricity distributors to reduce distribution system losses should be put in place, (5) all electricity consumers should fund electricity DSM and some retail DR initiatives through a transparent, non-bypassable consumption charge, and (6) the Board should design, develop and deliver information to consumers regarding energy conservation, energy efficiency, load management, and cleaner sources of energy. refs., 4 figs

  15. ARES: automated response function code. Users manual. [HPGAM and LSQVM

    Energy Technology Data Exchange (ETDEWEB)

    Maung, T.; Reynolds, G.M.

    1981-06-01

    This ARES user's manual provides detailed instructions for a general understanding of the Automated Response Function Code and gives step by step instructions for using the complete code package on a HP-1000 system. This code is designed to calculate response functions of NaI gamma-ray detectors, with cylindrical or rectangular geometries.

  16. Chance-constrained optimization of demand response to price signals

    DEFF Research Database (Denmark)

    Dorini, Gianluca Fabio; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    Household-based demand response is expected to play an increasing role in supporting the large scale integration of renewable energy generation in existing power systems and electricity markets. While the direct control of the consumption level of households is envisaged as a possibility......, a credible alternative is that of indirect control based on price signals to be sent to these end-consumers. A methodology is described here allowing to estimate in advance the potential response of flexible end-consumers to price variations, subsequently embedded in an optimal price-signal generator...

  17. Automatic demand response referred to electricity spot price. Demo description

    International Nuclear Information System (INIS)

    Grande, Ove S.; Livik, Klaus; Hals, Arne

    2006-05-01

    This report presents background, technical solution and results from a test project (Demo I) developed in the DRR Norway) project. Software and technology from two different vendors, APAS and Powel ASA, are used to demonstrate a scheme for Automatic Demand Response (ADR) referred to spot price level and a system for documentation of demand response and cost savings. Periods with shortage of energy supply and hardly any investments in new production capacity have turned focus towards the need for increased price elasticity on the demand side in the Nordic power market. The new technology for Automatic Meter Reading (AMR) and Remote Load Control (RLC) provides an opportunity to improve the direct market participation from the demand side by introducing automatic schemes that reduce the need for customer attention to hourly market prices. The low prioritized appliances, and not the total load, are in this report defined as the Demand Response Objects, based on the assumption that there is a limit for what the customers are willing to pay for different uses of electricity. Only disconnection of residential water heaters is included in the demo, due to practical limitations. The test was performed for a group of single family houses over a period of 2 months. All the houses were equipped with a radio controlled 'Ebox' unit attached to the water heater socket. The settlement and invoicing were based on hourly metered values (kWh/h), which means that the customer benefit is equivalent to the accumulated changes in the electricity cost per hour. The actual load reduction is documented by comparison between the real meter values for the period and a reference curve. The curves show significant response to the activated control in the morning hours. In the afternoon it is more difficult to register the response, probably due to 'disturbing' activities like cooking etc. Demo I shows that load reduction referred to spot price level can be done in a smooth way. The experiences

  18. Fuel switching? Demand destruction? Gas market responses to price spikes

    International Nuclear Information System (INIS)

    Lippe, D.

    2004-01-01

    This presentation defined fuel switching and addressed the issue regarding which consumers have the capability to switch fuels. In response to short term price aberrations, consumers with fuel switching capabilities reduce their use of one fuel and increase consumption of an alternative fuel. For example, natural gas consumption by some consumers declines in response to price spikes relative to prices of alternative fuels. This presentation also addressed the issue of differentiating between fuel switching and demand destruction. It also demonstrated how to compare gas prices versus alternative fuel prices and how to determine when consumers will likely switch fuels. Price spikes have implications for long term trends in natural gas demand, supply/demand balances and prices. The power generating sector represents a particular class of gas consumers that reduce operating rates of gas fired plants and increase operating rates of other plants. Some gas consumers even shut down plants until gas prices declines and relative economies improve. Some practical considerations for fuel switching include storage tank capacity, domestic refinery production, winter heating season, and decline in working gas storage. tabs., figs

  19. Demand response evaluation and forecasting — Methods and results from the EcoGrid EU experiment

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler; Pinson, Pierre; Leimgruber, Fabian

    2017-01-01

    into a real-time market. EcoGrid EU is a smart grid experiment with 1900 residential customers who are equipped with smart meters and automated devices reacting to five-minute electricity pricing. Customers are grouped and analysed according to the manufacturer that controlled devices. A number of advanced......Understanding electricity consumers participating in new demand response schemes is important for investment decisions and the design and operation of electricity markets. Important metrics include peak response, time to peak response, energy delivered, ramping, and how the response changes...

  20. Optimal Demand Response of Smart Home with PV Generators

    Directory of Open Access Journals (Sweden)

    Chao-Rong Chen

    2014-01-01

    Full Text Available Demand response (DR is used mainly to help to schedule a customer’s power utilization based on the electricity price that is announced by the power distribution company so that both demand and supply can optimally benefit. The work proposes a users’ load model and the interior point method for optimal scheduling with elastic power utilization to minimize power price. The interior point method has the advantages of rapid convergence and robustness. Customers can not only use PV generators and battery sets as backup power sources, but also benefit from green energy. As revealed by the results herein, the use of elastic power utilization time intervals enables customers to pay less power price.

  1. Demand Response Load Following of Source and Load Systems

    DEFF Research Database (Denmark)

    Hu, Jianqiang; Cao, Jinde; Yong, Taiyou

    2017-01-01

    This paper presents a demand response load following strategy for an interconnected source and load system, in which we utilize traditional units and population of cooling thermostatically controlled loads (TCLs) to follow the mismatched power caused by the load activities and the renewable power...... injection in real time. In the demand side of power systems, these TCLs are often affiliated to a bus load agent and can be aggregated to multiple TCL aggregators. Firstly, aggregate evaluation of the TCL aggregator is carried out based on a bilinear aggregate model so as to derive the available regulation...... capacities and regulation rates of aggregators. Based on the evaluation results, the dispatch center optimizes the real time load following trajectories for the generating units and the flexible load agents via look-ahead optimization by considering the injection of renewable power. Furthermore, we mainly...

  2. Modeling and prioritizing demand response programs in power markets

    International Nuclear Information System (INIS)

    Aalami, H.A.; Moghaddam, M. Parsa; Yousefi, G.R.

    2010-01-01

    One of the responsibilities of power market regulator is setting rules for selecting and prioritizing demand response (DR) programs. There are many different alternatives of DR programs for improving load profile characteristics and achieving customers' satisfaction. Regulator should find the optimal solution which reflects the perspectives of each DR stakeholder. Multi Attribute Decision Making (MADM) is a proper method for handling such optimization problems. In this paper, an extended responsive load economic model is developed. The model is based on price elasticity and customer benefit function. Prioritizing of DR programs can be realized by means of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Considerations of ISO/utility/customer regarding the weighting of attributes are encountered by entropy method. An Analytical Hierarchy Process (AHP) is used for selecting the most effective DR program. Numerical studies are conducted on the load curve of the Iranian power grid in 2007. (author)

  3. Optimized management of a distributed demand response aggregation model

    International Nuclear Information System (INIS)

    Prelle, Thomas

    2014-01-01

    The desire to increase the share of renewable energies in the energy mix leads to an increase in share of volatile and non-controllable energy and makes it difficult to meet the supply-demand balance. A solution to manage anyway theses energies in the current electrical grid is to deploy new energy storage and demand response systems across the country to counterbalance under or over production. In order to integrate all these energies systems to the supply and demand balance process, there are gathered together within a virtual flexibility aggregation power plant which is then seen as a virtual power plant. As for any other power plant, it is necessary to compute its production plan. Firstly, we propose in this PhD thesis an architecture and management method for an aggregation power plant composed of any type of energies systems. Then, we propose algorithms to compute the production plan of any types of energy systems satisfying all theirs constraints. Finally, we propose an approach to compute the production plan of the aggregation power plant in order to maximize its financial profit while complying with all the constraints of the grid. (author)

  4. Designing Pareto-superior demand-response rate options

    International Nuclear Information System (INIS)

    Horowitz, I.; Woo, C.K.

    2006-01-01

    We explore three voluntary service options-real-time pricing, time-of-use pricing, and curtailable/interruptible service-that a local distribution company might offer its customers in order to encourage them to alter their electricity usage in response to changes in the electricity-spot-market price. These options are simple and practical, and make minimal information demands. We show that each of the options is Pareto-superior ex ante, in that it benefits both the participants and the company offering it, while not affecting the non-participants. The options are shown to be Pareto-superior ex post as well, except under certain exceptional circumstances. (author)

  5. Including dynamic CO2 intensity with demand response

    International Nuclear Information System (INIS)

    Stoll, Pia; Brandt, Nils; Nordström, Lars

    2014-01-01

    Hourly demand response tariffs with the intention of reducing or shifting loads during peak demand hours are being intensively discussed among policy-makers, researchers and executives of future electricity systems. Demand response rates have still low customer acceptance, apparently because the consumption habits requires stronger incentive to change than any proposed financial incentive. An hourly CO 2 intensity signal could give customers an extra environmental motivation to shift or reduce loads during peak hours, as it would enable co-optimisation of electricity consumption costs and carbon emissions reductions. In this study, we calculated the hourly dynamic CO 2 signal and applied the calculation to hourly electricity market data in Great Britain, Ontario and Sweden. This provided a novel understanding of the relationships between hourly electricity generation mix composition, electricity price and electricity mix CO 2 intensity. Load shifts from high-price hours resulted in carbon emission reductions for electricity generation mixes where price and CO 2 intensity were positively correlated. The reduction can be further improved if the shift is optimised using both price and CO 2 intensity. The analysis also indicated that an hourly CO 2 intensity signal can help avoid carbon emissions increases for mixes with a negative correlation between electricity price and CO 2 intensity. - Highlights: • We present a formula for calculating hybrid dynamic CO 2 intensity of electricity generation mixes. • We apply the dynamic CO 2 Intensity on hourly electricity market prices and generation units for Great Britain, Ontario and Sweden. • We calculate the spearman correlation between hourly electricity market price and dynamic CO 2 intensity for Great Britain, Ontario and Sweden. • We calculate carbon footprint of shifting 1 kWh load daily from on-peak hours to off-peak hours using the dynamic CO 2 intensity. • We conclude that using dynamic CO 2 intensity for

  6. Demand Response Performance of GE Hybrid Heat Pump Water Heater

    Energy Technology Data Exchange (ETDEWEB)

    Widder, Sarah H.; Parker, Graham B.; Petersen, Joseph M.; Baechler, Michael C.

    2013-07-01

    This report describes a project to evaluate and document the DR performance of HPWH as compared to ERWH for two primary types of DR events: peak curtailments and balancing reserves. The experiments were conducted with GE second-generation “Brillion”-enabled GeoSpring hybrid water heaters in the PNNL Lab Homes, with one GE GeoSpring water heater operating in “Standard” electric resistance mode to represent the baseline and one GE GeoSpring water heater operating in “Heat Pump” mode to provide the comparison to heat pump-only demand response. It is expected that “Hybrid” DR performance, which would engage both the heat pump and electric elements, could be interpolated from these two experimental extremes. Signals were sent simultaneously to the two water heaters in the side-by-side PNNL Lab Homes under highly controlled, simulated occupancy conditions. This report presents the results of the evaluation, which documents the demand-response capability of the GE GeoSpring HPWH for peak load reduction and regulation services. The sections describe the experimental protocol and test apparatus used to collect data, present the baselining procedure, discuss the results of the simulated DR events for the HPWH and ERWH, and synthesize key conclusions based on the collected data.

  7. Identifying Demand Responses to Illegal Drug Supply Interdictions.

    Science.gov (United States)

    Cunningham, Scott; Finlay, Keith

    2016-10-01

    Successful supply-side interdictions into illegal drug markets are predicated on the responsiveness of drug prices to enforcement and the price elasticity of demand for addictive drugs. We present causal estimates that targeted interventions aimed at methamphetamine input markets ('precursor control') can temporarily increase retail street prices, but methamphetamine consumption is weakly responsive to higher drug prices. After the supply interventions, purity-adjusted prices increased then quickly returned to pre-treatment levels within 6-12 months, demonstrating the short-term effects of precursor control. The price elasticity of methamphetamine demand is -0.13 to -0.21 for self-admitted drug treatment admissions and between -0.24 and -0.28 for hospital inpatient admissions. We find some evidence of a positive cross-price effect for cocaine, but we do not find robust evidence that increases in methamphetamine prices increased heroin, alcohol, or marijuana drug use. This study can inform policy discussions regarding other synthesized drugs, including illicit use of pharmaceuticals. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  8. Demand Intensity, Market Parameters and Policy Responses towards Demand and Supply of Private Supplementary Tutoring in China

    Science.gov (United States)

    Kwok, Percy Lai Yin

    2010-01-01

    Based on some longitudinal studies of private tutoring in twelve cities, towns, municipalities and provinces of China, the paper endeavours to depict demand intensity, articulate market parameters and reflect on policy responses towards the demand-supply mechanism of the vast shadowy educational phenomena at primary and secondary levels. Such…

  9. Transactive Control of Commercial Buildings for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Hao, He; Corbin, Charles D.; Kalsi, Karanjit; Pratt, Robert G.

    2017-01-01

    Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Several case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.

  10. Reliability evaluation of microgrid considering incentive-based demand response

    Science.gov (United States)

    Huang, Ting-Cheng; Zhang, Yong-Jun

    2017-07-01

    Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

  11. Risk implications of investments in demand response from an aggregator perspective

    DEFF Research Database (Denmark)

    Katz, Jonas; Kitzing, Lena

    2016-01-01

    Aggregators are expected to play an important role in making households provide flexibility to the electricity system. We investigate the business case of aggregators offering a demand response product in a competitive retail market, then directly accessing their customers’ flexibility through...... gross margins and their probability distributions. We find that, for a case of Danish residential customers with optimistic assumptions on the available flexibility in terms of flexible volumes and load-shift time horizons, the benefits may be in the range of current investment cost for automation...... equipment. Furthermore, a Value-at-Risk analysis shows that income expectations are rather stable with more upside than downside potential. With foreseeable cost reductions for smart devices the aggregator business case might soon become attractive, particularly in markets with high shares of renewable...

  12. 2015 California Demand Response Potential Study - Charting California’s Demand Response Future. Interim Report on Phase 1 Results

    Energy Technology Data Exchange (ETDEWEB)

    Alstone, Peter; Potter, Jennifer; Piette, Mary Ann; Schwartz, Peter; Berger, Michael A.; Dunn, Laurel N.; Smith, Sarah J.; Sohn, Michael D.; Aghajanzadeh, Arian; Stensson, Sofia; Szinai, Julia

    2016-04-01

    Demand response (DR) is an important resource for keeping the electricity grid stable and efficient; deferring upgrades to generation, transmission, and distribution systems; and providing other customer economic benefits. This study estimates the potential size and cost of the available DR resource for California’s three investor-owned utilities (IOUs), as the California Public Utilities Commission (CPUC) evaluates how to enhance the role of DR in meeting California’s resource planning needs and operational requirements. As the state forges a clean energy future, the contributions of wind and solar electricity from centralized and distributed generation will fundamentally change the power grid’s operational dynamics. This transition requires careful planning to ensure sufficient capacity is available with the right characteristics – flexibility and fast response – to meet reliability needs. Illustrated is a snapshot of how net load (the difference between demand and intermittent renewables) is expected to shift. Increasing contributions from renewable generation introduces steeper ramps and a shift, into the evening, of the hours that drive capacity needs. These hours of peak capacity need are indicated by the black dots on the plots. Ultimately this study quantifies the ability and the cost of using DR resources to help meet the capacity need at these forecasted critical hours in the state.

  13. Developing an Algorithm to Consider Mutliple Demand Response Objectives

    Directory of Open Access Journals (Sweden)

    D. Behrens

    2018-02-01

    Full Text Available Due to technological improvement and changing environment, energy grids face various challenges, which, for example, deal with integrating new appliances such as electric vehicles and photovoltaic. Managing such grids has become increasingly important for research and practice, since, for example, grid reliability and cost benefits are endangered. Demand response (DR is one possibility to contribute to this crucial task by shifting and managing energy loads in particular. Realizing DR thereby can address multiple objectives (such as cost savings, peak load reduction and flattening the load profile to obtain various goals. However, current research lacks algorithms that address multiple DR objectives sufficiently. This paper aims to design a multi-objective DR optimization algorithm and to purpose a solution strategy. We therefore first investigate the research field and existing solutions, and then design an algorithm suitable for taking multiple objectives into account. The algorithm has a predictable runtime and guarantees termination.

  14. Dynamic pricing for demand response considering market price uncertainty

    DEFF Research Database (Denmark)

    Ghazvini, Mohammad Ali Fotouhi; Soares, Joao; Morais, Hugo

    2017-01-01

    Retail energy providers (REPs) can employ different strategies such as offering demand response (DR) programs, participating in bilateral contracts, and employing self-generation distributed generation (DG) units to avoid financial losses in the volatile electricity markets. In this paper......, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique. In the proposed model, the REP offers price-based DR programs while it faces uncertainties in the wholesale market price. The main contribution of this paper is using a robust optimization approach......,679 residential consumers. The deterministic approach and its robust counterpart are used to solve the problem. The results show that, with a slight decrease in the expected payoff, the REP can effectively protect itself against price variations. Offering time-variable retail rates also can increase the expected...

  15. Pilot Testing of Commercial Refrigeration-Based Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Hirsch, Adam [National Renewable Energy Lab. (NREL), Golden, CO (United States); Clark, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Deru, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Trenbath, Kim [National Renewable Energy Lab. (NREL), Golden, CO (United States); Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Studer, Daniel [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-10-08

    Supermarkets potentially offer a substantial demand response (DR) resource because of their high energy intensity and use patterns. This report describes a pilot project conducted to better estimate supermarket DR potential. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning (HVAC), lighting, and anti-condensate heaters. This project was concerned with evaluating DR using the refrigeration system and quantifying the DR potential inherent in supermarket refrigeration systems. Ancillary aims of the project were to identify practical barriers to the implementation of DR programs in supermarkets and to determine which high-level control strategies were most appropriate for achieving certain DR objectives. The scope of this project does not include detailed control strategy development for DR or development of a strategy for regional implementation of DR in supermarkets.

  16. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel; Goli, Sasank; Faulkner, David; McKane, Aimee

    2010-12-22

    This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demand response (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demand response (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

  17. Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Jennifer; Cappers, Peter

    2017-08-28

    The Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs research describe a variety of DR opportunities and the various bulk power system services they can provide. The bulk power system services are mapped to a generalized taxonomy of DR “service types”, which allows us to discuss DR opportunities and bulk power system services in fewer yet broader categories that share similar technological requirements which mainly drive DR enablement costs. The research presents a framework for the costs to automate DR and provides descriptions of the various elements that drive enablement costs. The report introduces the various DR enabling technologies and end-uses, identifies the various services that each can provide to the grid and provides the cost assessment for each enabling technology. In addition to a report, this research includes a Demand Response Advanced Controls Database and User Manual. They are intended to provide users with the data that underlies this research and instructions for how to use that database more effectively and efficiently.

  18. Design of demand side response model in energy internet demonstration park

    Science.gov (United States)

    Zhang, Q.; Liu, D. N.

    2017-08-01

    The implementation of demand side response can bring a lot of benefits to the power system, users and society, but there are still many problems in the actual operation. Firstly, this paper analyses the current situation and problems of demand side response. On this basis, this paper analyses the advantages of implementing demand side response in the energy Internet demonstration park. Finally, the paper designs three kinds of feasible demand side response modes in the energy Internet demonstration park.

  19. Automated data system for emergency meteorological response

    International Nuclear Information System (INIS)

    Kern, C.D.

    1975-01-01

    The Savannah River Plant (SRP) releases small amounts of radioactive nuclides to the atmosphere as a consequence of the production of radioisotopes. The potential for larger accidental releases to the atmosphere also exists, although the probability for most accidents is low. To provide for emergency meteorological response to accidental releases and to conduct research on the transport and diffusion of radioactive nuclides in the routine releases, a series of high-quality meteorological sensors have been located on towers in and about SRP. These towers are equipped with instrumentation to detect and record temperature and wind turbulence. Signals from the meterological sensors are brought by land-line to the SRL Weather Center-Analysis Laboratory (WC-AL). At the WC-AL, a Weather Information and Display (WIND) system has been installed. The WIND system consists of a minicomputer with graphical displays in the WC-AL and also in the emergency operating center (EOC) of SRP. In addition, data are available to the system from standard weat []er teletype services, which provide both routine surface weather observations and routine upper air wind and temperature observations for the southeastern United States. Should there be an accidental release to the atmosphere, available recorded data and computer codes would allow the calculation and display of the location, time, and downwind concentration of the atmospheric release. These data are made available to decision makers in near real-time to permit rapid decisive action to limit the consequences of such accidental releases. (auth)

  20. Varying Levels of Automation on UAS Operator Responses to Traffic Resolution Advisories in Civil Airspace

    Science.gov (United States)

    Kenny, Caitlin; Fern, Lisa

    2012-01-01

    Continuing demand for the use of Unmanned Aircraft Systems (UAS) has put increasing pressure on operations in civil airspace. The need to fly UAS in the National Airspace System (NAS) in order to perform missions vital to national security and defense, emergency management, and science is increasing at a rapid pace. In order to ensure safe operations in the NAS, operators of unmanned aircraft, like those of manned aircraft, may be required to maintain separation assurance and avoid loss of separation with other aircraft while performing their mission tasks. This experiment investigated the effects of varying levels of automation on UAS operator performance and workload while responding to conflict resolution instructions provided by the Tactical Collision Avoidance System II (TCAS II) during a UAS mission in high-density airspace. The purpose of this study was not to investigate the safety of using TCAS II on UAS, but rather to examine the effect of automation on the ability of operators to respond to traffic collision alerts. Six licensed pilots were recruited to act as UAS operators for this study. Operators were instructed to follow a specified mission flight path, while maintaining radio contact with Air Traffic Control and responding to TCAS II resolution advisories. Operators flew four, 45 minute, experimental missions with four different levels of automation: Manual, Knobs, Management by Exception, and Fully Automated. All missions included TCAS II Resolution Advisories (RAs) that required operator attention and rerouting. Operator compliance and reaction time to RAs was measured, and post-run NASA-TLX ratings were collected to measure workload. Results showed significantly higher compliance rates, faster responses to TCAS II alerts, as well as less preemptive operator actions when higher levels of automation are implemented. Physical and Temporal ratings of workload were significantly higher in the Manual condition than in the Management by Exception and

  1. 78 FR 21928 - Demand Response Coalition v. PJM Interconnection, L.L.C.; Notice of Complaint

    Science.gov (United States)

    2013-04-12

    ... Energy Regulatory Commission Demand Response Coalition v. PJM Interconnection, L.L.C.; Notice of... Regulatory Commission (Commission), 18 CFR 385.206, the Demand Response Coalition \\1\\ (Complainant) filed a... are therefore unenforceable. \\1\\ The Demand Response Coalition includes Comverge, Inc., Viridity...

  2. Market Design Project. Demand Response Resources in Sweden - a summary

    International Nuclear Information System (INIS)

    Fritz, Peter

    2006-06-01

    An important discussion in later years has been whether the necessary reserves in the electricity market are to be generated through normal market mechanisms, i.e. with the price as the primary controlling parameter, or if it requires a collectively financed capacity reserve and how regulations in such a case should be shaped. The issue is first and foremost a matter of where the line is drawn between that which 'the market' should handle and that which can be assured through regulation. Autumn 2002 Svenska Kraftnaet (the Swedish TSO) presented an investigation to the government in which it was suggested that the capacity balance should primarily be managed through the use of normal pricing mechanisms, but that the state should strengthen responsibility for the nation's capacity balance in the period up until 2008. When approaching an effect loss situation, spot prices and balancing power prices will skyrocket. Today, most people are in agreement that a condition for maintained delivery safety is that normal pricing mechanisms are in place and that consumption actually is affected by high prices. The main reason for this conclusion is that it is very expensive to keep production facilities in reserve for situations that are expected to occur very seldom - it is cheaper to encourage large customers to reduce their consumption. The other reason is that increased price sensitivity creates conditions for a more stable and more predictable pricing development in strained situations. While being aware that a response to increased demand is needed, we see too little of that on the market today. The aim of this project is to present concrete measures that will awaken this slumbering resource. In order to judge how much demand response that can reasonably be expected and if there is any financial gain for customers, electricity suppliers and grid operators; it has been necessary to cast a few predictions about future price peaks. We estimate price peaks in the 3-10 SEK

  3. A Retroactive-Burst Framework for Automated Intrusion Response System

    Directory of Open Access Journals (Sweden)

    Alireza Shameli-Sendi

    2013-01-01

    Full Text Available The aim of this paper is to present an adaptive and cost-sensitive model to prevent security intrusions. In most automated intrusion response systems, response selection is performed locally based on current threat without using the knowledge of attacks history. Another challenge is that a group of responses are applied without any feedback mechanism to measure the response effect. We address these problems through retroactive-burst execution of responses and a Response Coordinator (RC mechanism, the main contributions of this work. The retroactive-burst execution consists of several burst executions of responses with, at the end of each burst, a mechanism for measuring the effectiveness of the applied responses by the risk assessment component. The appropriate combination of responses must be considered for each burst execution to mitigate the progress of the attack without necessarily running the next round of responses, because of the impact on legitimate users. In the proposed model, there is a multilevel response mechanism. To indicate which level is appropriate to apply based on the retroactive-burst execution, we get help from a Response Coordinator mechanism. The applied responses can improve the health of Applications, Kernel, Local Services, Network Services, and Physical Status. Based on these indexes, the RC gives a general overview of an attacker’s goal in a distributed environment.

  4. Residential Demand Response Scheduling with Consideration of Consumer Preferences

    Directory of Open Access Journals (Sweden)

    Raka Jovanovic

    2016-01-01

    Full Text Available This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the job scheduling can be done at a lower cost. The model is evaluated by using the real data provided by the Department of Energy & Climate Change, UK. In the computational experiments, we examine the relation between the satisfaction of consumers based on the appliance usage preferences and the electricity costs by exploring the Pareto front of the related objective functions. The results show that the proposed model leads to significant savings in electricity cost, while maintaining a good level of customer satisfaction.

  5. Electricity Customer Clustering Following Experts’ Principle for Demand Response Applications

    Directory of Open Access Journals (Sweden)

    Jimyung Kang

    2015-10-01

    Full Text Available The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is no guarantee that the clustering results are applicable to real domains. In other words, the results might not coincide with those of domain experts. In this paper, we focus on formulating clusters that are applicable to real applications based on domain expert knowledge. More specifically, we try to define a distance between customers that generates clusters that are applicable to demand response applications. First, the k-sliding distance, which is a new distance between two electricity customers, is proposed for customer clustering. The effect of k-sliding distance is verified by expert knowledge. Second, a genetic programming framework is proposed to automatically determine a more improved distance measure. The distance measure generated by our framework can be considered as a reflection of the clustering principles of domain experts. The results of the genetic programming demonstrate the possibility of deriving clustering principles.

  6. An Informatics Approach to Demand Response Optimization in Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Simmhan, Yogesh; Aman, Saima; Cao, Baohua; Giakkoupis, Mike; Kumbhare, Alok; Zhou, Qunzhi; Paul, Donald; Fern, Carol; Sharma, Aditya; Prasanna, Viktor K

    2011-03-03

    Power utilities are increasingly rolling out “smart” grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response,Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid.

  7. Automated drop-on-demand system with real-time gravimetric control for precise dosage formulation.

    Science.gov (United States)

    Sahay, A; Brown, M; Muzzio, F; Takhistov, Paul

    2013-04-01

    Many of the therapies for personalized medicine have few dosage options, and the successful translation of these therapies to the clinic is significantly dependent on the drug/formulation delivery platform. We have developed a lab-scale integrated system for microdosing of drug formulations with high accuracy and precision that is capable of feedback control. The designed modular drug dispensing system includes a microdispensing valve unit and is fully automated with a LabVIEW-controlled computer interface. The designed system is capable of dispensing drug droplets with volumes ranging from nanoliters to microliters with high accuracy (relative standard deviation gravimetric control.

  8. Uganda Coffee Supply Response and Export Demand: An ...

    African Journals Online (AJOL)

    Econometric methods were used to estimate the supply and demand functions for Uganda's coffee using time series data for the period 1971-91. Eight major importing countries for Uganda's coffee: U.S., U.K., Japan, France, Italy, Spain, Germany, and the Netherlands were considered in export demand analysis.

  9. Fast demand response in support of the active distribution network

    NARCIS (Netherlands)

    MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

    2013-01-01

    Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

  10. Price responsive load programs: U.S. experience in creating markets for peak demand reductions

    International Nuclear Information System (INIS)

    Goldberg, Miriam L.; Michelman, Thomas; Rosenberg, Mitchell

    2003-01-01

    Demand response programs use a variety of pricing mechanisms to induce end-use customers to reduce demand at specified periods. U.S. distribution utilities, regional market operators, and their regulators have implemented demand response programs with the objectives of improving electric system reliability, avoiding price spikes, and relieving local transmission congestion. This paper reviews the design and performance of market-linked demand response programs operated in 2001 and 2002, focusing on the relationship between program design and customer participation and the development of accurate and feasible methods to measure demand response at the facility level

  11. A novel incentive-based retail demand response program for collaborative participation of small customers

    NARCIS (Netherlands)

    Zehir, M. A.; Wevers, M. H.; Batman, A.; Bagriyanik, M.; Hurink, J. L.; Kucuk, U.; Soares, F. J.; Ozdemir, A.

    2017-01-01

    Integration of aggregated demand response into the wholesale electricity market is an emerging field of research. Contrary to conventional service providers, most of the demand side participants act voluntarily. However, due to wholesale market regulations, reliable and effective participation of

  12. Selective responsiveness: Online public demands and government responsiveness in authoritarian China.

    Science.gov (United States)

    Su, Zheng; Meng, Tianguang

    2016-09-01

    The widespread use of information and communication technology (ICT) has reshaped the public sphere in the digital era, making online forums a new channel for political participation. Using big data analytics of full records of citizen-government interactions from 2008 to early 2014 on a nationwide political forum, we find that authoritarian China is considerably responsive to citizens' demands with a rapid growth of response rate; however, government responsiveness is highly selective, conditioning on actors' social identities and the policy domains of their online demands. Results from logistic and duration models suggest that requests which made by local citizens, expressed collectively, focused on the single task issue, and are closely related to economic growth are more likely to be responded to. These strategies adopted by Chinese provincial leaders reveal the scope and selectivity of authoritarian responsiveness. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Individual Differences in Response to Automation: The Five Factor Model of Personality

    Science.gov (United States)

    Szalma, James L.; Taylor, Grant S.

    2011-01-01

    This study examined the relationship of operator personality (Five Factor Model) and characteristics of the task and of adaptive automation (reliability and adaptiveness--whether the automation was well-matched to changes in task demand) to operator performance, workload, stress, and coping. This represents the first investigation of how the Five…

  14. 2025 California Demand Response Potential Study - Charting California’s Demand Response Future. Final Report on Phase 2 Results

    Energy Technology Data Exchange (ETDEWEB)

    Alstone, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Potter, Jennifer [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schwartz, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Berger, Michael A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dunn, Laurel N. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Aruab [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stensson, Sofia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Szinai, Julie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Walter, Travis [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKenzie, Lucy [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Lavin, Luke [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Schneiderman, Brendan [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Mileva, Ana [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Cutter, Eric [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Olson, Arne [Energy and Environmental Economics, Inc. (E3), San Francisco, CA (United States); Bode, Josh [Nexant, Inc., Nashville, TN (United States); Ciccone, Adriana [Nexant, Inc., Nashville, TN (United States); Jain, Ankit [Nexant, Inc., Nashville, TN (United States)

    2017-03-01

    California’s legislative and regulatory goals for renewable energy are changing the power grid’s dynamics. Increased variable generation resource penetration connected to the bulk power system, as well as, distributed energy resources (DERs) connected to the distribution system affect the grid’s reliable operation over many different time scales (e.g., days to hours to minutes to seconds). As the state continues this transition, it will require careful planning to ensure resources with the right characteristics are available to meet changing grid management needs. Demand response (DR) has the potential to provide important resources for keeping the electricity grid stable and efficient, to defer upgrades to generation, transmission and distribution systems, and to deliver customer economic benefits. This study estimates the potential size and cost of future DR resources for California’s three investor-owned utilities (IOUs): Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE), and San Diego Gas & Electric Company (SDG&E). Our goal is to provide data-driven insights as the California Public Utilities Commission (CPUC) evaluates how to enhance DR’s role in meeting California’s resource planning needs and operational requirements. We address two fundamental questions: 1. What cost-competitive DR service types will meet California’s future grid needs as it moves towards clean energy and advanced infrastructure? 2. What is the size and cost of the expected resource base for the DR service types?

  15. Estimating Demand Response Market Potential Among Large Commercialand Industrial Customers:A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Cappers, Peter

    2007-01-01

    Demand response is increasingly recognized as an essentialingredient to well functioning electricity markets. This growingconsensus was formalized in the Energy Policy Act of 2005 (EPACT), whichestablished demand response as an official policy of the U.S. government,and directed states (and their electric utilities) to considerimplementing demand response, with a particular focus on "price-based"mechanisms. The resulting deliberations, along with a variety of stateand regional demand response initiatives, are raising important policyquestions: for example, How much demand response is enough? How much isavailable? From what sources? At what cost? The purpose of this scopingstudy is to examine analytical techniques and data sources to supportdemand response market assessments that can, in turn, answer the secondand third of these questions. We focus on demand response for large(>350 kW), commercial and industrial (C&I) customers, althoughmany of the concepts could equally be applied to similar programs andtariffs for small commercial and residential customers.

  16. An online learning approach to dynamic pricing for demand response

    OpenAIRE

    Jia, Liyan; Tong, Lang; Zhao, Qing

    2014-01-01

    In this paper, the problem of optimal dynamic pricing for retail electricity with an unknown demand model is considered. Under the day-ahead dynamic pricing (a.k.a. real time pricing) mechanism, a retailer obtains electricity in a twosettlement wholesale market and serves its customers in real time. Without knowledge on the aggregated demand function of its customers, the retailer aims to maximize its retail surplus by sequentially adjusting its price based on the behavior of its customers in...

  17. Efficient Algorithm for Scalable Event-based Demand Response Management in Microgrids

    OpenAIRE

    Karapetyan, Areg; Khonji, Majid; Chau, Chi-Kin; Elbassioni, Khaled; Zeineldin, H. H.

    2016-01-01

    Demand response management has become one of the key enabling technologies for smart grids. Motivated by the increasing demand response incentives offered by service operators, more customers are subscribing to various demand response programs. However, with growing customer participation, the problem of determining the optimal loads to be curtailed in a microgrid during contingencies within a feasible time frame becomes computationally hard. This paper proposes an efficient approximation alg...

  18. Review of barriers to the introduction of residential demand response : A case study in the Netherlands

    NARCIS (Netherlands)

    Weck, M. H J; van Hooff, J.; van Sark, W. G J H M

    Demand response, defined as the shifting of electricity demand, is generally believed to have value both for the grid and for the market: by matching demand more closely to supply, consumers could profit from lower prices, while in a smart grid environment, more renewable electricity can be used and

  19. 78 FR 38023 - Demand Response Supporters v. New York Independent System Operator, Inc.; Notice of Complaint

    Science.gov (United States)

    2013-06-25

    ... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL13-74-000] Demand Response... Practice and Procedure of the Federal Energy Regulatory Commission (Commission), 18 CFR 385.206, Demand..., Inc. (NYISO or Respondents), seeking an order requiring NYISO to amend its tariffs to allow demand...

  20. Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alkadi, Nasr [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ma, Ookie [USDOE Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

    2013-09-01

    Demand response has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles for demand response that can provide more regional understanding and can be inserted into analysis software for further study.

  1. Automated Metadata Formatting for Cornell’s Print-on-Demand Books

    Directory of Open Access Journals (Sweden)

    Dianne Dietrich

    2009-11-01

    Full Text Available Cornell University Library has made Print-On Demand (POD books available for many of its digitized out-of-copyright books. The printer must be supplied with metadata from the MARC bibliographic record in order to produce book covers. Although the names of authors are present in MARC records, they are given in an inverted order suitable for alphabetical filing rather than the natural order that is desirable for book covers. This article discusses a process for parsing and manipulating the MARC author strings to identify their various component parts and to create natural order strings. In particular, the article focuses on processing non-name information in author strings, such as titles that were commonly used in older works, e.g., baron or earl, and suffixes appended to names, e.g., "of Bolsena." Relevant patterns are identified and a Python script is used to manipulate the author name strings.

  2. The adaptative response of jaw muscles to varying functional demands

    NARCIS (Netherlands)

    Grünheid, T.; Langenbach, G.E.J.; Korfage, J.A.M.; Zentner, A.; van Eijden, T.M.G.J.

    2009-01-01

    Jaw muscles are versatile entities that are able to adapt their anatomical characteristics, such as size, cross-sectional area, and fibre properties, to altered functional demands. The dynamic nature of muscle fibres allows them to change their phenotype to optimize the required contractile function

  3. Implementation and Test of Demand Response using Behaviour Descriptions

    DEFF Research Database (Denmark)

    Kullmann, Daniel; Gehrke, Oliver; Bindner, Henrik W.

    2011-01-01

    The term Smart Grid describes the effort to enable the integration of large numbers of renewable distributed energy resources into the power grid. The fluctuations inherent in renewable energy resources imply the need to also integrate the demand side actively into the control of the power system...

  4. Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty

    International Nuclear Information System (INIS)

    Hu, Ming-Che; Lu, Su-Ying; Chen, Yen-Haw

    2016-01-01

    Highlights: • Analyze the impact of a demand response program under uncertainty. • Stochastic Nash–Cournot competition model is formulated. • Case study of the Taiwanese electric power market is conducted. • Demand response decreases power price, generation, and emissions. • Demand uncertainty increases energy price and supply risk in the results. - Abstract: In the electricity market, demand response programs are designed to shift peak demand and enhance system reliability. A demand response program can reduce peak energy demand, power transmission congestion, or high energy-price conditions by changing consumption patterns. The purpose of this research is to analyze the impact of a demand response program in the energy market, under demand uncertainty. A stochastic–multiobjective Nash–Cournot competition model is formulated to simulate demand response in an uncertain energy market. Then, Karush–Kuhn–Tucker optimality conditions and a linear complementarity problem are derived for the stochastic Nash–Cournot model. Accordingly, the linear complementarity problem is solved and its stochastic market equilibrium solution is determined by using a general algebraic modeling system. Additionally, the case of the Taiwanese electric power market is taken up here, and the results show that a demand response program is capable of reducing peak energy consumption, energy price, and carbon dioxide emissions. The results show that demand response program decreases electricity price by 2–10%, total electricity generation by 0.5–2%, and carbon dioxide emissions by 0.5–2.5% in the Taiwanese power market. In the simulation, demand uncertainty leads to an 2–7% increase in energy price and supply risk in the market. Additionally, tradeoffs between cost and carbon dioxide emissions are presented.

  5. Performance Assessment of Aggregation Control Services for Demand Response

    DEFF Research Database (Denmark)

    Bondy, Daniel Esteban Morales; Costanzo, Giuseppe Tommaso; Heussen, Kai

    2014-01-01

    Aggregation algorithms that provide services to the grid via demand side management are moving from research ideas to the market. With the diversity of the technology delivering such services, it becomes essential to establish transparent performance standards from a service delivery perspective...... of the quality of service provided by an aggregation control algorithm. By a detailed case study we present and an application of the index, comparing the performance of two different control architectures for demand side management delivering a distribution grid service........ This paper formulates performance measures and an index to evaluate in hind sight the quality of service delivery by an aggregator, both with respect to ancillary service and asset management service. The index is based on requirements formulated in service contracts and provides an overall assessment...

  6. Demand response concepts in the German industry; Konzepte zur Lastreaktion in der deutschen Industrie

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von; Gobmaier, Thomas [Forschungsstelle fuer Energiewirtschaft (FfE) e.V., Muenchen (Germany)

    2011-07-01

    In the German industry the concept of load management for peak shaving is well established. Pooling these reserve power enables reliable power supply at short notice. In the U.S. this business concept - called Demand Response - is already quite successful. The article summarizes findings on the status quo and the technical and economic potential of implementing Demand Response in the German industry. (orig.)

  7. Demand Response in Low Voltage Distribution Networks with High PV Penetration

    DEFF Research Database (Denmark)

    Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    generation and load forecasts, network topology and market price signals as inputs, limits of network voltages, line power flows, transformer loading and demand response dynamics as constraints to find the required demand response at each time step. The proposed method can be used by the DSOs to purchase...

  8. Corporate Environmental Responsibility in Demand Networks (summary section only)

    OpenAIRE

    Kovács, Gyöngyi

    2006-01-01

    Research on corporate responsibility has traditionally focused on the responsibilities of companies within their corporate boundaries only. Yet this view is challenged today as more and more companies face the situation in which the environmental and social performance of their suppliers, distributors, industry or other associated partners impacts on their sales performance and brand equity. Simultaneously, policy-makers have taken up the discussion on corporate responsibility from the perspe...

  9. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Galetovic, Alexander [Facultad de Ciencias Economicas y Empresariales, Universidad de los Andes, Santiago (Chile); Munoz, Cristian M. [Departamento de Ingenieria Electrica, Universidad de Chile, Mariano Sanchez Fontecilla 310, piso 3 Las Condes, Santiago (Chile)

    2009-02-15

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower. (author)

  10. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    International Nuclear Information System (INIS)

    Galetovic, Alexander; Munoz, Cristian M.

    2009-01-01

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower. (author)

  11. Price responsiveness of demand for cigarettes: does rationality matter?

    Science.gov (United States)

    Laporte, Audrey

    2006-01-01

    Meta-analysis is applied to aggregate-level studies that model the demand for cigarettes using static, myopic, or rational addiction frameworks in an attempt to synthesize key findings in the literature and to identify determinants of the variation in reported price elasticity estimates across studies. The results suggest that the rational addiction framework produces statistically similar estimates to the static framework but that studies that use the myopic framework tend to report more elastic price effects. Studies that applied panel data techniques or controlled for cross-border smuggling reported more elastic price elasticity estimates, whereas the use of instrumental variable techniques and time trends or time dummy variables produced less elastic estimates. The finding that myopic models produce different estimates than either of the other two model frameworks underscores that careful attention must be given to time series properties of the data.

  12. Agricultural sectoral demand and crop productivity response across the world

    Science.gov (United States)

    Johnston, M.; Ray, D. K.; Cassidy, E. S.; Foley, J. A.

    2013-12-01

    With an increasing and increasingly affluent population, humans will need to roughly double agricultural production by 2050. Continued yield growth forms the foundation of all future strategies aiming to increase agricultural production while slowing or eliminating cropland expansion. However, a recent analysis by one of our co-authors has shown that yield trends in many important maize, wheat and rice growing regions have begun stagnating or declining from the highs seen during the green revolution (Ray et al. 2013). Additional research by our group has shown that nearly 50% of new agricultural production since the 1960s has gone not to direct human consumption, but instead to animal feed and other industrial uses. Our analysis for GLP looks at the convergence of these two trends by examining time series utilization data for 16 of the biggest crops to determine how demand from different sectors has shaped our land-use and intensification strategies around the world. Before rushing headlong into the next agricultural doubling, it would be prudent to first consult our recent agricultural history to better understand what was driving past changes in production. Using newly developed time series dataset - a fusion of cropland maps with historic agricultural census data gathered from around the world - we can examine yield and harvested area trends over the last half century for 16 top crops. We combine this data with utilization rates from the FAO Food Balance Sheet to see how demand from different sectors - food, feed, and other - has influenced long-term growth trends from the green revolution forward. We will show how intensification trends over time and across regions have grown or contracted depending on what is driving the change in production capacity. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield Trends Are Insufficient to Double Global Crop Production by 2050. PLoS ONE 8(6): e66428. doi:10.1371/journal.pone.0066428

  13. Benefits of Demand Side Response in Providing Frequency Response Service in the Future GB Power System

    Directory of Open Access Journals (Sweden)

    Fei eTeng

    2015-08-01

    Full Text Available The demand for ancillary service is expected to increase significantly in the future GB electricity system due to high penetration of wind. In particular, the need for frequency response, required to deal with sudden frequency drops following a loss of generator, will increase because of the limited inertia capability of wind plants. This paper quantifies the requirements for primary frequency response and analyses the benefits of frequency response provision from DSR. The results show dramatic changes in frequency response requirements driven by high penetration of wind. Case studies carried out by using an advanced stochastic generation scheduling model suggest that the provision of frequency response from DSR could greatly reduce the system operation cost, wind curtailment and carbon emissions in the future GB system characterised by high penetration of wind. Furthermore, the results demonstrate that the benefit of DSR shows significant diurnal and seasonal variation, whereas an even more rapid (instant delivery of frequency response from DSR could provide significant additional value. Our studies also indicate that the competing technologies to DSR, namely battery storage and more flexible generation could potentially reduce its value by up to 35%, still leaving significant room to deploy DSR as frequency response provider.

  14. Religiosity, attitude and the demand for socially responsible products

    NARCIS (Netherlands)

    Graafland, Johan

    In this paper, we examine the relationship between various Christian denominations and attitude and behavior regarding consumption of socially responsible (SR) products. Literature on the relationship between religiosity and pro-social behavior has shown that religiosity strengthens positive

  15. Water demand management: A policy response to climate change

    International Nuclear Information System (INIS)

    Rivers, R.; Tate, D.

    1990-01-01

    The impacts of climate change on the water resources of the Great Lakes region are discussed. It is predicted that there will be a relative water scarcity in the Great Lakes basin of Ontario as climate changes occur over the next two decades. Declines in water supply will be accompanied by deterioration in the quality of fresh water as higher temperatures and higher relative quantities of discharged wastewater to water bodies reduce both assimilative and dilutive capacity. The most cost effective policy is to encourage water conservation through programs of water demand management. Water should be priced at the point at which its marginal cost is equal to its marginal product, ie. if priced any higher, less efficient substitutes would be used. Not only would water usage, and subsequent degradation of used water, be reduced, but energy and other cost savings would be achieved. The additional costs that apply to water users could be returned to the communities as additional revenue to be applied against sewage treatment upgrades and other environmental enhancements. Communities involved in water study should consider the development of water use analysis models to assist with decision making about allocation, pricing and availability of water supplies. 10 refs

  16. Regional Energy Demand Responses To Climate Change. Methodology And Application To The Commonwealth Of Massachusetts

    International Nuclear Information System (INIS)

    Amato, A.D.; Ruth, M.; Kirshen, P.; Horwitz, J.

    2005-01-01

    Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles. In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand

  17. Strategic Demand-Side Response to Wind Power Integration

    DEFF Research Database (Denmark)

    Daraeepour, Ali; Kazempour, Seyyedjalal; Patiño-Echeverri, Dalia

    2016-01-01

    This paper explores the effects of allowing large, price-responsive consumers to provide reserves in a power system with significant penetration of wind energy. A bilevel optimization model represents the utility maximization problem of a large consumer, subject to a stochastic day-ahead co-optim...

  18. Relationship-Based Infant Care: Responsive, on Demand, and Predictable

    Science.gov (United States)

    Petersen, Sandra; Wittmer, Donna

    2008-01-01

    Young babies are easily overwhelmed by the pain of hunger or gas. However, when an infant's day is filled with caregiving experiences characterized by quick responses to his cries and accurate interpretations of the meaning of his communication, the baby learns that he can count on being fed and comforted. He begins to develop trust in his teacher…

  19. Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

    Directory of Open Access Journals (Sweden)

    Shengchun Yang

    2016-01-01

    Full Text Available Demand response (DR programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL, plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.

  20. Cardiac responsiveness to attention-demanding tasks in socially maladaptive children

    NARCIS (Netherlands)

    Althaus, M; Aarnoudse, CC; Minderaa, RB; Mulder, Gysbertus; Mulder, Lambertus

    Cardiac responsiveness to attention-demanding tasks in socially maladaptive children A psychofysiological study of the cardiac adaptivity to attention-demanding reaction time tasks demonstrated that children with a lesser variant of the pervasive developmental disorder (DSM-IV: PDDNOS) exhibit less

  1. Response of pressurized water reactor (PWR) to network power generation demands

    International Nuclear Information System (INIS)

    Schreiner, L.A.

    1991-01-01

    The flexibility of the PWR type reactor in terms of response to the variations of the network power demands, is demonstrated. The factors that affect the transitory flexibility and some design prospects that allow the reactor fits the requirements of the network power demands, are also discussed. (M.J.A.)

  2. How task demands shape brain responses to visual food cues.

    Science.gov (United States)

    Pohl, Tanja Maria; Tempelmann, Claus; Noesselt, Toemme

    2017-06-01

    Several previous imaging studies have aimed at identifying the neural basis of visual food cue processing in humans. However, there is little consistency of the functional magnetic resonance imaging (fMRI) results across studies. Here, we tested the hypothesis that this variability across studies might - at least in part - be caused by the different tasks employed. In particular, we assessed directly the influence of task set on brain responses to food stimuli with fMRI using two tasks (colour vs. edibility judgement, between-subjects design). When participants judged colour, the left insula, the left inferior parietal lobule, occipital areas, the left orbitofrontal cortex and other frontal areas expressed enhanced fMRI responses to food relative to non-food pictures. However, when judging edibility, enhanced fMRI responses to food pictures were observed in the superior and middle frontal gyrus and in medial frontal areas including the pregenual anterior cingulate cortex and ventromedial prefrontal cortex. This pattern of results indicates that task sets can significantly alter the neural underpinnings of food cue processing. We propose that judging low-level visual stimulus characteristics - such as colour - triggers stimulus-related representations in the visual and even in gustatory cortex (insula), whereas discriminating abstract stimulus categories activates higher order representations in both the anterior cingulate and prefrontal cortex. Hum Brain Mapp 38:2897-2912, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  3. Time-of-use based electricity demand response for sustainable manufacturing systems

    International Nuclear Information System (INIS)

    Wang, Yong; Li, Lin

    2013-01-01

    As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems. - Highlights: • We propose a TOU based demand response approach for manufacturing systems. • Both electricity consumption and demand are integrated into the system modeling. • Energy-efficient and demand-responsive production scheduling problems are formulated. • The meta-heuristic solution technique is provided. • The effects of various factors on the scheduling solutions are examined

  4. How price responsive is the demand for specialty care?

    Science.gov (United States)

    Maciejewski, Matthew L; Liu, Chuan-Fen; Kavee, Andrew L; Olsen, Maren K

    2012-08-01

    Outpatient visit co-payments have increased in recent years. We estimate the patient response to a price change for specialty care, based on a co-payment increase from $15 to $50 per visit for veterans with hypertension. A retrospective cohort of veterans required to pay co-payments was compared with veterans exempt from co-payments whose nonequivalence was reduced via propensity score matching. Specialty care expenditures in 2000-2003 were estimated via a two-part mixed model to account for the correlation of the use and level outcomes over time, and results from this correlated two-part model were compared with an uncorrelated two-part model and a correlated random intercept two-part mixed model. A $35 specialty visit co-payment increase had no impact on the likelihood of seeking specialty care but induced lower specialty expenditures over time among users who were required to pay co-payments. The log ratio of price responsiveness (semi-elasticity) for specialty care increased from -0.25 to -0.31 after the co-payment increase. Estimates were similar across the three models. A significant increase in specialty visit co-payments reduced specialty expenditures among patients obtaining medications at the Veterans Affairs medical centers. Longitudinal expenditure analysis may be improved using recent advances in two-part model methods. Published 2011. This article is a US Government work and is in the public domain in the USA.

  5. 75 FR 54063 - Demand Response Compensation in Organized Wholesale Energy Markets; Technical Conference

    Science.gov (United States)

    2010-09-03

    ... staff-led technical conference regarding two issues pertaining to demand response compensation, as... be available. Anyone with Internet access interested in viewing this conference can do so by...

  6. Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Marks, Gary [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wilcox, Edmund [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-02

    California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agricultural irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as

  7. The impact of residential demand response on the costs of a fossil-free system reserve

    DEFF Research Database (Denmark)

    Katz, Jonas; Balyk, Olexandr; Hevia Koch, Pablo Alejandro

    2016-01-01

    In order to achieve a better understanding of the system value of residential demand response, we study the potential impact of flexible demand on the costs of system reserves in a fossil-free electricity supply. Comparing these costs with traditional means of regulation our analysis aims...... to contribute to determining the least-cost options for regulation in a fossil-free power system. We extend an existing energy system model with demand response and reserve modelling and analyse the impact for the case of Denmark in 2035 to reflect a system based on renewable resources for electricity...

  8. Demand Response Integration Through Agent-Based Coordination of Consumers in Virtual Power Plants

    DEFF Research Database (Denmark)

    Clausen, Anders; Umair, Aisha; Ma, Zheng

    2016-01-01

    Power Plant design that is able to balance the demand of energy-intensive, industrial loads with the supply situation in the electricity grid. The proposed Virtual Power Plant design uses a novel inter-agent, multi-objective, multi-issue negotiation mechanism, to coordinate the electricity demands...... of industrial loads. Coordination happens in response to Demand Response events, while considering local objectives in the industrial domain. We illustrate the applicability of our approach on a Virtual Power Plant scenario with three simulated greenhouses. The results suggest that the proposed design is able...

  9. Coordinated Demand Response and Distributed Generation Management in Residential Smart Microgrids

    DEFF Research Database (Denmark)

    Anvari-Moghaddam, Amjad; Mokhtari, Ghassem; Guerrero, Josep M.

    2016-01-01

    potentials to increase the functionality of a typical demand-side management (DSM) strategy, and typical implementation of building-level DERs by integrating them into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems....... Finally, the effectiveness and applicability of the proposed model is tested and validated in different operating modes compared to the existing models. The findings of this chapter show that by the use of an expert EMS that coordinates supply and demand sides simultaneously, it is very possible not only......Nowadays with the emerging of small-scale integrated energy systems (IESs) in form of residential smart microgrids (SMGs), a large portion of energy can be saved through coordinated scheduling of smart household devices and management of distributed energy resources (DERs). There are significant...

  10. Future Earth: Reducing Loss By Automating Response to Earthquake Shaking

    Science.gov (United States)

    Allen, R. M.

    2014-12-01

    Earthquakes pose a significant threat to society in the U.S. and around the world. The risk is easily forgotten given the infrequent recurrence of major damaging events, yet the likelihood of a major earthquake in California in the next 30 years is greater than 99%. As our societal infrastructure becomes ever more interconnected, the potential impacts of these future events are difficult to predict. Yet, the same inter-connected infrastructure also allows us to rapidly detect earthquakes as they begin, and provide seconds, tens or seconds, or a few minutes warning. A demonstration earthquake early warning system is now operating in California and is being expanded to the west coast (www.ShakeAlert.org). In recent earthquakes in the Los Angeles region, alerts were generated that could have provided warning to the vast majority of Los Angelinos who experienced the shaking. Efforts are underway to build a public system. Smartphone technology will be used not only to issue that alerts, but could also be used to collect data, and improve the warnings. The MyShake project at UC Berkeley is currently testing an app that attempts to turn millions of smartphones into earthquake-detectors. As our development of the technology continues, we can anticipate ever-more automated response to earthquake alerts. Already, the BART system in the San Francisco Bay Area automatically stops trains based on the alerts. In the future, elevators will stop, machinery will pause, hazardous materials will be isolated, and self-driving cars will pull-over to the side of the road. In this presentation we will review the current status of the earthquake early warning system in the US. We will illustrate how smartphones can contribute to the system. Finally, we will review applications of the information to reduce future losses.

  11. Demand Response in Europe's Electricity Sector: Market barriers and outstanding issues

    International Nuclear Information System (INIS)

    Eid, Cherrelle

    2015-01-01

    In October 2014, Europe's drive for sustainability has been further continued with the set objectives for 2030, aiming for 40% emission reduction compared to 1990 levels and at least a 27% share of renewable energy sources. For the longer term, the European Commission (EC) targets a zero CO 2 emitting electricity sector in 2050. Those objectives for the electricity sector have a large impact on the expected development of electricity generation, but also on the evolution of demand. To meet those objectives, a larger share of electricity supply will come from intermittent sources like wind turbines and solar panels. In an electric system that is largely based on renewable electricity sources, it is desired to have higher electricity consumption in moments when more renewable electricity is being produced, and a lower consumption in times of lower renewable production. Demand response is related to the adaptability of the electricity demand to the availability of supply. The development of demand response is rooted in the need for carbon emission reductions and for efficient use of installed generation capacities with the growth of power consumption. In addition to providing flexibility to the electric system, demand response could be a direct source of revenue to households and businesses. In 2013, in the United States, businesses and homeowners earned over $2.2 billion in revenues from demand response together with other avoided investment in grid infrastructure and power plants. This source of direct revenue could also be made available in Europe and would release financial benefits to local economies (SEDC, 2014). The reliability improvements as well as the economic and sustainability potential coming from a more responsive electricity demand are fully acknowledged. However, demand response is still immaturely developed in Europe. If Europe wants to make a step forward to a more sustainable electricity sector, the development of demand response is an

  12. Assessing drivers' response during automated driver support system failures with non-driving tasks.

    Science.gov (United States)

    Shen, Sijun; Neyens, David M

    2017-06-01

    With the increase in automated driver support systems, drivers are shifting from operating their vehicles to supervising their automation. As a result, it is important to understand how drivers interact with these automated systems and evaluate their effect on driver responses to safety critical events. This study aimed to identify how drivers responded when experiencing a safety critical event in automated vehicles while also engaged in non-driving tasks. In total 48 participants were included in this driving simulator study with two levels of automated driving: (a) driving with no automation and (b) driving with adaptive cruise control (ACC) and lane keeping (LK) systems engaged; and also two levels of a non-driving task (a) watching a movie or (b) no non-driving task. In addition to driving performance measures, non-driving task performance and the mean glance duration for the non-driving task were compared between the two levels of automated driving. Drivers using the automated systems responded worse than those manually driving in terms of reaction time, lane departure duration, and maximum steering wheel angle to an induced lane departure event. These results also found that non-driving tasks further impaired driver responses to a safety critical event in the automated system condition. In the automated driving condition, driver responses to the safety critical events were slower, especially when engaged in a non-driving task. Traditional driver performance variables may not necessarily effectively and accurately evaluate driver responses to events when supervising autonomous vehicle systems. Thus, it is important to develop and use appropriate variables to quantify drivers' performance under these conditions. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

  13. Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid

    Energy Technology Data Exchange (ETDEWEB)

    Amam, Saima; Natarajan, Sreedhar; Yin, Wei; Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

    2011-11-01

    We describe and demonstrate a prototype software architecture to support data-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los Angeles Smart Grid Demonstration Project. The architecture includes a semantic information repository that integrates diverse data sources to support DR, demand forecasting using scalable machine-learned models, and detection of load curtailment opportunities by matching complex event patterns.

  14. Real-Time Procurement Strategies of a Proactive Distribution Company with Aggregator-Based Demand Response

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Wang, Qi; Wang, Jianhui

    2016-01-01

    In this paper, we present a real-time trading framework for distribution networks where a rational aggregator is identified as a broker by contracting with individual demands and dealing with the distribution company. Demand response capability is characterized by the coexistence of elastic and i....... The proposed model is then transformed into a solvable mathematical program with equilibrium constraints through a primal-dual approach. A modified 33-bus distribution network is utilized to demonstrate the effectiveness of the proposed model....

  15. Energy-environment policy goals and instruments and electricity demand response. A framework for the analysis

    International Nuclear Information System (INIS)

    Rio, Pablo del; Hernandez, F.

    2004-01-01

    The environment and energy realms have traditionally been two major focus of attention of EU and Member State (MS) policy. This attention has intensified in recent years as a response to, both, internal and external events and strategies (i.e., the Kyoto Protocol). In this context, the EU and its MS have set ambitious goals in the environmental and energy contexts and are already implementing packages of policies and measures. Both policies interact. Although there might be conflicts between both, there are also mutually reinforcing effects with significant policy implications. Actually, as stated in the Amsterdam Treaty, environmental protection is one of the major goals of energy policy (together with 'security of supply' and 'competitive energy systems'). On the other hand, the energy sector is instrumental in the success of environmental policy. In this context, a wide array of measures are currently being implemented in the EU and its MS which have a more or less direct impact on the electricity market. Particularly, Demand Side Management (DSM) activities, promotion of electricity from renewable energy sources (RES-E) and measures aimed at the mitigation of Greenhouse Gas (GHG) emissions are arguably three major instruments which have the potential to contribute to energy and environmental goals. The effectiveness and impact of there measures depends to a large extent on the demand response in the electricity market. Some of there measures affect the electricity demand curve, while others do not have a direct impact on the demand curve but affect the quantity of electricity demand by displacing the electricity supply curve. In turn, the effectiveness of energy and environmental policies may be different when electricity demand response varies (i.e., different elasticity demand). This paper entails an initial effort to provide a theoretical framework for the analysis of the interactions between electricity demand response and the above mentioned energy

  16. Assessing long-term effects of demand response policies in wholesale electricity markets

    International Nuclear Information System (INIS)

    Cepeda, Mauricio; Saguan, Marcelo

    2014-05-01

    This paper deals with the practical problems related to long-term issues in electricity markets in the presence of demand response development. Different policies have been implemented around the world aiming to develop demand response potential. Externalities, in particular the CO 2 externality, have been one of the key elements in the debate on the effectiveness of different policies regarding demand response development. Policy makers have several options to deal with this externality. The most direct one is to correct the externality by setting a CO 2 price at a level that corresponds to the cost to society of the corresponding CO 2 emissions. One alternative solution could be to subsidize carbon-free technologies as demand response. In this paper we examine potential long-term impacts of these two policies. We rely on a long-term market simulation model that characterizes expansion decisions in a competitive regime. We test for each policy two different scenarios regarding the possibility of internalization of the CO 2 externality. The results show that differences in development policies affect both investments and social costs in the wholesale electricity market and confirm previous findings that a market-driven development of demand response with the internalization of the CO 2 externality is the most efficient approach. (authors)

  17. Demand response power system optimization in presence of renewable energy sources

    Directory of Open Access Journals (Sweden)

    Dumbrava Virgil

    2017-07-01

    Full Text Available This paper optimizes the price-based demand response of a large customer in a power system with stochastic production and classical fuel-supplied power plants. The implemented method of optimization, under uncertainty, is helpful to model both the utility functions for the consumers and their technical limitations. The consumers exposed to price-based demand can reduce their cost for electricity procurement by modifying their behavior, possibly shifting their consumption during the day to periods with low electricity prices. The demand is considered elastic to electricity price if the consumer is willing and capable to buy various amounts of energy at different price levels, the demand function being represented as purchasing bidding blocks. The demand response is seen also by the scientific literature as a possible source of the needed flexibility of modern power systems, while the flexibility of conventional generation technologies is restricted by technical constraints, such as ramp rates. This paper shows how wind power generation affects short term operation of the electricity system. Fluctuations in the amount of wind power fed into the grid require, without storage capacities, compensating changes in the output of flexible generators or in the consumers’ behavior. In the presented case study, we show the minimization of the overall costs in presence of stochastic wind power production. For highlighting the variability degree of production from renewable sources, four scenarios of production were formulated, with different probabilities of occurrence. The contribution brought by the paper is represented by the optimization model for demand-response of a large customer in a power system with fossil fueled generators and intermittent renewable energy sources. The consumer can reduce the power system costs by modifying his demand. The demand function is represented as purchasing bidding blocks for the possible price forecasted realizations

  18. Influential Factors for Accurate Load Prediction in a Demand Response Context

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Kjærgaard, Mikkel Baun; Jørgensen, Bo Nørregaard

    2016-01-01

    Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence....... Next, the time of day that is being predicted greatly influence the prediction which is related to the weather pattern. By presenting these results we hope to improve the modeling of building loads and algorithms for Demand Response planning.......Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence...

  19. Distributed generation and demand response dispatch for a virtual power player energy and reserve provision

    DEFF Research Database (Denmark)

    Faria, Pedro; Soares, Tiago; Vale, Zita

    2014-01-01

    Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets’ environment, with deep concerns at the efficiency level. In this context, grid operators, market...... operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper...... proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources’ participation can be performed in both energy and reserve contexts. This methodology contemplates...

  20. Approaches for Accommodating Demand Response in Operational Problems and Assessing its Value

    DEFF Research Database (Denmark)

    O'Connell, Niamh

    . However, before the necessary investments can be made to establish and operate this novel resource, its value must be determined. As with all current power system resources, if distributed demand response is deployed on a large scale it will be required to interface with the power system and market...... investments will be made to establish and operate the resource. A positive commercial assessment will signal to investors that the resource can offer a return on their investment, and that it can thrive in a competitive environment. We consider both the social welfare and commercial value of demand response...... or revenue through energy arbitrage or load curtailment. This does not rule out that there maybe certain power systems, or sections thereof, that are currently experiencing sufficient resource scarcity to result in a favourable environment for the successful implementation of demand response. At the current...

  1. An Economic Customer-Oriented Demand Response Model in Electricity Markets

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2018-01-01

    demand response (DR) models have been developed based on this concept, this will also be deemed as a disadvantage for them. In this paper, we propose an economic DR model based on economic theories and mathematical methods. In addition to abate the defects of price-elasticity based DR models...... response to price changes is considered. Therefore, the consumer demand curve is a unique curve versus price changes. In the concept of PED, the elasticity investigation is performed only in a single point or over a small interval of the curve instead of the whole curve which is not suitable. Since most......, the proposed model has the ability to respond to the various consumers with distinct responses to price changes and can also adjust the consumer's demands according to the consumer's preferences during different periods of a day....

  2. Modeling of demand response in electricity markets : effects of price elasticity

    International Nuclear Information System (INIS)

    Banda, E.C.; Tuan, L.A.

    2007-01-01

    A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

  3. Demand response pilot event conducted August 2,2011 : summary report.

    Energy Technology Data Exchange (ETDEWEB)

    Lincoln, Donald; Evans, Christoper

    2012-01-01

    Energy management in a commercial facility can be segregated into two areas: energy efficiency and demand response (DR). Energy efficiency focuses on steady-state load minimization. Demand response reduces load for event driven periods during the peak load. Demand-response-driven changes in electricity use are designed to be short-term in nature, centered on critical hours during the day when demand is high or when the electricity supplier's reserve margins are low. Due to the recent Federal Energy Regulatory Commission (FERC) Order 745, Demand Response Compensation in Organized Wholesale Energy Markets the potential annual compensation to Sandia National Laboratories (SNL) from performing DR ranges from $300K to $2,400K. While the current energy supply contract does not offer any compensation for participating in DR, there is benefit in understanding the issues and potential value in performing a DR event. This Report will be helpful in upcoming energy supply contract negotiations to quantify the energy savings and power reduction potential from DR at SNL. On August 25, 2011 the Facilities Management and Operations Center (FMOC) performed the first DR pilot event at SNL/NM. This report describes the details and results of this DR event.

  4. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids.

    Science.gov (United States)

    Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

    2018-01-09

    In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

  5. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

    Directory of Open Access Journals (Sweden)

    Claudia Pop

    2018-01-01

    Full Text Available In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.. In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

  6. World oil demand's shift toward faster growing and less price-responsive products and regions

    International Nuclear Information System (INIS)

    Dargay, Joyce M.; Gately, Dermot

    2010-01-01

    Using data for 1971-2008, we estimate the effects of changes in price and income on world oil demand, disaggregated by product - transport oil, fuel oil (residual and heating oil), and other oil - for six groups of countries. Most of the demand reductions since 1973-74 were due to fuel-switching away from fuel oil, especially in the OECD; in addition, the collapse of the Former Soviet Union (FSU) reduced their oil consumption substantially. Demand for transport and other oil was much less price-responsive, and has grown almost as rapidly as income, especially outside the OECD and FSU. World oil demand has shifted toward products and regions that are faster growing and less price-responsive. In contrast to projections to 2030 of declining per-capita demand for the world as a whole - by the U.S. Department of Energy (DOE), International Energy Agency (IEA) and OPEC - we project modest growth. Our projections for total world demand in 2030 are at least 20% higher than projections by those three institutions, using similar assumptions about income growth and oil prices, because we project rest-of-world growth that is consistent with historical patterns, in contrast to the dramatic slowdowns which they project. (author)

  7. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

    Science.gov (United States)

    Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

    2018-01-01

    In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced. PMID:29315250

  8. Optimal Load Response to Time-of-Use Power Price for Demand Side Management in Denmark

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2010-01-01

    -of-use power price for demand side management in order to save the energy costs as much as possible. 3 typical different kinds of loads (industrial load, residential load and commercial load) in Denmark are chosen as study cases. The energy costs decrease up to 9.6% with optimal load response to time......-of-use power price for different loads. Simulation results show that the optimal load response to time-of-use power price for demand side management generates different load profiles and reduces the load peaks. This kind of load patterns may also have significant effects on the power system normal operation....

  9. 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2011-08-01

    This report describes the work of the Industrial Demand Response (DR) Team of Lawrence Berkeley National Laboratory’s Demand Response Research Center (DRRC) from 2008-2010, in the context of its mandate to conduct and disseminate research that broadens the knowledge base of DR strategies, with a focus on the Industrial-Agricultural-Water (IAW) sector. Through research and case studies of industrial sectors and entities, the DRRC-IAW Team continued to assimilate knowledge on the feasibility of industrial DR strategies with an emphasis on technical and economic evaluation and worked to encourage implementation of these strategies.

  10. Demand Response of Thermostatic Loads by Optimized Switching-Fraction Broadcast

    DEFF Research Database (Denmark)

    Totu, Luminita Cristiana; Wisniewski, Rafal

    2014-01-01

    Demand response is an important Smart Grid concept that aims at facilitating the integration of volatile energy resources into the electricity grid. This paper considers the problem of managing large populations of thermostat-based devices with on/off operation. The objective is to enable demand...... response capabilities within the intrinsic flexibility of the population. A temperature distribution model based on Fokker-Planck partial differential equations is used to capture the behavior of the population. To ensure probability conservation and high accuracy of the numerical solution, Finite Volume...

  11. Demand response impacts on off-grid hybrid photovoltaic-diesel generator microgrids

    Directory of Open Access Journals (Sweden)

    Aaron St. Leger

    2015-08-01

    Full Text Available Hybrid microgrids consisting of diesel generator set(s and converter based power sources, such as solar photovoltaic or wind sources, offer an alternative to generator based off-grid power systems. The hybrid approach has been shown to be economical in many off-grid applications and can result in reduced generator operation, fuel requirements, and maintenance. However, the intermittent nature of demand and renewable energy sources typically require energy storage, such as batteries, to properly operate the hybrid microgrid. These batteries increase the system cost, require proper operation and maintenance, and have been shown to be unreliable in case studies on hybrid microgrids. This work examines the impacts of leveraging demand response in a hybrid microgrid in lieu of energy storage. The study is performed by simulating two different hybrid diesel generator—PV microgrid topologies, one with a single diesel generator and one with multiple paralleled diesel generators, for a small residential neighborhood with varying levels of demand response. Various system designs are considered and the optimal design, based on cost of energy, is presented for each level of demand response. The solar resources, performance of solar PV source, performance of diesel generators, costs of system components, maintenance, and operation are modeled and simulated at a time interval of ten minutes over a twenty-five year period for both microgrid topologies. Results are quantified through cost of energy, diesel fuel requirements, and utilization of the energy sources under varying levels of demand response. The results indicate that a moderate level of demand response can have significant positive impacts to the operation of hybrid microgrids through reduced energy cost, fuel consumption, and increased utilization of PV sources.

  12. MARKET SUPPLY RESPONSE AND DEMAND FOR LOCAL RICE IN NIGERIA: IMPLICATIONS FOR SELF-SUFFICIENCY POLICY

    Directory of Open Access Journals (Sweden)

    M RAHJI

    2009-03-01

    Full Text Available This study examined the supply response and demand for local rice in Nigeria between 1960 and 2004. A system of equations using secondary data was estimated by OLS and 2SLS techniques. Area planted with local rice is mainly affected by expected price of output, agriculture wage rate and by the partial adjustment coefficient. The short-run response elasticity is 0.077. The implied long-run response elasticity is 1.578. The partial adjustment measure is 0.049. This, points to the difficulty of supply response to changing economic conditions. The price elasticity of demand obtained is 0.841. The demand for local rice is thus price inelastic. Rice income elasticity is 0.3378. It is also inelastic. The ban on rice importation in Nigeria could be said to be a step in the right direction. This policy should be continued and policed. However, price, output and non-price incentives that can exert significant influence on rice supply response and demand are required if the self-sufficiency goal is to be achieved.

  13. Modelling of Hot Water Storage Tank for Electric Grid Integration and Demand Response Control

    DEFF Research Database (Denmark)

    Sinha, Rakesh; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    , selection of a proper model is equally important. The results obtained from comparison of two models (when input to the model is thermal energy demand) are present with their significance and advantages for grid integration and demand response. Models mathematics are shown in detail with the validation......District heating (DH), based on electric boilers, when integrated into electric network has potential of flexible load with direct/indirect storage to increase the dynamic stability of the grid in terms of power production and consumption with wind and solar. The two different models of electric...... boilers for grid integration are investigated: single mass model (with uniform temperature inside tank) and two mass model (with ideal single stratified layers). In order to investigate the influence of demand response and grid voltage quality with the measurable parameter of electrical boiler in practice...

  14. Design and Co-simulation of Hierarchical Architecture for Demand Response Control and Coordination

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Lévesque, Martin; Bak-Jensen, Birgitte

    2017-01-01

    Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this study, we propose a hierarchical DR architecture (HDRA) to control an...

  15. Stochastic frequency-security constrained scheduling of a microgrid considering price-driven demand response

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Anvari-Moghaddam, Amjad; Rashidizadeh-Kermani, Homa

    2018-01-01

    This paper proposes a two-stage stochastic model for optimal frequency-security constrained energy and reserve scheduling in an islanded residential microgrid (MG) with price-responsive loads. Based on this model, scheduling of the controllable units in both supply and demand sides is done in a w...

  16. 75 FR 15362 - Demand Response Compensation in Organized Wholesale Energy Markets

    Science.gov (United States)

    2010-03-29

    ...\\ Some ISOs and RTOs are engaged in stakeholder discussions concerning the coordination necessary between... PJM and its stakeholders to continue analyzing the effectiveness of PJM's demand response program with... payment of LMP minus components of the retail rate, on the theory that such an approach permits all...

  17. 76 FR 16657 - Demand Response Compensation in Organized Wholesale Energy Markets

    Science.gov (United States)

    2011-03-24

    ... CONTACT: David Hunger (Technical Information), Office of Energy Policy and Innovation, Federal Energy Regulatory Commission, 888 First Street, NE., Washington, DC 20426, (202) 502-8148, david.hunger@ferc.gov... regarding its efforts to address issues related to demand response resources. In orders addressing SPP's...

  18. Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

    DEFF Research Database (Denmark)

    Soares, Tiago; Faria, Pedro; Vale, Zita

    2014-01-01

    The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...

  19. Day-ahead resource scheduling including demand response for electric vehicles

    DEFF Research Database (Denmark)

    Soares, Joao; Morais, Hugo; Sousa, Tiago

    2014-01-01

    the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs in the V2G approach. Three different DR programs...

  20. Flexibility dynamics in clusters of residential demand response and distributed generation

    NARCIS (Netherlands)

    MacDougall, P.A.; Kok, J.K.; Warmer, C.; Roossien, B.

    2013-01-01

    Supply and demand response is a untapped resource in the current electrical system. However little work has been done to investigate the dynamics of utilizing such flexibility as well as the potential effects it could have on the infrastructure. This paper provides a starting point to seeing the

  1. Impact of Competition on Quality of Service in Demand Responsive Transit

    NARCIS (Netherlands)

    Grootenboers, F.; De Weerdt, M.M.; Zargayouna, M.

    2010-01-01

    Demand responsive transportation has the potential to provide efficient public door-to-door transport with a high quality. In currently implemented systems in the Netherlands, however, we observe a decrease in the quality of service (QoS), expressed in longer travel times for the customers.

  2. Demands on Attention and the Role of Response Priming in Visual Discrimination of Feature Conjunctions

    Science.gov (United States)

    Fournier, Lisa R.; Herbert, Rhonda J.; Farris, Carrie

    2004-01-01

    This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less…

  3. Residential Demand Response Behaviour Modeling applied to Cyber-physical Intrusion Detection

    DEFF Research Database (Denmark)

    Heussen, Kai; Tyge, Emil; Kosek, Anna Magdalena

    2017-01-01

    A real-time demand response system can be viewed as a cyber-physical system, with physical systems dependent on cyber infrastructure for coordination and control, which may be vulnerable to cyber-attacks. The time domain dynamic behaviour of individual residential demand responses is governed...... by a mix of physical system parameters, exogenous influences, user behaviour and preferences, which can be characterized by unstructured models such as a time-varying finite impulse response. In this study, which is based on field data, it is shown how this characteristic response behaviours can...... be identified and how the characterization can be updated continuously. Finally, we propose an approach to apply this behaviour characterization to the identification of anomalous and potentially malicious behaviour modifications as part of a cyber-physical intrusion detection mechanism....

  4. Imperfect price-reversibility of US gasoline demand: Asymmetric responses to price increases and declines

    International Nuclear Information System (INIS)

    Gately, D.

    1992-01-01

    This paper describes a framework for analyzing the imperfect price-reversibility (hysteresis) of oil demand. The oil demand reductions following the oil price increases of the 1970s will not be completely reversed by the price cuts of the 1980s, nor is it necessarily true that these partial demand reversals themselves will be reversed exactly by future price increases. The author decomposes price into three monotonic series: price increases to maximum historic levels, price cuts, and price recoveries (increases below historic highs). He would expect that the response to price cuts would be no greater than to price recoveries, which in turn would be no greater than for increases in maximum historic price. For evidence of imperfect price-reversibility, he tests econometrically the following US data: vehicle miles per driver, the fuel efficiency of the automobile fleet, and gasoline demand per driver. In each case, the econometric results allow him to reject the hypothesis of perfect price-reversibility. The data show smaller response to price cuts than to price increases. This has dramatic implications for projections of gasoline and oil demand, especially under low-price assumptions. 26 refs., 13 figs., 3 tabs

  5. Energy Optimization and Management of Demand Response Interactions in a Smart Campus

    Directory of Open Access Journals (Sweden)

    Antimo Barbato

    2016-05-01

    Full Text Available The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling, the telecommunication infrastructure in charge of data exchanging and the integrated data repository devoted to information storage. We also discuss the relevant use cases and validate the framework in a few deployed demonstrators.

  6. Empirical analysis of the spot market implications of price-responsive demand

    International Nuclear Information System (INIS)

    Siddiqui, A.S.

    2006-01-01

    Although electricity is theoretically an inelastic good in the short term, the steep slope of the supply stack implies that even modest response by demand could translate into reduced capacity requirements and significant price decreases. This article examined the effect of price-responsive demand strategies in an actual deregulated electricity industry. Auction data from the New York Independent System Operator (NYISO) day-ahead electricity market were used to form supply stacks for various zones. A simple linear demand function was used to determine the effect of price responsiveness on equilibrium spot market price and consumption. The aim was to quantify the benefits from the pricing protocol and to determine whether modest levels of price elasticity can significantly lower prices and consumption. Market-clearing prices and quantities were estimated using various supply curves in order to quantify the responsiveness necessary to achieve given price reductions. Price response was induced in the demand curve by varying its slope. Estimates were then used to estimate the average level of slope needed to reduce the average market-clearing price during the year by a certain percentage. Results showed that an average slope of -50.04 was necessary for prices to be reduced by 25 per cent. Results also showed that necessary price responses can be ascertained for any desired reduction in the market-clearing price or quantity. Although price responsiveness unambiguously reduces the spot market price and quantity, its effect on the forward price is not yet clear. It was concluded that a separate analysis of peak hours may reveal the effectiveness of enhanced price response. 8 refs., 1 tab., 8 figs

  7. Optimal real time cost-benefit based demand response with intermittent resources

    International Nuclear Information System (INIS)

    Zareen, N.; Mustafa, M.W.; Sultana, U.; Nadia, R.; Khattak, M.A.

    2015-01-01

    Ever-increasing price of conventional energy resources and related environmental concern enforced to explore alternative energy sources. Inherent uncertainty of power generation and demand being strongly influenced by the electricity market has posed severe challenges for DRPs (Demand Response Programs). Definitely, the success of such uncertain energy systems under new market structures is critically decided by the advancement of innovative technical and financial tools. Recent exponential growth of DG (distributed generations) demanded both the grid reliability and financial cost–benefits analysis for deregulated electricity market stakeholders. Based on the SGT (signaling game theory), the paper presents a novel user-aware demand-management approach where the price are colligated with grid condition uncertainties to manage the peak residential loads. The degree of information disturbances are considered as a key factor for evaluating electricity bidding mechanisms in the presence of independent multi-generation resources and price-elastic demand. A correlation between the cost–benefit price and variable reliability of grid is established under uncertain generation and demand conditions. Impacts of the strategies on load shape, benefit of customers and the reduction of energy consumption are inspected and compared with Time-of-Used based DRPs. Simulation results show that the proposed DRP can significantly reduce or even eliminate peak-hour energy consumption, leading to a substantial raise of revenues with 18% increase in the load reduction and a considerable improvement in system reliability is evidenced. - Highlights: • Proposed an optimal real time cost-benefit based demand response model. • Used signaling game theory for the information disturbances in deregulated market. • Introduced a correlation between the cost–benefit price and variable grid reliability. • Derive robust bidding strategies for utility/customers successful participation.

  8. Demand Responsive and Energy Efficient Control Technologies andStrategies in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Kiliccote, Sila

    2006-09-01

    Commercial buildings account for a large portion of summer peak electric demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial buildings contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. The main objectives of the study were: (1) To evaluate the size of contributions of peak demand commercial buildings in the U.S.; (2) To understand how commercial building control systems support energy efficiency and DR; and (3) To disseminate the results to the building owners, facility managers and building controls industry. In order to estimate the commercial buildings contribution to peak demand, two sources of data are used: (1) Commercial Building Energy Consumption Survey (CBECS) and (2) National Energy Modeling System (NEMS). These two sources indicate that commercial buildings noncoincidental peak demand is about 330GW. The project then focused on technologies and strategies that deliver energy efficiency and also target 5-10% of this peak. Based on a building operations perspective, a demand-side management framework with three main features: (1) daily energy efficiency, (2) daily peak load management and (3) dynamic, event-driven DR are outlined. A general description of DR, its benefits, and nationwide DR potential in commercial buildings are presented. Case studies involving these technologies and strategies are described. The findings of this project are shared with building owners, building controls industry, researchers and government entities through a webcast and their input is requested. Their input is presented in the appendix section of this report.

  9. Demand Response Potential for California SubLAPs and Local Capacity Planning Areas: An Addendum to the 2025 California Demand Response Potential Study – Phase 2

    Energy Technology Data Exchange (ETDEWEB)

    Alstone, Peter [Humboldt State Univ., Arcata, CA (United States). Schatz Energy Research Center; Potter, Jennifer [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Piette, Mary Ann [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schwartz, Peter [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Berger, Michael A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dunn, Laurel N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Smith, Sarah J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sohn, Michael D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Aghajanzadeh, Arian [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Stensson, Sofia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Szinai, Julia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-04-01

    The 2025 California Demand Response Potential Study Phase 2 Report1 was released on March 1, 2017, and described a range of pathways for Demand Response (DR) to support a clean, stable, and cost-effective electric grid for California. One of the Report’s key findings was that while there appears to be very low future value for untargeted DR Shed aimed at system-wide peak load conditions, there could be significant value for locally focused Shed resources. Although the dynamics of renewable capacity expansion have reduced the pressure to build new thermal generation in general, there are still transmission-constrained areas of the state where load growth needs to be managed with the addition of new local capacity, which could include DERs and/or DR. This Addendum to the Phase 2 Report presents a breakdown of the expected future “Local Shed” DR potential at a finer geographic resolution than what is available in the original report, with results summarized by SubLAP and Local Capacity Area (LCA).

  10. Examining demand response, renewable energy and efficiencies to meet growing electricity needs

    International Nuclear Information System (INIS)

    Elliot, N.; Eldridge, M.; Shipley, A.M.; Laitner, J.S.; Nadel, S.; Silverstein, A.; Hedman, B.; Sloan, M.

    2007-01-01

    While Texas has already taken steps to improve its renewable energy portfolio (RPS), and its energy efficiency improvement program (EEIP), the level of savings that utilities can achieve through the EEIP can be greatly increased. This report estimated the size of energy efficiency and renewable energy resources in Texas, and suggested a range of policy options that might be adopted to further extend EEIP. Current forecasts suggest that peak demand in Texas will increase by 2.3 per cent annually from 2007-2012, a level of growth which is threatening the state's ability to maintain grid reliability at reasonable cost. Almost 70 per cent of installed generating capacity is fuelled by natural gas in Texas. Recent polling has suggested that over 70 per cent of Texans are willing support increased spending on energy efficiency. Demand response measures that may be implemented in the state include incentive-based programs that pay users to reduce their electricity consumption during specific times and pricing programs, where customers are given a price signal and are expected to moderate their electricity usage. By 2023, the widespread availability of time-varying retail electric rates and complementary communications and control methods will permanently change the nature of electricity demand in the state. At present, the integrated utilities in Texas offer a variety of direct load control and time-of-use, curtailable, and interruptible rates. However, with the advent of retail competition now available as a result of the structural unbundling of investor-owned utilities, there is less demand response available in Texas. It was concluded that energy efficiency, demand response, and renewable energy resources can meet the increasing demand for electricity in Texas over the next 15 years. 4 figs

  11. Experimental evaluation of BZ-GW (BACnet-ZigBee smart grid gateway) for demand response in buildings

    International Nuclear Information System (INIS)

    Hong, Seung Ho; Kim, Se Hwan; Kim, Gi Myung; Kim, Hyung Lae

    2014-01-01

    The SG (smart grid) is a modernized and a future-oriented electric grid that deals with the whole energy chain, from generation to consumer. Among the SG applications, DR (demand response) is an important control mechanism to manage the electricity consumption of the customer in response to supply conditions. In buildings, DR is managed through installed communication networks which support DR applications. BACnet is an international standard communication protocol for building automation and control systems. BACnet uses ZigBee as a wireless communication protocol. Both BACnet and ZigBee have their own DR applications. In this study, we developed a BACnet-ZigBee gateway that maps the DR application of BACnet to that of ZigBee and vice versa. In addition, we developed an experimental facility to demonstrate how the BACnet-ZigBee gateway can be implemented for DR applications in buildings. We also measured the communication delay to verify that the BZ-GW (BACnet-ZigBee smart grid gateway) developed here satisfies the requirements of real-time DR service in buildings. - Highlights: • Developed a gateway that maps the DR application of BACnet to that of ZigBee. • Verified satisfaction for real-time requirement using experimental facility. • The gateway and other device will play a infrastructure role in buildings. • The implementation method could become a reference model for future similar

  12. Critical kick-back mitigation through improved design of demand response

    DEFF Research Database (Denmark)

    Han, Xue; You, Shi; Bindner, Henrik W.

    2016-01-01

    The energy sector is adopting a lot of intermittent renewable energy sources nowadays. In order to successfully integrate these renewable sources, demand side resources (DSR), in a demand response (DR) setup, are able to provide power system services by exploiting their flexibility in power...... of load kick-back, not only the potential value of DR is limited significant but also power system operation can be jeopardized even more. In addition to explaining the severity of kick-back effect through illustrative examples, this paper proposes several methods to mitigate the critical kick-back effect...

  13. Development of an automated speech recognition interface for personal emergency response systems

    Directory of Open Access Journals (Sweden)

    Mihailidis Alex

    2009-07-01

    Full Text Available Abstract Background Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype. Methods The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults. Results and discussion The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability. Conclusion The use of an automated

  14. Design of capacity incentive and energy compensation for demand response programs

    Science.gov (United States)

    Liu, Zhoubin; Cui, Wenqi; Shen, Ran; Hu, Yishuang; Wu, Hui; Ye, Chengjin

    2018-02-01

    Variability and Uncertainties caused by renewable energy sources have called for large amount of balancing services. Demand side resources (DSRs) can be a good alternative of traditional generating units to provide balancing service. In the areas where the electricity market has not been fully established, e.g., China, DSRs can help balance the power system with incentive-based demand response programs. However, there is a lack of information about the interruption cost of consumers in these areas, making it hard to determine the rational amount of capacity incentive and energy compensation for the participants of demand response programs. This paper proposes an algorithm to calculate the amount of capacity incentive and energy compensation for demand response programs when there lacks the information about interruption cost. Available statistical information of interruption cost in referenced areas is selected as the referenced data. Interruption cost of the targeted area is converted from the referenced area by product per electricity consumption. On this basis, capacity incentive and energy compensation are obtained to minimize the payment to consumers. Moreover, the loss of consumers is guaranteed to be covered by the revenue they earned from load serving entities.

  15. Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage

    NARCIS (Netherlands)

    Korkas, C; Baldi, S.; Michailidis, I; Kosmatopoulos, EB

    2016-01-01

    Integration of renewable energy sources in microgrids can be achieved via demand response programs, which change the electric usage in response to changes in the availability and price of electricity over time. This paper presents a novel control algorithm for joint demand response management and

  16. Proceedings of the CEATI demand side management workshop on understanding customer response. CD-ROM ed.

    International Nuclear Information System (INIS)

    2006-01-01

    Demand for electricity continues to increase in the midst of environmental concerns, deregulation and the rapid evolution of technology. In order to succeed in a changing environment, utilities must be both adaptive and innovative. Growing concerns over supply and the environmental effects of rising consumption rates have led many utilities to establish demand side management (DSM) programs. However, some utilities have failed to consider the importance of customer behaviour in the success of DSM programs. This conference examined various successful initiatives to encourage customers to reduce their individual or corporate demands for energy. The influence of branding, technology, information prices signals and various other strategies were explored. Issues concerning energy efficiency and customer feedback were discussed. The effect of alternative pricing regimes on DSM programs was investigated. Various information system tools were also examined, and the value of real time electricity monitoring was evaluated. Various DSM initiatives in North America were used to establish benchmarks for the successful implementation of DSM strategies. The conference was divided into 3 sessions: (1) involving the customer in reducing demand; (2) the success of energy efficiency and demand response programs : the impact of branding and the impact of price signals; and (3) the technologies and innovations needed to make it work. The conference featured 13 presentations, of which 8 have been catalogued separately for inclusion in this database. refs., tabs., figs

  17. Solving a Location, Allocation, and Capacity Planning Problem with Dynamic Demand and Response Time Service Level

    Directory of Open Access Journals (Sweden)

    Carrie Ka Yuk Lin

    2014-01-01

    Full Text Available Logistic systems with uncertain demand, travel time, and on-site processing time are studied here where sequential trip travel is allowed. The relationship between three levels of decisions: facility location, demand allocation, and resource capacity (number of service units, satisfying the response time requirement, is analysed. The problem is formulated as a stochastic mixed integer program. A simulation-based hybrid heuristic is developed to solve the dynamic problem under different response time service level. An initial solution is obtained from solving static location-allocation models, followed by iterative improvement of the three levels of decisions by ejection, reinsertion procedure with memory of feasible and infeasible service regions. Results indicate that a higher response time service level could be achieved by allocating a given resource under an appropriate decentralized policy. Given a response time requirement, the general trend is that the minimum total capacity initially decreases with more facilities. During this stage, variability in travel time has more impact on capacity than variability in demand arrivals. Thereafter, the total capacity remains stable and then gradually increases. When service level requirement is high, the dynamic dispatch based on first-come-first-serve rule requires smaller capacity than the one by nearest-neighbour rule.

  18. Marketing automation

    Directory of Open Access Journals (Sweden)

    TODOR Raluca Dania

    2017-01-01

    Full Text Available The automation of the marketing process seems to be nowadays, the only solution to face the major changes brought by the fast evolution of technology and the continuous increase in supply and demand. In order to achieve the desired marketing results, businessis have to employ digital marketing and communication services. These services are efficient and measurable thanks to the marketing technology used to track, score and implement each campaign. Due to the technical progress, the marketing fragmentation, demand for customized products and services on one side and the need to achieve constructive dialogue with the customers, immediate and flexible response and the necessity to measure the investments and the results on the other side, the classical marketing approached had changed continue to improve substantially.

  19. Separation of metabolic supply and demand: aerobic glycolysis as a normal physiological response to fluctuating energetic demands in the membrane.

    Science.gov (United States)

    Epstein, Tamir; Xu, Liping; Gillies, Robert J; Gatenby, Robert A

    2014-01-01

    Cancer cells, and a variety of normal cells, exhibit aerobic glycolysis, high rates of glucose fermentation in the presence of normal oxygen concentrations, also known as the Warburg effect. This metabolism is considered abnormal because it violates the standard model of cellular energy production that assumes glucose metabolism is predominantly governed by oxygen concentrations and, therefore, fermentative glycolysis is an emergency back-up for periods of hypoxia. Though several hypotheses have been proposed for the origin of aerobic glycolysis, its biological basis in cancer and normal cells is still not well understood. We examined changes in glucose metabolism following perturbations in membrane activity in different normal and tumor cell lines and found that inhibition or activation of pumps on the cell membrane led to reduction or increase in glycolysis, respectively, while oxidative phosphorylation remained unchanged. Computational simulations demonstrated that these findings are consistent with a new model of normal physiological cellular metabolism in which efficient mitochondrial oxidative phosphorylation supplies chronic energy demand primarily for macromolecule synthesis and glycolysis is necessary to supply rapid energy demands primarily to support membrane pumps. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. The predictions were confirmed experimentally. Our results show that glycolytic metabolism serves a critical physiological function under normoxic conditions by responding to rapid energetic demand, mainly from membrane transport activities, even in the presence of oxygen. This supports a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Cells use efficient but slow-responding aerobic metabolism

  20. Suitability of semi-automated tumor response assessment of liver metastases using a dedicated software package

    International Nuclear Information System (INIS)

    Kalkmann, Janine; Ladd, S.C.; Greiff, A. de; Forsting, M.; Stattaus, J.

    2010-01-01

    Purpose: to evaluate the suitability of semi-automated compared to manual tumor response assessment (TRA) of liver metastases. Materials and methods: in total, 32 patients with colorectal cancer and liver metastases were followed by an average of 2.8 contrast-enhanced CT scans. Two observers (O1, O2) measured the longest diameter (LD) of 269 liver metastases manually and semi-automatically using software installed as thin-client on a PACS workstation (LMS-Liver, MEDIAN Technologies). LD and TRA (''progressive'', ''stable'', ''partial remission'') were performed according to RECIST (Response Evaluation Criteria in Solid Tumors) and analyzed for between-method, interobserver and intraobserver variability. The time needed for evaluation was compared for both methods. Results: all measurements correlated excellently (r ≥ 0.96). Intraobserver (semi-automated), interobserver (manual) and between-method differences (by O1) in LD of 1.4 ± 2.6 mm, 1.9 ± 1.9 mm and 2.1 ± 2.0 mm, respectively, were not significant. Interobserver (semi-automated) and between-method (by O2) differences in LD of 3.0 ± 3.0 mm and 2.6 ± 2.0 mm, respectively, reflected a significant variability (p < 0.01). The interobserver agreement in manual and semi-automated TRA was 91.4%. The intraobserver agreement in semi-automated TRA was 84.5%. Between both methods a TRA agreement of 86.2% was obtained. Semi-automated evaluation (2.7 min) took slightly more time than manual evaluation (2.3 min). Conclusion: semi-automated and manual evaluation of liver metastases yield comparable results in response assessments and require comparable effort. (orig.)

  1. The Activity Demands and Physiological Responses Encountered During Basketball Match-Play: A Systematic Review.

    Science.gov (United States)

    Stojanović, Emilija; Stojiljković, Nenad; Scanlan, Aaron T; Dalbo, Vincent J; Berkelmans, Daniel M; Milanović, Zoran

    2018-01-01

    Basketball is a popular, court-based team sport that has been extensively studied over the last decade. The purpose of this article was to provide a systematic review regarding the activity demands and physiological responses experienced during basketball match-play according to playing period, playing position, playing level, geographical location, and sex. An electronic database search of relevant articles published prior to 30 September 2016 was performed with PubMed, MEDLINE, ERIC, Google Scholar, SCIndex, and ScienceDirect. Studies that measured activity demands and/or physiological responses during basketball match-play were included. Following screening, 25 articles remained for review. During live playing time across 40-min matches, male and female basketball players travel 5-6 km at average physiological intensities above lactate threshold and 85% of maximal heart rate (HR). Temporal comparisons show a reduction in vigorous activities in the fourth quarter, likely contributing to lower blood lactate concentrations and HR responses evident towards the end of matches. Guards tend to perform a higher percentage of live playing time sprinting and performing high-intensity shuffling compared with forwards and centers. Guards also perform less standing and walking during match-play compared with forwards and centers. Variations in activity demands likely account for the higher blood lactate concentrations and HR responses observed for guards compared with forwards and centers. Furthermore, higher-level players perform a greater intermittent workload than lower-level players. Moreover, geographical differences may exist in the activity demands (distance and frequency) and physiological responses between Australian, African, and European basketball players, whereby Australian players sustain greater workloads. While activity demands and physiological data vary across playing positions, playing levels, and geographical locations, male and female players competing

  2. A bilevel model for electricity retailers' participation in a demand response market environment

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    2013-01-01

    Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small...... consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers...... find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real...

  3. Hierarchical control framework for integrated coordination between distributed energy resources and demand response

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Di; Lian, Jianming; Sun, Yannan; Yang, Tao; Hansen, Jacob

    2017-09-01

    Demand response is representing a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. In this paper, a hierarchical control framework is proposed to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. In the coordination layer, various resource aggregations are optimally coordinated in a distributed manner to achieve the system-level objectives. In the device layer, individual resources are controlled in real time to follow the optimal power generation or consumption dispatched from the coordination layer. For the purpose of practical applications, a method is presented to determine the utility functions of controllable loads by taking into account the real-time load dynamics and the preferences of individual customers. The effectiveness of the proposed framework is validated by detailed simulation studies.

  4. An Optimal and Distributed Demand Response Strategy for Energy Internet Management

    Directory of Open Access Journals (Sweden)

    Qian Liu

    2018-01-01

    Full Text Available This study proposes a new model of demand response management for a future smart grid that consists of smart microgrids. The microgrids have energy storage units, responsive loads, controllable distributed generation units, and renewable energy resources. They can buy energy from the utility company when the power generation in themselves cannot satisfy the load demand, and sell extra power generation to the utility company. The goal is to optimize the operation schedule of microgrids to minimize the microgrids’ payments and the utility company’s operation cost. A parallel distributed optimization algorithm based on games theory is developed to solve the optimization problem, in which microgrids only need to send their aggregated purchasing/selling energy to the utility company, thus avoid infringing its privacy. Microgrids can update their operation schedule simultaneously. A case study is implemented, and the simulation results show that the proposed method is effective and efficient.

  5. Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

    DEFF Research Database (Denmark)

    Soares, Tiago; Faria, Pedro; Vale, Zita

    2014-01-01

    The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...

  6. Using smart meter data to estimate demand response potential, with application to solar energy integration

    International Nuclear Information System (INIS)

    Dyson, Mark E.H.; Borgeson, Samuel D.; Tabone, Michaelangelo D.; Callaway, Duncan S.

    2014-01-01

    This paper presents a new method for estimating the demand response potential of residential air conditioning (A/C), using hourly electricity consumption data (“smart meter” data) from 30,000 customer accounts in Northern California. We apply linear regression and unsupervised classification methods to hourly, whole-home consumption and outdoor air temperature data to determine the hours, if any, that each home's A/C is active, and the temperature dependence of consumption when it is active. When results from our sample are scaled up to the total population, we find a maximum of 270–360 MW (95% c.i.) of demand response potential over a 1-h duration with a 4 °F setpoint change, and up to 3.2–3.8 GW of short-term curtailment potential. The estimated resource correlates well with the evening decline of solar production on hot, summer afternoons, suggesting that demand response could potentially act as reserves for the grid during these periods in the near future with expected higher adoption rates of solar energy. Additionally, the top 5% of homes in the sample represent 40% of the total MW-hours of DR resource, suggesting that policies and programs to take advantage of this resource should target these high users to maximize cost-effectiveness. - Highlights: • We use hourly electricity use data to estimate residential demand response (DR) potential. • The residential cooling DR resource is large and well-matched to solar variability. • Customer heterogeneity is large; programs should target high potential customers

  7. Fostering Residential Demand Response through Dynamic Pricing Schemes: A Behavioural Review of Smart Grid Pilots in Europe

    Directory of Open Access Journals (Sweden)

    Kris Kessels

    2016-09-01

    Full Text Available Many smart grid projects make use of dynamic pricing schemes aimed to motivate consumers to shift and/or decrease energy use. Based upon existing literature and analyses of current smart grid projects, this survey paper presents key lessons on how to encourage households to adjust energy end use by means of dynamic tariffs. The paper identifies four key hypotheses related to fostering demand response through dynamic tariff schemes and examines whether these hypotheses can be accepted or rejected based on a review of published findings from a range of European pilot projects. We conclude that dynamic pricing schemes have the power to adjust energy consumption behavior within households. In order to work effectively, the dynamic tariff should be simple to understand for the end users, with timely notifications of price changes, a considerable effect on their energy bill and, if the tariff is more complex, the burden for the consumer could be eased by introducing automated control. Although sometimes the mere introduction of a dynamic tariff has proven to be effective, often the success of the pricing scheme depends also on other factors influencing the behavior of end users. An important condition to make dynamic tariffs work is that the end users should be engaged with them.

  8. Behavioral aspects of regulation: A discussion on switching and demand response in Turkish electricity market

    International Nuclear Information System (INIS)

    Sirin, Selahattin Murat; Gonul, Mustafa Sinan

    2016-01-01

    Electricity sector has been transformed from state-owned monopolistic utilities to competitive markets with an aim to promote incentives for improving efficiency, reducing costs and increasing service quality to customers. One of the cardinal assumptions of the liberalized and competitive electricity markets is the rational actor, and decision-makers are assumed to make the best decisions that maximize their utility. However, a vast literature on behavioral economics has shown the weakness of economic theory in explaining and predicting individuals’ decision-making behavior. This issue is quite important for competition in electricity markets in which consumers’ preferences have a significant role. Despite its importance, this issue has almost been neglected in Turkey, which has taken major steps in electricity sector restructuring. Therefore, this paper aims to examine switching and demand response behavior in Turkish electricity market by using multiple correspondence and panel data analysis, and findings are discussed in light of the neoclassical and behavioral economics literature. Analyses’ results show that consumers’ switching and demand response behavior is consistent with the neoclassical literature to some extent; however, behavioral factors are also affecting consumers’ decisions. Furthermore, there are systemic problems that hinder effective functioning of the electricity market and restrict competition. - Highlights: • Behavioral economics can provide insights for consumer’ decisions. • Switching and demand response behavior is examined by econometric methods. • Results is consistent with the neoclassical literature to some extent • However, behavioral factors are also affecting consumers’ decisions.

  9. Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter; Mills, Andrew; Goldman, Charles; Wiser, Ryan; Eto, Joseph H.

    2011-09-10

    This scoping study focuses on the policy issues inherent in the claims made by some Smart Grid proponents that the demand response potential of mass market customers which is enabled by widespread implementation of Advanced Metering Infrastructure (AMI) through the Smart Grid could be the “silver bullet” for mitigating variable generation integration issues. In terms of approach, we will: identify key issues associated with integrating large amounts of variable generation into the bulk power system; identify demand response opportunities made more readily available to mass market customers through widespread deployment of AMI systems and how they can affect the bulk power system; assess the extent to which these mass market Demand Response (DR) opportunities can mitigate Variable Generation (VG) integration issues in the near-term and what electricity market structures and regulatory practices could be changed to further expand the ability for DR to mitigate VG integration issues over the long term; and provide a qualitative comparison of DR and other approaches to mitigate VG integration issues.

  10. Approaches to Enable Demand Response by Industrial Loads for Ancillary Services Provision

    Science.gov (United States)

    Zhang, Xiao

    Demand response has gained significant attention in recent years as it demonstrates potentials to enhance the power system's operational flexibility in a cost-effective way. Industrial loads such as aluminum smelters, steel manufacturers, and cement plants demonstrate advantages in supporting power system operation through demand response programs, because of their intensive power consumption, already existing advanced monitoring and control infrastructure, and the strong economic incentive due to the high energy costs. In this thesis, we study approaches to efficiently integrate each of these types of manufacturing processes as demand response resources. The aluminum smelting process is able to change its power consumption both accurately and quickly by controlling the pots' DC voltage, without affecting the production quality. Hence, an aluminum smelter has both the motivation and the ability to participate in demand response. First, we focus on determining the optimal regulation capacity that such a manufacturing plant should provide. Next, we focus on determining its optimal bidding strategy in the day-ahead energy and ancillary services markets. Electric arc furnaces (EAFs) in steel manufacturing consume a large amount of electric energy. However, a steel plant can take advantage of time-based electricity prices by optimally arranging energy-consuming activities to avoid peak hours. We first propose scheduling methods that incorporate the EAFs' flexibilities to reduce the electricity cost. We then propose methods to make the computations more tractable. Finally, we extend the scheduling formulations to enable the provision of spinning reserve. Cement plants are able to quickly adjust their power consumption rate by switching on/off the crushers. However, switching on/off the loading units only achieves discrete power changes, which restricts the load from offering valuable ancillary services such as regulation and load following, as continuous power changes

  11. A bi-level integrated generation-transmission planning model incorporating the impacts of demand response by operation simulation

    International Nuclear Information System (INIS)

    Zhang, Ning; Hu, Zhaoguang; Springer, Cecilia; Li, Yanning; Shen, Bo

    2016-01-01

    Highlights: • We put forward a novel bi-level integrated power system planning model. • Generation expansion planning and transmission expansion planning are combined. • The effects of two sorts of demand response in reducing peak load are considered. • Operation simulation is conducted to reflect the actual effects of demand response. • The interactions between the two levels can guarantee a reasonably optimal result. - Abstract: If all the resources in power supply side, transmission part, and power demand side are considered together, the optimal expansion scheme from the perspective of the whole system can be achieved. In this paper, generation expansion planning and transmission expansion planning are combined into one model. Moreover, the effects of demand response in reducing peak load are taken into account in the planning model, which can cut back the generation expansion capacity and transmission expansion capacity. Existing approaches to considering demand response for planning tend to overestimate the impacts of demand response on peak load reduction. These approaches usually focus on power reduction at the moment of peak load without considering the situations in which load demand at another moment may unexpectedly become the new peak load due to demand response. These situations are analyzed in this paper. Accordingly, a novel approach to incorporating demand response in a planning model is proposed. A modified unit commitment model with demand response is utilized. The planning model is thereby a bi-level model with interactions between generation-transmission expansion planning and operation simulation to reflect the actual effects of demand response and find the reasonably optimal planning result.

  12. 12 CFR 404.32 - Procedure in the event a decision concerning a demand is not made prior to the time a response to...

    Science.gov (United States)

    2010-01-01

    ... demand is not made prior to the time a response to the demand is required. 404.32 Section 404.32 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES INFORMATION DISCLOSURE Demands for Testimony of... event a decision concerning a demand is not made prior to the time a response to the demand is required...

  13. Monitoring the Performance of Human and Automated Scores for Spoken Responses

    Science.gov (United States)

    Wang, Zhen; Zechner, Klaus; Sun, Yu

    2018-01-01

    As automated scoring systems for spoken responses are increasingly used in language assessments, testing organizations need to analyze their performance, as compared to human raters, across several dimensions, for example, on individual items or based on subgroups of test takers. In addition, there is a need in testing organizations to establish…

  14. Physiological demands of women's rugby union: time-motion analysis and heart rate response.

    Science.gov (United States)

    Virr, Jody Lynn; Game, Alex; Bell, Gordon John; Syrotuik, Daniel

    2014-01-01

    The aim of this study was to determine the physical demands of women's rugby union match play using time-motion analysis and heart rate (HR) response. Thirty-eight premier club level female rugby players, ages 18-34 years were videotaped and HRs monitored for a full match. Performances were coded into 12 different movement categories: 5 speeds of locomotion (standing, walking, jogging, striding, sprinting), 4 forms of intensive non-running exertion (ruck/maul/tackle, pack down, scrum, lift) and 3 discrete activities (kick, jump, open field tackle). The main results revealed that backs spend significantly more time sprinting and walking whereas forwards spend more time in intensive non-running exertion and jogging. Forwards also had a significantly higher total work frequency compared to the backs, but a higher total rest frequency compared to the backs. In terms of HR responses, forwards displayed higher mean HRs throughout the match and more time above 80% of their maximum HR than backs. In summary, women's rugby union is characterised by intermittent bursts of high-intensity activity, where forwards and backs have similar anaerobic energy demands, but different specific match demands.

  15. Optimizing renewable energy, demand response and energy storage to replace conventional fuels in Ontario, Canada

    International Nuclear Information System (INIS)

    Richardson, David B.; Harvey, L.D. Danny

    2015-01-01

    Electricity systems with high penetrations of renewable energy require a mix of resources to balance supply with demand, and to maintain safe levels of system reliability. A load balancing methodology is developed to determine the optimal lowest-cost mix of renewable energy resources, demand response, and energy storage to replace conventional fuels in the Province of Ontario, Canada. Three successive cumulative scenarios are considered: the displacement of fossil fuel generation, the planned retirement of an existing nuclear reactor, and the electrification of the passenger vehicle fleet. The results show that each of these scenarios is achievable with energy generation costs that are not out of line with current and projected electricity generation costs. These transitions, especially that which proposes the electrification of the vehicle fleet, require significant investment in new generation, with installed capacities much higher than that of the current system. Transitions to mainly renewable energy systems require changes in our conceptualization of, and approach to, energy system planning. - Highlights: • Model three scenarios to replace conventional fuels with renewables, storage and DR (demand response). • Determine optimal low-cost mix of resources for each scenario. • Scenarios require much higher installed capacities than current system. • Energy transitions require changes in approach to energy system planning.

  16. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  17. Reducing Gridlock on the Grid: Utility Trends in Managing Peak Electric Load through Residential Demand Response

    Science.gov (United States)

    McDonald, Betsy

    Utilities across the United States are piloting residential demand response programs to help manage peak electric demand. Using publicly available program evaluations, this thesis analyzes nine such programs to uncover and synthesize the range of program offerings, goals, enrollment strategies, and customer experiences. This review reveals that program participation, components, and results differ based on a variety of factors, including geographic characteristics, program goals, and implementation strategies. The diversity of program designs and evaluation findings suggests an underlying tension between the need to generate cost-effective program impacts and the desire to increase accessibility so that program benefits are not exclusive to certain segments of the population. For more significant and impactful engagement, program goals may need to shift. State level policy support could help shift program goals toward increasing program accessibility. Future research should explore creative strategies that target existing barriers and allow for more inclusive deployment.

  18. Day-Ahead Congestion Management in Distribution Systems through Household Demand Response and Distribution Congestion Prices

    DEFF Research Database (Denmark)

    Liu, Weijia; Wu, Qiuwei; Wen, Fushuan

    2014-01-01

    With the development of smart grid technologies, some of the electric demands which are traditionally considered fixed and inflexible will become promising distributed energy resources (DERs) in future power systems. However, the participation of small scale or household energy sources...... into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the loca- tional marginal pricing (LMP) model......, the proposed DCPs are able to reflect the real congestion cost and further direct the schedule of the responses of electric demands. Based on the NordPool Spot market structure, the interactions between aggregators and the distribution system operator (DSO) are discussed, and the procedure for calculating DCPs...

  19. Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems

    Directory of Open Access Journals (Sweden)

    Mubbashir Ali

    2018-05-01

    Full Text Available From an environment perspective, the increased penetration of wind and solar generation in power systems is remarkable. However, as the intermittent renewable generation briskly grows, electrical grids are experiencing significant discrepancies between supply and demand as a result of limited system flexibility. This paper investigates the optimal sizing and control of the hydrogen energy storage system for increased utilization of renewable generation. Using a Finnish case study, a mathematical model is presented to investigate the optimal storage capacity in a renewable power system. In addition, the impact of demand response for domestic storage space heating in terms of the optimal sizing of energy storage is discussed. Finally, sensitivity analyses are conducted to observe the impact of a small share of controllable baseload production as well as the oversizing of renewable generation in terms of required hydrogen storage size.

  20. Agilometer: An Effective Implementation of Internet of Things for Agile Demand Response

    Directory of Open Access Journals (Sweden)

    Muhammad Babar

    2017-07-01

    Full Text Available Transactive based control mechanism (TCM needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an ap-proach to connect the current demand-driven (top-down energy management system (EMS with a market-driven (bottom-up demand response program. To this end, this paper considers multi-agent system (MAS to realize the approach and introduces the concept and standardize design of Agilometer. It is described as an elemental agent of the approach. Proposed by authors Agilometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design.

  1. Mean-risk efficient portfolio analysis of demand response and supply resources

    International Nuclear Information System (INIS)

    Deng, Shi-Jie; Xu, Li

    2009-01-01

    In the restructured electric power utility industry, reducing the risk exposure of profit to the highly volatile electricity wholesale price and the fluctuating demand of end users is essential to the financial success of load-serving entities (LSEs). Demand response (DR) programs have been utilized to manage the correlated price and volumetric risks, and simultaneously improve the reliability of the power system. This paper proposes an efficient portfolio framework for LSEs to evaluate the role of DR programs in achieving a desirable tradeoff between profit and risk. The mean-risk efficient frontier formed by the optimal portfolios allows LSEs to identify the least amount of risk to bear corresponding to a given profit target. Numerical examples are provided to illustrate the impact of DR programs on the composition of the optimal portfolios in achieving different levels of tradeoff between risk and reward. (author)

  2. Non-steady response of BOD biosensor for the determination of biochemical oxygen demand in wastewater.

    Science.gov (United States)

    Velling, Siiri; Mashirin, Alexey; Hellat, Karin; Tenno, Toomas

    2011-01-01

    A biochemical oxygen demand (BOD) biosensor for effective and expeditious BOD(7) estimations was constructed and the non-steady phase of the output signal was extensively studied. The modelling approach introduced allows response curve reconstruction and a curve fitting procedure of good quality, resulting in parameters indicating the relationship between response and organic substrate concentration and stability properties of the BOD biosensor. Also, the immobilization matrixes of different thicknesses were characterized to determine their suitability for bio-sensing measurements in non-stationary conditions, as well as for the determination of the mechanical durability of the BOD biosensor in time. The non-steady response of the experimental output of the BOD biosensor was fitted according to the developed model that enables to determine the stability of the biosensor output and dependency on biodegradable organic substrate concentration. The calibration range of the studied BOD biosensor in OECD synthetic wastewater was 15-110 mg O(2) L(-1). Repeatability tests showed relative standard deviation (RSD) values of 2.8% and 5.8% for the parameter τ(d), characterizing the transient output of the amperometric oxygen sensor in time, and τ(s), describing the dependency of the transient response of the BOD biosensor on organic substrate concentration, respectively. BOD biosensor experiments for the evaluation of the biochemical oxygen demand of easily degradable and refractory municipal wastewater showed good concurrence with traditional BOD(7) analysis.

  3. An economic welfare analysis of demand response in the PJM electricity market

    International Nuclear Information System (INIS)

    Walawalkar, Rahul; Blumsack, Seth; Apt, Jay; Fernands, Stephen

    2008-01-01

    We analyze the economic properties of the economic demand-response (DR) program in the PJM electricity market in the United States using DR market data. PJM's program provided subsidies to customers who reduced load in response to price signals. The program incorporated a 'trigger point', at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved introduce distortions into the market. We simulate demand-side bidding into the PJM market, and compare the social welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, we estimate that the social welfare gains exceed the distortions introduced by the subsidies. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment. We estimate that the socially optimal range for the incentive trigger point would be $66-77/MWh

  4. Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

    Science.gov (United States)

    Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

    2016-06-01

    The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

  5. Risk management and participation planning of electric vehicles in smart grids for demand response

    International Nuclear Information System (INIS)

    Nezamoddini, Nasim; Wang, Yong

    2016-01-01

    Demand response (DR) can serve as an effective tool to better balance the electricity demand and supply in the smart grid. It is defined as 'the changes in electricity usage by end-use customers from their normal consumption patterns' in response to pricing and incentive payments. This paper focuses on new opportunities for DR with electric vehicles (EVs). EVs are potential distributed energy resources that support both the grid-to-vehicle and vehicle-to-grid modes. Their participation in the time-based (e.g., time-of-use) and incentive-based (e.g., regulation services) DR programs helps improve the stability and reduce the potential risks to the grid. Smart scheduling of EV charging and discharging activities also supports high penetration of renewables with volatile energy generation. This paper proposes a novel stochastic model from the Independent System Operator's perspective for risk management and participation planning of EVs in the smart grid for DR. The risk factors considered in this paper involve those caused by uncertainties in renewables (wind and solar), load patterns, parking patterns, and transmission lines' reliability. The effectiveness of the model in response to various settings such as the area type (residential, commercial, and industrial), the EV penetration level, and the risk level has been investigated. - Highlights: • We identify new opportunities for demand response (DR) using electric vehicles (EVs). • We integrate EVs in both grid-to-vehicle and vehicle-to-grid modes in smart grids. • EV participation for both time- and incentive-based DR programs are modelled. • We consider uncertainties in renewables, load, parking, and transmission lines. • Model case studies are demonstrated in residential, commercial, and industrial areas.

  6. Estimation of demand response to energy price signals in energy consumption behaviour in Beijing, China

    International Nuclear Information System (INIS)

    He, Y.X.; Liu, Y.Y.; Xia, T.; Zhou, B.

    2014-01-01

    Highlights: • Demand response to energy price signals in energy consumption in Beijing is studied. • The electricity price is of great importance to Beijing’s energy market stability. • Industrial sectors have a large electricity self-elasticity and cross-elasticity. • When consuming electricity, customers pay more attention to natural gas price. • Analysis of demand response to energy price can provide guidance to energy policies. - Abstract: The energy price system in Beijing has not fully exploited customers’ price elasticity, and has a negative impact on achieving the goals of energy saving. This paper analyses the response behaviours of different customers to typical energy prices. As for electricity self-elasticity, the range of the primary, secondary, tertiary industry and residents are −0.026 to −0.033, −0.045 to −0.059, −0.035 to −0.047 and −0.024 to −0.032, respectively. As regards self-elasticity on coal, the range of the primary, secondary, tertiary industry and residents are −0.030 to −0.037, −0.066 to −0.093, −0.055 to −0.072 and −0.034 to −0.051, respectively. The self-elasticities on oil and natural gas are very weak. As for cross-elasticity, when consuming electricity and oil, customers mainly focus on the prices of natural gas, which are 0.185 and 0.112. When consuming coal and natural gas, customers are concerned about the electricity prices, and their cross-elasticities are 0.03 and 0.36, respectively. The estimation of demand response to energy price signals in energy consumption behaviours can provide a decision support for formulating rational energy price policies

  7. The neural dynamics of stimulus and response conflict processing as a function of response complexity and task demands

    Science.gov (United States)

    Donohue, Sarah E.; Appelbaum, Lawrence G.; McKay, Cameron C.; Woldorff, Marty G.

    2016-01-01

    Both stimulus and response conflict can disrupt behavior by slowing response times and decreasing accuracy. Although several neural activations have been associated with conflict processing, it is unclear how specific any of these are to the type of stimulus conflict or the amount of response conflict. Here, we recorded electrical brain activity, while manipulating the type of stimulus conflict in the task (spatial [Flanker] versus semantic [Stroop]) and the amount of response conflict (two versus four response choices). Behaviorally, responses were slower to incongruent versus congruent stimuli across all task and response types, along with overall slowing for higher response-mapping complexity. The earliest incongruency-related neural effect was a short-duration frontally-distributed negativity at ~200 ms that was only present in the Flanker spatial-conflict task. At longer latencies, the classic fronto-central incongruency-related negativity ‘Ninc’ was observed for all conditions, which was larger and ~100 ms longer in duration with more response options. Further, the onset of the motor-related lateralized readiness potential (LRP) was earlier for the two vs. four response sets, indicating that smaller response sets enabled faster motor-response preparation. The late positive complex (LPC) was present in all conditions except the two-response Stroop task, suggesting this late conflict-related activity is not specifically related to task type or response-mapping complexity. Importantly, across tasks and conditions, the LRP onset at or before the conflict-related Ninc, indicating that motor preparation is a rapid, automatic process that interacts with the conflict-detection processes after it has begun. Together, these data highlight how different conflict-related processes operate in parallel and depend on both the cognitive demands of the task and the number of response options. PMID:26827917

  8. Day-Ahead Scheduling Considering Demand Response as a Frequency Control Resource

    Directory of Open Access Journals (Sweden)

    Yu-Qing Bao

    2017-01-01

    Full Text Available The development of advanced metering technologies makes demand response (DR able to provide fast response services, e.g., primary frequency control. It is recognized that DR can contribute to the primary frequency control like thermal generators. This paper proposes a day-ahead scheduling method that considers DR as a frequency control resource, so that the DR resources can be dispatched properly with other resources. In the proposed method, the objective of frequency control is realized by defining a frequency limit equation under a supposed contingency. The frequency response model is used to model the dynamics of system frequency. The nonlinear frequency limit equation is transformed to a linear arithmetic equation by piecewise linearization, so that the problem can be solved by mixed integer linear programming (MILP. Finally, the proposed method is verified on numerical examples.

  9. Optimizing the response to surveillance alerts in automated surveillance systems.

    Science.gov (United States)

    Izadi, Masoumeh; Buckeridge, David L

    2011-02-28

    Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice. Copyright © 2011 John Wiley & Sons, Ltd.

  10. System behaviour modelling for demand response provision in a smart grid

    International Nuclear Information System (INIS)

    Dave, Saraansh; Sooriyabandara, Mahesh; Yearworth, Mike

    2013-01-01

    While pilot projects in the smart grid domain have abounded through public and private efforts, there is still uncertainty in identifying effective business models for the smart grid. In this paper we take the view of a new entrant in this market acting as a third party provider of demand response. New entrants are a key player in emerging technological domains but simulation and policy analysis from this perspective have not been forthcoming. We present a novel approach for evaluating business models within a regulatory context and avoid committing to specific technical solutions but instead embark on a parameter exploration through simple yet insightful agent-based models. Our simulations analyse the impact of system performance by three key variables; participant population size, household flexibility in terms of the maximum number of DR events allowed and size of load shifting/shedding available. The simulations indicate that benefits of avoided capital investment leads to valuing a participating household at approximately £1800 over a 20 year period. These results show how mandated infrastructure influenced by policy can affect the value proposition of a demand response service and provide a useful reference for system level parameter requirements. With weak business models, policy decisions can be crucial in providing the impetus needed to spur growth in this market. - Author-Highlights: • We model a demand response (DR) system to analyse interdependence of parameters. • Parameters analysed are number and flexibility of households and size of load shedding. • Challenges in providing a reliable DR service are explored. • A novel approach to evaluate business models for a DR service provider is presented. • The approach simultaneously evaluates business models in a regulatory context

  11. Demand Response Technology Readiness Levels for Energy Management in Blocks of Buildings

    Directory of Open Access Journals (Sweden)

    Tracey Crosbie

    2018-01-01

    Full Text Available Fossil fuels deliver most of the flexibility in contemporary electricity systems. The pressing need to reduce CO2 emissions requires new methods to provide this flexibility. Demand response (DR offers consumers a significant role in the delivery of flexibility by reducing or shifting their electricity usage during periods of stress or constraint. Blocks of buildings offer more flexibility in the timing and use of energy than single buildings, however, and a lack of relevant scalable ICT tools hampers DR in blocks of buildings. To ameliorate this problem, a current innovation project called “Demand Response in Blocks of Buildings” (DR-BoB: www.dr-bob.eu has integrated existing technologies into a scalable cloud-based solution for DR in blocks of buildings. The degree to which the DR-BoB energy management solution can increase the ability of any given site to participate in DR is dependent upon its current energy systems, i.e., the energy metering, the telemetry and control technologies in building management systems, and the existence/capacity of local power generation and storage plants. To encourage the owners and managers of blocks of buildings to participate in DR, a method of assessing and validating the technological readiness to participate in DR energy management solutions at any given site is required. This paper describes the DR-BoB energy management solution and outlines what we have called the demand response technology readiness levels (DRTRLs for the implementation of such a solution in blocks of buildings.

  12. Small Business Demand Response with Communicating Thermostats: SMUD's Summer Solutions Research Pilot

    Energy Technology Data Exchange (ETDEWEB)

    Herter, Karen; Wayland, Seth; Rasin, Josh

    2009-09-25

    This report documents a field study of 78 small commercial customers in the Sacramento Municipal Utility District service territory who volunteered for an integrated energy-efficiency/demand-response (EE-DR) program in the summer of 2008. The original objective for the pilot was to provide a better understanding of demand response issues in the small commercial sector. Early findings justified a focus on offering small businesses (1) help with the energy efficiency of their buildings in exchange for occasional load shed, and (2) a portfolio of options to meet the needs of a diverse customer sector. To meet these expressed needs, the research pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. An analysis of hourly load data indicates that the offices and retail stores in our sample provided significant demand response, while the restaurants did not. Thermostat data provides further evidence that restaurants attempted to precool and reduce AC service during event hours, but were unable to because their air-conditioning units were undersized. On a 100 F reference day, load impacts of all participants during events averaged 14%, while load impacts of office and retail buildings (excluding restaurants) reached 20%. Overall, pilot participants including restaurants had 2007-2008 summer energy savings of 20% and bill savings of 30%. About 80% of participants said that the program met or surpassed their expectations, and three-quarters said they would probably or definitely participate again without the $120 participation incentive. These results provide evidence that energy efficiency programs, dynamic rates and load control programs can be used concurrently and effectively in the small business sector, and that communicating thermostats are a reliable tool for providing air-conditioning load shed and enhancing the ability

  13. Integrated scheduling of renewable generation and demand response programs in a microgrid

    International Nuclear Information System (INIS)

    Mazidi, Mohammadreza; Zakariazadeh, Alireza; Jadid, Shahram; Siano, Pierluigi

    2014-01-01

    Highlights: • Participation of all types of customers in demand response programs. • Generating scenarios by using Latin hypercube sampling (LHS). • Energy and reserve scheduling in a microgrid using stochastic optimization. - Abstract: Wind and solar energy introduced significant operational challenges in a Microgrid (MG), especially when renewable generations vary from forecasts. In this paper, forecast errors of wind speed and solar irradiance are modeled by related probability distribution functions and then, by using the Latin hypercube sampling (LHS), the plausible scenarios of renewable generation for day-head energy and reserve scheduling are generated. A two-stage stochastic objective function aiming at minimizing the expected operational cost is implemented. In the proposed method, the reserve requirement for compensating renewable forecast errors is provided by both responsive loads and distributed generation units. All types of customers such as residential, commercial and industrial ones can participate in demand response programs which are considered in either energy or reserve scheduling. In order to validate the proposed methodology, the proposed approach is finally applied to a typical MG and simulation results are carried out

  14. Fast-responsive hydrogel as an injectable pump for rapid on-demand fluidic flow control.

    Science.gov (United States)

    Luo, Rongcong; Dinh, Ngoc-Duy; Chen, Chia-Hung

    2017-05-01

    Chemically synthesized functional hydrogels have been recognized as optimized soft pumps for on-demand fluidic regulation in micro-systems. However, the challenges regarding the slow responses of hydrogels have very much limited their application in effective fluidic flow control. In this study, a heterobifunctional crosslinker (4-hydroxybutyl acrylate)-enabled two-step hydrothermal phase separation process for preparing a highly porous hydrogel with fast response dynamics was investigated for the fabrication of novel microfluidic functional units, such as injectable valves and pumps. The cylinder-shaped hydrogel, with a diameter of 9 cm and a height of 2.5 cm at 25 °C, achieved a size reduction of approximately 70% in less than 30 s after the hydrogels were heated at 40 °C. By incorporating polypyrrole nanoparticles as photothermal transducers, a photo-responsive composite hydrogel was approached and exhibited a remotely triggerable fluidic regulation and pumping ability to generate significant flows, showing on-demand water-in-oil droplet generation by laser switching, whereby the droplet size could be tuned by adjusting the laser intensity and irradiation period with programmable manipulation.

  15. A survey of utility experience with real time pricing: implications for policymakers seeking price responsive demand

    International Nuclear Information System (INIS)

    Barbose, Galen; Goldman, Charles; Neenan, Bernard

    2005-01-01

    Economists and policy makers frequently propose real time pricing (RTP) as a strategy for facilitating price responsive demand, thereby improving the performance of electricity markets and regional networks. While theoretically appealing, many practical and empirical issues related to RTP remain unresolved or poorly understood. Over the past two decades, more than 70 utilities in the U.S. have offered voluntary RTP tariffs, on either a pilot or permanent basis. However, most have operated in relative obscurity, and little information has made its way into the public domain. To address this gap, we conducted a conducted a comprehensive review of voluntary RTP programs in the U.S. by surveying 43 U.S. utilities and reviewing regulatory documents, tariffs, program evaluations, and other publicly available sources. Based on this review of RTP program experience, we identify key trends related to utilities' motivations and goals for implementing RTP, evolution of RTP tariff design, program participation, participant price response, and program outlook. Experience with voluntary RTP programs has been mixed. Several utilities have demonstrated that voluntary RTP programs are capable of generating significant load reductions. However, most programs have attracted relatively few participants and therefore have generated quite limited load reductions. About 2700 non-residential customers were enrolled in RTP programs in 2003, representing more than 11 000 MW of load. We then draw from these findings to identify implications for policy makers and regulators that are currently considering RTP as a strategy for facilitating price responsive demand

  16. Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response

    International Nuclear Information System (INIS)

    Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; Hirohisa, Aki; Lai, Judy

    2009-01-01

    The US Department of Energy has launched the Zero-Net-Energy (ZNE) Commercial Building Initiative (CBI) in order to develop commercial buildings that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge energy-efficient technologies and meet their remaining energy needs through on-site renewable energy generation. We examine how such buildings may be implemented within the context of a cost- or carbon-minimizing microgrid that is able to adopt and operate various technologies, such as photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive/demand-response technologies. We use a mixed-integer linear program (MILP) that has a multi-criteria objective function: the minimization of a weighted average of the building's annual energy costs and carbon/CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the CBI. Using a nursing home in northern California and New York with existing tariff rates and technology data, we find that a ZNE building requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve ZNE. For comparison, we analyze a nursing home facility in New York to examine the effects of a flatter tariff structure and different load profiles. It has trouble reaching ZNE status and its load reductions as well as efficiency measures need to be more effective than those in the CA case

  17. Cyber Physical System Modelling of Distribution Power Systems for Dynamic Demand Response

    Science.gov (United States)

    Chu, Xiaodong; Zhang, Rongxiang; Tang, Maosen; Huang, Haoyi; Zhang, Lei

    2018-01-01

    Dynamic demand response (DDR) is a package of control methods to enhance power system security. A CPS modelling and simulation platform for DDR in distribution power systems is presented in this paper. CPS modelling requirements of distribution power systems are analyzed. A coupled CPS modelling platform is built for assessing DDR in the distribution power system, which combines seamlessly modelling tools of physical power networks and cyber communication networks. Simulations results of IEEE 13-node test system demonstrate the effectiveness of the modelling and simulation platform.

  18. Second life battery energy storage system for residential demand response service

    DEFF Research Database (Denmark)

    Saez-de-Ibarra, Andoni; Martinez-Laserna, Egoitz; Koch-Ciobotaru, Cosmin

    2015-01-01

    The integration of renewable energies and the usage of battery energy storage systems (BESS) into the residential buildings opens the possibility for minimizing the electricity bill for the end-user. This paper proposes the use of batteries that have already been aged while powering electric...... vehicles, during their main first life application, for providing residential demand response service. The paper considers the decayed characteristics of these batteries and optimizes the rating of such a second life battery energy storage system (SLBESS) for maximizing the economic benefits of the user...

  19. Economic demand response model in liberalised electricity markets with respect to flexibility of consumers

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    . The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...... electricity at flat rates while paying no attention to the problems of this industry. This attitude was the source of many problems, sometimes leading to collapse of power systems and widespread blackouts. Restructuring of the electricity industry however provided a multitude of solutions to these problems...

  20. Impact of thermostatically controlled loads' demand response activation on aggregated power: A field experiment

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam; Marinelli, Mattia; Kosek, Anna Magdalena

    2015-01-01

    This paper describes the impacts of different types of DR (demand response) activation on TCLs' (thermostatically controlled loads) aggregated power. The different parties: power system operators, DR service providers (or aggregators) and consumers, have different objectives in relation to DR...... activation. The outcome of this experimental study quantifies the actual flexibility of household TCLs and the consequence for the different parties with respect to power behaviour. Each DR activation method adopts different scenarios to meet the power reduction, and has different impacts on the parameters...

  1. Energy shift estimation of demand response activation on domestic refrigerators – A field test study

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam; Gudmand-Høyer, Kristian; Marinelli, Mattia

    2014-01-01

    This paper presents a method to estimate the amount of energy that can be shifted during demand response (DR) activation on domestic refrigerator. Though there are many methods for DR activation like load reduction, load shifting and onsite generation, the method under study is load shifting....... Electric heating and cooling equipment like refrigerators, water heaters and space heaters and coolers are preferred for such DR activation because of their energy storing capacity. Accurate estimation of available regulating power and energy shift is important to understand the value of DR activation...

  2. Impacts of demand response and renewable generation in electricity power market

    Science.gov (United States)

    Zhao, Zhechong

    This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

  3. Automated Critical Peak Pricing Field Tests: Program Descriptionand Results

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

    2006-04-06

    California utilities have been exploring the use of critical peak prices (CPP) to help reduce needle peaks in customer end-use loads. CPP is a form of price-responsive demand response (DR). Recent experience has shown that customers have limited knowledge of how to operate their facilities in order to reduce their electricity costs under CPP (Quantum 2004). While the lack of knowledge about how to develop and implement DR control strategies is a barrier to participation in DR programs like CPP, another barrier is the lack of automation of DR systems. During 2003 and 2004, the PIER Demand Response Research Center (DRRC) conducted a series of tests of fully automated electric demand response (Auto-DR) at 18 facilities. Overall, the average of the site-specific average coincident demand reductions was 8% from a variety of building types and facilities. Many electricity customers have suggested that automation will help them institutionalize their electric demand savings and improve their overall response and DR repeatability. This report focuses on and discusses the specific results of the Automated Critical Peak Pricing (Auto-CPP, a specific type of Auto-DR) tests that took place during 2005, which build on the automated demand response (Auto-DR) research conducted through PIER and the DRRC in 2003 and 2004. The long-term goal of this project is to understand the technical opportunities of automating demand response and to remove technical and market impediments to large-scale implementation of automated demand response (Auto-DR) in buildings and industry. A second goal of this research is to understand and identify best practices for DR strategies and opportunities. The specific objectives of the Automated Critical Peak Pricing test were as follows: (1) Demonstrate how an automated notification system for critical peak pricing can be used in large commercial facilities for demand response (DR). (2) Evaluate effectiveness of such a system. (3) Determine how customers

  4. Attributing Agency to Automated Systems: Reflections on Human-Robot Collaborations and Responsibility-Loci.

    Science.gov (United States)

    Nyholm, Sven

    2017-07-18

    Many ethicists writing about automated systems (e.g. self-driving cars and autonomous weapons systems) attribute agency to these systems. Not only that; they seemingly attribute an autonomous or independent form of agency to these machines. This leads some ethicists to worry about responsibility-gaps and retribution-gaps in cases where automated systems harm or kill human beings. In this paper, I consider what sorts of agency it makes sense to attribute to most current forms of automated systems, in particular automated cars and military robots. I argue that whereas it indeed makes sense to attribute different forms of fairly sophisticated agency to these machines, we ought not to regard them as acting on their own, independently of any human beings. Rather, the right way to understand the agency exercised by these machines is in terms of human-robot collaborations, where the humans involved initiate, supervise, and manage the agency of their robotic collaborators. This means, I argue, that there is much less room for justified worries about responsibility-gaps and retribution-gaps than many ethicists think.

  5. Comparison of the marketing of demand response capacity and of power plant capacity in the minutes reserve market; Vergleich der Vermarktung von Demand-Response- und Kraftwerksleistung auf dem Minutenreservemarkt

    Energy Technology Data Exchange (ETDEWEB)

    Marz, Waldemar; Tzscheutschler, Peter [Technische Univ. Muenchen (Germany). Lehrstuhl fuer Energiewirtschaft und Anwendungstechnik; Henle, Markus [Stadtwerke Muenchen (Germany). Energiewirtschaft

    2013-03-15

    The greatest challenge in integrating renewable energies into the German and European power supply system lies in levelling out the imbalances between the fluctuating supply of energy from the wind and sun on the one side and the steady demand of the consumers on the other. Aside from the expansion of supra-regional transmission systems and storage power plants one instrument that has raised great hopes is the possibility of adapting demand to supply. These methods are known by the names of demand response (DR) or demand side management (DSM) and are at the core of the ''smart grid'' concept.

  6. Demand Estimation

    OpenAIRE

    Elliot E. Combs

    2017-01-01

    Price elasticity shows the responsiveness of demand to changes in price. Negative price elasticity of demand (PED) signifies the inverse relationship between price and demand. According to the equation, PED is -1.19 for widgets, which means that an increase in price of $1 would result in a contraction of demand of $1.19. Since the change in price corresponds with a more than proportionate change in demand, PED is said to be elastic. As a result, an increase in price would discourage consumers...

  7. Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response

    Directory of Open Access Journals (Sweden)

    Yongli Wang

    2018-03-01

    Full Text Available With the application of distributed generation and the development of smart grid technology, micro-grid, an economic and stable power grid, tends to play an important role in the demand side management. Because micro-grid technology and demand response have been widely applied, what Demand Response actions can realize the economic operation of micro-grid has become an important issue for utilities. In this proposed work, operation optimization modeling for micro-grid is done considering distributed generation, environmental factors and demand response. The main contribution of this model is to optimize the cost in the context of considering demand response and system operation. The presented optimization model can reduce the operation cost of micro-grid without bringing discomfort to the users, thus increasing the consumption of clean energy effectively. Then, to solve this operational optimization problem, genetic algorithm is used to implement objective function and DR scheduling strategy. In addition, to validate the proposed model, it is employed on a smart micro-grid from Tianjin. The obtained numerical results clearly indicate the impact of demand response on economic operation of micro-grid and development of distributed generation. Besides, a sensitivity analysis on the natural gas price is implemented according to the situation of China, and the result shows that the natural gas price has a great influence on the operation cost of the micro-grid and effect of demand response.

  8. Reliability constrained decision model for energy service provider incorporating demand response programs

    International Nuclear Information System (INIS)

    Mahboubi-Moghaddam, Esmaeil; Nayeripour, Majid; Aghaei, Jamshid

    2016-01-01

    Highlights: • The operation of Energy Service Providers (ESPs) in electricity markets is modeled. • Demand response as the cost-effective solution is used for energy service provider. • The market price uncertainty is modeled using the robust optimization technique. • The reliability of the distribution network is embedded into the framework. • The simulation results demonstrate the benefits of robust framework for ESPs. - Abstract: Demand response (DR) programs are becoming a critical concept for the efficiency of current electric power industries. Therefore, its various capabilities and barriers have to be investigated. In this paper, an effective decision model is presented for the strategic behavior of energy service providers (ESPs) to demonstrate how to participate in the day-ahead electricity market and how to allocate demand in the smart distribution network. Since market price affects DR and vice versa, a new two-step sequential framework is proposed, in which unit commitment problem (UC) is solved to forecast the expected locational marginal prices (LMPs), and successively DR program is applied to optimize the total cost of providing energy for the distribution network customers. This total cost includes the cost of purchased power from the market and distributed generation (DG) units, incentive cost paid to the customers, and compensation cost of power interruptions. To obtain compensation cost, the reliability evaluation of the distribution network is embedded into the framework using some innovative constraints. Furthermore, to consider the unexpected behaviors of the other market participants, the LMP prices are modeled as the uncertainty parameters using the robust optimization technique, which is more practical compared to the conventional stochastic approach. The simulation results demonstrate the significant benefits of the presented framework for the strategic performance of ESPs.

  9. A Comparison of Sales Response Predictions From Demand Models Applied to Store-Level versus Panel Data

    NARCIS (Netherlands)

    Andrews, Rick L.; Currim, Imran S.; Leeflang, Peter S. H.

    In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate

  10. Emergency response network design for hazardous materials transportation with uncertain demand

    Directory of Open Access Journals (Sweden)

    Kamran Shahanaghi

    2012-10-01

    Full Text Available Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats, such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method.

  11. Market and policy barriers for demand response providing ancillary services in U.S. markets

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); MacDonald, Jason [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Goldman, Charles [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

    2013-03-01

    This study provides an examination of various market and policy barriers to demand response providing ancillary services in both ISO/RTO and non-ISO/RTO regions, especially at the program provider level. It is useful to classify barriers in order to create a holistic understanding and identify parties that could be responsible for their removal. This study develops a typology of barriers focusing on smaller customers that must rely on a program provider (i.e., electric investor owned utility or IOU, ARC) to create an aggregated DR resource in order to bring ancillary services to the balancing authority. The barriers were identified through examinations of regulatory structures, market environments, and product offerings; and discussions with industry stakeholders and regulators. In order to help illustrate the differences in barriers among various wholesale market designs and their constituent retail environments, four regions were chosen to use as case studies: Colorado, Texas, Wisconsin, and New Jersey.

  12. Review of Real-time Electricity Markets for Integrating Distributed Energy Resources and Demand Response

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu; Ding, Yi

    2015-01-01

    The high penetration of both Distributed Energy Resources (DER) and Demand Response (DR) in modern power systems requires a sequence of advanced strategies and technologies for maintaining system reliability and flexibility. Real-time electricity markets (RTM) are the nondiscriminatory transaction...... and DR to participate in balancing market transactions, while handling their meteorological or intermittent characteristics, facilitating asset utilization, and stimulating their active responses. Consequently, RTMs are dedicated to maintaining the flexibility and reliability of power systems. This paper...... platforms for providing necessary balancing services, where the market clearing (nodal or zonal prices depending on markets) is very close to real time operations of power systems. One of the primary functions of RTMs in modern power systems is establishing an efficient and effective mechanism for small DER...

  13. A Methodology for Estimating Large-Customer Demand Response MarketPotential

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Cappers,Peter

    2007-08-01

    Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of $500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.

  14. Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

    Science.gov (United States)

    Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

    2017-12-01

    In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

  15. Field Testing of Telemetry for Demand Response Control of Small Loads

    Energy Technology Data Exchange (ETDEWEB)

    Lanzisera, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Adam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liao, Anna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schetrit, Oren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2018-01-30

    The electricity system in California, from generation through loads, must be prepared for high renewable penetration and increased electrification of end uses while providing increased resilience and lower operating cost. California has an aggressive renewable portfolio standard that is complemented by world-leading greenhouse gas goals. The goal of this project was to evaluate methods of enabling fast demand response (DR) signaling to small loads for low-cost site enablement. We used OpenADR 2.0 to meet telemetry requirements for providing ancillary services, and we used a variety of low-cost devices coupled with open-source software to enable an end-to-end fast DR. The devices, architecture, implementation, and testing of the system is discussed in this report. We demonstrate that the emerging Internet of Things (IoT) and Smart Home movements provide an opportunity for diverse small loads to provide fast, low-cost demand response. We used Internet-connected lights, thermostats, load interruption devices, and water heaters to demonstrate an ecosystem of controllable devices. The system demonstrated is capable of providing fast load shed for between 20 dollars and $300 per kilowatt (kW) of available load. The wide range results from some loads may have very low cost but also very little shed capability (a 10 watt [W] LED light can only shed a maximum of 10 W) while some loads (e.g., water heaters or air conditioners) can shed several kilowatts but have a higher initial cost. These costs, however, compare well with other fast demand response costs, with typically are over $100/kilowatt of shed. We contend these loads are even more attractive than their price suggests because many of them will be installed for energy efficiency or non-energy benefits (e.g., improved lighting quality or controllability), and the ability to use them for fast DR is a secondary benefit. Therefore the cost of enabling them for DR may approach zero if a software-only solution can be

  16. Web-based energy information systems for energy management and demand response in commercial buildings

    Energy Technology Data Exchange (ETDEWEB)

    Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

    2003-04-18

    Energy Information Systems (EIS) for buildings are becoming widespread in the U.S., with more companies offering EIS products every year. As a result, customers are often overwhelmed by the quickly expanding portfolio of EIS feature and application options, which have not been clearly identified for consumers. The object of this report is to provide a technical overview of currently available EIS products. In particular, this report focuses on web-based EIS products for large commercial buildings, which allow data access and control capabilities over the Internet. EIS products combine software, data acquisition hardware, and communication systems to collect, analyze and display building information to aid commercial building energy managers, facility managers, financial managers and electric utilities in reducing energy use and costs in buildings. Data types commonly processed by EIS include energy consumption data; building characteristics; building system data, such as heating, ventilation, and air-conditioning (HVAC) and lighting data; weather data; energy price signals; and energy demand-response event information. This project involved an extensive review of research and trade literature to understand the motivation for EIS technology development. This study also gathered information on currently commercialized EIS. This review is not an exhaustive analysis of all EIS products; rather, it is a technical framework and review of current products on the market. This report summarizes key features available in today's EIS, along with a categorization framework to understand the relationship between EIS, Energy Management and Control Systems (EMCSs), and similar technologies. Four EIS types are described: Basic Energy Information Systems (Basic-EIS); Demand Response Systems (DRS); Enterprise Energy Management (EEM); and Web-based Energy Management and Control Systems (Web-EMCS). Within the context of these four categories, the following characteristics of EIS

  17. An ILP based Algorithm for Optimal Customer Selection for Demand Response in SmartGrids

    Energy Technology Data Exchange (ETDEWEB)

    Kuppannagari, Sanmukh R. [Univ. of Southern California, Los Angeles, CA (United States); Kannan, Rajgopal [Louisiana State Univ., Baton Rouge, LA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-12-07

    Demand Response (DR) events are initiated by utilities during peak demand periods to curtail consumption. They ensure system reliability and minimize the utility’s expenditure. Selection of the right customers and strategies is critical for a DR event. An effective DR scheduling algorithm minimizes the curtailment error which is the absolute difference between the achieved curtailment value and the target. State-of-the-art heuristics exist for customer selection, however their curtailment errors are unbounded and can be as high as 70%. In this work, we develop an Integer Linear Programming (ILP) formulation for optimally selecting customers and curtailment strategies that minimize the curtailment error during DR events in SmartGrids. We perform experiments on real world data obtained from the University of Southern California’s SmartGrid and show that our algorithm achieves near exact curtailment values with errors in the range of 10-7 to 10-5, which are within the range of numerical errors. We compare our results against the state-of-the-art heuristic being deployed in practice in the USC SmartGrid. We show that for the same set of available customer strategy pairs our algorithm performs 103 to 107 times better in terms of the curtailment errors incurred.

  18. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, C. Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Liu, Jialin [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton MA (United States)

    2017-01-07

    The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

  19. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton, MA (United States)

    2017-01-06

    The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.

  20. Multi-Objective Low-Carbon Economic Dispatch Considering Demand Response with Wind Power Integrated Systems

    Directory of Open Access Journals (Sweden)

    Liu Wenjuan

    2017-01-01

    Full Text Available The generation cost, carbon emissions and customers’ satisfaction are considered in this paper. On the basis of this, the multi-objective and low-carbon economic dispatch model with wind farm, this considers demand response, is established. The model user stochastic programming theory to describe the uncertainty of the wind power and converts it into an equivalent deterministic model by using distribution function of wind power output, optimizes demand side resources to adjust the next day load curve and to improve load rate and absorptive capacity of wind power, introduce customers’ satisfaction to ensure that the scheduling scheme satisfies customer and integrate the resources of source and load to unify coordination wind farm access to network and to meet the requirements of energy saving and emission reduction. The search process of artificial fish school algorithm introducing Tabu search and more targeted search mechanism, an multi-objective improved artificial fish school algorithm is proposed to solve this model. Using the technique for order preference by similarity to ideal solution (TOPSIS to sort the Pareto frontier, the optimal scheduling scheme is determined. Simulation results verify the rationality and validity of the proposed model and algorithm.

  1. An update of the Canadian initiatives of IEA Task 13 : demand response resources

    International Nuclear Information System (INIS)

    Malme, R. |; International Energy Agency, Paris

    2006-01-01

    The International Energy Agency Demand Side Management (IEA DSM) program is an international collaboration with 17 IEA member countries and the European Commission. The program aims to clarify and promote opportunities for DSM through load management, energy efficiency and strategic conservation. Task 13 of the program is charged with reviewing demand response resource (DRR) practices in various markets around the world and developing recommendations and tools for integrating DRR into regular market activities. The Ontario Power Authority (OPA), National Research Council (NRC) and CEA Technologies Inc. (CEATI) are leading participation in Task 13 in Canada. The team is currently collecting market information as well as creating tools to provide references to activities in other markets. This presentation reviewed the team's subtasks, which include: the development of DR market benchmarks and translation methods; the collection of DR consumer surveys and utilization methods; the creation of a DR market potential calculator to provide estimates for generating target marketing strategies; the creation of a valuation guide for technical users, administrators and regulators; a catalogue describing the technologies and systems that are available for use in DR programs; identifying market barriers; and the creation of a web portal that will be a virtual centre of excellence concerning DR methods, technologies and applications. DR programs in Norway, Finland, the Netherlands were also reviewed. refs., tabs., figs

  2. A Price-Based Demand Response Scheme for Discrete Manufacturing in Smart Grids

    Directory of Open Access Journals (Sweden)

    Zhe Luo

    2016-08-01

    Full Text Available Demand response (DR is a key technique in smart grid (SG technologies for reducing energy costs and maintaining the stability of electrical grids. Since manufacturing is one of the major consumers of electrical energy, implementing DR in factory energy management systems (FEMSs provides an effective way to manage energy in manufacturing processes. Although previous studies have investigated DR applications in process manufacturing, they were not conducted for discrete manufacturing. In this study, the state-task network (STN model is implemented to represent a discrete manufacturing system. On this basis, a DR scheme with a specific DR algorithm is applied to a typical discrete manufacturing—automobile manufacturing—and operational scenarios are established for the stamping process of the automobile production line. The DR scheme determines the optimal operating points for the stamping process using mixed integer linear programming (MILP. The results show that parts of the electricity demand can be shifted from peak to off-peak periods, reducing a significant overall energy costs without degrading production processes.

  3. Data-Driven Baseline Estimation of Residential Buildings for Demand Response

    Directory of Open Access Journals (Sweden)

    Saehong Park

    2015-09-01

    Full Text Available The advent of advanced metering infrastructure (AMI generates a large volume of data related with energy service. This paper exploits data mining approach for customer baseline load (CBL estimation in demand response (DR management. CBL plays a significant role in measurement and verification process, which quantifies the amount of demand reduction and authenticates the performance. The proposed data-driven baseline modeling is based on the unsupervised learning technique. Specifically we leverage both the self organizing map (SOM and K-means clustering for accurate estimation. This two-level approach efficiently reduces the large data set into representative weight vectors in SOM, and then these weight vectors are clustered by K-means clustering to find the load pattern that would be similar to the potential load pattern of the DR event day. To verify the proposed method, we conduct nationwide scale experiments where three major cities’ residential consumption is monitored by smart meters. Our evaluation compares the proposed solution with the various types of day matching techniques, showing that our approach outperforms the existing methods by up to a 68.5% lower error rate.

  4. Raising the accommodation ceiling for wind power by intelligent response of demand and distributed generation

    Energy Technology Data Exchange (ETDEWEB)

    MacDougall, Pamella; Kok, Koen [TNO (Netherlands). Smart Grid group; Warmer, Cor [Energy Research Centre of the Netherlands (ECN) (Netherlands)

    2011-07-01

    With the world becoming ever more conscious of the necessity for clean, sustainable energy sources, an increased proportion of energy produced by wind resources is expected. In the current power system, the integration of such large capacity of non-controllable and intermittent supply leads to several challenges, one of which is to control the balance between demand and supply. A large - not yet utilized - source that may provide flexibility to contribute to this balance is available at the household level. Efficient heating systems such as heat pumps, distributed generation from e.g. micro-CHP and storage facilities as provided by electric vehicles can be intelligently controlled in the future smart grid in order to adapt in near real-time to fluctuating wind power. One of these enabling technologies, the PowerMatcher, has already been proven in several field trials in real-life circumstances. This multi-agent-based system uses electronic markets to coordinate devices with the objective of matching electricity supply and demand. In this paper, the potential of the PowerMatcher technology is explored to accommodate mass integration of electricity produced by wind energy by adapting flexible household demand and supply to the availability of wind power. In this way the need for - fossil fuel based - extra reserve capacity will be minimized as compared to business as usual. These studies, from the European FP 7 project Smart House Smart Grid, have been achieved by running large-scale simulations, of one million households, under real-life conditions. In these simulation studies the Dutch WLO-SE scenario has been followed, that foresees a strong increase in capacity of off-shore wind energy from 3 GW in 2020 to 10 GW in 2040 in the Netherlands. Results have been extrapolated to even faster wind energy growth scenarios as envisioned by the wind energy industry (e.g. We rate at sea). We will show that by using demand response in homes we can accommodate mass integration

  5. The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory

    International Nuclear Information System (INIS)

    Tan, Zhongfu; Ju, Liwei; Reed, Brent; Rao, Rao; Peng, Daoxin; Li, Huanhuan; Pan, Ge

    2015-01-01

    Highlights: • Our research focuses on demand response behaviors of multi-type customers. • A wind power simulation method is proposed based on the Brownian motion theory. • Demand response revenue functions are proposed for multi-type customers. • A robust stochastic optimization model is proposed for wind power consumptive. • Models are built to measure the impacts of demand response on wind power consumptive. - Abstract: In order to relieve the influence of wind power uncertainty on power system operation, demand response and robust stochastic theory are introduced to build a stochastic scheduling optimization model. Firstly, this paper presents a simulation method for wind power considering external environment based on Brownian motion theory. Secondly, price-based demand response and incentive-based demand response are introduced to build demand response model. Thirdly, the paper constructs the demand response revenue functions for electric vehicle customers, business customers, industry customers and residential customers. Furthermore, robust stochastic optimization theory is introduced to build a wind power consumption stochastic optimization model. Finally, simulation analysis is taken in the IEEE 36 nodes 10 units system connected with 650 MW wind farms. The results show the robust stochastic optimization theory is better to overcome wind power uncertainty. Demand response can improve system wind power consumption capability. Besides, price-based demand response could transform customers’ load demand distribution, but its load curtailment capacity is not as obvious as incentive-based demand response. Since price-based demand response cannot transfer customer’s load demand as the same as incentive-based demand response, the comprehensive optimization effect will reach best when incentive-based demand response and price-based demand response are both introduced.

  6. Area price and demand response in a market with 25% wind power

    DEFF Research Database (Denmark)

    Grohnheit, Poul Erik; Møller Andersen, Frits; Larsen, Helge V.

    2011-01-01

    events were few, and the current infrastructure and market organisation have been able to handle the amount of wind power installed so far. This recommends that geographical bidding area for the wholesale electricity market reflects external transmission constraints caused by wind power....... not only on the electricity wholesale prices, but also on the development of the market. Hourly market data are available from the website of Danish TSO from 1999. In this paper these data are analysed for the period 2004–2010. Electricity generators and customers may respond to hourly price variations......, which can improve market efficiency, and a welfare gain is obtained. An important limitation for demand response is events of several consecutive hours with extreme values. The analysis in this paper is a summary and update of some of the issues covered by the EU RESPOND project. It shows that extreme...

  7. Heat Pump Water Heaters: Controlled Field Research of Impact on Space Conditioning and Demand Response Characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Parker, Graham B.; Widder, Sarah H.; Eklund, Ken; Petersen, Joseph M.; Sullivan, Greg

    2015-10-05

    A new generation of heat pump water heaters (HPWH) has been introduced into the U.S. market that promises to provide significant energy savings for water heating. Many electric utilities are promoting their widespread adoption as a key technology for meeting energy conservation goals and reducing greenhouse gas emissions. There is, however, considerable uncertainty regarding the space conditioning impact of an HPWH installed in a conditioned space. There is also uncertainty regarding the potential for deployment of HPWHs in demand response (DR) programs to help manage and balance peak utility loads in a similar manner as conventional electric resistance water heaters (ERWH). To help answer these uncertainties, controlled experiments have been undertaken over 30 months in a matched pair of unoccupied Lab Homes located on the campus of the Pacific Northwest National Laboratory (PNNL) in Richland, Washington.

  8. Demand Response Design and Use Based on Network Locational Marginal Prices

    DEFF Research Database (Denmark)

    Morais, Hugo; Faria, Pedro; Vale, Zita

    2014-01-01

    Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation...... (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper...... proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific...

  9. Technical Resource Potential of Non-disruptive Residential Demand Response in Denmark

    DEFF Research Database (Denmark)

    Mathieu, Johanna; Rasmussen, Theis Bo; Sørensen, Mads

    2014-01-01

    Denmark has one of the most aggressive renewable energy strategies in the world; however, large penetrations of fluctuating renewable energy resources will pose new problems in the Danish power system. Demand response (DR) has the potential to mitigate these problems by providing a new source...... technical resource potentials, and use real data from Denmark. We find that country-wide load flexibility is on the order of GWs and GWhs, and will increase drastically over the next 20 years due to electrification of space heating systems and vehicles. However, we also find that flexibility is time...... of flexibility. This paper estimates the technical resource potential of residential DR in Denmark. We focus on DR that is non-disruptive to the consumer, meaning that DR actions harness inherent load flexibility and are not noticeable by the consumer. We build on existing methodologies for computing DR...

  10. Real-time Trading Strategies for Proactive Distribution Company with Distributed Generation and Demand Response

    DEFF Research Database (Denmark)

    Wang, Qi

    Distributed energy resources (DERs), such as distributed generation (DG) and demand response (DR), have been recognized worldwide as valuable resources. High integration of DG and DR in the distribution network inspires a potential deregulated environment for the distribution company (DISCO......) directly procuring capacities from local DG and DR. In this situation, a hierarchical market structure is achieved comprising the transmission-level (TL) and distribution-level (DL) markets. Focusing on the real-time process, as the interface actor, the DISCO's behavior covers downwardly procuring DL DG...... and DR resources, and upwardly trading in the TL real-time market, resulting in a proactive manner. The DL aggregator (DA) is dened to manage these small-scale and dispersed DGs and DRs. A methodology is proposed in this thesis for a proactive DISCO (PDISCO) to strategically trade with DAs...

  11. Methodology for validating technical tools to assess customer Demand Response: Application to a commercial customer

    International Nuclear Information System (INIS)

    Alcazar-Ortega, Manuel; Escriva-Escriva, Guillermo; Segura-Heras, Isidoro

    2011-01-01

    The authors present a methodology, which is demonstrated with some applications to the commercial sector, in order to validate a Demand Response (DR) evaluation method previously developed and applied to a wide range of industrial and commercial segments, whose flexibility was evaluated by modeling. DR is playing a more and more important role in the framework of electricity systems management for the effective integration of other distributed energy resources. Consequently, customers must identify what they are using the energy for in order to use their flexible loads for management purposes. Modeling tools are used to predict the impact of flexibility on the behavior of customers, but this result needs to be validated since both customers and grid operators have to be confident in these flexibility predictions. An easy-to-use two-steps method to achieve this goal is presented in this paper.

  12. The effect of demand response on purchase intention of distributed generation: Evidence from Japan

    International Nuclear Information System (INIS)

    Nakada, Tatsuhiro; Shin, Kongjoo; Managi, Shunsuke

    2016-01-01

    Participation in demand response (DR) may affect a consumer's electric consumption pattern through consumption load curtailment, a shift in the consumption timing or increasing the utilization of distributed generation (DG). This paper attempts to provide empirical evidence of DR's effect on DG adoption by household consumers. By using the original Internet survey data of 5442 household respondents in Japan conducted in January 2015, we focus on the effect of the time-of-use (TOU) tariff on the purchasing intention of photovoltaic systems (PV). The empirical results show the following: 1) current TOU plan users have stronger PV purchase intentions than the other plan users, 2) respondents who are familiar with the DR program have relatively higher purchase intentions compared with their counterparts, and 3) when the respondents are requested to assume participation in the virtual TOU plan designed for the survey, which resembles plans currently available through major companies, 1.2% of the households have decided to purchase PV. In addition, we provide calculations of TOU's impacts on the official PV adoption and emissions reduction targets, and discuss policy recommendations to increase recognitions and participations in TOU programs. - Highlights: •Studies the effect of demand response on purchase intention of PV. •Uses originally collected Internet Japanese household survey data in 2015. •Finds that time-of-use (TOU) plan has positive effect on PV purchase intentions. •Calculates latent TOU impacts on PV installations and emissions reduction targets. •Discusses policy recommendations to increase participations in TOU programs.

  13. Optimizing Industrial Consumer Demand Response Through Disaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

    Science.gov (United States)

    Abdulaal, Ahmed

    The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.

  14. A bilevel model for electricity retailers' participation in a demand response market environment

    International Nuclear Information System (INIS)

    Zugno, Marco; Morales, Juan Miguel; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. - Highlights: ► We model the game between electricity retailers and consumers under dynamic pricing. ► The retailer cuts procurement costs by shifting demand in time via price-incentive. ► Imbalance costs for the retailer taper

  15. Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel J.; Matson, Nance; Sohn, Michael D.; Rose, Cody; Dudley, Junqiao; Goli, Sasank; Kiliccote, Sila; Hummon, Marissa; Palchak, David; Denholm, Paul; Jorgenson, Jennie

    2013-09-09

    Demand response (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demand response availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demand response through production cost modeling, which informs infrastructure and investment planning.

  16. Stomatal response of an anisohydric grapevine cultivar to evaporative demand, available soil moisture and abscisic acid.

    Science.gov (United States)

    Rogiers, Suzy Y; Greer, Dennis H; Hatfield, Jo M; Hutton, Ron J; Clarke, Simon J; Hutchinson, Paul A; Somers, Anthony

    2012-03-01

    Stomatal responsiveness to evaporative demand (air vapour pressure deficit (VPD)) ranges widely between species and cultivars, and mechanisms for stomatal control in response to VPD remain obscure. The interaction of irrigation and soil moisture with VPD on stomatal conductance is particularly difficult to predict, but nevertheless is critical to instantaneous transpiration and vulnerability to desiccation. Stomatal sensitivity to VPD and soil moisture was investigated in Semillon, an anisohydric Vitis vinifera L. variety whose leaf water potential (Ψ(l)) is frequently lower than that of other grapevine varieties grown under similar conditions in the warm grape-growing regions of Australia. A survey of Semillon vines across seven vineyards revealed that, regardless of irrigation treatment, midday Ψ(l) was dependent on not only soil moisture but VPD at the time of measurement. Predawn Ψ(l) was more closely correlated to not only soil moisture in dry vineyards but to night-time VPD in drip-irrigated vineyards, with incomplete rehydration during high night-time VPD. Daytime stomatal conductance was low only under severe plant water deficits, induced by extremes in dry soil. Stomatal response to VPD was inconsistent across irrigation regime; however, in an unirrigated vineyard, stomatal sensitivity to VPD-the magnitude of stomatal response to VPD-was heightened under dry soils. It was also found that stomatal sensitivity was proportional to the magnitude of stomatal conductance at a reference VPD of 1kPa. Exogenous abscisic acid (ABA) applied to roots of Semillon vines growing in a hydroponic system induced stomatal closure and, in field vines, petiole xylem sap ABA concentrations rose throughout the morning and were higher in vines with low Ψ(l). These data indicate that despite high stomatal conductance of this anisohydric variety when grown in medium to high soil moisture, increased concentrations of ABA as a result of very limited soil moisture may augment

  17. A nationwide web-based automated system for early outbreak detection and rapid response in China

    Directory of Open Access Journals (Sweden)

    Yilan Liao

    2011-03-01

    Full Text Available Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

  18. An assessment of market and policy barriers for demand response providing ancillary services in U.S. electricity markets

    International Nuclear Information System (INIS)

    Cappers, Peter; MacDonald, Jason; Goldman, Charles; Ma, Ookie

    2013-01-01

    An impact of increased variable renewable generation is the need for balancing authorities to procure more ancillary services. While demand response resources are technically capable of providing these services, current experience across the U.S. illustrates they are relatively minor players in most regions. Accessing demand response resources for ancillary services may require a number of changes to policies and common practices at multiple levels. Regional reliability councils must first define ancillary services such that demand response resources may provide them. Once the opportunity exists, balancing authorities define and promulgate rules that set the infrastructure investments and performance attributes of a resource wishing to provide such services. These rules also dictate expected revenue streams which reveal the cost effectiveness of these resources. The regulatory compact between utility and state regulators, along with other statutes and decisions by state policymakers, may impact the interest of demand response program providers to pursue these resources as ancillary service providers. This paper identifies within these broad categories specific market and policy barriers to demand response providing ancillary services in different wholesale and retail environments, with emphasis on smaller customers who must be aggregated through a program provider to meet minimum size requirements for wholesale transactions. - Highlights: • We identify barriers keeping demand response from providing ancillary services. • Institutional, financial and program provider business model barriers exist. • Product definitions and rules do not always accommodate demand response well. • Expected revenues are uncertain and may not exceed required investments costs. • Regulatory compact and state statutes limit opportunities for program providers

  19. Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

    International Nuclear Information System (INIS)

    Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

    2017-01-01

    Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

  20. Stopping coal-fired electricity imports on smog days : a review of the OPA's proposed 250 MW demand response program

    International Nuclear Information System (INIS)

    Gibbons, J.

    2006-01-01

    This paper proposed an alternative to importing coal-fired electricity from the Ohio Valley on smog alert days in Ontario. It was suggested that the Ontario Power Authority (OPA) should pay large electricity consumers to shift some of their consumption from peak to off-peak hours. It was observed that demand response programs which pay consumers to shift demands to off-peak hours can provide multiple benefits to Ontario, including reduced air pollution on smog-alert days, a reduction in the spot price of electricity and reduced price volatility. In addition, demand response programs reduce the risk of blackouts and brownouts, as well as the need for new electricity generation and transmission infrastructure. It was noted that the Independent Electricity System Operator (IESO) and the OPA are planning to introduce demand response programs for the summer of 2006. However, the IESO's emergency load reduction program will be operated only during emergency situations to avoid the need for voltage reductions, while the OPA proposes to introduce a non-emergency demand response program which will be activated during most smog-alert days. Various amendments to the proposed program were suggested in this paper, including the establishment of price parity with coal-fired electricity imports; the provision of notification by 3 PM of the need for demand reductions the following day; no capping on the quantity of demand reductions that the OPA will purchase at a lower cost than electricity imports; and that the OPA's proposed Capacity Building Demand Response Program should proceed as quickly as possible without a pre-determined MW cap. 4 refs., 6 figs

  1. Participation through Automation: Fully Automated Critical PeakPricing in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Kiliccote,Sila; Linkugel, Eric

    2006-06-20

    California electric utilities have been exploring the use of dynamic critical peak prices (CPP) and other demand response programs to help reduce peaks in customer electric loads. CPP is a tariff design to promote demand response. Levels of automation in DR can be defined as follows: Manual Demand Response involves a potentially labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. They refer to this as Auto-DR. This paper describes the development, testing, and results from automated CPP (Auto-CPP) as part of a utility project in California. The paper presents the project description and test methodology. This is followed by a discussion of Auto-DR strategies used in the field test buildings. They present a sample Auto-CPP load shape case study, and a selection of the Auto-CPP response data from September 29, 2005. If all twelve sites reached their maximum saving simultaneously, a total of approximately 2 MW of DR is available from these twelve sites that represent about two million ft{sup 2}. The average DR was about half that value, at about 1 MW. These savings translate to about 0.5 to 1.0 W/ft{sup 2} of demand reduction. They are continuing field demonstrations and economic evaluations to pursue increasing penetrations of automated DR that has demonstrated ability to provide a valuable DR resource for California.

  2. Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); MacDonald, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goldman, Charles [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-03-01

    In this study, we attempt to provide a comprehensive examination of various market and policy barriers to demand response providing ancillary services in both ISO/RTO and non-ISO/RTO regions, especially at the program provider level. It is useful to classify barriers in order to create a holistic understanding and identify parties that could be responsible for their removal. This study develops a typology of barriers focusing on smaller customers that must rely on a program provider (i.e., electric investor owned utility or IOU, ARC) to create an aggregated DR resource in order to bring ancillary services to the balancing authority.ii The barriers were identified through examinations of regulatory structures, market environments, and product offerings; and discussions with industry stakeholders and regulators. In order to help illustrate the differences in barriers among various wholesale market designs and their constituent retail environments, four regions were chosen to use as case studies: Colorado, Texas, Wisconsin, and New Jersey. We highlight the experience in each area as it relates to the identified barriers.

  3. Massive coordination of residential embedded electricity generation and demand response using the PowerMatcher approach

    International Nuclear Information System (INIS)

    Kamphuis, I.G.; Hommelberg, M.P.F.; Warmer, C.J.; Kok, J.K.

    2007-01-01

    Different driving forces push the electricity production towards decentralization. The projected increase of distributed power generation on the residential level with an increasing proportion of intermittent renewable energy resources poses problems for continuously matching the energy balance when coordination takes place centrally. On the other hand, new opportunities arise by intelligent clustering of generators and demand in so-called Virtual Power Plants. Part of the responsibility for new coordination mechanisms, then, has to be laid locally. To achieve this, the current electricity infrastructure is expected to evolve into a network of networks (including ICT (Information and Communication Technology)-networks), in which all system parts communicate with one another, are aware of each other's context and may influence each other. In this paper, a multi-agent systems approach, using price signal-vectors from an electronic market is presented as an appropriate technology needed for massive control and coordination tasks in these future electricity networks. The PowerMatcher, a market-based control concept for supply and demand matching (SDM) in electricity networks, is discussed. The results within a simulation study show the ability to raise the simultaneousness of electricity production and consumption within (local) control clusters with cogeneration and heat-pumps by exchanging price signals and coordinated allocation using market algorithms. The control concept, however, can also be applied in other business cases like reduction of imbalance cost in commercial portfolios or virtual power plant operators, utilizing distributed generators. Furthermore, a PowerMatcher-based field test configuration with 15 Stirling-engine powered micro-CHP's is described, which is currently in operation within a field test in the Netherlands

  4. Field Testing and Modeling of Supermarket Refrigeration Systems as a Demand Response Resource

    Energy Technology Data Exchange (ETDEWEB)

    Deru, Michael; Hirsch, Adam; Clark, Jordan; Anthony, Jamie

    2016-08-26

    Supermarkets offer a substantial demand response (DR) resource because of their high energy intensity and use patterns; however, refrigeration as the largest load has been challenging to access. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning; lighting; and anti-sweat heaters. This project evaluated and quantified the DR potential inherent in supermarket refrigeration systems in the Bonneville Power Administration service territory. DR events were carried out and results measured in an operational 45,590-ft2 supermarket located in Hillsboro, Oregon. Key results from the project include the rate of temperature increase in freezer reach-in cases and walk-ins when refrigeration is suspended, the load shed amount for DR tests, and the development of calibrated models to quantify available DR resources. Simulations showed that demand savings of 15 to 20 kilowatts (kW) are available for 1.5 hours for a typical store without precooling and for about 2.5 hours with precooling using only the low-temperature, non-ice cream cases. This represents an aggregated potential of 20 megawatts within BPA's service territory. Inability to shed loads for medium-temperature (MT) products because of the tighter temperature requirements is a significant barrier to realizing larger DR for supermarkets. Store owners are reluctant to allow MT case set point changes, and laboratory tests of MT case DR strategies are needed so that owners become comfortable testing, and implementing, MT case DR. The next-largest barrier is the lack of proper controls in most supermarket displays over ancillary equipment, such as anti-sweat heaters, lights, and fans.

  5. Stochastic Security and Risk-Constrained Scheduling for an Autonomous Microgrid with Demand Response and Renewable Energy Resources

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Rashidizadeh-Kermani, Homa; Najafi, Hamid Reza

    2017-01-01

    Increasing penetration of intermittent renewable energy sources and the development of advanced information give rise to questions on how responsive loads can be managed to optimise the use of resources and assets. In this context, demand response as a way for modifying the consumption pattern of...

  6. Provision of secondary frequency control via demand response activation on thermostatically controlled loads: Solutions and experiences from Denmark

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam; Marinelli, Mattia; Hu, Junjie

    2016-01-01

    This paper studies the provision of secondary frequency control in electric power systems based on demand response (DR) activation on thermostatically controlled loads (TCLs) and quantifies the computation resource constraints for the control of large TCL population. Since TCLs are fast responsive...

  7. Feasibility of automated speech sample collection with stuttering children using interactive voice response (IVR) technology.

    Science.gov (United States)

    Vogel, Adam P; Block, Susan; Kefalianos, Elaina; Onslow, Mark; Eadie, Patricia; Barth, Ben; Conway, Laura; Mundt, James C; Reilly, Sheena

    2015-04-01

    To investigate the feasibility of adopting automated interactive voice response (IVR) technology for remotely capturing standardized speech samples from stuttering children. Participants were 10 6-year-old stuttering children. Their parents called a toll-free number from their homes and were prompted to elicit speech from their children using a standard protocol involving conversation, picture description and games. The automated IVR system was implemented using an off-the-shelf telephony software program and delivered by a standard desktop computer. The software infrastructure utilizes voice over internet protocol. Speech samples were automatically recorded during the calls. Video recordings were simultaneously acquired in the home at the time of the call to evaluate the fidelity of the telephone collected samples. Key outcome measures included syllables spoken, percentage of syllables stuttered and an overall rating of stuttering severity using a 10-point scale. Data revealed a high level of relative reliability in terms of intra-class correlation between the video and telephone acquired samples on all outcome measures during the conversation task. Findings were less consistent for speech samples during picture description and games. Results suggest that IVR technology can be used successfully to automate remote capture of child speech samples.

  8. Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

    Science.gov (United States)

    Breed, Julie; Fox, Jeffrey A.; Powers, Edward I. (Technical Monitor)

    2001-01-01

    True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables

  9. Management by Trajectory Trade Study of Roles and Responsibilities Between Participants and Automation Report

    Science.gov (United States)

    Fernandes, Alicia D.; Kaler, Curt; Leiden, Kenneth; Atkins, Stephen; Bell, Alan; Kilbourne, Todd; Evans, Mark

    2017-01-01

    This report describes a trade study of roles and responsibilities associated with the Management by Trajectory (MBT) concept. The MBT concept describes roles, responsibilities, and information and automation requirements for providing air traffic controllers and managers the ability to quickly generate, evaluate and implement changes to an aircraft's trajectory. In addition, the MBT concept describes mechanisms for imposing constraints on flight operator preferred trajectories only to the extent necessary to maintain safe and efficient traffic flows, and the concept provides a method for the exchange of trajectory information between ground automation systems and the aircraft that allows for trajectory synchronization and trajectory negotiation. The participant roles considered in this trade study include: airline dispatcher, flight crew, radar controller, traffic manager, and Air Traffic Control System Command Center (ATCSCC) traffic management specialists. The proposed allocation of roles and responsibilities was based on analysis of several use cases that were developed for this purpose as well as for walking through concept elements. The resulting allocation of roles and responsibilities reflects both increased automation capability to support many aviation functions, as well as increased flexibility to assign responsibilities to different participants - in many cases afforded by the increased automation capabilities. Note that the selection of participants to consider for allocation of each function is necessarily rooted in the current environment, in that MBT is envisioned as an evolution of the National Airspace System (NAS), and not a revolution. A key feature of the MBT allocations is a vision for the traffic management specialist to take on a greater role. This is facilitated by the vision that separation management functions, in addition to traffic management functions, will be carried out as trajectory management functions. This creates an opportunity

  10. Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs

    International Nuclear Information System (INIS)

    Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Zare, Kazem

    2014-01-01

    Highlights: • Short-term self-scheduling problem of customers with CHP units is conducted. • Power demand and pool prices are forecasted using ARIMA models. • Risk management problem is conducted by implementing CVaR methodology. • The demand response program is implemented in self-scheduling problem of CHP units. • Non-convex feasible operation region in different types of CHP units is modeled. - Abstract: This paper presents a stochastic programming framework for solving the scheduling problem faced by an industrial customer with cogeneration facilities, conventional power production system, and heat only units. The power and heat demands of the customer are supplied considering demand response (DR) programs. In the proposed DR program, the responsive load can vary in different time intervals. In the paper, the heat-power dual dependency characteristic in different types of CHP units is taken into account. In addition, a heat buffer tank, with the ability of heat storage, has been incorporated in the proposed framework. The impact of the market and load uncertainties on the scheduling problem is characterized through a stochastic programming formulation. Autoregressive integrated moving average (ARIMA) technique is used to generate the electricity price and the customer demand scenarios. The daily and weekly seasonalities of demand and market prices are taken into account in the scenario generation procedure. The conditional value-at-risk (CVaR) methodology is implemented in order to limit the risk of expected profit due to market price and load forecast volatilities

  11. Culturally responsive middle school science: A case study of needs, demands, and challenges

    Science.gov (United States)

    Woodrow, Kelli Ellen

    2007-12-01

    Culturally responsive programming has been proposed as a remedy for the well-documented disconnect between schools and the ethnically and culturally diverse students who attend them. These programs often focus on creating instructional materials and pedagogical practices that are aligned with the knowledges, perspectives and practices of these students. This study builds on that literature and examines the needs, demands, and challenges of developing a culturally responsive health science program for ethnically and culturally diverse urban middle school students. I approached this problem through a content analysis of the intended curriculum and a microethnography of the enacted curriculum. In my analysis of the intended curriculum, I adapted a science textbook analysis instrument created by the American Association for the Advancement of Science (AAAS) to include criteria related to identified features of culturally responsive education. Using these modified analytic criteria, I found that the pilot drafts of the curricular materials excelled in the areas of engaging students in relevant phenomenon but lacked many of these specifically culturally responsive elements. Recommendations were made to redress these deficiencies. In my analysis of the enacted curriculum, I observed in five eighth grade classrooms where the program was being implemented. I used participant observation, audio and video tape recordings, artifacts, and interviews over a six-month period to investigate teacher/student interactions, the social organization of the classrooms, and students' culturally distinctive knowledge resources---or what is sometimes referred to as their "funds of knowledge." I found that the affective interactions between teachers and students were precursors to any reform, and that students and teachers similarly defined these interactions as "teacher care." In addition, I found that the social organization of the classroom often privileged official content and ways of

  12. The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming

    International Nuclear Information System (INIS)

    Falsafi, Hananeh; Zakariazadeh, Alireza; Jadid, Shahram

    2014-01-01

    This paper focuses on using DR (Demand Response) as a means to provide reserve in order to cover uncertainty in wind power forecasting in SG (Smart Grid) environment. The proposed stochastic model schedules energy and reserves provided by both of generating units and responsive loads in power systems with high penetration of wind power. This model is formulated as a two-stage stochastic programming, where first-stage is associated with electricity market, its rules and constraints and the second-stage is related to actual operation of the power system and its physical limitations in each scenario. The discrete retail customer responses to incentive-based DR programs are aggregated by DRPs (Demand Response Providers) and are submitted as a load change price and amount offer package to ISO (Independent System Operator). Also, price-based DR program behavior and random nature of wind power are modeled by price elasticity concept of the demand and normal probability distribution function, respectively. In the proposed model, DRPs can participate in energy market as well as reserve market and submit their offers to the wholesale electricity market. This approach is implemented on a modified IEEE 30-bus test system over a daily time horizon. The simulation results are analyzed in six different case studies. The cost, emission and multiobjective functions are optimized in both without and with DR cases. The multiobjective generation scheduling model is solved using augmented epsilon constraint method and the best solution can be chosen by Entropy and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The results indicate demand side participation in energy and reserve scheduling reduces the total operation costs and emissions. - Highlights: • Simultaneous participation of loads in both energy and reserve scheduling. • Environmental/economical scheduling of energy and reserve. • Using demand response for covering wind generation forecast

  13. Optimal behavior of responsive residential demand considering hybrid phase change materials

    International Nuclear Information System (INIS)

    Shafie-khah, M.; Kheradmand, M.; Javadi, S.; Azenha, M.; Aguiar, J.L.B. de; Castro-Gomes, J.; Siano, P.; Catalão, J.P.S.

    2016-01-01

    Highlights: • An operational model of HEM system incorporating with a hybrid PCM is proposed in this paper. • Incorporation of hybrid PCM mortar had a complementary effect on the proposed HEM system. • The proposed model ensures the technical and economic limits of batteries and electrical appliances. • The customer’s electricity cost can be reduced up to 48% by utilizing the proposed model. - Abstract: Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customer’s cost in different DRPs but also to guaranty the habitants’ satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customer’s electricity cost can be reduced up to 48% by utilizing the proposed model.

  14. A Closed-Loop Control Strategy for Air Conditioning Loads to Participate in Demand Response

    Directory of Open Access Journals (Sweden)

    Xiaoqing Hu

    2015-08-01

    Full Text Available Thermostatically controlled loads (TCLs, such as air conditioners (ACs, are important demand response resources—they have a certain heat storage capacity. A change in the operating status of an air conditioner in a small range will not noticeably affect the users’ comfort level. Load control of TCLs is considered to be equivalent to a power plant of the same capacity in effect, and it can significantly reduce the system pressure to peak load shift. The thermodynamic model of air conditioning can be used to study the aggregate power of a number of ACs that respond to the step signal of a temperature set point. This paper analyzes the influence of the parameters of each AC in the group to the indoor temperature and the total load, and derives a simplified control model based on the two order linear time invariant transfer function. Then, the stability of the model and designs its Proportional-Integral-Differential (PID controller based on the particle swarm optimization (PSO algorithm is also studied. The case study presented in this paper simulates both scenarios of constant ambient temperature and changing ambient temperature to verify the proposed transfer function model and control strategy can closely track the reference peak load shifting curves. The study also demonstrates minimal changes in the indoor temperature and the users’ comfort level.

  15. DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

    Energy Technology Data Exchange (ETDEWEB)

    Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay; Kar, Koushik

    2017-05-19

    In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models of individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.

  16. Hardware-in-the-Loop Co-simulation of Distribution Grid for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Rotger-Griful, Sergi; Chatzivasileiadis, Spyros; Jacobsen, Rune H.; Stewart, Emma M.; Domingo, Javier M.; Wetter, Michael

    2016-06-20

    In modern power systems, co-simulation is proposed as an enabler for analyzing the interactions between disparate systems. This paper introduces the co-simulation platform Virtual Grid Integration Laboratory (VirGIL) including Hardware-in-the-Loop testing, and demonstrates its potential to assess demand response strategies. VirGIL is based on a modular architecture using the Functional Mock-up Interface industrial standard to integrate new simulators. VirGIL combines state-of-the-art simulators in power systems, communications, buildings, and control. In this work, VirGIL is extended with a Hardware-in-the-Loop component to control the ventilation system of a real 12-story building in Denmark. VirGIL capabilities are illustrated in three scenarios: load following, primary reserves and load following aggregation. Experimental results show that the system can track one minute changing signals and it can provide primary reserves for up-regulation. Furthermore, the potential of aggregating several ventilation systems is evaluated considering the impact at distribution grid level and the communications protocol effect.

  17. DEVELOPING GIS-BASED DEMAND-RESPONSIVE TRANSIT SYSTEM IN TEHRAN CITY

    Directory of Open Access Journals (Sweden)

    H. Faroqi

    2015-12-01

    Full Text Available Create, maintain and development of public transport network in metropolitan are important problems in the field of urban transport management. In public transport, maximize the efficient use of public fleet capacity has been considered. Concepts and technologies of GIS have provided suitable way for management and optimization of the public transports systems. In demand-responsive public transportation system, firstly fellow traveller groups have been established for applicants based on spatial concepts and tools of GIS, second for each group according to its’ members and their paths, a public vehicle has been allocated to them then based on dynamic routing, the fellow passenger group has been gathered from their origins and has been moved to their destinations through optimal route. The suggested system has been implemented based on network data and commuting trips statistics of 1 to 6 districts in Tehran city. Evaluation performed on the results show the 34% increase using of Taxi capacity, 13% increase using of Van capacity and 10% increase using of Bus capacity in comparison between current public transport system and suggested public transportation system has been improved.

  18. Important Factors for Early Market Microgrids: Demand Response and Plug-in Electric Vehicle Charging

    Science.gov (United States)

    White, David Masaki

    Microgrids are evolving concepts that are growing in interest due to their potential reliability, economic and environmental benefits. As with any new concept, there are many unresolved issues with regards to planning and operation. In particular, demand response (DR) and plug-in electric vehicle (PEV) charging are viewed as two key components of the future grid and both will likely be active technologies in the microgrid market. However, a better understanding of the economics associated with DR, the impact DR can have on the sizing of distributed energy resource (DER) systems and how to accommodate and price PEV charging is necessary to advance microgrid technologies. This work characterizes building based DR for a model microgrid, calculates the DER systems for a model microgrid under DR through a minimization of total cost, and determines pricing methods for a PEV charging station integrated with an individual building on the model microgrid. It is shown that DR systems which consist only of HVAC fan reductions provide potential economic benefits to the microgrid through participation in utility DR programs. Additionally, peak shaving DR reduces the size of power generators, however increasing DR capacity does not necessarily lead to further reductions in size. As it currently stands for a microgrid that is an early adopter of PEV charging, current installation costs of PEV charging equipment lead to a system that is not competitive with established commercial charging networks or to gasoline prices for plug-in hybrid electric vehicles (PHEV).

  19. Big Data Analytics for Demand Response: Clustering Over Space and Time

    Energy Technology Data Exchange (ETDEWEB)

    Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Kolte, Jahanvi [Nirma Univ., Gujarat (India); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-10-29

    The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

  20. Responsible management of tropical peatlands: balancing competing demands on a fragile resource

    Science.gov (United States)

    Page, Susan; Evans, Christopher; Gauci, Vincent

    2017-04-01

    In 2010 the International Peatland Society published a strategy for responsible peatland management, with the following guiding principles: (i) ensure that high conservation value peatlands are identified and conserved, (ii) manage 'utilised' peatlands responsibly, and (iii) rehabilitate or restore drained, degraded or otherwise irreversibly changed peatlands to restore as many ecological and landscape functions as possible. At the time of its publication, the main focus of the strategy was on northern peatlands, although a few partner organisations in SE Asia were involved in the strategy consultation process. Given the rapid rate of peatland development in SE Asia in the last 7 years and the growing interest in tropical peatland rehabilitation and restoration, we believe that it is now timely to review what a strategy for responsible tropical peatland management might look like. SE Asia's peatlands cover 250,000 km2 of the region and store 69 Gt C but they are subject to continuing deforestation, biodiversity loss, land subsidence/flooding, increasing greenhouse gas (GHG) emissions, and health impacts due to air pollution from land-clearing fires, all of which pose huge regional and global challenges. Around 75% of the peatlands have been deforested in the last 20 years, with 35% of cleared land now under industrial plantation, 34% under smallholder cultivation, and 25% unutilised, largely as a result of uncontrolled land-clearing fires. The production intensity (GHG emissions per calorie produced) of crops grown on SE Asian organic soils is among the highest in the world (Carlson et al. 2016). There are clear tensions between reconciling peatland management for conservation goals (of biodiversity, carbon and natural resources) with economic and livelihood development goals. A balance needs to be struck between the absolute value and distribution of short term economic gains vs. peatland management strategies that deliver longer-term, sustainable and shared

  1. China's Rare Earth Supply Chain: Illegal Production, and Response to new Cerium Demand

    Science.gov (United States)

    Nguyen, Ruby Thuy; Imholte, D. Devin

    2016-07-01

    As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China's supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructed a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the US market starting from 2018. Results showed that market share of the illegal sector has grown since 2007-2015, ranging between 22% and 25% of China's rare earth supply, translating into 59-65% illegal heavy rare earths and 14-16% illegal light rare earths. There will be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Finally, we illustrate revenue streams for different ore compositions in China in 2015.

  2. On the Trade-off Between Real-time Pricing and the Social Acceptability Costs of Demand Response

    DEFF Research Database (Denmark)

    da Silva, Hendrigo Batista; Santiago, Leonardo

    2018-01-01

    on the social acceptability costs of implementing demand response programs, and we discuss the key features of implementing a real-time price to energy. Although the literature acknowledges the existence of a social acceptability cost, it does not propose an explicit approach to dealing with this issue. A model...... for investigating the implications of the social acceptability cost is thus introduced and through it, we discuss thoroughly the joint impact of the elasticity and externality parameters on the tariff design of a demand response program. We explore how the increases in elasticity and in externality effects...... influence price changes in such programs and how the social acceptability cost could be reduced as a function of pricing policies. We conclude by discussing the policy design mechanisms in line with demand elasticity and their role in decreasing price variations to cope with the minimum volatility principle...

  3. A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

    Directory of Open Access Journals (Sweden)

    S. Sofana Reka

    2016-06-01

    Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

  4. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

    International Nuclear Information System (INIS)

    Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

    2016-01-01

    Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

  5. Economic potential of demand response at household level—Are Central-European market conditions sufficient?

    International Nuclear Information System (INIS)

    Prüggler, Natalie

    2013-01-01

    The aim of this paper is to show the economic potential of demand response (DR) on household level at Central European market conditions. Thereby, required economic benefits for consumers' participation, the realistic load shifting potential at household level and the estimation of essential intelligent infrastructure costs are discussed. The core of this paper builds a case-study applying spot market-oriented load shifting from the supplier's point of view by using Austrian electricity market data, household load profiles as well as a heat pump and e-car charging load profile. It is demonstrated which cost savings for suppliers can be derived from such load shifting procedure at household level. Furthermore, upper cost limits for intelligent infrastructure in order to break-even are derived. Results suggest to take a critical look at European discussions on DR implementation on household level, showing that at Central European market conditions the potential for DR at household level is restricted to significant loads and hence, the applied load shifting strategy is only beneficial with application to heat pumps. In contrast, the frequently discussed shifting of conventional household devices' loads (such as washing machines) economically does not add up. - Highlights: • Calculation of economic potential of domestic DR at Central European market conditions. • Model and case-study of spot market-oriented load shifting from supplier's perspective. • Derivation of supplier's cost savings and upper cost limits for ICT infrastructure. • Results show economic potential of domestic DR to be restricted to significant loads. • Shifting of washing machines economically does not pay off in contrast to heat pumps

  6. Demand Side Management in a competitive European market: Who should be responsible for its implementation?

    International Nuclear Information System (INIS)

    Didden, Marcel H.; D'Haeseleer, William D.

    2003-01-01

    Demand side management (DSM), more specifically energy efficiency, is standing in the spotlight due to the Kyoto commitments. An additional factor, the liberalization of the electricity markets, causes every country to review its own DSM activities. Especially in Europe, where the directive for opening the electricity market has a direct impact on the current DSM frameworks, governments will have to consider a change in this framework. In order to achieve this, much research has been done in the past years on how to change the DSM framework in a way that the requirements of both liberalization and the Kyoto Protocol will be met. In this paper, we review the current DSM activities and ongoing research from the starting point 'who should be responsible for implementing DSM'. We conclude that countries have to make explicit choices on how to arrange their DSM activities for the different customers groups. They have to be aware of the fact that some combinations of DSM activities will lead to counter-productive results and therefore inefficiency. This paper also investigates which of these DSM activities fits best in the open market; a critical review of Integrated Resource Planning (IRP) is used as a starting point. We agree with various proponents of IRP that planning towards minimal societal costs is theoretically appropriate, looking from a societal point of view. We also indicate in this paper that the planning process IRP is partly applicable in the open market. But looking at the practical application of IRP in the past, we must conclude that there are better alternatives for achieving energy efficient goals in a liberalized market

  7. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  8. Fluid milk consumption and demand response to advertising for non-alcoholic beverages

    Directory of Open Access Journals (Sweden)

    K. RICKERTSEN

    2008-12-01

    Full Text Available Norwegian fluid milk consumption has declined steadily over the last twenty years, despite the dairy industry spending increasing amounts of money on advertising. Using a two-stage model, we investigate whether advertising has increased the demand for milk. No effect of advertising on the demand for non-alcoholic beverages is found in the first stage. In the second stage, an almost ideal demand system including advertising expenditures on competing beverages is estimated. The effects of generic advertising within the beverage group are positive and significant for whole milk and negative and significant for lower fat milk. The own-advertising elasticity for the combined fluid milk group is 0.0008. This highly inelastic elasticity suggests that increased advertising will not be profitable for the producers. Several cross-advertising effects are statistically significant, emphasizing the usefulness of a demand system approach.

  9. Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response

    Directory of Open Access Journals (Sweden)

    Antonio Gabaldón

    2018-02-01

    Full Text Available The objectives of improving the efficiency, and integration, of renewable sources by 2030–2050 are complex in practice and should be linked to an increase of demand-side flexibility. The main challenges to achieving this flexibility are the lack of incentives and an adequate framework. For instance, customers’ revenue is usually low, the volatility of prices is high and there is not any practical feedback to customers from smart meters. The possibility of increasing customer revenue could reduce the uncertainty with respect to economic concerns, improving investments in efficiency, enabling technology and thus, engaging more customers in these policies. This objective could be achieved by the participation of customers in several markets. Moreover, Demand Response and Energy Efficiency can share ICT technologies but this participation needs to perform an aggregation of demand. The idea of this paper is to present some methodologies for facilitating the definition and evaluation of energy versus cost curves; and subsequently to estimate potential revenues due to Demand Response. This can be accomplished by models that estimate: demand and energy aggregation; economic opportunities and benefits; impacts on customer convenience; customer feedback and price analysis. By doing so, we would have comprehensive information that can help customers and aggregators to define energy packages and their monetary value with the objective of fostering their market participation.

  10. Bus operators' responses to job strain: An experimental test of the job demand-control model.

    Science.gov (United States)

    Cendales-Ayala, Boris; Useche, Sergio Alejandro; Gómez-Ortiz, Viviola; Bocarejo, Juan Pablo

    2017-10-01

    The research aim was to test the Job Demand-Control (JDC) Model demands × Control interaction (or buffering) hypothesis in a simulated bus driving experiment. The buffering hypothesis was tested using a 2 (low and high demands) × 2 (low and high decision latitude) design with repeated measures on the second factor. A sample of 80 bus operators were randomly assigned to the low (n = 40) and high demands (n = 40) conditions. Demands were manipulated by increasing or reducing the number of stops to pick up passengers, and decision latitude by imposing or removing restrictions on the Rapid Transit Bus (BRT) operators' pace of work. Outcome variables include physiological markers (heart rate [HR], heart rate variability [HRV], breathing rate [BR], electromyography [EMG], and skin conductance [SC]), objective driving performance and self-report measurements of psychological wellbeing (psychological distress, interest/enjoyment [I/E], perceived competence, effort/importance [E/I], and pressure/tension [P/T]). It was found that job decision latitude moderates the effect of job demands on both physiological arousal (BR: F(1, 74) = 4.680, p = .034, SC: F(1, 75) = 6.769, p = .011, and EMG: F(1, 75) = 6.550, p = .013) and psychological well-being (P/T: F(1, 75) = 4.289, p = .042 and I/E: F(1, 74) = 4.548, p = .036). Consistently with the JDC model buffering hypothesis, the experimental findings suggest that increasing job decision latitude can moderate the negative effect of job demands on different psychophysiological outcomes. This finding is useful for designing organizational and clinical interventions in an occupational group at high risk of work stress-related disease. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  11. Strategy-making for a proactive distribution company in the real-time market with demand response

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Wang, Qi; Wang, Jianhui

    2016-01-01

    This paper proposes a methodology to optimize the trading strategies of a proactive distribution company (PDISCO) in the real-time market by mobilizing the demand response. Each distribution-level demand is considered as an elastic one. To capture the interrelation between the PDISCO and the real......, a primal-dual approach is used to translate this bi-level model into a single-level mathematical program with equilibrium constraints. Results of case studies are reported to show the effectiveness of the proposed model. (C) 2016 Elsevier Ltd. All rights reserved....

  12. Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management

    International Nuclear Information System (INIS)

    Aghajani, G.R.; Shayanfar, H.A.; Shayeghi, H.

    2015-01-01

    Highlights: • Using DRPs to cover the uncertainties resulted from power generation by WT and PV. • Proposing the use of price-offer packages and amount of DR for implement DRPs. • Considering a multi-objective scheduling model and use of MOPSO algorithm. - Abstract: In this paper, a multi-objective energy management system is proposed in order to optimize micro-grid (MG) performance in a short-term in the presence of Renewable Energy Sources (RESs) for wind and solar energy generation with a randomized natural behavior. Considering the existence of different types of customers including residential, commercial, and industrial consumers can participate in demand response programs. As with declare their interruptible/curtailable demand rate or select from among different proposed prices so as to assist the central micro-grid control in terms of optimizing micro-grid operation and covering energy generation uncertainty from the renewable sources. In this paper, to implement Demand Response (DR) schedules, incentive-based payment in the form of offered packages of price and DR quantity collected by Demand Response Providers (DRPs) is used. In the typical micro-grid, different technologies including Wind Turbine (WT), PhotoVoltaic (PV) cell, Micro-Turbine (MT), Full Cell (FC), battery hybrid power source and responsive loads are used. The simulation results are considered in six different cases in order to optimize operation cost and emission with/without DR. Considering the complexity and non-linearity of the proposed problem, Multi-Objective Particle Swarm Optimization (MOPSO) is utilized. Also, fuzzy-based mechanism and non-linear sorting system are applied to determine the best compromise considering the set of solutions from Pareto-front space. The numerical results represented the effect of the proposed Demand Side Management (DSM) scheduling model on reducing the effect of uncertainty obtained from generation power and predicted by WT and PV in a MG.

  13. Cigarette demand is responsive to higher prices: findings from a survey of University students in Jordan.

    Science.gov (United States)

    Sweis, Nadia J; Cherukupalli, Rajeev

    2016-11-01

    To estimate the price elasticity of cigarette demand for university students aged 18-24 years in Jordan. Questions from the Global Adult Tobacco Survey were adapted and administered to students from 10 public universities in Jordan in 2014. A two-part econometric model of cigarette demand was estimated. Nearly one-third of university students in Jordan smoke, purchasing 33.2 packs per month and paying 1.70 Jordanian dinars on average (US$2.40) for a pack of 20 cigarettes. The price elasticity of cigarette demand was estimated to be -1.15. Higher taxes may be particularly effective in reducing smoking among University students in Jordan. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  14. Emergency response planning and sudden cardiac arrests in high schools after automated external defibrillator legislation.

    Science.gov (United States)

    Watson, Andrew M; Kannankeril, Prince J; Meredith, Mark

    2013-12-01

    To compare medical emergency response plan (MERP) and automated external defibrillator (AED) prevalence and define the incidence and outcomes of sudden cardiac arrest (SCA) in high schools before and after AED legislation. In 2011, Tennessee Secondary School Athletic Association member schools were surveyed regarding AED placement, MERPs, and on-campus SCAs within the last 5 years. Results were compared with a similar study conducted in 2006, prior to legislation requiring AEDs in schools. Of the schools solicited, 214 (54%, total enrollment 182 289 students) completed the survey. Compared with 2006, schools in the 2011 survey had a significantly higher prevalence of MERPs (84% vs 71%, P defibrillators (90% vs 47%, P defibrillators but rates of cardiopulmonary resuscitation training and overall compliance with guidelines remained low. Copyright © 2013 Mosby, Inc. All rights reserved.

  15. Tools for Designing, Evaluating, and Certifying NextGen Technologies and Procedures: Automation Roles and Responsibilities

    Science.gov (United States)

    Kanki, Barbara G.

    2011-01-01

    Barbara Kanki from NASA Ames Research Center will discuss research that focuses on the collaborations between pilots, air traffic controllers and dispatchers that will change in NextGen systems as automation increases and roles and responsibilities change. The approach taken by this NASA Ames team is to build a collaborative systems assessment template (CSAT) based on detailed task descriptions within each system to establish a baseline of the current operations. The collaborative content and context are delineated through the review of regulatory and advisory materials, policies, procedures and documented practices as augmented by field observations and interviews. The CSAT is developed to aid the assessment of key human factors and performance tradeoffs that result from considering different collaborative arrangements under NextGen system changes. In theory, the CSAT product may be applied to any NextGen application (such as Trajectory Based Operations) with specified ground and aircraft capabilities.

  16. An Econometric Analysis of Electricity Demand Response to Price Changes at the Intra-Day Horizon: The Case of Manufacturing Industry in West Denmark

    DEFF Research Database (Denmark)

    Møller, Niels Framroze; Møller Andersen, Frits

    2015-01-01

    The use of renewable energy implies a more variable supply of power. Market effciency may improve if demand can absorb some of this variability by being more flexible, e.g. by responding quickly to changes in the market price of power. To learn about this, in particular, whether demand responds...... considerably or demand response technologies be installed....

  17. Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms

    International Nuclear Information System (INIS)

    Neves, Diana; Silva, Carlos A.

    2015-01-01

    The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs

  18. Improving the dynamic response of a mediator-less microbial fuel cell as a biochemical oxygen demand (BOD) sensor.

    Science.gov (United States)

    Moon, Hyunsoo; Chang, In Seop; Kang, Kui Hyun; Jang, Jae Kyung; Kim, Byung Hong

    2004-11-01

    The dynamic behavior of a mediator-less, microbial fuel cell (MFC) was studied as a continuous biochemical oxygen demand (BOD) sensor. The response time and the sensitivity were analyzed through the step-change testing of the fuel concentration. The MFC of 25 ml had the shortest response time of 36 +/- 2 min at the fuel-feeding rate of 0.53 ml min(-1) and the resistance of 10 ohms. A smaller MFC of 5 ml had a response time of 5 +/- 1 min.

  19. Overvoltage Mitigation Using Coordinated Control of Demand Response and Grid-tied Photovoltaics

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2015-01-01

    Overvoltages in low voltage distribution grids with high solar photovoltaic (PV) integration are usually alleviated by implementing various active/reactive power control techniques. As those methods create revenue loss or inverter cost increase to PV owners, a coordinated control of load demand...

  20. Effect of Bioenergy Demands and Supply Response on Markets, Carbon, and Land Use

    Science.gov (United States)

    Karen L. Abt; Robert C. Abt; Christopher Galik

    2012-01-01

    An increase in the demand for wood for energy, including liquid fuels, bioelectricity, and pellets, has the potential to affect traditional wood users, forestland uses, management intensities, and, ultimately, carbon sequestration. Recent studies have shown that increases in bioenergy harvests could lead to displacement of traditional wood-using industries in the short...

  1. UV-crosslinkable and thermo-responsive chitosan hybrid hydrogel for NIR-triggered localized on-demand drug delivery.

    Science.gov (United States)

    Wang, Lei; Li, Baoqiang; Xu, Feng; Xu, Zheheng; Wei, Daqing; Feng, Yujie; Wang, Yaming; Jia, Dechang; Zhou, Yu

    2017-10-15

    Innovative drug delivery technologies based on smart hydrogels for localized on-demand drug delivery had aroused great interest. To acquire smart UV-crosslinkable chitosan hydrogel for NIR-triggered localized on-demanded drug release, a novel UV-crosslinkable and thermo-responsive chitosan was first designed and synthesized by grafting with poly N-isopropylacrylamide, acetylation of methacryloyl groups and embedding with photothermal carbon. The UV-crosslinkable unit (methacryloyl groups) endowed chitosan with gelation via UV irradiation. The thermo-responsive unit (poly N-isopropylacrylamide) endowed chitosan hydrogel with temperature-triggered volume shrinkage and reversible swelling/de-swelling behavior. The chitosan hybrid hydrogel embedded with photothermal carbon exhibited distinct NIR-triggered volume shrinkage (∼42% shrinkage) in response to temperature elevation as induced by NIR laser irradiation. As a demonstration, doxorubicin release rate was accelerated and approximately 40 times higher than that from non-irradiated hydrogels. The UV-crosslinkable and thermal-responsive hybrid hydrogel served as in situ forming hydrogel-based drug depot is developed for NIR-triggered localized on-demand release. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Assessment of precast beam-column using capacity demand response spectrum subject to design basis earthquake and maximum considered earthquake

    Science.gov (United States)

    Ghani, Kay Dora Abd.; Tukiar, Mohd Azuan; Hamid, Nor Hayati Abdul

    2017-08-01

    Malaysia is surrounded by the tectonic feature of the Sumatera area which consists of two seismically active inter-plate boundaries, namely the Indo-Australian and the Eurasian Plates on the west and the Philippine Plates on the east. Hence, Malaysia experiences tremors from far distant earthquake occurring in Banda Aceh, Nias Island, Padang and other parts of Sumatera Indonesia. In order to predict the safety of precast buildings in Malaysia under near field ground motion the response spectrum analysis could be used for dealing with future earthquake whose specific nature is unknown. This paper aimed to develop of capacity demand response spectrum subject to Design Basis Earthquake (DBE) and Maximum Considered Earthquake (MCE) in order to assess the performance of precast beam column joint. From the capacity-demand response spectrum analysis, it can be concluded that the precast beam-column joints would not survive when subjected to earthquake excitation with surface-wave magnitude, Mw, of more than 5.5 Scale Richter (Type 1 spectra). This means that the beam-column joint which was designed using the current code of practice (BS8110) would be severely damaged when subjected to high earthquake excitation. The capacity-demand response spectrum analysis also shows that the precast beam-column joints in the prototype studied would be severely damaged when subjected to Maximum Considered Earthquake (MCE) with PGA=0.22g having a surface-wave magnitude of more than 5.5 Scale Richter, or Type 1 spectra.

  3. Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power

    International Nuclear Information System (INIS)

    Azizipanah-Abarghooee, Rasoul; Golestaneh, Faranak; Gooi, Hoay Beng; Lin, Jeremy; Bavafa, Farhad; Terzija, Vladimir

    2016-01-01

    Highlights: • Suggesting a new UC mixing a probabilistic security and incentive demand response. • Investigating the effects of uncertainty on UC using chance-constraint programming. • Proposing an efficient spinning reserve satisfaction based on a new ED correction. • Presenting a new operational cycles way to convert binary variable to discrete one. - Abstract: We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers’ benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n − 1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved Jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems.

  4. Future Opportunities and Challenges with Using Demand Response as a Resource in Distribution System Operation and Planning Activities

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); MacDonald, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Page, Janie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Potter, Jennifer [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stewart, Emma [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-01-01

    This scoping study focuses on identifying the ability for current and future demand response opportunities to contribute to distribution system management. To do so, this scoping study will identify the needs of a distribution system to operate efficiently, safely and reliably; summarize both benefits and challenges for the operation of the distribution system with high penetration levels of distributed energy resources; define a suite of services based on those changing operational needs that could be provided by resources; identify existing demand response opportunities sponsored by distribution utilities and/or aggregators of retail customers; assess the extent to which distribution system services can be provided via DR opportunities both in their current form and with alterations to their design; and provide a qualitative assessment of coordination issues that bulk power and distribution system providers of DR opportunities will need to address.

  5. Family stressors, home demands and responsibilities, coping resources, social connectedness, and Thai older adult health problems: examining gender variations.

    Science.gov (United States)

    Krishnakumar, Ambika; Narine, Lutchmie; Soonthorndhada, Amara; Thianlai, Kanchana

    2015-03-01

    To examine gender variations in the linkages among family stressors, home demands and responsibilities, coping resources, social connectedness, and older adult health problems. Data were collected from 3,800 elderly participants (1,654 men and 2,146 women) residing in Kanchanaburi province, Thailand. Findings indicated gender variations in the levels of these constructs and in the mediational pathways. Thai women indicated greater health problems than men. Emotional empathy was the central variable that linked financial strain, home demands and responsibilities, and older adult health problems through social connectedness. Financial strain (and negative life events for women) was associated with lowered coping self-efficacy and increased health problems. The model indicated greater strength in predicting female health problems. Findings support gender variations in the relationships between ecological factors and older adult health problems. © The Author(s) 2014.

  6. Method of Modeling Questions for Automated Grading of Students’ Responses in E-Learning Systems

    Directory of Open Access Journals (Sweden)

    A. A. Gurchenkov

    2015-01-01

    Full Text Available Introduction. Problem relevance. The capability to check a solution of practical problems automatically is an important functionality of any learning management system (LMS. Complex types of questions, implying creative approach to problem solving are of particular interest. There are a lot of studies presenting automated scoring algorithms of students' answers, such as mathematical expressions, graphs, molecules, etc. However, the most common types of problems in the open LMS that are being actively implemented in Russian and foreign universities (Moodle, Sakai, Ilias etc. remain simple types of questions such as, for example, multiple choice.Study subject and goal. The purpose of study is to create a method that allows integrating arbitrary algorithms of answer scoring into any existing LMS, as well as its practical implementation in the form of an independent software module, which will handle questions in LMS.Method. The model for objects of type "algorithmic question" is considered. A unified format for storing objects of this type, allowing keeping their state, is developed. The algorithm is a set of variables, which defines the responses versus input data (or vice versa. Basis variables (input are selected pseudo-randomly from a predetermined range, and based on these values resulting variables (responses are calculated. This approach allows us to synthesize variations of the same question. State of the question is saved by means of "seed" of pseudo-random number generator. A set of algorithmic problems was used to build the lifecycle management functions, namely: initialization create (, rendering render (, and evaluation answer (. These functions lay the foundation for the Application Program Interface (API and allow us to control software module responsible for the questions in LMS.Practical results. This study is completed with the implementation of software module responsible for mapping the interaction with the student and automated

  7. A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture

    International Nuclear Information System (INIS)

    Reihani, Ehsan; Motalleb, Mahdi; Thornton, Matsu; Ghorbani, Reza

    2016-01-01

    Highlights: • Designing a DR market to increase renewable resources and decrease air pollution. • Explaining two economic models for DR market for selling available DR quantities. • Optimal allocating DR quantity to houses under each DR aggregator control. • Proposing a discomfort cost function for residential DR resources. • Performing a sensitivity analysis on discomfort cost function coefficients. - Abstract: With the increasing presence of intermittent renewable energy generation sources, variable control over loads and energy storage devices on the grid become even more important to maintain this balance. Increasing renewable energy penetration depends on both technical and economic factors. Distribution system consumers can contribute to grid stability by controlling residential electrical device power consumed by water heaters and battery storage systems. Coupled with dynamic supply pricing strategies, a comprehensive system for demand response (DR) exist. Proper DR management will allow greater integration of renewable energy sources partially replacing energy demand currently met by the combustion of fossil-fuels. An enticing economic framework providing increased value to consumers compensates them for reduced control of devices placed under a DR aggregator. Much work has already been done to develop more effective ways to implement DR control systems. Utilizing an integrated approach that combines consumer requirements into aggregate pools, and provides a dynamic response to market and grid conditions, we have developed a mathematical model that can quantify control parameters for optimum demand response and decide which resources to switch and when. In this model, optimization is achieved as a function of cost savings vs. customer comfort using mathematical market analysis. Two market modeling approaches—the Cournot and SFE—are presented and compared. A quadratic function is used for presenting the cost function of each DRA (Demand

  8. Water and Climate Impacts on Power System Operations: The Importance of Cooling Systems and Demand Response Measures

    Energy Technology Data Exchange (ETDEWEB)

    Macknick, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Zhou, Ella [National Renewable Energy Lab. (NREL), Golden, CO (United States); O' Connell, Matthew [National Renewable Energy Lab. (NREL), Golden, CO (United States); Brinkman, Gregory [National Renewable Energy Lab. (NREL), Golden, CO (United States); Miara, Ariel [City College of New York, NY (United States); Ibanez, Eduardo [GE Energy Connections, Atlanta, GA (United States); Hummon, Marissa [Tendril, Denver, CO (United States)

    2016-12-01

    The U.S. electricity sector is highly dependent upon water resources; changes in water temperatures and water availability can affect operational costs and the reliability of power systems. Despite the importance of water for power system operations, the effects of changes in water characteristics on multiple generators in a system are generally not modeled. Moreover, demand response measures, which can change the magnitude and timing of loads and can have beneficial impacts on power system operations, have not yet been evaluated in the context of water-related power vulnerabilities. This effort provides a first comprehensive vulnerability and cost analysis of water-related impacts on a modeled power system and the potential for demand response measures to address vulnerability and cost concerns. This study uniquely combines outputs and inputs of a water and power plant system model, production cost, model, and relative capacity value model to look at variations in cooling systems, policy-related thermal curtailments, and demand response measures to characterize costs and vulnerability for a test system. Twenty-five scenarios over the course of one year are considered: a baseline scenario as well as a suite of scenarios to evaluate six cooling system combinations, the inclusion or exclusion of policy-related thermal curtailments, and the inclusion or exclusion of demand response measures. A water and power plant system model is utilized to identify changes in power plant efficiencies resulting from ambient conditions, a production cost model operating at an hourly scale is used to calculate generation technology dispatch and costs, and a relative capacity value model is used to evaluate expected loss of carrying capacity for the test system.

  9. An Analysis of Decentralized Demand Response as Frequency Control Support under CriticalWind Power Oscillations

    Directory of Open Access Journals (Sweden)

    Jorge Villena

    2015-11-01

    Full Text Available In power systems with high wind energy penetration, the conjunction of wind power fluctuations and power system inertia reduction can lead to large frequency excursions, where the operating reserves of conventional power generation may be insufficient to restore the power balance. With the aim of evaluating the demand-side contribution to frequency control, a complete process to determine critical wind oscillations in power systems with high wind penetration is discussed and described in this paper. This process implies thousands of wind power series simulations, which have been carried out through a validated offshore wind farm model. A large number of different conditions have been taken into account, such as frequency dead bands, the percentages of controllable demand and seasonal factor influence on controllable loads. Relevant results and statistics are also included in the paper.

  10. Response of residential electricity demand to price: The effect of measurement error

    International Nuclear Information System (INIS)

    Alberini, Anna; Filippini, Massimo

    2011-01-01

    In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV are greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants. - Research Highlights: → Updated information on price elasticities for the US energy policy. → Taking into account measurement error in the price variable increase price elasticity. → Room for discouraging residential electricity consumption using price increases.

  11. Children with dyslexia show cortical hyperactivation in response to increasing literacy processing demands

    Directory of Open Access Journals (Sweden)

    Frøydis eMorken

    2014-12-01

    Full Text Available This fMRI study aimed to examine how differences in literacy processing demands may affect cortical activation patterns in 11- to 12-year-old children with dyslexia as compared to children with typical reading skills. 11 children with and 18 without dyslexia were assessed using a reading paradigm based on different stages of literacy development. In the analyses, six regions showed an interaction effect between group and condition in a factorial ANOVA. These regions were selected as regions of interest for further analyses. Overall, the dyslexia group showed cortical hyperactivation compared to the typical group. The difference between the groups tended to increase with increasing processing demands. Differences in cortical activation were not reflected in in-scanner reading performance. The six regions further grouped into three patterns, which are discussed in terms of processing demands, compensatory mechanisms, orthography and contextual facilitation. We conclude that the observed hyperactivation is chiefly a result of compensatory activity, modulated by other factors.

  12. BEYOND JOB POSITIONS. A SOCIAL RESPONSE TO THE CHANGES IN JOB DEMAND

    Directory of Open Access Journals (Sweden)

    Tomasz Pirog

    2009-01-01

    Full Text Available In this paper we present an analysis of the recent changes in the job market and discuss the process this triggered in the social politics of the welfare states. We examine the economic reasons for the changes in job demand and furthermore explore the associated changes in the social structures. New forms of employment and gratification demand a restructurization in the social politics in order to elasticise the job supply. The mismatch between the demand and supply on the job market may result in unemployment, work outside the norms of the law and a growing deficit of social security. This in turn leads to the situation where the sale of own work force doesn't always result in a dignified life standard. As a result, new ways to support people outside the regular job market need to be found. These new solution are essential in the modern society where the distribution of work is an important issue shaping the social bonds and individual identities.

  13. Fuzzy Stochastic Unit Commitment Model with Wind Power and Demand Response under Conditional Value-At-Risk Assessment

    Directory of Open Access Journals (Sweden)

    Jiafu Yin

    2018-02-01

    Full Text Available With the increasing penetration of wind power and demand response integrated into the grid, the combined uncertainties from wind power and demand response have been a challenging concern for system operators. It is necessary to develop an approach to accommodate the combined uncertainties in the source side and load side. In this paper, the fuzzy stochastic conditional value-at-risk criterions are proposed as the risk measure of the combination of both wind power uncertainty and demand response uncertainty. To improve the computational tractability without sacrificing the accuracy, the fuzzy stochastic chance-constrained goal programming is proposed to transfer the fuzzy stochastic conditional value-at-risk to a deterministic equivalent. The operational risk of forecast error under fuzzy stochastic conditional value-at-risk assessment is represented by the shortage of reserve resource, which can be further divided into the load-shedding risk and the wind curtailment risk. To identify different priority levels for the different objective functions, the three-stage day-ahead unit commitment model is proposed through preemptive goal programming, in which the reliability requirement has the priority over the economic operation. Finally, a case simulation is performed on the IEEE 39-bus system to verify the effectiveness and efficiency of the proposed model.

  14. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    International Nuclear Information System (INIS)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita

    2015-01-01

    Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks

  15. An Integrated Behavioural Model towards Evaluating and Influencing Energy Behaviour—The Role of Motivation in Behaviour Demand Response

    Directory of Open Access Journals (Sweden)

    Julia Blanke

    2017-12-01

    Full Text Available The change in the actual use of buildings by its occupants is receiving more and more attention. Over the lifecycle of a building the occupants and therefore the demands towards the buildings often change a lot. To match these altering conditions, particularly in the context of the demand for energy efficiency, purely technical approaches usually cannot solve the problem on their own or are not financially viable. It is therefore essential to take the behaviour of the end user into account and ask the fundamental question: “How is it possible to influence people’s behaviour towards a more pro-environmental outcome, and also in the long-term?” To approach this question we will present a model-driven approach for dynamically involving building occupants into the energy optimisation process. To do so we will further develop an integrated behavioural model based on established behavioural theories, having a closer look how motivational variables can be integrated into the process. This should lead to novel approaches for behaviour demand response, enabling additional demand shifting and shedding through targeted real-time engagement with energy prosumers.

  16. An Optimization Model for Large–Scale Wind Power Grid Connection Considering Demand Response and Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Zhongfu Tan

    2014-11-01

    Full Text Available To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs and energy storage systems (ESSs are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users’ demand elasticity, thermal units’ startup-shutdown, thermal units’ output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.

  17. ROS-responsive microspheres for on demand antioxidant therapy in a model of diabetic peripheral arterial disease.

    Science.gov (United States)

    Poole, Kristin M; Nelson, Christopher E; Joshi, Rucha V; Martin, John R; Gupta, Mukesh K; Haws, Skylar C; Kavanaugh, Taylor E; Skala, Melissa C; Duvall, Craig L

    2015-02-01

    A new microparticle-based delivery system was synthesized from reactive oxygen species (ROS)-responsive poly(propylene sulfide) (PPS) and tested for "on demand" antioxidant therapy. PPS is hydrophobic but undergoes a phase change to become hydrophilic upon oxidation and thus provides a useful platform for ROS-demanded drug release. This platform was tested for delivery of the promising anti-inflammatory and antioxidant therapeutic molecule curcumin, which is currently limited in use in its free form due to poor pharmacokinetic properties. PPS microspheres efficiently encapsulated curcumin through oil-in-water emulsion and provided sustained, on demand release that was modulated in vitro by hydrogen peroxide concentration. The cytocompatible, curcumin-loaded microspheres preferentially targeted and scavenged intracellular ROS in activated macrophages, reduced in vitro cell death in the presence of cytotoxic levels of ROS, and decreased tissue-level ROS in vivo in the diabetic mouse hind limb ischemia model of peripheral arterial disease. Interestingly, due to the ROS scavenging behavior of PPS, the blank microparticles also showed inherent therapeutic properties that were synergistic with the effects of curcumin in these assays. Functionally, local delivery of curcumin-PPS microspheres accelerated recovery from hind limb ischemia in diabetic mice, as demonstrated using non-invasive imaging techniques. This work demonstrates the potential for PPS microspheres as a generalizable vehicle for ROS-demanded drug release and establishes the utility of this platform for improving local curcumin bioavailability for treatment of chronic inflammatory diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs

    International Nuclear Information System (INIS)

    Nwulu, Nnamdi I.; Xia, Xiaohua

    2015-01-01

    Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model

  19. Demand Response Control in Low Voltage Grids for Technical and Commercial Aggregation Services

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Szczesny, Ireneusz; Pillai, Jayakrishnan Radhakrishna

    2016-01-01

    . In this way, a system operator playing a role of an aggregator not only could trade flexible demand in the power markets but also materialize its energy agreements while ensuring the local network security and reliability. To verify the effectiveness of this extended method, a Danish low voltage networks...... is considered. The results show that it is possible to fulfill energy commitments in energy markets such as the regulation power market while respecting the proper network operation. However, the activation of the flexibility offered might be limited depending on the network characteristics and the season...

  20. Different Optimal Control Strategies for Exploitation of Demand Response in the Smart Grid

    DEFF Research Database (Denmark)

    Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver

    2012-01-01

    resources, intermittent renewable energy resources in the Smart Grid. This paper presents different optimal control (Genetic Algorithm-based and Model Predictive Control-based) algorithms that schedule controlled loads in the industrial and residential sectors, based on dynamic price and weather forecast......, considering users’ comfort settings to meet an optimization objective, such as maximum profit or minimum energy consumption. It is demonstrated in this work that the GA-based and MPC-based optimal control strategies are able to achieve load shifting for grid reliability and energy savings, including demand...

  1. Transitioning Resolution Responsibility between the Controller and Automation Team in Simulated NextGen Separation Assurance

    Science.gov (United States)

    Cabrall, C.; Gomez, A.; Homola, J.; Hunt, S..; Martin, L.; Merccer, J.; Prevott, T.

    2013-01-01

    As part of an ongoing research effort on separation assurance and functional allocation in NextGen, a controller- in-the-loop study with ground-based automation was conducted at NASA Ames' Airspace Operations Laboratory in August 2012 to investigate the potential impact of introducing self-separating aircraft in progressively advanced NextGen timeframes. From this larger study, the current exploratory analysis of controller-automation interaction styles focuses on the last and most far-term time frame. Measurements were recorded that firstly verified the continued operational validity of this iteration of the ground-based functional allocation automation concept in forecast traffic densities up to 2x that of current day high altitude en-route sectors. Additionally, with greater levels of fully automated conflict detection and resolution as well as the introduction of intervention functionality, objective and subjective analyses showed a range of passive to active controller- automation interaction styles between the participants. Not only did the controllers work with the automation to meet their safety and capacity goals in the simulated future NextGen timeframe, they did so in different ways and with different attitudes of trust/use of the automation. Taken as a whole, the results showed that the prototyped controller-automation functional allocation framework was very flexible and successful overall.

  2. Short-term nurse scheduling in response to daily fluctuations in supply and demand.

    Science.gov (United States)

    Bard, Jonathan F; Purnomo, Hadi W

    2005-11-01

    Hourly changes in patient census and acuity require hospitals to update their staffling needs on a continuing basis. This paper discusses the problem that management faces several times a day as the demand for nursing services departs from the planned schedule. Prior to the start of each shift, the number of nurses who are scheduled to be on duty over the next 24 hours is compared with the number actually available, and if shortages exist a series of decisions have to be made to ensure that each unit in the hospital has sufficient coverage. These decisions involve the use of overtime, outside nurses, and floaters. To address this problem, we have developed an integer programming model that takes the current set of rosters for regular and pool nurses and the expected demand for the upcoming 24 hours as input, and produces a revised schedule that makes the most efficient use of the available resources. The model is formulated and solved at a hospital-wide level rather than for each unit separately. To determine its applicability, a representative set of scenarios was investigated using data obtained from a medium-size facility in the U.S. with 14 units. The results indicate that problem instances with up to 120 nurses can be solved in a negligible amount of time.

  3. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    DEFF Research Database (Denmark)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

    2015-01-01

    Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price...... spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests...... to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also...

  4. Load kick-back effects due to activation of demand response in view of distribution grid operation

    DEFF Research Database (Denmark)

    Han, Xue; Sossan, Fabrizio; Bindner, Henrik W.

    2014-01-01

    There are increasing potentials to utilize the flexibilities from demand side resource (DSR) units. They can provide grid operation services by shifting or curtailing their energy consumption. The service provision can be achieved by aggregating a large quantity of DSR units in the network....... The paper has shown how aggregated consumption dynamics introduce new peaks in the system due to the synchronous behaviors of a portfolio of homogeneous DSRs, which is instructed by the flexibility management system. This dynamic effect is recognized as load kick-back effect. The impact of load kick......-back effects onto the distribution grid is analysed in this paper by establishing scenarios based on the estimation of DSR penetration levels from the system operator. The results indicate some risks that the activation of demand response may create critical peaks in the local grid due to kick-back effects....

  5. Evaluation of Reliability in Risk-Constrained Scheduling of Autonomous Microgrids with Demand Response and Renewable Resources

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2018-01-01

    is presented to maximize the expected profit of a microgrid operator under uncertainties of renewable resources, demand load and electricity price. In the proposed model, the trade-off between maximizing the operator’s expected profit and the risk of getting low profits in undesired scenarios is modeled......Uncertain natures of the renewable energy resources and consumers’ participation in demand response (DR) programs have introduced new challenges to the energy and reserve scheduling of microgrids, particularly in the autonomous mode. In this paper, a risk-constrained stochastic framework...... by using conditional value at risk (CVaR) method. The influence of consumers’ participation in DR programs and their emergency load shedding for different values of lost load (VOLL) are then investigated on the expected profit of operator, CVaR, expected energy not served (EENS) and scheduled reserves...

  6. Technical and economical tools to assess customer demand response in the commercial sector

    International Nuclear Information System (INIS)

    Alvarez Bel, Carlos; Ortega, Manuel Alcazar; Escriva, Guillermo Escriva; Gabaldon Marin, Antonio

    2009-01-01

    The authors present a methodology to evaluate and quantify the economic parameters (costs and benefits) attached to customer electricity consumption by analyzing the service provided by the different 'pieces' of absorbed electricity. The first step of this methodology is to perform a process oriented market segmentation to identify segments according to their flexibility potential. After that, a procedure based on comprehensive simulations to identify and quantify the actual demand that can be managed in the short term is presented and, finally, the required economic analysis is performed. The methodology, which is demonstrated with some applications to the commercial sector, not only helps the customers to integrate in flexible distribution systems but also offers the necessary economical parameters for them to integrate in electricity markets.

  7. Modeling Demand Response in Electricity Retail Markets as a Stackelberg Game

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price-sequence, w......We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price...... with Equilibrium Constraints (MPEC) and cast as a Mixed Integer Linear Program (MILP), which can be solved using off-the-shelf optimization software. In an illustrative example, we consider a retailer associated with both flexible demand and wind power production. Such an example shows the efficiency of dynamic...

  8. An Integrated Multiperiod OPF Model with Demand Response and Renewable Generation Uncertainty

    DEFF Research Database (Denmark)

    Bukhsh, Waqquas Ahmed; Zhang, Chunyu; Pinson, Pierre

    2015-01-01

    stage realizes generation from the renewable resources and optimally accommodates it by relying on the demand-side flexibilities and limited available flexibilities from the conventional generating units. The proposed model is illustrated on a 4-bus and a 39- bus system. Numerical results show......Renewable energy sources such as wind and solar have received much attention in recent years, and large amount of renewable generation is being integrated to the electricity networks. A fundamental challenge in a power system operation is to handle the intermittent nature of the renewable...... generation. In this paper we present a stochastic programming approach to solve a multiperiod optimal power flow problem under renewable generation uncertainty. The proposed approach consists of two stages. In the first stage, operating points for the conventional power plants are determined. The second...

  9. Future water supply and demand in response to climate change and agricultural expansion in Texas

    Science.gov (United States)

    Lee, K.; Zhou, T.; Gao, H.; Huang, M.

    2016-12-01

    With ongoing global environmental change and an increasing population, it is challenging (to say the least) to understand the complex interactions of irrigation and reservoir systems. Irrigation is critical to agricultural production and food security, and is a vital component of Texas' agricultural economy. Agricultural irrigation currently accounts for about 60% of total water demand in Texas, and recent occurrences of severe droughts has brought attention to the availability and use of water in the future. In this study, we aim to assess future agricultural irrigation water demand, and to estimate how changes in the fraction of crop irrigated land will affect future water availability in Texas, which has the largest farm area and the highest value of livestock production in the United States. The Variable Infiltration Capacity (VIC) model, which has been calibrated and validated over major Texas river basins during the historical period, is employed for this study. The VIC model, coupling with an irrigation scheme and a reservoir module, is adopted to simulate the water management and regulations. The evolution on agricultural land is also considered in the model as a changing fraction of crop for each grid cell. The reservoir module is calibrated and validated based on the historical (1915-2011) storage records of major reservoirs in Texas. The model is driven by statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The lowest (RCP 2.6) and highest (RC P8.5) greenhouse-gas concentration scenarios are adopted for future projections to provide an estimate of uncertainty bounds. We expect that our results will be helpful to assist decision making related to reservoir operations and agricultural water planning for Texas under future climate and environmental changes.

  10. Sudden cardiac arrests, automated external defibrillators, and medical emergency response plans in Tennessee high schools.

    Science.gov (United States)

    Meredith, Mark L; Watson, Andrew M; Gregory, Andrew; Givens, Timothy G; Abramo, Thomas J; Kannankeril, Prince J

    2013-03-01

    Schools are important public locations of sudden cardiac arrest (SCA), and the American Heart Association (AHA) recommends medical emergency response plans (MERPs), which may include an automated external defibrillator (AED) in schools. The objective of this study was to determine the incidence of SCA and the prevalence of AEDs and MERPs in Tennessee high schools. Tennessee Secondary School Athletic Association member schools were surveyed regarding SCA on campus within 5 years, AED presence, and MERP characteristics. Of 378 schools, 257 (68%) completed the survey. There were 21 (5 student and 16 adult) SCAs on school grounds, yielding a 5-year incidence of 1 SCA per 12 high schools. An AED was present at 11 of 21 schools with SCA, and 6 SCA victims were treated with an AED shock. A linear increase in SCA frequency was noted with increasing school size (schools, 71% had an MERP, 48% had an AED, and only 4% were fully compliant with AHA recommendations. Schools with a history of SCA were more likely to be compliant (19% vs. 3%, P = 0.011). The 5-year incidence of SCA in Tennessee high schools is 1 in 12, but increases to 1 in 7 for schools with more than 1000 students. Compliance with AHA guidelines for MERPs is poor, but improved in schools with recent SCA. Future recommendations should encourage the inclusion of AED placement in schools with more than 1000 students.

  11. A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program

    International Nuclear Information System (INIS)

    Safamehr, Hossein; Rahimi-Kian, Ashkan

    2015-01-01

    Providing a cost-efficient and reliable energy is one of the main issues in human societies of the 21st century. In response to this demand, new features of micro grid technology have provided huge potentials, specifically by the capability of having an interactive coordination between energy suppliers and consumers. Accordingly, this paper offers an improved model for achieving an optimal Demand Response programing. To solve the proposed multi-objective optimization problem, Artificial Bee Colony algorithm and quasi-static technique are utilized. The considered objectives in this paper are minimizing the overall cost of energy consumption and also improving the technical parameters of micro grid over a time horizon. This optimization is subject to several constraints such as satisfying the energy balance and the operating constraints of each energy supply sources. Manageable load or load as source is another enabling feature existing in smart energy networks, which is considered in this paper and its effect on cost reduction and reliability improvement is studied. Trying to examine the performance of the proposed Demand Response Programing in real conditions, the uncertainties are also analyzed by stochastic methods. The results show significant improvements which are obtained by applying just intelligent programming and management. - Highlights: • This paper presents a cost-efficient and reliable energy management of a micro-grid. • New models of battery and manageable loads are formulated. • Artificial Bee Colony algorithm is used to solve the optimization problem. • Quasi-static technique is used to simplify the solving procedure. • The uncertainties are also analyzed by stochastic methods.

  12. Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

    2017-11-01

    A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

  13. Power management and frequency regulation for microgrid and smart grid: A real-time demand response approach

    Science.gov (United States)

    Pourmousavi Kani, Seyyed Ali

    Future power systems (known as smart grid) will experience a high penetration level of variable distributed energy resources to bring abundant, affordable, clean, efficient, and reliable electric power to all consumers. However, it might suffer from the uncertain and variable nature of these generations in terms of reliability and especially providing required balancing reserves. In the current power system structure, balancing reserves (provided by spinning and non-spinning power generation units) usually are provided by conventional fossil-fueled power plants. However, such power plants are not the favorite option for the smart grid because of their low efficiency, high amount of emissions, and expensive capital investments on transmission and distribution facilities, to name a few. Providing regulation services in the presence of variable distributed energy resources would be even more difficult for islanded microgrids. The impact and effectiveness of demand response are still not clear at the distribution and transmission levels. In other words, there is no solid research reported in the literature on the evaluation of the impact of DR on power system dynamic performance. In order to address these issues, a real-time demand response approach along with real-time power management (specifically for microgrids) is proposed in this research. The real-time demand response solution is utilized at the transmission (through load-frequency control model) and distribution level (both in the islanded and grid-tied modes) to provide effective and fast regulation services for the stable operation of the power system. Then, multiple real-time power management algorithms for grid-tied and islanded microgrids are proposed to economically and effectively operate microgrids. Extensive dynamic modeling of generation, storage, and load as well as different controller design are considered and developed throughout this research to provide appropriate models and simulation

  14. Load shift incentives for household demand response: A model to evaluate effects from a Danish field experiment

    DEFF Research Database (Denmark)

    Katz, Jonas; Møller Andersen, Frits; Morthorst, Poul Erik

    2015-01-01

    We use a long-term electricity market equilibrium model to assess the impact of variable price products for household electricity customers. The analysed product structures resemble a rebate provided to customers within a field experiment in Southern Denmark. The developed model provides a clearer...... picture of what to expect from household demand response under spot pricing schemes as compared and simplified product schemes; it also prepares for interpreting the field experiment results. Using preliminary assumptions we estimate both short-term and long-term welfare effects of a shift of customers...

  15. Optimum residential load management strategy for real time pricing (RTP) demand response programs

    International Nuclear Information System (INIS)

    Lujano-Rojas, Juan M.; Monteiro, Cláudio; Dufo-López, Rodolfo; Bernal-Agustín, José L.

    2012-01-01

    This paper presents an optimal load management strategy for residential consumers that utilizes the communication infrastructure of the future smart grid. The strategy considers predictions of electricity prices, energy demand, renewable power production, and power-purchase of energy of the consumer in determining the optimal relationship between hourly electricity prices and the use of different household appliances and electric vehicles in a typical smart house. The proposed strategy is illustrated using two study cases corresponding to a house located in Zaragoza (Spain) for a typical day in summer. Results show that the proposed model allows users to control their diary energy consumption and adapt their electricity bills to their actual economical situation. - Highlights: ► This work shows an optimal load management strategy for residential consumers. ► It has been considered the communication infrastructure of the future smart grid. ► A study case shows the optimal utilization of some appliances and electric vehicles. ► Results showed that the proposed model allows users to reduce their electricity bill.

  16. Optimal pricing of default customers in electrical distribution systems: Effect behavior performance of demand response models

    International Nuclear Information System (INIS)

    Yusta, J.M.; Khodr, H.M.; Urdaneta, A.J.

    2007-01-01

    The response of a non-linear mathematical model is analyzed for the calculation of the optimal prices for electricity assuming default customers under different scenarios and using five different mathematical functions for the consumer response: linear, hyperbolic, potential, logarithmic and exponential. The mathematical functions are defined to simulate the hourly changes in the consumer response according to the load level, the price of electricity, and also depending on the elasticity at every hour. The behavior of the optimization model is evaluated separately under two different objective functions: the profit of the electric utility and the social welfare. The optimal prices as well as the served load are calculated for two different operation schemes: in an hourly basis and also assuming a single constant price for the 24 h of the day. Results obtained by the optimization model are presented and compared for the five different consumer load functions. (author)

  17. Demand responsive transport as a social innovation - the case of Skewiel mobiel

    NARCIS (Netherlands)

    Schotman, H.; Ludden, Geke Dina Simone

    2014-01-01

    People are increasingly growing older. Growing older is likely to come with, for example, decreasing mobility and therefore increasing dependency. This can reduce the social connectedness of older people. As an effect, a social challenge is growing: loneliness. In response to this challenge, local

  18. Is the mineralisation response to root exudation controlled by the microbial stoichiometric demand in subarctic soils?

    Science.gov (United States)

    Rousk, Johannes; Hicks, Lettice; Leizeaga, Ainara; Michelsen, Anders; Rousk, Kathrin

    2017-04-01

    Climate change will expose arctic and subarctic systems to warming and a shift towards plant communities with more rhizosphere labile C input. Labile C can also increase the rate of loss of native soil organic matter (SOM); a phenomenon termed 'priming'. We investigated how warming (+1.1˚ C over ambient using open top chambers) and the addition of plant litter (90 g m-2 y-1) or organic nitrogen (N) (fungal fruit bodies; 90 g m-2 y-1) in the Subarctic influenced the susceptibility of SOM mineralisation to priming, and its microbial underpinnings. Root exudation were simulated with the addition of labile organic matter both in the form of only labile C (13C-glucose) or in the form of labile C and N (13C-alanine). We hypothesized that labile C would induce a higher mineralization of N than C sourced from SOM ("N mining"); a response unrelated to microbial growth responses. We also hypothesized that the N mining effect would be more pronounced in climate change simulation treatments of higher C/N (plant litter) than treatments with lower C/N (fungal fruitbodies and warming), with the control treatments intermediate. We also hypothesized that the addition of labile C and N would not result in selective N mining, but instead coupled responses of C and N mineralisation sourced from SOM; a response that would coincide with stimulated microbial growth responses. Labile C appeared to inhibit the mineralisation of C from SOM by up to 60% within hours. In contrast, the mineralisation of N from SOM was stimulated by up to 300%. These responses occurred rapidly and were unrelated to microbial successional dynamics, suggesting catabolic responses. Considered separately, the labile-C inhibited C mineralisation is compatible with previously reported findings termed 'preferential substrate utilisation' or 'negative apparent priming', while the stimulated N mineralisation responses echo recent reports of 'real priming' of SOM mineralisation. However, C and N mineralisation responses

  19. Drivers anticipate lead-vehicle conflicts during automated longitudinal control: Sensory cues capture driver attention and promote appropriate and timely responses.

    Science.gov (United States)

    Morando, Alberto; Victor, Trent; Dozza, Marco

    2016-12-01

    Adaptive Cruise Control (ACC) has been shown to reduce the exposure to critical situations by maintaining a safe speed and headway. It has also been shown that drivers adapt their visual behavior in response to the driving task demand with ACC, anticipating an impending lead vehicle conflict by directing their eyes to the forward path before a situation becomes critical. The purpose of this paper is to identify the causes related to this anticipatory mechanism, by investigating drivers' visual behavior while driving with ACC when a potential critical situation is encountered, identified as a forward collision warning (FCW) onset (including false positive warnings). This paper discusses how sensory cues capture attention to the forward path in anticipation of the FCW onset. The analysis used the naturalistic database EuroFOT to examine visual behavior with respect to two manually-coded metrics, glance location and glance eccentricity, and then related the findings to vehicle data (such as speed, acceleration, and radar information). Three sensory cues (longitudinal deceleration, looming, and brake lights) were found to be relevant for capturing driver attention and increase glances to the forward path in anticipation of the threat; the deceleration cue seems to be dominant. The results also show that the FCW acts as an effective attention-orienting mechanism when no threat anticipation is present. These findings, relevant to the study of automation, provide additional information about drivers' response to potential lead-vehicle conflicts when longitudinal control is automated. Moreover, these results suggest that sensory cues are important for alerting drivers to an impending critical situation, allowing for a prompt reaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power

    International Nuclear Information System (INIS)

    Wang Jianhui; Liu Cong; Ton, Dan; Zhou Yan; Kim, Jinho; Vyas, Anantray

    2011-01-01

    This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced. - Research highlights: → A unit commitment model is used to simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). → Different PHEV charging scenarios are simulated on the Illinois power system → Load shifting and shaving enabled by DR programs are also modeled. → The simulation results show that the operating cost can be reduced with DR and optimal PHEV charging.

  1. Stochastic Unit Commitment of Wind-Integrated Power System Considering Air-Conditioning Loads for Demand Response

    Directory of Open Access Journals (Sweden)

    Xiao Han

    2017-11-01

    Full Text Available As a result of extensive penetration of wind farms into electricity grids, power systems face enormous challenges in daily operation because of the intermittent characteristics of wind energy. In particular, the load peak-valley gap has been dramatically widened in wind energy-integrated power systems. How to quickly and efficiently meet the peak-load demand has become an issue to practitioners. Previous literature has illustrated that the demand response (DR is an important mechanism to direct customer usage behaviors and reduce the peak load at critical times. This paper introduces air-conditioning loads (ACLs as a load shedding measure in the DR project. On the basis of the equivalent thermal parameter model for ACLs and the state-queue control method, a compensation cost calculation method for the ACL to shift peak load is proposed. As a result of the fluctuation and uncertainty of wind energy, a two-stage stochastic unit commitment (UC model is developed to analyze the ACL users’ response in the wind-integrated power system. A simulation study on residential and commercial ACLs has been performed on a 10-generator test system. The results illustrate the feasibility of the proposed stochastic programming strategy and that the system peak load can be effectively reduced through the participation of ACL users in DR projects.

  2. Challenge Online Time Series Clustering For Demand Response A Theory to Break the ‘Curse of Dimensionality'

    Energy Technology Data Exchange (ETDEWEB)

    Pal, Ranjan [Univ. of Southern California, Los Angeles, CA (United States); Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor [Univ. of Southern California, Los Angeles, CA (United States)

    2015-07-15

    The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring considerable computational resources and efficient algorithms. To overcome this Big Data challenge, data clustering techniques have been proposed. Current approaches however do not scale in the face of the “increasing dimensionality” problem where a cluster point is represented by the entire customer consumption time series. To overcome this aspect we first rethink the way cluster points are created and designed, and then design an efficient online clustering technique for demand response (DR) in order to analyze high volume, high dimensional energy consumption time series data at scale, and on the fly. Our online algorithm is randomized in nature, and provides optimal performance guarantees in a computationally efficient manner. Unlike prior work we (i) study the consumption properties of the whole population simultaneously rather than developing individual models for each customer separately, claiming it to be a ‘killer’ approach that breaks the “curse of dimensionality” in online time series clustering, and (ii) provide tight performance guarantees in theory to validate our approach. Our insights are driven by the field of sociology, where collective behavior often emerges as the result of individual patterns and lifestyles.

  3. Behavioural and physiological responses of laying hens to automated monitoring equipment.

    Science.gov (United States)

    Buijs, Stephanie; Booth, Francesca; Richards, Gemma; McGaughey, Laura; Nicol, Christine J; Edgar, Joanne; Tarlton, John F

    2018-02-01

    Automated monitoring of behaviour can offer a wealth of information in circumstances where observing behaviour is difficult or time consuming. However, this often requires attaching monitoring devices to the animal which can alter behaviour, potentially invalidating any data collected. Birds often show increased preening and energy expenditure when wearing devices and, especially in laying hens, there is a risk that individuals wearing devices will attract aggression from conspecifics. We studied the behavioural and physiological response of 20 laying hens to backpacks containing monitoring devices fastened with elastic loops around the wing base. We hypothesised that backpacks would lead to a stress-induced decrease in peripheral temperature, increased preening, more aggression from conspecifics, and reduced bodyweights. This was evaluated by thermography of the eye and comb (when isolated after fitting backpacks), direct observations of behaviour (when isolated, when placed back into the group, and on later days), and weighing (before and after each 7-day experimental period). Each hen wore a backpack during one of the two experimental periods only and was used as her own control. Contrary to our hypothesis, eye temperature was higher when hens wore a backpack (No backpack: 30.2 °C (IQR: 29.0-30.6) vs. Backpack: 30.9 °C (IQR: 30.0-32.0), P e., pecking the backpack or leg rings) was still affected 2-7 days after fitting (No backpack: 0 pecks/hen/minute (IQR: 0-0), vs. Backpack: 0 (IQR: 0-0.07), P < 0.05). We found no effect of our backpacks on bodyweight. In conclusion, our backpacks seem suitable to attach monitoring equipment to hens with only a very minor effect on their behaviour after a short acclimation period (≤2 days).

  4. Demand response to improved walking infrastructure: A study into the economics of walking and health behaviour change.

    Science.gov (United States)

    Longo, Alberto; Hutchinson, W George; Hunter, Ruth F; Tully, Mark A; Kee, Frank

    2015-10-01

    Walking is the most common form of moderate-intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 min of at least moderate-intensity physical activity per week. We model walking in an individual's local neighbourhood as a 'weak complement' to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood characteristics, substitutes, and individual's characteristics, including their opportunity cost of time. Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood. Using a sample of 1209 respondents surveyed over a 12 month period (Feb 2010-Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people's perception of access to shops and facilities would lead to an increase in walking of about 36 min/person/week, valued at £13.65/person/week. When focussing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Application of qualitative response models in a relevance study of older adults' health depreciation and medical care demand.

    Science.gov (United States)

    Weng, Shuo-Chun; Chen, Yu-Chi; Chen, Ching-Yu; Cheng, Yuan-Yang; Tang, Yih-Jing; Yang, Shu-Hui; Lin, Jwu-Rong

    2017-04-01

    The effect of health depreciation in older people on medical care demand is not well understood. We tried to assess the medical care demand with length of hospitalization and their impact on profits as a result of health depreciation. All participants who underwent comprehensive geriatric assessment were from a prospective cohort study at a tertiary hospital. A total of 1191 cases between September 2008 to October 2012 were investigated. Three sets of qualitative response models were constructed to estimate the impact of older adults' health depreciation on multidisciplinary geriatric care services. Furthermore, we analyzed the factors affecting the composite end-point of rehospitalization within 14 days, re-admission to the emergency department within 3 days and patient death. Greater health depreciation in elderly patients was positively correlated with greater medical care demand. Three major components were defined as health depreciation: elderly adaptation function, geriatric syndromes and multiple chronic diseases. On admission, the better the basic living functions, the shorter the length of hospitalization (coefficient = -0.35, P < 0.001 in Poisson regression; coefficient = -0.33, P < 0.001 in order choice profit model; coefficient = -0.29, P < 0.001 in binary choice profit model). The major determinants for poor outcome were male sex, middle old age and length of hospitalization. However, factors that correlated with relatively good outcome were functional improvement after medical care services and level of disease education. An optimal allocation system for selection of cases into multidisciplinary geriatric care is required because of limited resources. Outcomes will improve with health promotion and preventive care services. Geriatr Gerontol Int 2017; 17: 645-652. © 2016 Japan Geriatrics Society.

  6. Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

    International Nuclear Information System (INIS)

    Tabar, Vahid Sohrabi; Jirdehi, Mehdi Ahmadi; Hemmati, Reza

    2017-01-01

    Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. - Highlights: • Introducing portable renewable energy resource (PRER) and considering effect of them. • Considering reserve margin and sensitivity analysis for validate robustness. • Multi objective and stochastic management with considering various loads and sources. • Using augmented Epsilon-constraint method to solve multi objective program. • Highly decreasing total cost and pollution with PRER in stochastic state.

  7. A stimuli responsive liposome loaded hydrogel provides flexible on-demand release of therapeutic agents.

    Science.gov (United States)

    O'Neill, Hugh S; Herron, Caroline C; Hastings, Conn L; Deckers, Roel; Lopez Noriega, Adolfo; Kelly, Helena M; Hennink, Wim E; McDonnell, Ciarán O; O'Brien, Fergal J; Ruiz-Hernández, Eduardo; Duffy, Garry P

    2017-01-15

    Lysolipid-based thermosensitive liposomes (LTSL) embedded in a chitosan-based thermoresponsive hydrogel matrix (denoted Lipogel) represents a novel approach for the spatiotemporal release of therapeutic agents. The entrapment of drug-loaded liposomes in an injectable hydrogel permits local liposome retention, thus providing a prolonged release in target tissues. Moreover, release can be controlled through the use of a minimally invasive external hyperthermic stimulus. Temporal control of release is particularly important for complex multi-step physiological processes, such as angiogenesis, in which different signals are required at different times in order to produce a robust vasculature. In the present work, we demonstrate the ability of Lipogel to provide a flexible, easily modifiable release platform. It is possible to tune the release kinetics of different drugs providing a passive release of one therapeutic agent loaded within the gel and activating the release of a second LTSL encapsulated agent via a hyperthermic stimulus. In addition, it was possible to modify the drug dosage within Lipogel by varying the duration of hyperthermia. This can allow for adaption of drug dosing in real time. As an in vitro proof of concept with this system, we investigated Lipogels ability to recruit stem cells and then elevate their production of vascular endothelial growth factor (VEGF) by controlling the release of a pro-angiogenic drug, desferroxamine (DFO) with an external hyperthermic stimulus. Initial cell recruitment was accomplished by the passive release of hepatocyte growth factor (HGF) from the hydrogel, inducing a migratory response in cells, followed by the delayed release of DFO from thermosensitive liposomes, resulting in a significant increase in VEGF expression. This delayed release could be controlled up to 14days. Moreover, by changing the duration of the hyperthermic pulse, a fine control over the amount of DFO released was achieved. The ability to trigger

  8. Enhancement of membrane stability on magnetic responsive hydrogel microcapsules for potential on-demand cell separation.

    Science.gov (United States)

    Wen, Huiyun; Gao, Ting; Fu, Zizhen; Liu, Xing; Xu, Jiatong; He, Yishu; Xu, Ningxia; Jiao, Ping; Fan, An; Huang, Saipeng; Xue, Weiming

    2017-02-10

    It is of high interest to obtain hydrogel membranes with optimum mechanical stability, which is a prerequisite to the successful fabrication of hydrogel microcapsules for cell separation. In this work, we developed magnetic responsive alginate/chitosan (MAC) hydrogel microcapsules by co-encapsulation of microbial cells and superparamagnetic iron oxide nanoparticles (SPIONs) reacting under a high voltage electrostatic field. We investigated the influence of the molecular weight of chitosan, microcapsules size, and membrane crosslinking time on the swelling behavior of microcapsules as an indicator of stability of the membranes. The results demonstrated that the suitable membrane stability conditions were obtained by a crosslinking of the microspheres with a chitosan presenting a molecular weight of 70kDa for 15-30min resulting in a membrane thickness of approximately 30mm. Considering the need of maintaining the cells inside the microcapsules, fermentation at 37°C and at neutral pH was favorable. Moreover, the MAC microcapsules sizing between 300 and 380μm were suitable for immobilizing Bacillus licheniformis in a 286h multiple fed-bath operation with no leakage of the SPIONs and cells. Overall, the results of this study provided strategies for the rational design of magnetic microcapsules exhibiting suitable mechanical stable membranes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Energy efficiency options for the New England Demand Response Initiative (NEDRI) -- Framing paper No.4

    Energy Technology Data Exchange (ETDEWEB)

    Schlegel, Jeff

    2002-05-01

    In response to direction from the Connecticut Department of Public Utility Control (DPUC) in Docket 99-09-30, the Connecticut Light and Power Company (CL&P) has assessed the role of third parties (e.g., ESCOs) in its current energy efficiency programs as well as additional opportunities for third parties to participate in future programs. In addition to working with consultants to the Energy Conservation Management Board, CL&P asked an independent consultant to develop a descriptive framework (i.e., typology) that summarizes alternative approaches to using third parties in ratepayer-funded energy efficiency programs. For each approach, experiences of energy efficiency program administrators (EEA) in other states are summarized, major policy objectives and goals that motivated regulators or EEAs to pursue that option are identified, and lessons learned (e.g., strengths and weaknesses) are summarized. Existing program offerings of CL&P are then classified using this typology in order to characterize the current situation in Connecticut and the potential implications for Connecticut's energy efficiency programs are discussed.

  10. Responses of Lower-Body Power and Match Running Demands Following Long-Haul Travel in International Rugby Sevens Players.

    Science.gov (United States)

    Mitchell, John A; Pumpa, Kate L; Pyne, David B

    2017-03-01

    Mitchell, JA, Pumpa, KL, and Pyne, DB. Responses of lowerbody power and match running demands after long-haul travel in international rugby sevens players. J Strength Cond Res 31(3): 686-695, 2017-This study determined the effect of long-haul (>5 hours) travel on lower-body power and match running demands in international rugby sevens players. Lower-body power was assessed in 22 male international rugby sevens players (age 21.7 ± 2.7 years, mass 89.0 ± 6.7 kg, stature 180.5 ± 6.2 cm; mean ± SD) monitored over 17 rugby sevens tournaments. A countermovement jump was used to monitor lower-body power (peak and mean power) over repeated three week travel and competition periods (pretravel, posttravel, and posttournament). Small decreases were evident in peak power after both short and long-haul travel (-4.0%, ±3.2%; mean, ±90% confidence limits) with further reductions in peak and mean power posttournament (-4.5%, ±2.3% and -3.8%, ±1.5%) culminating in a moderate decrease in peak power overall (-7.4%, ±4.0%). A subset of 12 players (completing a minimum of 8 tournaments) had the effects of match running demands assessed with lower-body power. In this subset, long-haul travel elicited a large decrease in lower-body peak (-9.4%, ±3.5%) and mean power (-5.6%, ±2.9%) over the monitoring period, with a small decrease (-4.3%, ±3.0% and -2.2%, ±1.7%) posttravel and moderate decrease (-5.4%, ±2.5% and -3.5%, ±1.9%) posttournament, respectively. Match running demands were monitored through global positioning system. In long-haul tournaments, the 12 players covered ∼13%, ±13% greater total distance (meter) and ∼11%, ±10% higher average game meters >5 m·s when compared with short-haul (rugby sevens tournaments after long-haul travel.

  11. Experimental analysis of flexibility change with different levels of power reduction by demand response activation on thermostat controlled loads

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam; Marinelli, Mattia; Hu, Junjie

    2017-01-01

    This paper studies the flexibility available with thermostatically controlled loads (TCLs) to provide power system services by demand response (DR) activation. Although the DR activation on TCLs can provide power system ancillary services, it is important to know how long such services can...... be provided for when different levels of power reduction are imposed. The flexibility change with different levels of power reduction is tested experimentally with domestic fridges used by real customers with unknown user interaction. The investigation quantifies the flexibility of household fridges...... and the impact of DR activation in terms of deviation in the average temperature. The maximum possible power reduction with the cluster of refrigerators is 67% and the available flexibility with the cluster of refrigerators is 10%. The resulting deviation in the average temperature is 14%....

  12. Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Soares, J.

    2015-01-01

    In the smart grids context, distributed energy resources management plays an important role in the power systems' operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important...... to develop adequate methodologies to schedule the electric vehicles' charge and discharge processes, avoiding network congestions and providing ancillary services.This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed......, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting...

  13. INFLUENCE OF SUPPLY AND DEMAND FACTORS AT THE DEVELOPMENT OF ENVIRONMENTALLY RESPONSIBLE HOUSING AND UTILITIES SECTOR IN THE RUSSIAN FEDERATION

    Directory of Open Access Journals (Sweden)

    Natalia B. Safronova

    2016-11-01

    Full Text Available Empirical marketing regional research on supply and demand factors of housing and communal services (HCS revealed determinants of customer loyalty and satisfaction with the service level and factors influencing on willingness to purchase additional services. Specific features of housing and utilities sector (HUS as a social significant industry determine requirements to models reflecting reciprocal influence of indices of satisfaction, loyalty and economic indices of operation. The article presents definition of requirements along with development of techniques for modeling influence of satisfaction and loyalty on consumer behaviour of clients. The authors demonstrate trustworthy statistical results of correlative interrelationship of different factors. There have been designed regression models for taking management solutions by executives of management company housing and communal services at the development environmental responsibility. The causes that lead and hamper development of socially oriented services in different regions of the Russian Federation have been identified.

  14. On the Inclusion of Energy-Shifting Demand Response in Production Cost Models: Methodology and a Case Study

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Hale, Elaine; Doebber, Ian

    In the context of future power system requirements for additional flexibility, demand response (DR) is an attractive potential resource. Its proponents widely laud its prospective benefits, which include enabling higher penetrations of variable renewable generation at lower cost than alternative ...... values), simultaneously evaluating DR from multiple resources, and economically competing DR resources based on their costs of enablement and the trade-offs between end-user disutility and participation payments....... a case study of aggregated supermarket refrigeration systems providing balancing energy reserves in real-time markets at different levels of variable generation (VG). This DR resource is implemented in a test power system that represents a subset of the U.S Western Interconnection centered on Colorado...... penetration (increasing). Future work includes extending this method and developing new methods to be able to model physically realistic DR resources at scale. Some important aspects not studied here include capturing all possible value streams for a single resource (capacity, energy, and ancillary service...

  15. Real-time pricing strategy of micro-grid energy centre considering price-based demand response

    Science.gov (United States)

    Xu, Zhiheng; Zhang, Yongjun; Wang, Gan

    2017-07-01

    With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.

  16. Automated Scoring of Constructed-Response Science Items: Prospects and Obstacles

    Science.gov (United States)

    Liu, Ou Lydia; Brew, Chris; Blackmore, John; Gerard, Libby; Madhok, Jacquie; Linn, Marcia C.

    2014-01-01

    Content-based automated scoring has been applied in a variety of science domains. However, many prior applications involved simplified scoring rubrics without considering rubrics representing multiple levels of understanding. This study tested a concept-based scoring tool for content-based scoring, c-rater™, for four science items with rubrics…

  17. Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems

    International Nuclear Information System (INIS)

    Kitapbayev, Yerkin; Moriarty, John; Mancarella, Pierluigi

    2015-01-01

    Highlights: • We calculate the real option value of flexibility from CHP-thermal storage. • Stochastic optimal feedback control problem is solved under uncertain market prices. • Efficient real-time numerical solutions combine simulation, regression and recursion. • Clear, interpretable feedback control maps are produced for each hour of the day. • We give a realistic UK case study using projected market gas and electricity prices. - Abstract: In district energy systems powered by Combined Heat and Power (CHP) plants, thermal storage can significantly increase CHP flexibility to respond to real time market signals and therefore improve the business case of such demand response schemes in a Smart Grid environment. However, main challenges remain as to what is the optimal way to control inter-temporal storage operation in the presence of uncertain market prices, and then how to value the investment into storage as flexibility enabler. In this outlook, the aim of this paper is to propose a model for optimal and dynamic control and long term valuation of CHP-thermal storage in the presence of uncertain market prices. The proposed model is formulated as a stochastic control problem and numerically solved through Least Squares Monte Carlo regression analysis, with integrated investment and operational timescale analysis equivalent to real options valuation models encountered in finance. Outputs are represented by clear and interpretable feedback control strategy maps for each hour of the day, thus suitable for real time demand response under uncertainty. Numerical applications to a realistic UK case study with projected market gas and electricity prices exemplify the proposed approach and quantify the robustness of the selected storage solutions

  18. Integrated offering strategy for profit enhancement of distributed resources and demand response in microgrids considering system uncertainties

    International Nuclear Information System (INIS)

    Shayeghi, H.; Sobhani, B.

    2014-01-01

    Highlights: • Modelling mathematical integration of the proposed central bidding strategy for microgrids. • Considering and modelling the intra-market for adjusting the energy imbalances. • Analyzing effect of uncertainty of demand response and imbalance prices in profit of MG components. - Abstract: Due to the uncertain nature and limited predictability of wind and PV generated power, these resources participating in most of electricity markets are subject to significant deviation penalties during market settlements. In order to balance the unpredicted wind and PV power variations, system operators need to schedule additional reserves. This paper presents the optimal integrated participation model of wind and PV energy including demand response, storage devices, and dispatchable distributed generations in microgrids or virtual microgrids to increase their revenues in the intra-market. This market is considered 3–7 h before the delivered time, so that the amount of the contracted energy could be updated to reduce the produced power deviation of microgrid. A stochastic programming approach is considered in the development of the proposed bidding strategies for microgrid producers and loads. The optimization model is characterized by making the analysis of several scenarios and simultaneously treating three kinds of uncertainty including wind and PV power, intra-market, and imbalance prices. In order to predict these uncertainty variables, a neuro-fuzzy based approach has been applied. Historic data are used to forecast future prices and wind and PV power production in the adjustment markets. Also, a probabilistic approach based on the error of forecasted and real historic data is considered for estimating the future IM and imbalance prices of wind and PV produced power. Further, a test case is applied to example the microgrid using the Spanish market rules during one week, month, and year period to illustrate the potential benefits of the proposed joint

  19. An integrated stochastic multi-regional long-term energy planning model incorporating autonomous power systems and demand response

    International Nuclear Information System (INIS)

    Koltsaklis, Nikolaos E.; Liu, Pei; Georgiadis, Michael C.

    2015-01-01

    The power sector faces a rapid transformation worldwide from a dominant fossil-fueled towards a low carbon electricity generation mix. Renewable energy technologies (RES) are steadily becoming a greater part of the global energy mix, in particular in regions that have put in place policies and measures to promote their utilization. This paper presents an optimization-based approach to address the generation expansion planning (GEP) problem of a large-scale, central power system in a highly uncertain and volatile electricity industry environment. A multi-regional, multi-period linear mixed-integer linear programming (MILP) model is presented, combining optimization techniques with a Monte Carlo (MCA) method and demand response concepts. The optimization goal concerns the minimization of the total discounted cost by determining optimal power capacity additions per time interval and region, and the power generation mix per technology and time period. The model is evaluated on the Greek power system (GPS), taking also into consideration the scheduled interconnection of the mainland power system with those of selected autonomous islands (Cyclades and Crete), and aims at providing full insight into the composition of the long-term energy roadmap at a national level. - Highlights: • A spatial, multi-period, long-term generation expansion planning model is presented. • A Monte-Carlo method along with a demand response mechanism are incorporated. • Autonomous power systems interconnection is considered. • Electricity and CO 2 emission trade are taken into account. • Lignite, natural gas and wind power comprise the dominant power technologies

  20. Heterogeneity of demand responses in modelling the distributional consequences of tradable carbon permits in the road transport sector

    International Nuclear Information System (INIS)

    Wadud, Zia; Noland, Robert B.; Graham, Daniel J.

    2007-01-01

    Personal road transport sector is one of the largest and fastest growing sources of CO 2 emissions. This paper investigates a tradable permit policy for mitigating carbon emissions from personal road transport and discusses various issues of permit allocation. As tradable permits will effectively raise the price of fuel, the policy has important distributional implications. The distribution of burden depends on permit allocation strategies and on the consumer response to an increase in price. The behavioural response may vary among different segments of the population depending on their travel needs, which in turn are contingent upon their income, location of residence and other factors. Consumer Expenditure Survey micro dataset from 1997 to 2002 has been used to econometrically model the possible variation of price elasticity for different socio-economic groups in the USA. Results indicate that the response of gasoline demand to a change in price does depend on income level or location of the household. Distributional impacts of the tradable permit policy are then evaluated using the micro dataset for year 2002. In this regard, different permit allocation schemes are considered in the analysis. Impacts on households owning a vehicle and households with no vehicles have been evaluated as well

  1. Robotics and Office Automation: Implications for Vocational Education.

    Science.gov (United States)

    Fraser, Jeannette L.; And Others

    Directed to individuals responsible for program planning in vocational education at the national and state levels, this review and synthesis of technological developments in robotics and office automation identifies the potential demand for skills in these technologies in the next 3 to 5 years. The procedures for the study are described in the…

  2. Neonatal hearing screening of high-risk infants using automated auditory brainstem response: a retrospective analysis of referral rates.

    LENUS (Irish Health Repository)

    McGurgan, I J

    2013-10-07

    The past decade has seen the widespread introduction of universal neonatal hearing screening (UNHS) programmes worldwide. Regrettably, such a programme is only now in the process of nationwide implementation in the Republic of Ireland and has been largely restricted to one screening modality for initial testing; namely transient evoked otoacoustic emissions (TEOAE). The aim of this study is to analyse the effects of employing a different screening protocol which utilises an alternative initial test, automated auditory brainstem response (AABR), on referral rates to specialist audiology services.

  3. Serum brain-derived neurotrophic factor and interleukin-6 response to high-volume mechanically demanding exercise.

    Science.gov (United States)

    Verbickas, Vaidas; Kamandulis, Sigitas; Snieckus, Audrius; Venckunas, Tomas; Baranauskiene, Neringa; Brazaitis, Marius; Satkunskiene, Danguole; Unikauskas, Alvydas; Skurvydas, Albertas

    2018-01-01

    The aim of this study was to follow circulating brain-derived neurotrophic factor (BDNF) and interleukin-6 (IL-6) levels in response to severe muscle-damaging exercise. Young healthy men (N = 10) performed a bout of mechanically demanding stretch-shortening cycle exercise consisting of 200 drop jumps. Voluntary and electrically induced knee extension torque, serum BDNF levels, and IL-6 levels were measured before and for up to 7 days after exercise. Muscle force decreased by up to 40% and did not recover by 24 hours after exercise. Serum BDNF was decreased 1 hour and 24 hours after exercise, whereas IL-6 increased immediately and 1 hour after but recovered to baseline by 24 hours after exercise. IL-6 and 100-Hz stimulation torque were correlated (r = -0.64, P exercise. In response to acute, severe muscle-damaging exercise, serum BDNF levels decrease, whereas IL-6 levels increase and are associated with peripheral fatigue. Muscle Nerve 57: E46-E51, 2018. © 2017 Wiley Periodicals, Inc.

  4. An assessment of the role mass market demand response could play in contributing to the management of variable generation integration issues

    International Nuclear Information System (INIS)

    Cappers, Peter; Mills, Andrew; Goldman, Charles; Wiser, Ryan; Eto, Joseph H.

    2012-01-01

    The penetration of wind and solar generating resources is expected to dramatically increase in the United States over the coming years. It is widely understood that large scale deployment of these types of renewable energy sources (e.g., wind, solar) that have variable and less predictable production characteristics than traditional thermal resources poses integration challenges for bulk power system operators. At present, bulk power system operators primarily utilize strategies that rely on existing thermal generation resources and improved wind and solar energy production forecasts to manage this uncertainty; a host of additional options are also envisioned for the near future including demand response (DR). There are well-established bodies of research that examine variable generation integration issues as well as demand response potential; but, the existing literature that provides a comparative assessment of the two neither treats this topic comprehensively nor in a highly integrated fashion. Thus, this paper seeks to address these missing pieces by considering the full range of opportunities and challenges for mass market DR rates and programs to support integration of variable renewable generation. - Highlights: ► Mass market demand response can help manage the integration of renewable resources. ► To be more effective, retail electricity rates must apply contemporaneous prices. ► Demand response programs will require shorter duration and more frequent events. ► Mass market customers will likely need to accept control technology. ► Market rules and regulatory policies must change to expand demand response's role.

  5. Metabolomics reveals differences in postprandial responses to breads and fasting metabolic characteristics associated with postprandial insulin demand in postmenopausal women.

    Science.gov (United States)

    Moazzami, Ali A; Shrestha, Aahana; Morrison, David A; Poutanen, Kaisa; Mykkänen, Hannu

    2014-06-01

    Changes in serum metabolic profile after the intake of different food products (e.g., bread) can provide insight into their interaction with human metabolism. Postprandial metabolic responses were compared after the intake of refined wheat (RWB), whole-meal rye (WRB), and refined rye (RRB) breads. In addition, associations between the metabolic profile in fasting serum and the postprandial concentration of insulin in response to different breads were investigated. Nineteen postmenopausal women with normal fasting glucose and normal glucose tolerance participated in a randomized, controlled, crossover meal study. The test breads, RWB (control), RRB, and WRB, providing 50 g of available carbohydrate, were each served as a single meal. The postprandial metabolic profile was measured using nuclear magnetic resonance and targeted LC-mass spectrometry and was compared between different breads using ANOVA and multivariate models. Eight amino acids had a significant treatment effect (P effect (P fasting metabolic profile and the postprandial concentration of insulin. Women with higher fasting concentrations of leucine and isoleucine and lower fasting concentrations of sphingomyelins and phosphatidylcholines had higher insulin responses despite similar glucose concentration after all kinds of bread (cross-validated ANOVA, P = 0.048). High blood concentration of branched-chain amino acids, i.e., leucine and isoleucine, has been associated with the increased risk of diabetes, which suggests that additional consideration should be given to bread proteins in understanding the beneficial health effects of different kinds of breads. The present study suggests that the fasting metabolic profile can be used to characterize the postprandial insulin demand in individuals with normal glucose metabolism that can be used for establishing strategies for the stratification of individuals in personalized nutrition. © 2014 American Society for Nutrition.

  6. Interobserver agreement of semi-automated and manual measurements of functional MRI metrics of treatment response in hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Bonekamp, David; Bonekamp, Susanne; Halappa, Vivek Gowdra; Geschwind, Jean-Francois H.; Eng, John; Corona-Villalobos, Celia Pamela; Pawlik, Timothy M.; Kamel, Ihab R.

    2014-01-01

    Purpose: To assess the interobserver agreement in 50 patients with hepatocellular carcinoma (HCC) before and 1 month after intra-arterial therapy (IAT) using two semi-automated methods and a manual approach for the following functional, volumetric and morphologic parameters: (1) apparent diffusion coefficient (ADC), (2) arterial phase enhancement (AE), (3) portal venous phase enhancement (VE), (4) tumor volume, and assessment according to (5) the Response Evaluation Criteria in Solid Tumors (RECIST), and (6) the European Association for the Study of the Liver (EASL). Materials and methods: This HIPAA-compliant retrospective study had institutional review board approval. The requirement for patient informed consent was waived. Tumor ADC, AE, VE, volume, RECIST, and EASL in 50 index lesions was measured by three observers. Interobserver reproducibility was evaluated using intraclass correlation coefficients (ICC). P < 0.05 was considered to indicate a significant difference. Results: Semi-automated volumetric measurements of functional parameters (ADC, AE, and VE) before and after IAT as well as change in tumor ADC, AE, or VE had better interobserver agreement (ICC = 0.830–0.974) compared with manual ROI-based axial measurements (ICC = 0.157–0.799). Semi-automated measurements of tumor volume and size in the axial plane before and after IAT had better interobserver agreement (ICC = 0.854–0.996) compared with manual size measurements (ICC = 0.543–0.596), and interobserver agreement for change in tumor RECIST size was also higher using semi-automated measurements (ICC = 0.655) compared with manual measurements (ICC = 0.169). EASL measurements of tumor enhancement in the axial plane before and after IAT ((ICC = 0.758–0.809), and changes in EASL after IAT (ICC = 0.653) had good interobserver agreement. Conclusion: Semi-automated measurements of functional changes assessed by ADC and VE based on whole-lesion segmentation demonstrated better reproducibility than

  7. Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

    International Nuclear Information System (INIS)

    Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

    2016-01-01

    Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics. In particular the model provides an explicit quantification of the economic value of DSR against alternative investment strategies. Through sensitivity analysis it is able to indicate the maximum price payable for DSR service such that DSR remains economically optimal against these alternatives. The proposed model thus provides Regulators with clear insights for overseeing DSR contractual arrangements. Further it highlights that differences exist in the economic perspective of the regulated DNO business and of customers. Our proposed model is therefore capable of highlighting instances where a particular investment strategy is favorable to the DNO but not to its customers, or vice-versa, and thus aspects of the regulatory framework which may

  8. An econometric analysis of electricity demand response to price changes at the intra-day horizon: The case of manufacturing industry in West Denmark

    Directory of Open Access Journals (Sweden)

    Niels Framroze Møller

    2015-06-01

    Full Text Available The use of renewable energy implies a more variable supply of power. Market efficiency may improve if demand can absorb some of this variability by being more flexible, e.g. by responding quickly to changes in the market price of power. To learn about this, in particular, whether demand responds already within the same day, we suggest an econometric model for hourly consumption- and price time series. This allows for multi-level seasonality and that information about day-ahead prices does not arrive every hour but every 24th hour (as a vector of 24 prices. We confront the model with data from the manufacturing industry of West Denmark (2007-2011. The results clearly suggest a lack of response. The policy implication is that relying exclusively on hourly price response by consumers for integrating volatile renewable electricity production is questionable. Either hourly price variation has to increase considerably or demand response technologies be installed.

  9. A Novel Demand Response Method for Smart Microgrids Related to the Uncertainties of Renewable Energy Resources and Energy Price

    Directory of Open Access Journals (Sweden)

    R. Roofegari Nejad

    2016-06-01

    Full Text Available This paper presents novel methods for Demand Response (DR programs by considering welfare state of consumers, to deal with the operational uncertainties, such as wind energy and energy price, within the framework of a smart microgrid. In this regard, total loads of microgrid are classified into two groups and each one is represented by a typical load. First group is energy storage capability represents by heater loads and second is curtailment capability loads represents by lighting loads. Next by the proposed DR methods, consumed energy of the all loads is coupled to the wind energy rate and energy price. Finally these methods are applied in the operation of a smart microgrid, consists of dispatchable supplier (microturbine, nondispatchable supplier (wind turbine, energy storage system and loads with the capability of energy exchanging with upstream distribution network. In order to consider uncertainties, Monte Carlo simulation method is used, which various scenarios are generated and applied in the operation of microgrid. In the end, the simulation results on a typical microgrid show that implementing proposed DR methods contributes to increasing total operational profit of smart microgrid and also decreasing the risk of low profit too.

  10. Breaking through the hydrogen cost barrier by using electrolysis loads to access ancillary services and demand response programs

    International Nuclear Information System (INIS)

    Wilson, D.; McGillivray, R.

    2009-01-01

    This presentation described the use of hydrogen electrolysis as a load resource for handling grid instability resulting from the increased penetration of intermittent renewable power. In particular, it focused on Hydrogenics, the leading global supplier of industrial scale electrolysis equipment and fuel cells. The presentation included an overview of the current incentive and market value of ancillary services provided by the company and demand responses in a number of grids around the world. There is a link between the amount of ancillary services required by the grid and the penetration level of renewable energy power such as wind and solar. The ability of hydrogen generation from electrolysis to satisfy all the requirements of ancillary services markets was also demonstrated. The economic analysis of hydrogen generation was discussed with particular reference to the cost of hydrogen fully loading all capital, energy and operating costs. The resulting reduction in the cost of hydrogen was compared to the existing markets for hydrogen, including use of hydrogen as a fuel for municipal bus fleets relative to the existing cost of fossil fuel fleets. Current industrial hydrogen merchant and bulk market prices were also compared

  11. A Time-Varying Potential-Based Demand Response Method for Mitigating the Impacts of Wind Power Forecasting Errors

    Directory of Open Access Journals (Sweden)

    Jia Ning

    2017-11-01

    Full Text Available The uncertainty of wind power results in wind power forecasting errors (WPFE which lead to difficulties in formulating dispatching strategies to maintain the power balance. Demand response (DR is a promising tool to balance power by alleviating the impact of WPFE. This paper offers a control method of combining DR and automatic generation control (AGC units to smooth the system’s imbalance, considering the real-time DR potential (DRP and security constraints. A schematic diagram is proposed from the perspective of a dispatching center that manages smart appliances including air conditioner (AC, water heater (WH, electric vehicle (EV loads, and AGC units to maximize the wind accommodation. The presented model schedules the AC, WH, and EV loads without compromising the consumers’ comfort preferences. Meanwhile, the ramp constraint of generators and power flow transmission constraint are considered to guarantee the safety and stability of the power system. To demonstrate the performance of the proposed approach, simulations are performed in an IEEE 24-node system. The results indicate that considerable benefits can be realized by coordinating the DR and AGC units to mitigate the WPFE impacts.

  12. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-21

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  13. Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems.

    Science.gov (United States)

    Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

    2016-10-28

    Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.

  14. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-03

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  15. Demand response strategy management with active and reactive power incentive in the smart grid: a two-level optimization approach

    Directory of Open Access Journals (Sweden)

    Ryuto Shigenobu

    2017-05-01

    Full Text Available High penetration of distributed generators (DGs using renewable energy sources (RESs is raising some important issues in the operation of modern po­wer system. The output power of RESs fluctuates very steeply, and that include uncertainty with weather conditions. This situation causes voltage deviation and reverse power flow. Several methods have been proposed for solving these problems. Fundamentally, these methods involve reactive power control for voltage deviation and/or the installation of large battery energy storage system (BESS at the interconnection point for reverse power flow. In order to reduce the installation cost of static var compensator (SVC, Distribution Company (DisCo gives reactive power incentive to the cooperating customers. On the other hand, photovoltaic (PV generator, energy storage and electric vehicle (EV are introduced in customer side with the aim of achieving zero net energy homes (ZEHs. This paper proposes not only reactive power control but also active power flow control using house BESS and EV. Moreover, incentive method is proposed to promote participation of customers in the control operation. Demand response (DR system is verified with several DR menu. To create profit for both side of DisCo and customer, two level optimization approach is executed in this research. Mathematical modeling of price elasticity and detailed simulations are executed by case study. The effectiveness of the proposed incentive menu is demonstrated by using heuristic optimization method.

  16. On the Inclusion of Energy-Shifting Demand Response in Production Cost Models: Methodology and a Case Study

    Energy Technology Data Exchange (ETDEWEB)

    O' Connell, Niamh [Technical Univ. of Denmark, Lyngby (Denmark); Hale, Elaine [National Renewable Energy Lab. (NREL), Golden, CO (United States); Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-07-20

    In the context of future power system requirements for additional flexibility, demand response (DR) is an attractive potential resource. Its proponents widely laud its prospective benefits, which include enabling higher penetrations of variable renewable generation at lower cost than alternative storage technologies, and improving economic efficiency. In practice, DR from the commercial and residential sectors is largely an emerging, not a mature, resource, and its actual costs and benefits need to be studied to determine promising combinations of physical DR resource, enabling controls and communications, power system characteristics, regulatory environments, market structures, and business models. The work described in this report focuses on the enablement of such analysis from the production cost modeling perspective. In particular, we contribute a bottom-up methodology for modeling load-shifting DR in production cost models. The resulting model is sufficiently detailed to reflect the physical characteristics and constraints of the underlying flexible load, and includes the possibility of capturing diurnal and seasonal variations in the resource. Nonetheless, the model is of low complexity and thus suitable for inclusion in conventional unit commitment and market clearing algorithms. The ability to simulate DR as an operational resource on a power system over a year facilitates an assessment of its time-varying value to the power system.

  17. Turnkey Heating, Ventilating, and Air Conditioning and Lighting Retrofit Solution Combining Energy Efficiency and Demand Response Benefits

    Energy Technology Data Exchange (ETDEWEB)

    Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Deru, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Trenbath, Kim [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-04-12

    NREL worked with the Bonneville Power Administration's Technology Innovation Office to demonstrate a turnkey, retrofit technology that combines demand response (DR) and energy efficiency (EE) benefits for HVAC and lighting in retail buildings. As a secondary benefit, we also controlled various plug loads and electric hot water heaters (EHWH). The technology demonstrated was Transformative Wave's eIQ Building Management System (BMS) automatically responding to DR signals. The BMS controlled the HVAC rooftop units (RTU) using the CATALYST retrofit solution also developed by Transformative Wave. The non-HVAC loads were controlled using both hardwired and ZigBee wireless communication. The wireless controllers, manufactured by Autani, were used when the building's electrical layout was too disorganized to leverage less expensive hardwired control. The six demonstration locations are within the Seattle metro area. Based on the assets curtailed by the BMS at each location, we projected the DR resource. We were targeting a 1.7 W/ft2 shed for the summer Day-Ahead events and a 0.7 W/ft2 shed for the winter events. While summarized in Table ES-1, only one summer DR event was conducted at Casino #2.

  18. Development of a Technology Transfer Score for Evaluating Research Proposals: Case Study of Demand Response Technologies in the Pacific Northwest

    Science.gov (United States)

    Estep, Judith

    researcher and recipient relationship, specific to technology transfer. In this research, the evaluation criteria of several research organizations were assessed to understand the extent to which the success attributes that were identified in literature were considered when reviewing research proposals. While some of the organizations included a few of the success attributes, none of the organizations considered all of the attributes. In addition, none of the organizations quantified the value of the success attributes. The effectiveness of the model relies extensively on expert judgments to complete the model validation and quantification. Subject matter experts ranging from senior executives with extensive experience in technology transfer to principal research investigators from national labs, universities, utilities, and non-profit research organizations were used to ensure a comprehensive and cross-functional validation and quantification of the decision model. The quantified model was validated using a case study involving demand response (DR) technology proposals in the Pacific Northwest. The DR technologies were selected based on their potential to solve some of the region's most prevalent issues. In addition, several sensitivity scenarios were developed to test the model's response to extreme case scenarios, impact of perturbations in expert responses, and if it can be applied to other than demand response technologies. In other words, is the model technology agnostic? In addition, the flexibility of the model to be used as a tool for communicating which success attributes in a research proposal are deficient and need strengthening and how improvements would increase the overall technology transfer score were assessed. The low scoring success attributes in the case study proposals (e.g. project meetings, etc.) were clearly identified as the areas to be improved for increasing the technology transfer score. As a communication tool, the model could help a research

  19. Individual differences in oscillatory brain activity in response to varying attentional demands during a word recall and oculomotor dual task

    Directory of Open Access Journals (Sweden)

    Gusang eKwon

    2015-06-01

    Full Text Available Every day, we face situations that involve multi-tasking. How our brain utilizes cortical resources during multi-tasking is one of many interesting research topics. In this study, we tested whether a dual-task can be differentiated in the neural and behavioral responses of healthy subjects with varying degree of working memory capacity (WMC. We combined word recall and oculomotor tasks because they incorporate common neural networks including the fronto-parietal (FP network. Three different types of oculomotor tasks (eye fixation; Fix-EM, predictive & random smooth pursuit eye movement; P-SPEM & R-SPEM were combined with two memory load levels (low-load: 5 words, high-load: 10 words for a word recall task. Each of those dual-task combinations was supposed to create varying cognitive loads on the FP network. We hypothesize that each dual-task requires different cognitive strategies for allocating the brain’s limited cortical resources and affects brain oscillation of the FP network. In addition, we hypothesized that groups with different WMC will show differential neural and behavioral responses. We measured oscillatory brain activity with simultaneous MEG and EEG recordings and behavioral performance by word recall. Prominent frontal midline (FM theta (4-6 Hz synchronization emerged in the EEG of the high-WMC group experiencing R-SPEM with high-load conditions during the early phase of the word maintenance period. Conversely, significant parietal upper alpha (10-12 Hz desynchronization was observed in the EEG and MEG of the low-WMC group experiencing P-SPEM under high-load conditions during the same period. Different brain oscillatory patterns seem to depend on each individual’s WMC and varying attentional demands from different dual-task combinations. These findings suggest that specific brain oscillations may reflect different strategies for allocating cortical resources during combined word recall and oculomotor dual-tasks.

  20. Identification of Value Proposition and Development of Innovative Business Models for Demand Response Products and Services Enabled by the DR-BOB Solution

    Directory of Open Access Journals (Sweden)

    Mario Sisinni

    2017-10-01

    Full Text Available The work presented is the result of an ongoing European H2020 project entitled DR-BOB Demand Response in Blocks of Buildings (DR-BOB that seeks to integrate existing technologies to create a scalable solution for Demand Response (DR in blocks of buildings. In most EU countries, DR programs are currently limited to the industrial sector and to direct asset control. The DR-BOB solution extends applicability to the building sector, providing predictive building management in blocks of buildings, enabling facilities managers to respond to implicit and explicit DR schemes, and enabling the aggregation of the DR potential of many blocks of buildings for use in demand response markets. The solution consists of three main components: the Local Energy Manager (LEM, which adds intelligence and provides the capacity for predictive building management in blocks of buildings, a Consumer Portal (CP to enable building managers and building occupants to interact with the system and be engaged in demand response operations, and a Decentralized Energy Management System (DEMS®, Siemens plc, Nottingham, England, UK, which enables the aggregation of the DR potential of many blocks of buildings, thus allowing participation in incentive-based demand response with or without an aggregator. The paper reports the key results around Business Modelling development for demand response products and services enabled by the DR-BOB solution. The scope is threefold: (1 illustrate how the functionality of the demand response solution can provide value proposition to underpin its exploitation by four specific customer segments, namely aggregators and three types of Owners of Blocks of Buildings in different market conditions, (2 explore key aspects of the Business Model from the point of view of a demand response solution provider, in particular around most the suitable revenue stream and key partnership, and (3 assess the importance of key variables such as market maturity, user

  1. Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria

    International Nuclear Information System (INIS)

    Marten, Katharina; Auer, Florian; Schmidt, Stefan; Rummeny, Ernst J.; Engelke, Christoph; Kohl, Gerhard

    2006-01-01

    The purpose of this study was to compare relative values of manual unidimensional measurements (MD) and automated volumetry (AV) for longitudinal treatment response assessment in patients with pulmonary metastases. Fifty consecutive patients with pulmonary metastases and repeat chest multidetector-row CT (median interval=2 months) were independently assessed by two radiologists for treatment response using Response Evaluation Criteria In Solid Tumours (RECIST). Statistics included relative measurement errors (RME), intra-/interobserver correlations, limits of agreement (95% LoA), and kappa. A total of 202 metastases (median volume=182.22 mm 3 ; range=3.16-5,195.13 mm 3 ) were evaluated. RMEs were significantly higher for MD than for AV (intraobserver RME=2.34-3.73% and 0.15-0.22% for MD and AV respectively; P 3 for AV. The interobserver 95% LoA were -1.46 to 1.92 mm for MD and -11.17 to 9.33 mm 3 for AV. There was total intra-/interobserver agreement on response using AV (κ=1). MD intra- and interobserver agreements were 0.73-0.84 and 0.77-0.80 respectively. Of the 200 MD response ratings, 28 (14/50 patients) were discordant. Agreement using MD dropped significantly from total remission to progressive disease (P<0.05). We therefore conclude that AV allows for better reproducibility of response evaluation in pulmonary metastases and should be preferred to MD in these patients. (orig.)

  2. Demand Uncertainty

    DEFF Research Database (Denmark)

    Nguyen, Daniel Xuyen

    . This retooling addresses several shortcomings. First, the imperfect correlation of demands reconciles the sales variation observed in and across destinations. Second, since demands for the firm's output are correlated across destinations, a firm can use previously realized demands to forecast unknown demands...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles......This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models...

  3. Evaluating price-based demand response in practice – with application to the EcoGrid EU Experiment

    DEFF Research Database (Denmark)

    Le Ray, Guillaume; Larsen, Emil Mahler; Pinson, Pierre

    2016-01-01

    -scale EcoGrid EU experiment. In this project, 1900 houses were equipped with smart meters and other automation devices in order to adapt consumption to real-time electricity prices every five minutes, while monitoring it with the same resolution. Our approach first relies on the clustering of residential...

  4. Automated Contingency Management for Propulsion Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency...

  5. Prediction of Treatment Response to Donepezil using Automated Hippocampal Subfields Volumes Segmentation in Patients with Mild Alzheimer's Disease.

    Science.gov (United States)

    Um, Yoo Hyun; Kim, Tae-Won; Jeong, Jong-Hyun; Seo, Ho-Jun; Han, Jin-Hee; Hong, Seung-Chul; Lee, Chang-Uk; Lim, Hyun Kook

    2017-09-01

    Previous studies reported some relationships between donepezil treatment and hippocampus in Alzheimer's disease (AD). However, due to methodological limitations, their close relationships remain unclear. The aim of this study is to predict treatment response to donepezil by utilizing the automated segmentation of hippocampal subfields volumes (ASHS) in AD. Sixty four AD patients were prescribed with donepezil and were followed up for 24 weeks. Cognitive function was measured to assess whether there was a response from the donepezil treatment. ASHS was implemented on non-responder (NR) and responder (TR) groups, and receiver operator characteristic (ROC) analysis was conducted to evaluate the sensitivity, specificity, and accuracy of hippocampal subfields in predicting response to donepezil. The left total hippocampus and the CA1 area of the NR were significantly smaller than those of the TR group. The ROC curve analysis showed the left CA1 volumes showed highest area under curve (AUC) of 0.85 with a sensitivity of 88.0%, a specificity of 74.0% in predicting treatment response to donepezil treatment. We expect that hippocampal subfields volume measurements that predict treatment responses to current AD drugs will enable more evidence-based, individualized prescription of medications that will lead to more favorable treatment outcomes.

  6. Influence of game format and number of players on heart rate responses and physical demands in small-sided soccer games.

    Science.gov (United States)

    Castellano, Julen; Casamichana, David; Dellal, Alexandre

    2013-05-01

    The aim of the study was to examine the extent to which changing the game format (possession play vs. regulation goals and goalkeepers vs. small goals only) and the number of players (3 vs. 3, 5 vs. 5 and 7 vs. 7) influenced the physiological and physical demands of small-sided games (SSGs) in soccer in semiprofessional players. Fourteen semiprofessional male soccer players were monitored with global positioning system and heart rate devices. Heart rate, player load, distance covered, running speed, and the number of accelerations were recorded for 9 different SSGs. The results show that changes both in game format and the number of players affect the players' physiological and physical demands. Possession play places greater physiological and physical demands on players, although reducing the number of players only increases the physiological load. In the 7 vs. 7 games, changing the game format did not alter the heart rate responses. Finally, in the possession play format, changing the number of players did not produce significant differences in heart rate responses, although physical demands did decrease in line with a reduction in the number of players. These results should help coaches to understand how modifying different aspects of SSGs has a differential effect on the players' physiological and physical demands. Moreover, coaches in semiprofessional and amateur teams have now consistent information to design and optimize their training time in mixing the technical, tactical, and physical aspects.

  7. Implementation of Capacity Planning Agent of Demand Responsive Planning Framework : Master’s Thesis in Production Engineering of The Royal Institute of Technology

    OpenAIRE

    Juhong, Nirut

    2013-01-01

    This master’s thesis is conducted as a conclusion of Master degree of Science in Production Engineering and Management at The Royal Institute of Technology. The focus of this thesis work is to implement a Capacity planning agent. Nowadays, companies need to adapt themselves to be as responsive to customers’ demand as possible. However, the responsiveness is usually limited by the fixed capacity of the production. Evolvable Production System (EPS), motivated by the limitation mentioned above, ...

  8. Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response

    International Nuclear Information System (INIS)

    Zheng, Menglian; Meinrenken, Christoph J.; Lackner, Klaus S.

    2014-01-01

    Highlights: • Storage-based demand response (loadshifting) is underutilized in residential sector. • Economics (arbitrage savings versus equipment cost) are not well understood. • Stochastic demand models and real-life tariffs can illuminate economic viability. • A range of available storage options provide economically viable DR. • Daily/seasonal stochastic demand variations crucial to understanding optimum capacity. - Abstract: Demand response (DR) is one of many approaches to address temporal mismatches in demand and supply of grid electricity. More common in the commercial sector, DR usually refers to reducing consumption at certain hours or seasons, thus reducing peak demand from the grid. In the residential sector, where sophisticated appliance-level controls such as automatic dimming of lights or on-demand lowering of air conditioning are less common, building-based electricity storage to shift grid consumption from peak to off-peak times could provide DR without requiring consumers to operate their appliances on shifted or reduced schedules: Storage would be dispatched to appliances as needed while still shaving peaks on the grid. Technologically, storage and two-way-inverters are readily available to enable such residential DR. Economically, however, the situation is less clear. Specifically, are time-varying electricity tariffs available such that electricity cost reduction via arbitrage could offset manufacturing, financing, and installation costs of the required storage? To address this question we (i) devise an agent-based appliance-level stochastic model to simulate the electricity demand of an average U.S. household; (ii) loadshift the demand via simple dispatch strategies; and (iii) determine potential profits to the building owner, i.e. reduced electricity cost of the modified demand with realistic tariffs (Con Edison, NY) minus storage cost. We determine the economic viability for a range of traditional and advanced storage technologies

  9. Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography.

    Science.gov (United States)

    Pradhan, Zia S; Rao, Harsha L; Puttaiah, Narendra K; Kadambi, Sujatha V; Dasari, Srilakshmi; Reddy, Hemanth B; Palakurthy, Meena; Riyazuddin, Mohammed; Rao, Dhanaraj A S

    2017-05-01

    To predict the magnitude of functional damage [mean deviation (MD) on visual field examination] and structural damage [retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) thickness on spectral domain optical coherence tomography] in glaucoma from monocular pupillary light response measurements using automated pupillography. In total, 59 subjects (118 eyes) with either a confirmed or suspected diagnosis of glaucoma underwent automated pupillography, along with visual fields and spectral domain optical coherence tomography examinations. Association between pupillary light response measurements of each eye [amplitude of constriction, latency of onset of constriction (Loc), latency of maximal constriction (Lmaxc), velocity of constriction and velocity of redilation] and corresponding MD, average RNFL, and average GCC measurements were evaluated using univariate and multivariate regression analysis after accounting for the multicollinearity. Goodness of fit of the multivariate models was evaluated using coefficient of determination (R). Multivariate regression models that contained Loc and Lmaxc showed the best association with MD (R of 0.30), average RNFL thickness (R=0.18) and average GCC thickness (R=0.26). The formula that best predicts the MD could be described as: MD=-14.06-0.15×Loc+0.06×Lmaxc. The formula that best predicts the average RNFL thickness could be described as: Average RNFL thickness=67.18-0.22×Loc+0.09×Lmaxc. Glaucomatous damage as estimated by MD, RNFL, and GCC thickness measurements were best predicted by the latency parameters (Loc and Lmaxc) of pupillography. Worsening of glaucomatous damage resulted in a delayed onset of pupillary constriction and a decreased Lmaxc.

  10. Low-dose DNA damage and replication stress responses quantified by optimized automated single-cell image analysis

    DEFF Research Database (Denmark)

    Mistrik, Martin; Oplustilova, Lenka; Lukas, Jiri

    2009-01-01

    Maintenance of genome integrity is essential for homeostasis and survival as impaired DNA damage response (DDR) may predispose to grave pathologies such as neurodegenerative and immunodeficiency syndromes, cancer and premature aging. Therefore, accurate assessment of DNA damage caused...... and demand for trained personnel. Here we present an option how to transform a regular fluorescence microscope and personal computer with common software into a functional alternative to high-throughput screening devices. In two detailed protocols we introduce a new semi-automatic procedure allowing for very...

  11. DeMand: A tool for evaluating and comparing device-level demand and supply forecast models

    DEFF Research Database (Denmark)

    Neupane, Bijay; Siksnys, Laurynas; Pedersen, Torben Bach

    2016-01-01

    Fine-grained device-level predictions of both shiftable and non-shiftable energy demand and supply is vital in order to take advantage of Demand Response (DR) for efficient utilization of Renewable Energy Sources. The selection of an effective device-level load forecast model is a challenging task......, mainly due to the diversity of the models and the lack of proper tools and datasets that can be used to validate them. In this paper, we introduce the DeMand system for fine-tuning, analyzing, and validating the device-level forecast models. The system offers several built-in device-level measurement...... datasets, forecast models, features, and errors measures, thus semi-automating most of the steps of the forecast model selection and validation process. This paper presents the architecture and data model of the DeMand system; and provides a use-case example on how one particular forecast model...

  12. Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote,Sila

    2008-01-01

    Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load

  13. Processing Demands Impact 3-Year-Olds' Performance in a Spontaneous-Response Task: New Evidence for the Processing-Load Account of Early False-Belief Understanding.

    Science.gov (United States)

    Scott, Rose M; Roby, Erin

    2015-01-01

    Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children's ability to demonstrate this capacity depends on the processing demands of the task and children's processing skills. When processing demands exceed young children's processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children's performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children's performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character's false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children's performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task involves an elicited

  14. Processing Demands Impact 3-Year-Olds’ Performance in a Spontaneous-Response Task: New Evidence for the Processing-Load Account of Early False-Belief Understanding

    Science.gov (United States)

    Scott, Rose M.; Roby, Erin

    2015-01-01

    Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children’s ability to demonstrate this capacity depends on the processing demands of the task and children’s processing skills. When processing demands exceed young children’s processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children’s performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children’s performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character’s false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children’s performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task

  15. Automated Generation of Traffic Incident Response Plan Based on Case-Based Reasoning and Bayesian Theory

    Directory of Open Access Journals (Sweden)

    Yongfeng Ma

    2014-01-01

    Full Text Available Traffic incident response plan, specifying response agencies and their responsibilities, can guide responders to take actions effectively and timely after traffic incidents. With a reasonable and feasible traffic incident response plan, related agencies will save many losses, such as humans and wealth. In this paper, how to generate traffic incident response plan automatically and specially was solved. Firstly, a well-known and approved method, Case-Based Reasoning (CBR, was introduced. Based on CBR, a detailed case representation and R5-cycle of CBR were developed. To enhance the efficiency of case retrieval, which was an important procedure, Bayesian Theory was introduced. To measure the performance of the proposed method, 23 traffic incidents caused by traffic crashes were selected an