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

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

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...... 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...... to coordinate the electricity demands of industrial loads, in compliance with external Demand Response events....

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.

The business value of demand response for balance responsible parties

OpenAIRE

Jonsson, Mattias

2014-01-01

By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part of the larger concept called smart grids. Previous work in this area has concerned the utilization of demand response by grid owners. In this thesis the focus will instead be shifted towards the electrical companies that have balance responsibility, and how they could use demand response in order to make profits. By investigating electrical applian...

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

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.

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)

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)

Aggregated Demand Modelling Including Distributed Generation, Storage and Demand Response

OpenAIRE

Marzooghi, Hesamoddin; Hill, David J.; Verbic, Gregor

2014-01-01

It is anticipated that penetration of renewable energy sources (RESs) in power systems will increase further in the next decades mainly due to environmental issues. In the long term of several decades, which we refer to in terms of the future grid (FG), balancing between supply and demand will become dependent on demand actions including demand response (DR) and energy storage. So far, FG feasibility studies have not considered these new demand-side developments for modelling future demand. I...

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

Market design for rapid demand response

DEFF Research Database (Denmark)

Nielsen, Kurt; Tamirat, Tseganesh Wubale

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...... 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...... 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...

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...

Two-stage discrete-continuous multi-objective load optimization: An industrial consumer utility approach to demand response

International Nuclear Information System (INIS)

Abdulaal, Ahmed; Moghaddass, Ramin; Asfour, Shihab

2017-01-01

Highlights: •Two-stage model links discrete-optimization to real-time system dynamics operation. •The solutions obtained are non-dominated Pareto optimal solutions. •Computationally efficient GA solver through customized chromosome coding. •Modest to considerable savings are achieved depending on the consumer’s preference. -- Abstract: In the wake of today’s highly dynamic and competitive energy markets, optimal dispatching of energy sources requires effective demand responsiveness. Suppliers have adopted a dynamic pricing strategy in efforts to control the downstream demand. This method however requires consumer awareness, flexibility, and timely responsiveness. While residential activities are more flexible and schedulable, larger commercial consumers remain an obstacle due to the impacts on industrial performance. This paper combines methods from quadratic, stochastic, and evolutionary programming with multi-objective optimization and continuous simulation, to propose a two-stage discrete-continuous multi-objective load optimization (DiCoMoLoOp) autonomous approach for industrial consumer demand response (DR). Stage 1 defines discrete-event load shifting targets. Accordingly, controllable loads are continuously optimized in stage 2 while considering the consumer’s utility. Utility functions, which measure the loads’ time value to the consumer, are derived and weights are assigned through an analytical hierarchy process (AHP). The method is demonstrated for an industrial building model using real data. The proposed method integrates with building energy management system and solves in real-time with autonomous and instantaneous load shifting in the hour-ahead energy price (HAP) market. The simulation shows the occasional existence of multiple load management options on the Pareto frontier. Finally, the computed savings, based on the simulation analysis with real consumption, climate, and price data, ranged from modest to considerable amounts

The integration of Price Responsive Demand into Regional Transmission Organization (RTO) wholesale power markets and system operations

International Nuclear Information System (INIS)

Centolella, Paul

2010-01-01

A number of states and utilities are pursuing demand response based on dynamic and time-differentiated retail prices and utility investments in Advanced Metering Infrastructure (AMI), often as part of Smart Grid initiatives. These developments could produce large amounts of Price Responsive Demand, demand that predictably responds to changes in wholesale prices. Price Responsive Demand could provide significant reliability and economic benefits. However, existing RTO tariffs present potential barriers to the development of Price Responsive Demand. Effectively integrating Price Responsive Demand into RTO markets and operations will require changes in demand forecasting, scarcity pricing reform, synchronization of scarcity pricing with capacity markets, tracking voluntary hedging by price responsive loads, and a non-discriminatory approach in curtailments in capacity emergencies. The article describes changes in RTO policies and systems needed incorporate Price Responsive Demand. (author)

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)

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

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.

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.

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.

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

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

Demand Response and Energy Storage Integration Study

Energy Technology Data Exchange (ETDEWEB)

Ma, Ookie; Cheung, Kerry; Olsen, Daniel J.; Matson, Nance; Sohn, Michael D.; Rose, Cody M.; Dudley, Junqiao Han; Goli, Sasank; Kiliccote, Sila; Cappers, Peter; MacDonald, Jason; Denholm, Paul; Hummon, Marissa; Jorgenson, Jennie; Palchak, David; Starke, Michael; Alkadi, Nasr; Bhatnagar, Dhruv; Currier, Aileen; Hernandez, Jaci; Kirby, Brendan; O' Malley, Mark

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.

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.

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.

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).

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...

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)

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.

Making Demand Response a Reality in Europe: Policy, Regulations, and Deployment Status

OpenAIRE

Lamprinos, Ilias; Hatziargyriou, Nikos D.; Kokos, Isidoros; Dimeas, Aris Dimeas

2016-01-01

Power systems undergo massive operational and technological changes amid increasing demand for environmental sustainability and energy efficiency. The traditional, supplydriven approach, relying on large-scale generation plants, which has dominated old utilities, is reconsidered to incorporate the increased penetration of variable renewable energy sources, distributed generation and storage. Demand Response is an important instrument for improving energy efficiency, since it increases consume...

HOUSEHOLD FOOD DEMAND IN INDONESIA: A TWO-STAGE BUDGETING APPROACH

Directory of Open Access Journals (Sweden)

Agus Widarjono

2016-05-01

Full Text Available A two-stage budgeting approach was applied to analyze the food demand in urban areas separated by geographical areas and classified by income groups. The demographically augmented Quadratic Almost Ideal Demand System (QUAIDS was employed to estimate the demand elasticity. Data from the National Social and Economic Survey of Households (SUSENAS in 2011 were used. The demand system is a censored model because the data contains zero expenditures and is estimated by employing the consistent two-step estimation procedure to solve biased estimation. The results show that price and income elasticities become less elastic from poor households to rich households. Demand by urban households in Java is more responsive to price but less responsive to income than urban households outside of Java. Simulation policies indicate that an increase in food prices would have more adverse impacts than a decrease in income levels. Poor families would suffer more than rich families from rising food prices and/or decreasing incomes. More importantly, urban households on Java are more vulnerable to an economic crisis, and would respond by reducing their food consumption. Economic policies to stabilize food prices are better than income policies, such as the cash transfer, to maintain the well-being of the population in Indonesia

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

Constrained consumption shifting management in the distributed energy resources scheduling considering demand response

International Nuclear Information System (INIS)

Faria, Pedro; Vale, Zita; Baptista, Jose

2015-01-01

Highlights: • Consumption reduction and/or shift to several periods before and after. • Optimization problem for scheduling of demand response and distributed generation. • Minimization of the Virtual Power Player operation (remuneration) costs. • Demand response can be efficient to meet distributed generation shortages. • Consumers benefit with the remuneration of the participation in demand response. - Abstract: Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods

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

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.

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.

Demand-Side Flexibility for Energy Transitions: Ensuring the Competitive Development of Demand Response Options

OpenAIRE

Nursimulu, Anjali; Florin, Marie-Valentine; Vuille, François

2015-01-01

This report provides an overview of the current debates about demand response development, focusing primarily on Europe, with some comparisons to the United States. ‘Demand response’ includes strategies that involve end-use customers adapting or altering their electricity demand in response to grid conditions or market prices. It is viewed as a multi-purpose power-system resource that enhances the energy system’s capacity to cope with increasing demand, rising costs of conventional transmissi...

History of demand side management and classification of demand response control schemes

NARCIS (Netherlands)

Lampropoulos, I.; Kling, W.L.; Ribeiro, P.F.; Berg, van den J.

2013-01-01

The scope of this paper is to provide a review on the topic of demand side management. A historical overview provides a critical insight to applied cases, while the discovery of new evidence calls for reconsideration of the design of demand response control schemes. The developments at the demand

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

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...... this simulation, real power system data from the Danish island of Bornholm is introduced and methods to quantify an aggregated load is developed. These methods can be used for real-time operation and to support investment decisions. More specifically, they can be used to forecast the response to electricity...... pricing and to classify different types of customers. The proposed models are then embedded into new fiveminute electricity markets for system balancing and local congestion management. New market tools for exploiting and maintaining a degree of control over demand are developed, and the value of DR using...

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...

Demand response in a market environment

OpenAIRE

Larsen, Emil Mahler; Pinson, Pierre; Ding, Yi; Østergaard, Jacob

2016-01-01

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 occasion...

A summary of demand response in electricity markets

International Nuclear Information System (INIS)

Albadi, M.H.; El-Saadany, E.F.

2008-01-01

This paper presents a summary of demand response (DR) in deregulated electricity markets. The definition and the classification of DR as well as potential benefits and associated cost components are presented. In addition, the most common indices used for DR measurement and evaluation are highlighted, and some utilities' experiences with different demand response programs are discussed. Finally, the effect of demand response in electricity prices is highlighted using a simulated case study. (author)

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.

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.

Benefits and challenges of electrical demand response: A critical review

DEFF Research Database (Denmark)

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

2014-01-01

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...... for demand response is the lack of experience, and the consequent need to employ extensive assumptions when modelling and evaluating this resource. This paper concludes with an examination of these assumptions, which range from assuming a fixed linear price–demand relationship for price responsive demand...

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

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.

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.

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.

The development of demand elasticity model for demand response in the retail market environment

NARCIS (Netherlands)

Babar, M.; Nguyen, P.H.; Kamphuis, I.G.

2015-01-01

In the context of liberalized energy market, increase in distributed generation, storage and demand response has expanded the price elasticity of demand, thus causing the addition of uncertainty to the supply-demand chain of power system. In order to cope with the challenges of demand uncertainty

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

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

users is exploited in the power system, e.g. for system balancing. However, very few real-world experiments have been carried out and price-based demand response has consistently been found difficult to assess and quantify. It is our aim here to describe an approach to do so, as motivated by the large......Increased emphasis is placed today on various types of demand response, motivated by the integration of renewable energy generation and efficiency improvements in electricity markets. Some advocated for the development of price-based approaches, where the conditional dynamic elasticity of final...

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.

Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

Directory of Open Access Journals (Sweden)

Jeyhun I. Mikayilov

2017-11-01

Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

A meta-analysis of the price elasticity of gasoline demand. A SUR approach

Energy Technology Data Exchange (ETDEWEB)

Brons, Martijn; Rietveld, Piet [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands); Tinbergen Institute Amsterdam (TIA), Roetersstraat 31, 1018 WB Amsterdam (Netherlands); Nijkamp, Peter [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands); Tinbergen Institute Amsterdam (TIA), Roetersstraat 31, 1018 WB Amsterdam (Netherlands); The Netherlands Organisation of Scientific Research (NWO), postbus 93138 - 2509 AC Den Haag (Netherlands); Pels, Eric [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands)

2008-09-15

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. (author)

A meta-analysis of the price elasticity of gasoline demand. A SUR approach

International Nuclear Information System (INIS)

Brons, Martijn; Rietveld, Piet; Nijkamp, Peter; Pels, Eric

2008-01-01

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. (author)

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.

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)

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.

Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception

International Nuclear Information System (INIS)

Bartusch, Cajsa; Wallin, Fredrik; Odlare, Monica; Vassileva, Iana; Wester, Lars

2011-01-01

Increased demand response is essential to fully exploit the Swedish power system, which in turn is an absolute prerequisite for meeting political goals related to energy efficiency and climate change. Demand response programs are, nonetheless, still exceptional in the residential sector of the Swedish electricity market, one contributory factor being lack of knowledge about the extent of the potential gains. In light of these circumstances, this empirical study set out with the intention of estimating the scope of households' response to, and assessing customers' perception of, a demand-based time-of-use electricity distribution tariff. The results show that households as a whole have a fairly high opinion of the demand-based tariff and act on its intrinsic price signals by decreasing peak demand in peak periods and shifting electricity use from peak to off-peak periods. - Highlights: → Households are sympathetic to demand-based tariffs, seeing as they relate to environmental issues. → Households adjust their electricity use to the price signals of demand-based tariffs. → Demand-based tariffs lead to a shift in electricity use from peak to off-peak hours. → Demand-based tariffs lead to a decrease in maximum demand in peak periods. → Magnitude of these effects increases over time.

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.

Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market

OpenAIRE

Heshmati, Almas

2012-01-01

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study demand, consumer baseline (CBL) and demand response in the electricity market. After characterizing the general demand models, it reviews consumer baseline based on which further study the demand response...

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)

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.

Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System

Directory of Open Access Journals (Sweden)

Bo Lin

2017-10-01

Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.

US residential energy demand and energy efficiency: A stochastic demand frontier approach

International Nuclear Information System (INIS)

Filippini, Massimo; Hunt, Lester C.

2012-01-01

This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modeled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.

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.

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.

Which electricity market design to encourage the development of demand response?

OpenAIRE

Vincent Rious, Fabien Roques and Yannick Perez

2012-01-01

Demand response is a cornerstone problem in electricity markets under climate change constraint. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper, focusing on demand response and smart metering for mid-size and small consumers,...

Which electricity market design to encourage the development of demand response?

OpenAIRE

Rious , Vincent; Perez , Yannick; Roques , Fabien

2015-01-01

International audience; Demand response is a cornerstone problem in electricity markets under climate change constraints. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper focusing on demand response and smart metering for mid-­...

Certification prerequisites for activities related to the trading of demand response resources

International Nuclear Information System (INIS)

Alcázar-Ortega, Manuel; Calpe, Carmen; Theisen, Thomas; Rodríguez-García, Javier

2015-01-01

Certification according to international standards brings many benefits to the society, including technical, economic and environmental aspects. In this context, this paper highlights the benefits of certification of Demand Response, including the additional credibility which provides to the trading of flexibility and higher confidence between different players. The consequence is a dynamic environment which facilitates the market acceptance of Demand Response services and products, providing significant benefits to providers and users of such services. A methodology for the systematic certification of different activities related to the transaction of Demand Response resources has been developed and it is presented here. In particular, three types of certificate have been specified, considering the certification of the entity providing the resource (Demand Response Provider), the contractual framework between the provider and the requester (Demand Response Product) and the physical platform to enable and guarantee such transaction (Demand Response Energy Service Trader). The results of this paper may help regulators and standardization bodies in the design and specification of a future norm to allow the certification of the above-mentioned activities, or a further development of existing regulation for certification of energy efficiency systems (like ISO (International Standard Organization) 50001), where certification of Demand Response activities could be complementary. - Highlights: • Inexistence of a standard on Demand Response limits the application of demand flexibility. • Demand flexibility is essential for the cost-effective integration of renewable generation technologies. • Benefits of certification of activities in the trading of Demand Response are highlighted. • Necessary activities for a standard interchange of Demand Response are identified. • The specifications of a new standard for Demand Response certification are given.

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.

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.

A predictive control scheme for automated demand response mechanisms

NARCIS (Netherlands)

Lampropoulos, I.; Bosch, van den P.P.J.; Kling, W.L.

2012-01-01

The development of demand response mechanisms can provide a considerable option for the integration of renewable energy sources and the establishment of efficient generation and delivery of electrical power. The full potential of demand response can be significant, but its exploration still remains

Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

Directory of Open Access Journals (Sweden)

Ntombizodwa J. Matsoma

2017-10-01

Full Text Available Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. Findings: The results revealed that both hierarchical and optimal approaches should be considered in clothing manufacturing. Managerial implications: In order to improve demand planning practices in the clothing industry, managers are recommended to apply hierarchical and optimal demand planning approaches, which might bring about improvements to demand planning in the Gauteng clothing industry. Conclusion: It is recommended that clothing manufacturers consider the types of product offering before making decisions about adopting the hierarchical or optimal demand planning approaches. When planning for basic clothes, manufacturers should consider a hierarchical demand planning approach, whereas the optimal demand planning approach is recommended for fashion clothes.

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...

Aggregated Demand Response Modelling for Future Grid Scenarios

OpenAIRE

Marzooghi, Hesamoddin; Verbic, Gregor; Hill, David J.

2015-01-01

With the increased penetration of intermittent renewable energy sources (RESs) in future grids (FGs), balancing between supply and demand will become more dependent on demand response (DR) and energy storage. Thus, FG feasibility studies will need to consider DR for modelling nett future demand. Against this backdrop, this paper proposes a demand model which integrates the aggregated effect of DR in a simplified representation of the effect of market/dispatch processes aiming at minimising th...

Demand response from the non-domestic sector: Early UK experiences and future opportunities

International Nuclear Information System (INIS)

Grünewald, Philipp; Torriti, Jacopo

2013-01-01

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system. In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment. The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads. - Highlights: • Empirical demand response data from non-domestic sector evaluated. • Load profiles suggest strong sector dependence on availability response at system peak. • Majority of aggregated demand response still stems from stand-by generation, not from demand turn down. • Scope for substantial increase in demand response capacity if response times were extended

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

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. �

Modelling Commodity Demands and Labour Supply with m-Demands

OpenAIRE

Browning, Martin

1999-01-01

In the empirical modelling of demands and labour supply we often lack data on a full set of goods. The usual response is to invoke separability assumptions. Here we present an alternative based on modelling demands as a function of prices and the quantity of a reference good rather than total expenditure. We term such demands m-demands. The advantage of this approach is that we make maximum use of the data to hand without invoking implausible separability assumptions. In the theory section qu...

Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City

International Nuclear Information System (INIS)

Gilbraith, Nathaniel; Powers, Susan E.

2013-01-01

Many urban areas in the United States have experienced difficulty meeting the National Ambient Air Quality Standards (NAAQS), partially due to pollution from electricity generating units. We evaluated the potential for residential demand response to reduce pollutant emissions on days with above average pollutant emissions and a high potential for poor air quality. The study focused on New York City (NYC) due to non-attainment with NAAQS standards, large exposed populations, and the existing goal of reducing pollutant emissions. The baseline demand response scenario simulated a 1.8% average reduction in NYC peak demand on 49 days throughout the summer. Nitrogen oxide and particulate matter less than 2.5 μm in diameter emission reductions were predicted to occur (−70, −1.1 metric tons (MT) annually), although, these were not likely to be sufficient for NYC to meet the NAAQS. Air pollution mediated damages were predicted to decrease by $100,000–$300,000 annually. A sensitivity analysis predicted that substantially larger pollutant emission reductions would occur if electricity demand was shifted from daytime hours to nighttime hours, or the total consumption decreased. Policies which incentivize shifting electricity consumption away from periods of high human and environmental impacts should be implemented, including policies directed toward residential consumers. - Highlights: • The impact of residential demand response on air emissions was modeled. • Residential demand response will decrease pollutant emissions in NYC. • Emissions reductions occur during periods with high potential for poor air quality. • Shifting demand to nighttime hours was more beneficial than to off-peak daytime hours

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)

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...

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.

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.

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.

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

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.

Demand response offered by households with direct electric heating

International Nuclear Information System (INIS)

Kofod, C.; Togeby, M.

2004-01-01

The peak power balance in the Nordic power system is gradually turning to be very tight, especially in the electric area of southern Sweden and eastern Denmark. Power stations are closed and hardly any investments in new production are carried out. Demand response is considered essential when the formation of spot prices shall send the signal of needed investments in new capacity. Demand response which are based on individual preferences, and carried out automatically, can be one way to increase the volume of price elastic demand. Demand response need hourly metering for calculation and documentation of the decrease in demand, and controllability in order to meet the timing requirements. Within the EU SAVE project EFFLOCOM (2002 - 2004), a Danish demand response pilot project was established in 2003 including 25 single family homes with direct electrical heating. The system has been tested during the winter 2003/2004. The tested technologies include hourly metering, communication by GRPS as well as the Internet. GPRS is used for daily remote meter reading and automatic control of the electric heating including individual control of up to five zones. The system is designed for automatic activation when the Nord Pool hourly Elspot prices exceed preset levels. The system can also be used as regulating power. The EFFLOCOM Web Bite includes an interactive demonstrator of the system. The developed customer Web Bite is including the services: 1) Access to setting the limits for the maximum duration of interruption for up to five different control zones for two periods of the day and for three price levels. 2) Access to stop an actual interruption. 3) A report on the hourly, daily, weekly and monthly use of electricity and the saved bonus by demand response control. The report is updated daily. The goals of up to 5 kW controlled per house were fulfilled. Besides the demand response bonus the customers have also saved electricity. A customer survey did show that the

Measuring the financial impact of demand response for electricity retailers

International Nuclear Information System (INIS)

Feuerriegel, Stefan; Neumann, Dirk

2014-01-01

Due to the integration of intermittent resources of power generation such as wind and solar, the amount of supplied electricity will exhibit unprecedented fluctuations. Electricity retailers can partially meet the challenge of matching demand and volatile supply by shifting power demand according to the fluctuating supply side. The necessary technology infrastructure such as Advanced Metering Infrastructures for this so-called Demand Response (DR) has advanced. However, little is known about the economic dimension and further effort is strongly needed to realistically quantify the financial impact. To succeed in this goal, we derive an optimization problem that minimizes procurement costs of an electricity retailer in order to control Demand Response usage. The evaluation with historic data shows that cost volatility can be reduced by 7.74%; peak costs drop by 14.35%; and expenditures of retailers can be significantly decreased by 3.52%. - Highlights: • Ex post simulation to quantify financial impacts of demand response. • Effects of Demand Response are simulated based on real-world data. • Procurement costs of an average electricity retailer decrease by 3.4%. • Retailers can cut hourly peak expenditures by 12.1%. • Cost volatility is reduced by 12.2%

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.

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 inevitable

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 for portf...

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.

Demand Side Management: An approach to peak load smoothing

Science.gov (United States)

Gupta, Prachi

A preliminary national-level analysis was conducted to determine whether Demand Side Management (DSM) programs introduced by electric utilities since 1992 have made any progress towards their stated goal of reducing peak load demand. Estimates implied that DSM has a very small effect on peak load reduction and there is substantial regional and end-user variability. A limited scholarly literature on DSM also provides evidence in support of a positive effect of demand response programs. Yet, none of these studies examine the question of how DSM affects peak load at the micro-level by influencing end-users' response to prices. After nearly three decades of experience with DSM, controversy remains over how effective these programs have been. This dissertation considers regional analyses that explore both demand-side solutions and supply-side interventions. On the demand side, models are estimated to provide in-depth evidence of end-user consumption patterns for each North American Electric Reliability Corporation (NERC) region, helping to identify sectors in regions that have made a substantial contribution to peak load reduction. The empirical evidence supports the initial hypothesis that there is substantial regional and end-user variability of reductions in peak demand. These results are quite robust in rapidly-urbanizing regions, where air conditioning and lighting load is substantially higher, and regions where the summer peak is more pronounced than the winter peak. It is also evident from the regional experiences that active government involvement, as shaped by state regulations in the last few years, has been successful in promoting DSM programs, and perhaps for the same reason we witness an uptick in peak load reductions in the years 2008 and 2009. On the supply side, we estimate the effectiveness of DSM programs by analyzing the growth of capacity margin with the introduction of DSM programs. The results indicate that DSM has been successful in offsetting the

Pupillary Response to Cognitive Demand in Parkinson's Disease: A Pilot Study.

Science.gov (United States)

Kahya, Melike; Moon, Sanghee; Lyons, Kelly E; Pahwa, Rajesh; Akinwuntan, Abiodun E; Devos, Hannes

2018-01-01

Previous studies have shown that pupillary response, a physiological measure of cognitive workload, reflects cognitive demand in healthy younger and older adults. However, the relationship between cognitive workload and cognitive demand in Parkinson's disease (PD) remains unclear. The aim of this pilot study was to examine the pupillary response to cognitive demand in a letter-number sequencing (LNS) task between 16 non-demented individuals with PD (age, median (Q1-Q3): 68 (62-72); 10 males) and 10 control participants (age: 63 (59-67); 2 males), matched for age, education, and Montreal Cognitive Assessment (MOCA) scores. A mixed model analysis was employed to investigate cognitive workload changes as a result of incremental cognitive demand for both groups. As expected, no differences were found in cognitive scores on the LNS between groups. Cognitive workload, exemplified by greater pupil dilation, increased with incremental cognitive demand in both groups ( p = 0.003). No significant between-group ( p = 0.23) or interaction effects were found ( p = 0.45). In addition, individuals who achieved to complete the task at higher letter-number (LN) load responded differently to increased cognitive demand compared with those who completed at lower LN load ( p demand in non-demented people with PD and healthy controls. Further research is needed to investigate the pupillary response to incremental cognitive demand of PD patients with dementia compared to non-demented PD and healthy controls. Highlights -Pupillary response reflects cognitive demand in both non-demented people with PD and healthy controls-Although not significant due to insufficient power, non-demented individuals with PD had increased cognitive workload compared to the healthy controls throughout the testing-Pupillary response may be a valid measure of cognitive demand in non-demented individuals with PD-In future, pupillary response might be used to detect cognitive impairment in individuals with PD.

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

12 CFR 602.23 - Responses to demands served on FCA employees.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Responses to demands served on FCA employees. 602.23 Section 602.23 Banks and Banking FARM CREDIT ADMINISTRATION ADMINISTRATIVE PROVISIONS RELEASING....23 Responses to demands served on FCA employees. (a) An employee served with a demand or a subpoena...

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.

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.

Milton Hydro's Energy Drill Program : demand response based on behavioural responses to price signals

International Nuclear Information System (INIS)

Thorne, D.; Heeney, D.

2006-01-01

The Energy Drill Program is a demand response tool and economic instrument based on a fire drill protocol. The aim of the program is to reduce peak demand and emissions and improve system reliability and price volatility. This presentation provided details of an Energy Drill pilot program, conducted in Milton, Ontario. Customized approaches were used in the buildings partaking in the drill, which included the Milton Hydro Headquarters, the Robert Baldwin Public School, and a leisure centre. Building assessments inventoried building systems and equipment usage patterns. Pilot monitoring and evaluation was conducted through the use of checklists completed by marshals and building coordinators. Energy use data was tracked by Milton Hydro, and report cards were sent after each drill. A short-term drop in demand was observed in all the buildings, as well as overall reductions in peak period demand. Energy consumption data for all the buildings were provided. Results of the pilot program suggested that rotating the drills among participating buildings may prove to be a more effective strategy for the program to adopt in future. A greater emphasis on energy efficiency was also recommended. It was concluded that the eventual roll-out strategy should carefully consider the number and types of buildings involved in the program; internal commitment to the program; available resources; and timing for implementation. refs., tabs., figs

Data-Driven Optimization of Incentive-based Demand Response System with Uncertain Responses of Customers

Directory of Open Access Journals (Sweden)

Jimyung Kang

2017-10-01

Full Text Available Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective.

Smart electric storage heating and potential for residential demand response

OpenAIRE

Darby, S

2017-01-01

Low-carbon transition plans for temperate and sub-polar regions typically involve some electrification of space heating. This poses challenges to electricity system operation and market design, as it increases overall demand and alters the temporal patterns of that demand. One response to the challenge is to ‘smarten’ electrical heating, enabling it to respond to network conditions by storing energy at times of plentiful supply, releasing it in response to customer demands and offering rapid-...

Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider

International Nuclear Information System (INIS)

Bradley, Peter; Coke, Alexia; Leach, Matthew

2016-01-01

Whilst tariff-based approaches to load-shifting are common in the residential sector, incentive-based approaches are rare. This is so, even though providing customers incentives to shape their power consumption patterns has substantial potential. This paper presents findings from an exploratory UK pilot study that trials financial payments and detailed energy feedback to incentivise load-shifting of residential electricity consumption. An intervention study was implemented measuring actual energy use by individual households as well as conducting surveys and interviews. From the trials it was found that the approaches resulted in reductions in peak time energy use. Evidence from the study found that the incentives-based approaches were able to overcome some of the barriers to response experienced in Time-of-Use studies, though less good on others. Interestingly, the height of the barriers varied by the electricity-using practice and the incentivising approach applied. The height of the barriers also varied by participant. The study concludes by identifying that broad participation in demand response is likely to require a suite of incentivising approaches that appeal to different people, a key policy finding of interest to international agencies, government, public and private sector entities. - Highlights: • Novel study of financial incentive approaches for shifting residential energy. • First academic paper comprehensively identifying barriers to time of use tariffs. • First study reporting barriers to financial incentive approaches for demand response. • Incentive study design can be applied by government and energy companies.

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.

Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network

Directory of Open Access Journals (Sweden)

Yi Yu

2018-02-01

Full Text Available The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.

Power systems balancing with high penetration renewables: The potential of demand response in Hawaii

International Nuclear Information System (INIS)

Critz, D. Karl; Busche, Sarah; Connors, Stephen

2013-01-01

Highlights: • Demand response for Oahu results in system cost savings. • Demand response improves thermal power plant operations. • Increased use of wind generation possible with demand response. • WILMAR model used to simulate various levels and prices of demand response. - Abstract: The State of Hawaii’s Clean Energy policies call for 40% of the state’s electricity to be supplied by renewable sources by 2030. A recent study focusing on the island of Oahu showed that meeting large amounts of the island’s electricity needs with wind and solar introduced significant operational challenges, especially when renewable generation varies from forecasts. This paper focuses on the potential of demand response in balancing supply and demand on an hourly basis. Using the WILMAR model, various levels and prices of demand response were simulated. Results indicate that demand response has the potential to smooth overall power system operation, with production cost savings arising from both improved thermal power plant operations and increased wind production. Demand response program design and cost structure is then discussed drawing from industry experience in direct load control programs

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 �

Modeling workforce demand in North Dakota: a System Dynamics approach

OpenAIRE

Muminova, Adiba

2015-01-01

This study investigates the dynamics behind the workforce demand and attempts to predict the potential effects of future changes in oil prices on workforce demand in North Dakota. The study attempts to join System Dynamics and Input-Output models in order to overcome shortcomings in both of the approaches and gain a more complete understanding of the issue of workforce demand. A system dynamics simulation of workforce demand within different economic sector...

Predictive Control of a Domestic Freezer for Real-Time Demand Response Applications

NARCIS (Netherlands)

Baghina, N.G.; Lampropoulos, I.; Asare-Bediako, B.; Kling, W.L.; Ribeiro, P.F.

2012-01-01

Demand side management and demand response aim to maximize the efficiency of the electricity delivery process by exploiting the flexibility of customers. At residential level, demand response can be applied only to a limited number of appliances, through load management, due to user intervention or

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Directory of Open Access Journals (Sweden)

Pedro Faria

2015-06-01

Full Text Available Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

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

Science.gov (United States)

2010-09-03

... FEDERAL ENERGY REGULATORY COMMISSION 18 CFR Part 35 [Docket No. RM10-17-000] Demand Response... for determining when to compensate demand response providers and the allocation of costs associated with demand response. DATES: The technical conference will be held at the Federal Energy Regulatory...

Demand Response at the Naval Postgraduate School

National Research Council Canada - National Science Library

Stouffer, Dean; Wilson, Daryl

2008-01-01

The purpose of this MBA project is to assist the Naval Postgraduate School's Public Works department to assimilate into a Demand Response program that will not only benefit the school but also the community...

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

the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system......In this paper, application of demand response to accommodate maximum PV power in a low-voltage distribution network is discussed. A centralized control based on model predictive control method is proposed for the computation of optimal demand response on an hourly basis. The proposed method uses PV...

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

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.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

OpenAIRE

Faria, Pedro; Vale, Zita; Baptista, José

2015-01-01

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the prese...

Willingness to pay and price elasticities of demand for energy-efficient appliances: Combining the hedonic approach and demand systems

Energy Technology Data Exchange (ETDEWEB)

Galarraga, Ibon, E-mail: ibon.galarraga@bc3research.org; Gonzalez-Eguino, Mikel, E-mail: mikel.gonzalez@bc3research.org; Markandya, Anil, E-mail: anil.markandya@bc3research.org

2011-12-15

This article proposes a combined approach for estimating willingness to pay for the attributes represented by energy efficiency labels and providing reliable price elasticities of demand (own and cross) for close substitutes (e.g. those with low energy efficiency and those with higher energy efficiency). This is done by using the results of the hedonic approach together with the Quantity Based Demand System (QBDS) model. The elasticity results obtained with the latter are then compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). The methodology is applied to the dishwasher market in Spain: it is found that 15.6% of the final price is actually paid for the energy efficiency attribute. This accounts for about Euro 80 of the average market price. The elasticity results confirm that energy efficient appliances are more price elastic than regular ones. - Highlights: > The article shows a combined approach for estimating willingness to pay for energy efficiency labels and price elasticities. > The results of the hedonic approach is used together with the Quantity Based Demand System (QBDS) model. > The elasticity results are compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). > The methodology is applied to the dishwasher market in Spain.

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

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)

Pupillary Response to Cognitive Demand in Parkinson’s Disease: A Pilot Study

Directory of Open Access Journals (Sweden)

Melike Kahya

2018-04-01

Full Text Available Previous studies have shown that pupillary response, a physiological measure of cognitive workload, reflects cognitive demand in healthy younger and older adults. However, the relationship between cognitive workload and cognitive demand in Parkinson’s disease (PD remains unclear. The aim of this pilot study was to examine the pupillary response to cognitive demand in a letter-number sequencing (LNS task between 16 non-demented individuals with PD (age, median (Q1–Q3: 68 (62–72; 10 males and 10 control participants (age: 63 (59–67; 2 males, matched for age, education, and Montreal Cognitive Assessment (MOCA scores. A mixed model analysis was employed to investigate cognitive workload changes as a result of incremental cognitive demand for both groups. As expected, no differences were found in cognitive scores on the LNS between groups. Cognitive workload, exemplified by greater pupil dilation, increased with incremental cognitive demand in both groups (p = 0.003. No significant between-group (p = 0.23 or interaction effects were found (p = 0.45. In addition, individuals who achieved to complete the task at higher letter-number (LN load responded differently to increased cognitive demand compared with those who completed at lower LN load (p < 0.001, regardless of disease status. Overall, the findings indicated that pupillary response reflects incremental cognitive demand in non-demented people with PD and healthy controls. Further research is needed to investigate the pupillary response to incremental cognitive demand of PD patients with dementia compared to non-demented PD and healthy controls.Highlights-Pupillary response reflects cognitive demand in both non-demented people with PD and healthy controls-Although not significant due to insufficient power, non-demented individuals with PD had increased cognitive workload compared to the healthy controls throughout the testing-Pupillary response may be a valid measure of cognitive demand in

Electric Water Heater Modeling and Control Strategies for Demand Response

Energy Technology Data Exchange (ETDEWEB)

Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

2012-07-22

Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

Demand response policies for the implementation of smart grids

NARCIS (Netherlands)

Koliou, E.

2016-01-01

With the grasp of a smart grid in sight, discussions have shifted the focus of system security measures away from generation capacity; apart from modifying the supply side, demand may also be exploited to keep the system in balance. Specifically, Demand Response (DR) is the concept of consumer load

The causes of international labor migrations--a demand-determined approach.

Science.gov (United States)

Straubhaar, T

1986-01-01

The author first studies the reasons why people migrate using a neoclassical approach concerning income differentials. He tests this approach empirically and demonstrates its limits. A demand-determination approach based on human capital theory is then outlined to overcome these limits and to take into account restrictive immigration controls. Migration from Italy, Spain, Greece, Portugal, and Turkey to the European Community destination countries is examined. It is concluded that "the demand for immigrants in the destination country is the decisive condition for the phenomenon of international labor migration, and the supply of migration-willing workers is only a necessary condition." excerpt

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.

Aggregate modeling of fast-acting demand response and control under real-time pricing

International Nuclear Information System (INIS)

Chassin, David P.; Rondeau, Daniel

2016-01-01

Highlights: • Demand elasticity for fast-acting demand response load under real-time pricing. • Validated first-principles logistic demand curve matches random utility model. • Logistic demand curve suitable for diversified aggregate loads market-based transactive control systems. - Abstract: This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

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...... and the PVs, considering electric vehicles (EVs) as potential demand response resource, is proposed in this study to alleviate the overvoltages. A two-stage control is designed to comprehend the proposed coordinated control such that a centralized stage periodically determines optimum operating set......-points for PVs/EVs and a decentralized stage adaptively control the PVs/EVs in real-time. To demonstrate effectiveness of the proposed approach, simulations are performed in a typical 0.4 kV/400 kVA Danish distribution network containing 45 detached residential consumers. The presented method demonstrates better...

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...

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.

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.

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

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.

Simulating residential demand response: Improving socio-technical assumptions in activity-based models of energy demand

OpenAIRE

McKenna, E.; Higginson, S.; Grunewald, P.; Darby, S. J.

2017-01-01

Demand response is receiving increasing interest as a new form of flexibility within low-carbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, ...

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.

A consolidated solution of a demand dispatch problem for different demand response schemes

NARCIS (Netherlands)

Babar, M.; Nguyen, P.H.; Cuk, V.; Kamphuis, I.G.

2014-01-01

Advance infrastructures have changed the passive consumers into active because now they can share information, perform automatic control as well as directly influence the electricity market via demand response (DR) programs. Till today, many DR Programs are proposed in Smart Grid (SG) paradigm and

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.

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

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.

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…

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

Distributed generation, storage, demand response and energy efficiency as alternatives to grid capacity enhancement

International Nuclear Information System (INIS)

Poudineh, Rahmatallah; Jamasb, Tooraj

2014-01-01

The need for investment in capital intensive electricity networks is on the rise in many countries. A major advantage of distributed resources is their potential for deferring investments in distribution network capacity. However, utilizing the full benefits of these resources requires addressing several technical, economic and regulatory challenges. A significant barrier pertains to the lack of an efficient market mechanism that enables this concept and also is consistent with business model of distribution companies under an unbundled power sector paradigm. This paper proposes a market-oriented approach termed as “contract for deferral scheme” (CDS). The scheme outlines how an economically efficient portfolio of distributed generation, storage, demand response and energy efficiency can be integrated as network resources to reduce the need for grid capacity and defer demand driven network investments. - Highlights: • The paper explores a practical framework for smart electricity distribution grids. • The aim is to defer large capital investments in the network by utilizing and incentivising distributed generation, demand response, energy efficiency and storage as network resources. • The paper discusses a possible new market model that enables integration of distributed resources as alternative to grid capacity enhancement

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.

A Hybrid Approach on Tourism Demand Forecasting

Science.gov (United States)

Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

2018-04-01

Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

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.

What is demand response? Contributing to secure security-of-supply at the electricity markets

International Nuclear Information System (INIS)

Grenaa Jensen, Stine; Skytte, Klaus; Togeby, Mikael

2004-01-01

There is a common understanding that demand response can reduce the total costs of electricity reliability. There has especially been a growing interest in the electricity market where high spot prices in peak periods and blackouts have recently been seen. It is not easy from the existing literature to find a common definition of demands response. Often the term demand response is used broadly without looking at the time dimension. However, it does not make sense to talk about demand response without talking about when, for how long the energy is used or saved, and at which costs. This paper surveys these subjects and set up a systematic grouping of the different characteristics of demand response. It especially looks at the time dimension. (au)

Market Design for Rapid Demand Response - The Case of Kenya

OpenAIRE

Kurt Nielsen; Tseganesh Wubale Tamirat

2014-01-01

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 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...

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.

Design and Implementation of Demand Response Information Interactive Service Platform Based on “Internet Plus” Smart Energy

Science.gov (United States)

Cui, Gaoying; Fan, Jie; Qin, Yuchen; Wang, Dong; Chen, Guangyan

2017-05-01

In order to promote the effective use of demand response load side resources, promote the interaction between supply and demand, enhance the level of customer service and achieve the overall utilization of energy, this paper briefly explain the background significance of design demand response information platform and current situation of domestic and foreign development; Analyse the new demand of electricity demand response combined with the application of Internet and big data technology; Design demand response information platform architecture, construct demand responsive system, analyse process of demand response strategy formulate and intelligent execution implement; study application which combined with the big data, Internet and demand response technology; Finally, from information interaction architecture, control architecture and function design perspective design implementation of demand response information platform, illustrate the feasibility of the proposed platform design scheme implemented in a certain extent.

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

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.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

Science.gov (United States)

Kanta, L.; Berglund, E. Z.; Soh, M. H.

2017-12-01

Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden

Extending the bidding format to promote demand response

International Nuclear Information System (INIS)

Liu, Yanchao; Holzer, Jesse T.; Ferris, Michael C.

2015-01-01

We propose an extended bidding structure to allow more realistic demand characteristics and behaviors to be expressed via flexible bids. In today's ISO-run energy markets, demand bid formats are all separable over time. However, a significant and growing segment of demand can be shifted across time and therefore has no way to bid its true valuation of consumption. We propose additional bid types that allow deferrable, adjustable and storage-type loads to better express their value, and thus elicit demand response in the most natural way – via direct participation in the market. We show that the additional bid types are easily incorporated into the existing market with no technological barrier and that they preserve the market's efficiency and incentive-compatibility properties. Using real market data, we give a numerical demonstration that the extended bid format could substantially increase social welfare, and also present additional insight on storage expansion scenarios. - Highlights: • Three new bid types are proposed to enrich demand-side participation. • Time value of electricity demand can be clearly conveyed to central dispatcher. • The extended format preserves market efficiency and incentive compatibility. • Energy storage is most effective to neutralize price volatility, with a limitation.

Demand response driven load pattern elasticity analysis for smart households

NARCIS (Netherlands)

Paterakis, N.G.; Catalao, J.P.S.; Tascikaraoglu, A.; Bakirtzis, A.G.; Erdinc, O.

2015-01-01

The recent interest in smart grid vision enables several smart applications in different parts of the power grid structure, where specific importance should be given to the demand side. As a result, changes in load patterns due to demand response (DR) activities at end-user premises, such as smart

A bottom-up approach of stochastic demand allocation in water quality modelling

NARCIS (Netherlands)

Blokker, E.J.M.; Vreeburg, J.H.G.; Beverloo, H.; Klein Arfman, M.; Van Dijk, J.C.

2010-01-01

An “all pipes” hydraulic model of a drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor

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

Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach

International Nuclear Information System (INIS)

Adom, Philip Kofi; Bekoe, William; Akoena, Sesi Kutri Komla

2012-01-01

In spite of the varying supply boosting efforts made by various governments to deal with the existing demand–supply gap in the electricity sector, the incessant growth in aggregate domestic electricity demand has made these efforts futile. As an objective, this paper attempts to identify the factors responsible for the historical growth trends in aggregate domestic electricity demand quantifying their effects both in the short-run and long-run periods using the ARDL Bounds cointegration approach and the sample period 1975 to 2005. In the long-run, real per capita GDP, industry efficiency, structural changes in the economy, and degree of urbanisation are identified as the main driving force behind the historical growth trend in aggregate domestic electricity demand. However, in the short-run, real per capita GDP, industry efficiency, and degree of urbanisation are the main drivers of aggregate domestic electricity demand. Industry efficiency is the only factor that drives aggregate domestic electricity demand downwards. However, the negative efficiency effect is insufficient to have outweighed the positive income, output, and demographic effects, hence the continual growth in aggregate domestic electricity demand. As a policy option, we recommend that appropriate electricity efficiency standards be implemented at the industry level. - Highlights: ► Real per capita GDP is the primary determinant of electricity demand both in the short and long-run. ► Industrial efficiency, structural changes and urbanisation rate play secondary role. ► The positive income, output, and demographic effects outweigh the negative efficiency effects.

Quantifying Spatial Variation in Ecosystem Services Demand : A Global Mapping Approach

NARCIS (Netherlands)

Wolff, S.; Schulp, C. J E; Kastner, T.; Verburg, P. H.

2017-01-01

Understanding the spatial-temporal variability in ecosystem services (ES) demand can help anticipate externalities of land use change. This study presents new operational approaches to quantify and map demand for three non-commodity ES on a global scale: animal pollination, wild medicinal plants and

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

A Dynamic Market Mechanism for Markets with Shiftable Demand Response

DEFF Research Database (Denmark)

Hansen, Jacob; Knudsen, Jesper Viese; Kiani, Arman

2014-01-01

renewables, this mechanism accommodates both consumers with a shiftable Demand Response and an adjustable Demand Response. The overall market mechanism is evaluated in a Day Ahead Market and is shown in a numerical example to result in a reduction of the cost of electricity for the consumer, as well......In this paper, we propose a dynamic market mechanism that converges to the desired market equilibrium. Both locational marginal prices and the schedules for generation and consumption are determined through a negotiation process between the key market players. In addition to incorporating...

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.

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

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

Smart Grid as advanced technology enabler of demand response

Energy Technology Data Exchange (ETDEWEB)

Gellings, C.W.; Samotyj, M. [Electric Power Research Institute (EPRI), Palo Alto, CA (United States)

2013-11-15

Numerous papers and articles presented worldwide at different conferences and meetings have already covered the goals, objectives, architecture, and business plans of Smart Grid. The number of electric utilities worldwide has followed up with demonstration and deployment efforts. Our initial assumptions and expectations of Smart Grid functionality have been confirmed. We have indicated that Smart Grid will fulfill the following goals: enhance customer service, improve operational efficiency, enhance demand response and load control, transform customer energy use behavior, and support new utility business models. For the purpose of this paper, we shall focus on which of those above-mentioned Smart Grid functionalities are going to facilitate the ever-growing need for enhanced demand response and load control.

Demand forecasting for automotive sector in Malaysia by system dynamics approach

International Nuclear Information System (INIS)

Zulkepli, Jafri; Abidin, Norhaslinda Zainal; Fong, Chan Hwa

2015-01-01

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars

Demand forecasting for automotive sector in Malaysia by system dynamics approach

Energy Technology Data Exchange (ETDEWEB)

Zulkepli, Jafri, E-mail: zhjafri@uum.edu.my; Abidin, Norhaslinda Zainal, E-mail: nhaslinda@uum.edu.my [School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah (Malaysia); Fong, Chan Hwa, E-mail: hfchan7623@yahoo.com [SWM Environment Sdn. Bhd.Level 17, Menara LGB, Taman Tun Dr. Ismail Kuala Lumpur (Malaysia)

2015-12-11

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

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.

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

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...

Cost function approach for estimating derived demand for composite wood products

Science.gov (United States)

T. C. Marcin

1991-01-01

A cost function approach was examined for using the concept of duality between production and input factor demands. A translog cost function was used to represent residential construction costs and derived conditional factor demand equations. Alternative models were derived from the translog cost function by imposing parameter restrictions.

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.

OECD (Organization of Economic Cooperation and Development) oil demand

International Nuclear Information System (INIS)

Huntington, H.G.

1993-01-01

Econometric response surfaces for nine different world oil models are estimated for aggregate oil demand with in the developed countries of the Organization of Economic Cooperation and Development (OECD). The estimates are based upon scenario results reported for the 1989-2010 period in a recent model comparison study. The response surface approach provides a parsimonious summary of model responses. It enables one to estimate long-run price elasticities directly rather than to infer such responses from 20-year cross-scenario results. It also shows more directly the significant effect of initial demand conditions (in 1988) on future oil demand growth. Due to the dynamic nature of the oil demand response, past prices exert a strongly positive effect on future oil demands in some models, but little or even negative effect in other models. On the basis of this finding, we urge demand modellers to be much more explicit about what their systems reveal about the extent of disequilibrium embedded in their model's starting oil demand conditions. (author)

Beyond the internal dynamics of organizational responses to conflicting institutional demands

Directory of Open Access Journals (Sweden)

Viviana Gutiérrez‐Rincón

2014-10-01

Full Text Available This paper presents some reflections on strategic response models, in particular the models proposed by Pache, Santos and Oliver, and it evaluates their complementarity and differences, especially regarding the interactions between decision making and the possible strategic responses to institutional demands. It is argued that the theoretical contributions of Pache and Santos can be categorized under the dimension of utility, because they can enhance the potential to operationalize and test the model. However, the reflections made in this paper not only highlight the need to take into account other external and internal factors for the study of strategic responses, but also the integration of different linkages of the decision process with strategic responses to institutional demands.

A New Approach to Site Demand-Based Level Inventory Optimization

Science.gov (United States)

2016-06-01

Note: If probability distributions are estimated based on mean and variance , use ˆ qix  and 2ˆ( )qi to generate these. q in , number of...TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION by Tacettin Ersoz June 2016 Thesis Advisor: Javier Salmeron Second Reader: Emily...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE A NEW APPROACH TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION 5. FUNDING NUMBERS 6

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.

Teaching Aggregate Demand and Supply Models

Science.gov (United States)

Wells, Graeme

2010-01-01

The author analyzes the inflation-targeting model that underlies recent textbook expositions of the aggregate demand-aggregate supply approach used in introductory courses in macroeconomics. He shows how numerical simulations of a model with inflation inertia can be used as a tool to help students understand adjustments in response to demand and…

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.

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.

A cost-emission model for fuel cell/PV/battery hybrid energy system in the presence of demand response program: ε-constraint method and fuzzy satisfying approach

International Nuclear Information System (INIS)

Nojavan, Sayyad; Majidi, Majid; Najafi-Ghalelou, Afshin; Ghahramani, Mehrdad; Zare, Kazem

2017-01-01

Highlights: • Cost-emission performance of PV/battery/fuel cell hybrid energy system is studied. • Multi-objective optimization model for cost-emission performance is proposed. • ε-constraint method is proposed to produce Pareto solutions of multi-objective model. • Fuzzy satisfying approach selected the best optimal solution from Pareto solutions. • Demand response program is proposed to reduce both cost and emission. - Abstract: Optimal operation of hybrid energy systems is a big challenge in power systems. Nowadays, in addition to the optimum performance of energy systems, their pollution issue has been a hot topic between researchers. In this paper, a multi-objective model is proposed for economic and environmental operation of a battery/fuel cell/photovoltaic (PV) hybrid energy system in the presence of demand response program (DRP). In the proposed paper, the first objective function is minimization of total cost of hybrid energy system. The second objective function is minimization of total CO_2 emission which is in conflict with the first objective function. So, a multi-objective optimization model is presented to model the hybrid system’s optimal and environmental performance problem with considering DRP. The proposed multi-objective model is solved by ε-constraint method and then fuzzy satisfying technique is employed to select the best possible solution. Also, positive effects of DRP on the economic and environmental performance of hybrid system are analyzed. A mixed-integer linear program is used to simulate the proposed model and the obtained results are compared with weighted sum approach to show the effectiveness of proposed method.

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

Teaching Price, Income, and Cross Elasticity of Demand: Another Approach.

Science.gov (United States)

Zahka, William J.

One of the most important, yet difficult concepts to teach in an undergraduate course in intermediate microeconomics is the all-embracing concept of elasticity of demand. This paper details a four part teaching approach developed to make this most important aspect of microeconomic theory more understandable. Part 1 develops the approach for…

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.

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

Science.gov (United States)

2013-04-12

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL13-57-000] Demand Response... Demand Response Coalition \\1\\ (Complainant) filed a formal complaint against the PJM Interconnection, L.L... Plan Enhancements'') violate section 205 of the FPA and are therefore unenforceable. \\1\\ The Demand...

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

Domestic and outbound tourism demand in Australia: a System-of-Equations Approach

OpenAIRE

George Athanasopoulos; Minfeng Deng; Gang Li; Haiyan Song

2013-01-01

This study uses a system-of-equations approach to model the substitution relationship between Australian domestic and outbound tourism demand. A new price variable based on relative ratios of purchasing power parity index is developed for the substitution analysis. Short-run demand elasticities are calculated based on the estimated dynamic almost ideal demand system. The empirical results reveal significant substitution relationships between Australian domestic tourism and outbound travel to ...

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.)

Managing electrical demand through difficult periods: California's experience with demand response

International Nuclear Information System (INIS)

Wikler, G.; Ghosh, D.Ph.D.

2010-01-01

This paper provides a brief overview of California's electricity situation and the relevance of Demand Response (DR) in addressing some of the challenges faced by the State's electricity system. It then discusses California's experience with DR, market rules that influence what role DR plays and attempts to integrate wholesale-retail level program offerings in the State, and some of the key drivers that are likely to enhance the role of DR. Lastly, the paper identifies some of the key challenges facing implementers of DR programs and discusses how many of those challenges could potentially be overcome. (authors)

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.

PETRA - an Activity-based Approach to Travel Demand Analysis

DEFF Research Database (Denmark)

Fosgerau, Mogens

2001-01-01

This paper concerns the PETRA model developed by COWI in a project funded by the Danish Ministry of Transport, the Danish Transport Council and the Danish Energy Research Program. The model provides an alternative approach to activity based travel demand analysis that excludes the time dimension...

The value of online information for demand response in Walrasian electricity markets

NARCIS (Netherlands)

F.N. Claessen (Felix); B.J. Liefers (Bart); M. Kaisers (Michael); J.A. La Poutré (Han)

2015-01-01

textabstractSmart energy systems integrate renewables and demand response. Most European electricity markets coordinate the resulting time-varying flexibility in demand and supply by organising day-ahead trade with Walrasian mechanisms, using simultaneous call auctions and sealed bids. These

Responsive demand to mitigate slow recovery voltage sags

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; da Silva, Luiz Carlos Pereira; Xu, Zhao

2012-01-01

, and reactive power reserve for peak load management through price responsive methods and also as energy providers through embedded generation technologies. This article introduces a new technology, called demand as voltagecontrolled reserve, which can help mitigation of momentary voltage sags. The technology...... faults. This article presents detailed models, discussion, and simulation tests to demonstrate the technical viability and effectiveness of the demand as voltage-controlled reserve technology for mitigating voltage sags....... can be provided by thermostatically controlled loads as well as other types of load. This technology has proven to be effective in distribution systems with a large composition of induction motors, when voltage sags present slow recovery characteristics because of the deceleration of the motors during...

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.

Autonomic Nervous System Responses to Hearing-Related Demand and Evaluative Threat.

Science.gov (United States)

Mackersie, Carol L; Kearney, Lucia

2017-10-12

This paper consists of 2 parts. The purpose of Part 1 was to review the potential influence of internal (person-related) factors on listening effort. The purpose of Part 2 was to present, in support of Part 1, preliminary data illustrating the interactive effects of an external factor (task demand) and an internal factor (evaluative threat) on autonomic nervous system measures. For Part 1, we provided a brief narrative review of motivation and stress as modulators of listening effort. For Part 2, we described preliminary data from a study using a repeated-measures (2 × 2) design involving manipulations of task demand (high, low) and evaluative threat (high, low). The low-demand task consisted of repetition of sentences from a narrative. The high-demand task consisted of answering questions about the narrative, requiring both comprehension and recall. During the high evaluative threat condition, participants were filmed and told that their video recordings would be evaluated by a panel of experts. During the low evaluative threat condition, no filming occurred; participants were instructed to "do your best." Skin conductance (sympathetic nervous system activity) and heart rate variability (HRV, parasympathetic activity) were measured during the listening tasks. The HRV measure was the root mean square of successive differences of adjacent interbeat intervals. Twelve adults with hearing loss participated. Skin conductance increased and HRV decreased relative to baseline (no task) for all listening conditions. Skin conductance increased significantly with an increase in evaluative threat, but only for the more demanding task. There was no significant change in HRV in response to increasing evaluative threat or task demand. Listening effort may be influenced by factors other than task difficulty, as reviewed in Part 1. This idea is supported by the preliminary data indicating that the sympathetic nervous system response to task demand is modulated by social evaluative

A Column Generation Approach to the Capacitated Vehicle Routing Problem with Stochastic Demands

DEFF Research Database (Denmark)

Christiansen, Christian Holk; Lysgaard, Jens

. The CVRPSD can be formulated as a Set Partitioning Problem. We show that, under the above assumptions on demands, the associated column generation subproblem can be solved using a dynamic programming scheme which is similar to that used in the case of deterministic demands. To evaluate the potential of our......In this article we introduce a new exact solution approach to the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD). In particular, we consider the case where all customer demands are distributed independently and where each customer's demand follows a Poisson distribution...

Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids

OpenAIRE

Rassaei, Farshad; Soh, Wee-Seng; Chua, Kee-Chaing

2015-01-01

Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be utilized to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer or an aggregator. In this paper, we propose a demand response (DR) technique to manage vehicle-to-grid (V2G) enabled PEVs' e...

Demand response in Germany: Technical potential, benefits and regulatory challenges

OpenAIRE

Stede, Jan

2016-01-01

An increased flexibility of the electricity demand side through demand response (DR) is an opportunity to support the integration of renewable energies. By optimising the use of the generation, transmission and distribution infrastructure, DR reduces the need for costly investments and contributes to system security. There is a significant technical DR potential for load reduction from industrial production processes in Germany, as well as from cross-cutting technologies in industry and the t...

Quantifying the Flexibility of Residential Electricity Demand in 2050: a Bottom-Up Approach

OpenAIRE

van Stiphout, Arne; Engels, Jonas; Guldentops, Dries; Deconinck, Geert

2015-01-01

This work presents a new method to quantify the flexibility of automatic demand response applied to residential electricity demand using price elasticities. A stochastic bottom-up model of flexible electricity demand in 2050 is presented. Three types of flexible devices are implemented: electrical heating, electric vehicles and wet appliances. Each house schedules its flexible demand w.r.t. a varying price signal, in order to minimize electricity cost. Own- and cross-price elasticities are ob...

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

International Nuclear Information System (INIS)

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

2010-01-01

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority. (author)

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

Demand for food products in Finland: A demand system approach

Directory of Open Access Journals (Sweden)

Ilkka P. Laurila

1994-07-01

, the estimated models did not satisfy the Slutsky conditions. The goodness-of-fit measures were good, and, compared to static specifications, dynamics usually provided a better fit. The misspecification tests indicated that the dynamic specification was correct, but some form of misspecification was found. The structural change in parameters indicated that the modelling failed to track a stable preference structure - if there is one. The estimated demand system was employed in projecting the future consumption of food products in Finland to the year 2000. The approach was to choose a certain change in the real total consumption expenditure and alternative sets of relative prices for the forecast period. Four different options of price variables were defined. Three of the options relied on the historical price trends recorded in Finland, whereas one option measured the expected consequences of Finland's possible membership in the European Union. A predicted consequence of the membership in the European Union is that the share of food in consumers’ budget would decrease. The expected decrease is somewhat faster than the decrease that would take place if future price developments were based on the historical trends. If Finland joins the Union, the budget share of Food-at-Home would decrease from 21% in 1991 to 18% in 2000, whereas the budget share of Food-at-Home excluding Alcoholic Drinks would decrease from 16% in 1991 to 14% in 2000.

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

Consumer choice theory is a branch of microeconomics. This theory relates to adjusting consumption expenditures and consumer demand curve. Consumer choice science is trying to realize the buyer's decision-making process. This science studies customer characteristics, such as behavioral criteria......, to understand the consumer’s need. The concept of price elasticity of demand (PED) has also been derived from this theory. In fact, the PED is the percentage of changes in the amount of demand relative to the price changes. In consumer choice theory, for each consumer according to behavioral criteria, a unique...... 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...

Demand-side management and European environmental and energy goals: An optimal complementary approach

International Nuclear Information System (INIS)

Bergaentzlé, Claire; Clastres, Cédric; Khalfallah, Haikel

2014-01-01

Demand side management (DSM) in electricity markets could improve energy efficiency and achieve environmental targets through controlled consumption. For the past 10 years or so DSM programmes have registered significant results. However, detailed analysis of its real impact as observed by a large number of pilot studies suggests that such programmes need to be fine-tuned to suit clearly identified conditions. This study aims to provide recommendations for the instruments to be used to prompt demand response with a view to maximizing energy and environmental efficiencies of various countries. The present study suggests that different DSM models should be deployed depending on the specific generation mix in any given country. Beside the natural benefits from cross-borders infrastructures, DSM improves the flexibility and reliability of the energy system, absorbing some shock on generation mix. We show efficiency increases with demand response but at a decreasing rate. So, according to rebound and report effects, simple DSM tools could be preferred. - Highlights: • Demand side management could improve energy and environmental efficiency. • Several instruments should be used to achieve significant load-shedding. • DSM models should be deployed depending on generation mix. • Efficiency increases with demand response but at a decreasing rate. • Rebound and report effects reduce positive impacts

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.

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...

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.

Report of the advisory group on demand-side management and demand response in Ontario in response to the Minister's directive to the Ontario Energy Board

International Nuclear Information System (INIS)

2003-01-01

The Ontario Energy Board was directed in June 2003 to consult with stakeholders to identify and review 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 (distributors) in such activities. A total of 118 stakeholders participated in the consultation process, and 31 representatives from all sectors were then invited to take part in an advisory working group to develop options to be considered by the Board when preparing the recommendations to the Minister. This report presents a consolidation of the Group's working documents and the results of deliberations both as a unit and in small groups. The best way to present the many newly developed models was as a single Central Agency model demonstrating variations in the role of the Central Agency and other players in the electricity market. The paper was divided into the following six sections: introduction; market issues; demand response framework option; central agency framework-alternative models; Ontario Energy Board-wires companies DSM framework; and, general issues

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

Directory of Open Access Journals (Sweden)

Karin Kandananond

2011-08-01

Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications

International Nuclear Information System (INIS)

Feuerriegel, Stefan; Neumann, Dirk

2016-01-01

Demand Response allows for the management of demand side resources in real-time; i.e. shifting electricity demand according to fluctuating supply. When integrated into electricity markets, Demand Response can be used for load shifting and as a replacement for both control reserve and balancing energy. These three usage scenarios are compared based on historic German data from 2011 to determine that load shifting provides the highest benefit: its annual financial savings accumulate to €3.110 M for both households and the service sector. This equals to relative savings of 2.83% compared to a scenario without load shifting. To improve Demand Response integration, the proposed model suggests policy implications: reducing bid sizes, delivery periods and the time-lag between market transactions and delivery dates in electricity markets. - Highlights: •Comparison of 3 scenarios to integrate Demand Response into electricity markets. •These are: optimize procurement, offer as control reserve, avoid balancing energy. •Ex post simulation to quantify financial impact and policy implications. •Highest savings from load shifting with a cost reduction of 3%. •Model suggests reducing bid sizes, delivery periods and time lags as policy issues.

Ethanol demand in Brazil: Regional approach

International Nuclear Information System (INIS)

Freitas, Luciano Charlita de; Kaneko, Shinji

2011-01-01

Successive studies attempting to clarify national aspects of ethanol demand have assisted policy makers and producers in defining strategies, but little information is available on the dynamic of regional ethanol markets. This study aims to analyze the characteristics of ethanol demand at the regional level taking into account the peculiarities of the developed center-south and the developing north-northeast regions. Regional ethanol demand is evaluated based on a set of market variables that include ethanol price, consumer's income, vehicle stock and prices of substitute fuels; i.e., gasoline and natural gas. A panel cointegration analysis with monthly observations from January 2003 to April 2010 is employed to estimate the long-run demand elasticity. The results reveal that the demand for ethanol in Brazil differs between regions. While in the center-south region the price elasticity for both ethanol and alternative fuels is high, consumption in the north-northeast is more sensitive to changes in the stock of the ethanol-powered fleet and income. These, among other evidences, suggest that the pattern of ethanol demand in the center-south region most closely resembles that in developed nations, while the pattern of demand in the north-northeast most closely resembles that in developing nations. - Research highlights: → Article consists of a first insight on regional demand for ethanol in Brazil. → It proposes a model with multiple fuels, i.e., hydrous ethanol, gasohol and natural gas. → Results evidence that figures for regional demand for ethanol differ amongst regions and with values reported for national demand. → Elasticities for the center-south keep similarities to patterns for fuel demand in developed nations while coefficients for the north-northeast are aligned to patterns on developing countries.

Ethanol demand in Brazil: Regional approach

Energy Technology Data Exchange (ETDEWEB)

Freitas, Luciano Charlita de, E-mail: lucianofreitas@hiroshima-u.ac.j [Graduate School for International Development and Cooperation, Development Policy, Hiroshima University 1-5-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8529 (Japan); Kaneko, Shinji [Graduate School for International Development and Cooperation, Development Policy, Hiroshima University 1-5-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8529 (Japan)

2011-05-15

Successive studies attempting to clarify national aspects of ethanol demand have assisted policy makers and producers in defining strategies, but little information is available on the dynamic of regional ethanol markets. This study aims to analyze the characteristics of ethanol demand at the regional level taking into account the peculiarities of the developed center-south and the developing north-northeast regions. Regional ethanol demand is evaluated based on a set of market variables that include ethanol price, consumer's income, vehicle stock and prices of substitute fuels; i.e., gasoline and natural gas. A panel cointegration analysis with monthly observations from January 2003 to April 2010 is employed to estimate the long-run demand elasticity. The results reveal that the demand for ethanol in Brazil differs between regions. While in the center-south region the price elasticity for both ethanol and alternative fuels is high, consumption in the north-northeast is more sensitive to changes in the stock of the ethanol-powered fleet and income. These, among other evidences, suggest that the pattern of ethanol demand in the center-south region most closely resembles that in developed nations, while the pattern of demand in the north-northeast most closely resembles that in developing nations. - Research highlights: {yields} Article consists of a first insight on regional demand for ethanol in Brazil. {yields} It proposes a model with multiple fuels, i.e., hydrous ethanol, gasohol and natural gas. {yields} Results evidence that figures for regional demand for ethanol differ amongst regions and with values reported for national demand. {yields} Elasticities for the center-south keep similarities to patterns for fuel demand in developed nations while coefficients for the north-northeast are aligned to patterns on developing countries.

Drivers for the Value of Demand Response under Increased Levels of Wind and Solar Power; NREL (National Renewable Energy Laboratory)

Energy Technology Data Exchange (ETDEWEB)

Hale, Elaine

2015-07-30

Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.

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.

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

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......-time market, a bi-level model is presented for the PDISCO to render continuous offers and bids strategically. The upper level problem expresses the PDISCO's profit maximization, while the lower-level problem minimizes the operation cost of the transmission-level real-time market. To solve the proposed model......, 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....

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.

A novel machine learning approach for estimation of electricity demand: An empirical evidence from Thailand

International Nuclear Information System (INIS)

Mostafavi, Elham Sadat; Mostafavi, Seyyed Iman; Jaafari, Arefeh; Hosseinpour, Fariba

2013-01-01

Highlights: • A hybrid approach is presented for the estimation of the electricity demand. • The proposed method integrates the capabilities of GP and SA. • The GSA model makes accurate predictions of the electricity demand. - Abstract: This study proposes an innovative hybrid approach for the estimation of the long-term electricity demand. A new prediction equation was developed for the electricity demand using an integrated search method of genetic programming and simulated annealing, called GSA. The annual electricity demand was formulated in terms of population, gross domestic product (GDP), stock index, and total revenue from exporting industrial products of the same year. A comprehensive database containing total electricity demand in Thailand from 1986 to 2009 was used to develop the model. The generalization of the model was verified using a separate testing data. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the electricity demand. The GSA model provides accurate predictions of the electricity demand. Furthermore, the proposed model outperforms a regression and artificial neural network-based models

Effect of Financial Innovations on Demand for Money in Pakistan: An ARDL approach

Directory of Open Access Journals (Sweden)

Qais Aslam

2010-12-01

Full Text Available An increasing array of development of banking system of Pakistan, through the use of information technology and modernization of products and services has led to financial innovations to be considered as important determinant of demand for money. This paper investigates the relationship of financial innovations and demand for money in Pakistan using Pesaran and Shin (1995 ARDL approach for long run and ECM for short run determination using yearly observations from 1957 to 2008. Using the ARDL coefficient estimation approach financial innovations demonstrates positive relationship, not found to significant but highly elastic and does not have deterministic trend for long run estimation whereas positively significant and deterministic trend for money demand function in short run in case of Pakistan.

Generation of flexible domestic load profiles to evaluate demand side management approaches

NARCIS (Netherlands)

Hoogsteen, Gerwin; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria

2016-01-01

Various Demand Side Management (DSM) approaches have been developed the last couple of years to avoid costly grid upgrades. However, evaluation of these DSM methodologies is usually restricted to a use-case specific example, making comparison between different DSM approaches hard. This paper

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.

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

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.

Food safety information and food demand

DEFF Research Database (Denmark)

Smed, Sinne; Jensen, Jørgen Dejgård

2005-01-01

Purpose – The purpose of this paper is to analyze how news about food-related health risks affects consumers’ demands for safe food products. Design/methodology/approach – By identifying structural breaks in an econometrically estimated demand model, news with permanent impact on demand...... induces a permanent increase in the demand for pasteurized eggs, while more moderate negative news influences demand temporarily and to a lesser extent. There is, however, considerable variation in the response to food safety news across socio-demographic groups of consumers. Research limitations...... is distinguished from news with temporary impact. The Danish demand for pasteurized versus shell eggs is used as an illustrative case. Findings – Negative safety news about one product variety can provide significant stimulation to the demand for safe varieties. Severe negative news about the safety of shell eggs...

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

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

OpenAIRE

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

2017-01-01

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 less grid capacity may be needed. However, the introduction of residential demand response programmes to support the development of smart grids that includes renewable generation is hampered by a ...

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...

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...... Method is used to spatially discretize these equations. Next, a broadcast strategy with two switching-fraction signals is proposed for actuating the population. This is applied in an open-loop scenario for tracking a power reference by running an optimization with a multilinear objective....

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

Energy Technology Data Exchange (ETDEWEB)

Teng, Fei, E-mail: fei.teng09@imperial.ac.uk; Aunedi, Marko; Pudjianto, Danny; Strbac, Goran [Department of Electrical and Electronic Engineering, Imperial College London, London (United Kingdom)

2015-08-18

The demand for ancillary service is expected to increase significantly in the future Great Britain (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 demand-side response (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 characterized 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.

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

International Nuclear Information System (INIS)

Teng, Fei; Aunedi, Marko; Pudjianto, Danny; Strbac, Goran

2015-01-01

The demand for ancillary service is expected to increase significantly in the future Great Britain (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 demand-side response (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 characterized 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.

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

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.

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.)

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

2004-10-01

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 discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

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.

Technological progress and long-term energy demand - a survey of recent approaches and a Danish case

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

2001-01-01

This paper discusses di!erent approaches to incorporating technological progress in energy-economy models and the e!ecton long-term energy demand projections. Approaches to modelling based on an exogenous annual change of energy e$ciencyto an endogenous explanation of innovation for energy...... technologies are covered. Technological progress is an important issue for modelling long-term energy demand and is often characterised as the main contributor to the di!erent energy demand forecasts from di!erent models. New economic theoretical developments in the "elds of endogenous growth and industrial...... description, two models of residential energy demand in Denmark are compared. A Danish macroeconometric model is compared to a technological vintage model that is covering electric appliances and residential heating demand. The energy demand projection of the two models diverges, and the underlying...

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.

Responsiveness of residential electricity demand to dynamic tariffs : experiences from a large field test in the Netherlands

NARCIS (Netherlands)

Klaassen, E.A.M.; Kobus, C.B.A.; Frunt, J.; Slootweg, J.G.

2016-01-01

To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand

Responsiveness of residential electricity demand to dynamic tariffs : Experiences from a large field test in the Netherlands

NARCIS (Netherlands)

Klaassen, EAM; Kobus, C.B.A.; Frunt, J; Slootweg, JG

2016-01-01

To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand

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.

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.

Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

OpenAIRE

Ntombizodwa J. Matsoma; Intaher M. Ambe

2017-01-01

Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. ...

FACTORS DECREASING HOUSEHOLD ELECTRICITY DEMAND – A QUALITATIVE APPROACH

Directory of Open Access Journals (Sweden)

Shimon ELBAZ

2018-05-01

Full Text Available Reducing energy consumption through changes in individual consumers’ behaviors is one of the most important challenges of the present society and near future. Our qualitative study, based on semi-structured interviews, deals with the investigation of household consumer behavior, in order to explore ways for reducing the electricity demand, in the particular cultural context of a country with high levels of energy consumption in both summer and winter times – Israel. Various approaches, coming from economics, sociology, psychology or education were tested, for limiting the use of a particular, invisible and intangible merchandise - electricity. The main objective of the present study was to determine consumers’ perceptions about the various approaches that could be used to decrease the domestic demand and consumption of electricity. A secondary objective was to identify, based on consumers’ perceptions, the factors of influence that could be used in future quantitative researches and governance strategies. We found out that investigated families have a high level of education in the field of electricity consumption and marketing campaigns, which would make the classic energy educational approach less efficient. Household electricity consumers in Israel have awareness and willingness not to waste or consume electricity beyond what is necessary, but the necessary level is positioned quite high. The social comparison approach appears to be ineffective, as well, even if it proved its efficiency in other cultures. The psychological and the economic approach could be partially efficient, if certain influence factors are widely used. These factors include mainly the magnitude of the savings, the perceived behavioral control, the personal thermal comfort and the pro-environmental attitude. The most important managerial implication concerns the strategies that could be conceived by electricity companies and national authorities – based on un

Agent-Based Architectures and Algorithms for Energy Management in Smart Grids. Application to Smart Power Generation and Residential Demand Response

International Nuclear Information System (INIS)

Roche, Robin

2012-01-01

Due to the convergence of several profound trends in the energy sector, smart grids are emerging as the main paradigm for the modernization of the electric grid. Smart grids hold many promises, including the ability to integrate large shares of distributed and intermittent renewable energy sources, energy storage and electric vehicles, as well as the promise to give consumers more control on their energy consumption. Such goals are expected to be achieved through the use of multiple technologies, and especially of information and communication technologies, supported by intelligent algorithms. These changes are transforming power grids into even more complex systems, that require suitable tools to model, simulate and control their behaviors. In this dissertation, properties of multi-agent systems are used to enable a new systemic approach to energy management, and allow for agent-based architectures and algorithms to be defined. This new approach helps tackle the complexity of a cyber-physical system such as the smart grid by enabling the simultaneous consideration of multiple aspects such as power systems, the communication infrastructure, energy markets, and consumer behaviors. The approach is tested in two applications: a 'smart' energy management system for a gas turbine power plant, and a residential demand response system. An energy management system for gas turbine power plants is designed with the objective to minimize operational costs and emissions, in the smart power generation paradigm. A gas turbine model based on actual data is proposed, and used to run simulations with a simulator specifically developed for this problem. A meta-heuristic achieves dynamic dispatch among gas turbines according to their individual characteristics. Results show that the system is capable of operating the system properly while reducing costs and emissions. The computing and communication requirements of the system, resulting from the selected architecture, are

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...

Demand Response Within Current Electricity Wholesale Market Design

OpenAIRE

Ramos Gutierrez, Ariana Isabel; De Jonghe, Cedric; Six, Daan; Belmans, Ronnie

2013-01-01

The introduction of intermittent energy resources calls for the ability to modulate consumption patterns according to electricity availability. This paper provides a brief overview of the main electricity market design characteristics and places demand response within the framework of the existing timeline of market operation. The main differences between electricity markets lie in the price formation mechanisms where some markets pay-as- cleared and some pay- as- bid for the electricity tran...

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

Economic demand and essential value.

Science.gov (United States)

Hursh, Steven R; Silberberg, Alan

2008-01-01

The strength of a rat's eating reflex correlates with hunger level when strength is measured by the response frequency that precedes eating (B. F. Skinner, 1932a, 1932b). On the basis of this finding, Skinner argued response frequency could index reflex strength. Subsequent work documented difficulties with this notion because responding was affected not only by the strengthening properties of the reinforcer but also by the rate-shaping effects of the schedule. This article obviates this problem by measuring strength via methods from behavioral economics. This approach uses demand curves to map how reinforcer consumption changes with changes in the "price" different ratio schedules impose. An exponential equation is used to model these demand curves. The value of this exponential's rate constant is used to scale the strength or essential value of a reinforcer, independent of the scalar dimensions of the reinforcer. Essential value determines the consumption level to be expected at particular prices and the response level that will occur to support that consumption. This approach permits comparing reinforcers that differ in kind, contributing toward the goal of scaling reinforcer value. (c) 2008 APA, all rights reserved

Fuel switching in Harare: An almost ideal demand system approach

International Nuclear Information System (INIS)

Chambwera, Muyeye; Folmer, Henk

2007-01-01

In urban areas several energy choices are available and the amount of (a given type of) fuel consumed is based on complex household decision processes. This paper analyzes urban fuel (particularly firewood) demand in an energy mix context by means of an Almost Ideal Demand System based on a survey carried out among 500 households in Harare in 2003. Using a multi-stage budgeting approach, the model estimates the share of energy in total household expenditure and the shares of firewood, electricity and kerosene in total energy expenditure. Using the model results simulations show that the main policy handles to reduce the demand for firewood and to mitigate environmental degradation such as deforestation include decreasing prices of alternative fuels, notably kerosene. Moreover, in the long run sound economic policy will positively impact on the energy budget whereas education and the degree of electrification will contribute to a reduction of the use of firewood

Energy demand projections based on an uncertain dynamic system modeling approach

International Nuclear Information System (INIS)

Dong, S.

2000-01-01

Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

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

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.

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

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Directory of Open Access Journals (Sweden)

Hee-Jun Cha

2015-12-01

Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands

OpenAIRE

Klaassen, EAM; Kobus, C.B.A.; Frunt, J; Slootweg, JG

2016-01-01

To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand response, a dynamic tariff and smart appliances were used. The participating households were informed about the tariff day-ahead through a home energy management system, connected to a display instal...

A predictive control scheme for real-time demand response applications

NARCIS (Netherlands)

Lampropoulos, I.; Baghina, N.G.; Kling, W.L.; Ribeiro, P.F.

2013-01-01

In this work, the focus is placed on the proof of concept of a novel control scheme for demand response. The control architecture considers a uniform representation of non-homogeneous distributed energy resources and allows the participation of virtually all system users in electricity markets. The

An empirical analysis of petroleum demand for Indonesia. An application of the cointegration approach

Energy Technology Data Exchange (ETDEWEB)

Sa' ad, Suleiman [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

2009-11-15

This paper uses selection criteria from various models in a bounds testing approach to cointegration to estimate the price and income elasticities of demand for total petroleum products (gasoline and diesel) and gasoline share in total products in Indonesia. The results suggest that both total products and gasoline share estimates are more responsive to changes in income than changes in the real price of petroleum products. These results have important policy implications as they suggest that policy makers may need to use market-based pricing policies and other policies such as public enlightenment in addition to regulations like minimum energy efficiency standards to promote efficiency and conservation and curb the rising consumption of petroleum products in Indonesia. (author)

An empirical analysis of petroleum demand for Indonesia. An application of the cointegration approach

International Nuclear Information System (INIS)

Sa'ad, Suleiman

2009-01-01

This paper uses selection criteria from various models in a bounds testing approach to cointegration to estimate the price and income elasticities of demand for total petroleum products (gasoline and diesel) and gasoline share in total products in Indonesia. The results suggest that both total products and gasoline share estimates are more responsive to changes in income than changes in the real price of petroleum products. These results have important policy implications as they suggest that policy makers may need to use market-based pricing policies and other policies such as public enlightenment in addition to regulations like minimum energy efficiency standards to promote efficiency and conservation and curb the rising consumption of petroleum products in Indonesia. (author)

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...

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.

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

Optimal stochastic short-term thermal and electrical operation of fuel cell/photovoltaic/battery/grid hybrid energy system in the presence of demand response program

International Nuclear Information System (INIS)

Majidi, Majid; Nojavan, Sayyad; Zare, Kazem

2017-01-01

Highlights: • On-grid photovoltaic/battery/fuel cell system is considered as hybrid system. • Thermal and electrical operation of hybrid energy system is studied. • Hybrid energy system is used to reduce dependency on upstream grid for load serving. • Demand response program is proposed to manage the electrical load. • Demand response program is proposed to reduce hybrid energy system’s operation cost. - Abstract: In this paper, cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system has been evaluated in the presence of demand response program. Each load curve has off-peak, mid and peak time periods in which the energy prices are different. Demand response program transfers some amount of load from peak periods to other periods to flatten the load curve and minimize total cost. So, the main goal is to meet the energy demand and propose a cost-efficient approach to minimize system’s total cost including system’s electrical cost and thermal cost and the revenue from exporting power to the upstream grid. A battery has been utilized as an electrical energy storage system and a heat storage tank is used as a thermal energy storage system to save energy in off-peak and mid-peak hours and then supply load in peak hours which leads to reduction of cost. The proposed cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system is modeled by a mixed-integer linear program and solved by General algebraic modeling system optimization software under CPLEX solver. Two case studies are investigated to show the effects of demand response program on reduction of total cost.

Demand response in liberalized electricity markets - the Nordic case

International Nuclear Information System (INIS)

Bjoerndal, Mette; Lund, Arne-Christian; Rud, Linda

2005-01-01

The liberalization of the Nordic electricity markets started with the deregulation of the Norwegian market, and the later inclusion of Sweden, Denmark and Finland in The Nord Pool area has provided a truly international marketplace, where prices are quoted for all the Nordic countries except Iceland. The structure of the Norwegian supply side was a favorable starting point for the liberalization process with many independent (hydropower) producers and, following the Energy Act of 1991, the vertical separation of competitive production on the one hand and regulated transmission / distribution one the other hand (implemented as a requirement of separation of financial accounts). Moreover, since the mid 1990s (unregulated) retail competition has provided market based price-signals to customers, even to individual households. In this paper we will focus on the potential benefits of demand flexibility in order to enhance the performance of the electricity market in attaining optimal operation and development of the electricity system. These benefits will depend on the price elasticity of the demand. However, whether it is possible to act on price changes also depends on the information provided to and from the customers. Especially for short run flexibility, this may require two way communication devises for larger customer groups, which raises questions like who is to pay for the investments needed, and who will benefit from them. Demand response also depends on the marginal signals resulting from the different contracts offered to the customers. Today this includes ''variable'' price, spot price (based on Nord Pool Elspot) and fixed price contracts. Customer flexibility depends on the possibility of substitution for instance to other fuels / alternative energy provisions. Finally, flexibility will differ between customer classes, for instance households, industry, power intensive industry etc. In this paper we investigate demand response and customer flexibility in

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

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

Energy Technology Data Exchange (ETDEWEB)

Amato, A.D.; Ruth, M. [Environmental Policy Program, School of Public Policy, University of Maryland, 3139 Van Munching Hall, College Park, MD (United States); Kirshen, P. [Department of Civil and Environmental Engineering, Tufts University, Anderson Hall, Medford, MA (United States); Horwitz, J. [Climatological Database Consultant, Binary Systems Software, Newton, MA (United States)

2005-07-01

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.

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

Enhancement of building operations: A successful approach towards national electrical demand management

International Nuclear Information System (INIS)

Al-Mulla, A.; Maheshwari, G.P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.

2013-01-01

Highlights: • Enhanced building operations were applied for eight large government buildings in Kuwait. • The enhanced building operations led to demand savings of 8.90 MW during the national peak hour. • Nationwide guidelines were developed for implementing the enhanced operations in similar government buildings in Kuwait. • The peak electrical demand reduction is likely to be 488 MW by the year 2030. - Abstract: An approach for managing electrical demand through enhanced building operations in hot climates is evaluated and demonstrated in this paper. The approach focuses on implementing enhanced operations in government buildings, since they are easier to implement and administer. These enhanced operations included early reduction of cooling supply before the end of the occupancy period, improved time-of-day control after occupancy period and reduced lighting. A total of eight government buildings with different construction and system characteristics were selected for implementing these enhanced operations. These buildings have a total air-conditioning area of 4.39 × 10 5 m 2 and a combined peak electrical demand of 29.3 MW. The enhanced operations resulted in demand savings of 8.90 MW during the national peak hour. Temperatures build up inside the buildings were monitored and found to be within acceptable ranges. Guidelines for nationwide implementation in similar buildings were developed based on the results of this work. Implementation is estimated to reduce demand by 488 MW by the year 2030, which amounts to capital savings of $585 million. These projected values would be important to adopt energy efficient policies for the country. Additional reductions in energy and fuel consumption are added benefits, which would result in large financial and environmental savings to the country. Moreover, the enhanced building operations would be an important tool to avoid any blackouts by properly reducing the peak electrical demand as well as operating the

Dynamics of Electricity Demand in Lesotho: A Kalman Filter Approach

Directory of Open Access Journals (Sweden)

Thamae Retselisitsoe Isaiah

2015-04-01

Full Text Available This study provides an empirical analysis of the time-varying price and income elasticities of electricity demand in Lesotho for the period 1995-2012 using the Kalman filter approach. The results reveal that economic growth has been one of the main drivers of electricity consumption in Lesotho while electricity prices are found to play a less significant role since they are monopoly-driven and relatively low when compared to international standards. These findings imply that increases in electricity prices in Lesotho might not have a significant impact on consumption in the short-run. However, if the real electricity prices become too high over time, consumers might change their behavior and sensitivity to price and hence, energy policymakers will need to reconsider their impact in the long-run. Furthermore, several exogenous shocks seem to have affected the sensitivity of electricity demand during the period prior to regulation, which made individuals, businesses and agencies to be more sensitive to electricity costs. On the other hand, the period after regulation has been characterized by more stable and declining sensitivity of electricity demand. Therefore, factors such as regulation and changes in the country’s economic activities appear to have affected both price and income elasticities of electricity demand in Lesotho.

Estimating petroleum products demand elasticities in Nigeria. A multivariate cointegration approach

International Nuclear Information System (INIS)

Iwayemi, Akin; Adenikinju, Adeola; Babatunde, M. Adetunji

2010-01-01

This paper formulates and estimates petroleum products demand functions in Nigeria at both aggregative and product level for the period 1977 to 2006 using multivariate cointegration approach. The estimated short and long-run price and income elasticities confirm conventional wisdom that energy consumption responds positively to changes in GDP and negatively to changes in energy price. However, the price and income elasticities of demand varied according to product type. Kerosene and gasoline have relatively high short-run income and price elasticities compared to diesel. Overall, the results show petroleum products to be price and income inelastic. (author)

Estimating petroleum products demand elasticities in Nigeria. A multivariate cointegration approach

Energy Technology Data Exchange (ETDEWEB)

Iwayemi, Akin; Adenikinju, Adeola; Babatunde, M. Adetunji [Department of Economics, University of Ibadan, Ibadan (Nigeria)

2010-01-15

This paper formulates and estimates petroleum products demand functions in Nigeria at both aggregative and product level for the period 1977 to 2006 using multivariate cointegration approach. The estimated short and long-run price and income elasticities confirm conventional wisdom that energy consumption responds positively to changes in GDP and negatively to changes in energy price. However, the price and income elasticities of demand varied according to product type. Kerosene and gasoline have relatively high short-run income and price elasticities compared to diesel. Overall, the results show petroleum products to be price and income inelastic. (author)

Demand Response to Advertising in the Australian Meat Industry

OpenAIRE

Nicholas E. Piggott; James A. Chalfant; Julian M. Alston; Garry R. Griffith

1996-01-01

The implications of model specification choices for the measurement of demand response to advertising are examined using Australian data. Single-equation models versus complete systems and alternative corrections for autocorrelation are evaluated. Competing advertising efforts by two producer bodies are included. Across all specifications, the evidence on advertising effects is fairly consistent. In the preferred model, the only statistically significant effects of advertising are for Austral...

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.

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...

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)

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.

Estimating Asymmetric Advertising Response: An Application to U.S. Nonalcoholic Beverage Demand

OpenAIRE

Zheng, Yuqing; Kaiser, Harry M.

2008-01-01

We propose a regime-switching model that allows demand to respond asymmetrically to upward and downward advertising changes. With the introduction of a smooth transition function, the model features smooth rather than abrupt parameter changes between regimes. We apply the model to nonalcoholic beverage data in the United States for 1974 through 2005 to investigate asymmetric advertising response. Results indicate that a decrease in milk advertising had a more profound impact on milk demand th...

Understanding energy consumption behaviors in order to adapt demand response measures

Energy Technology Data Exchange (ETDEWEB)

Vassileva, Iana; Wallin, Fredrik; Dahlquist, Erik [Malardalen University (Sweden)], email: iana.vassileva@mdh.se, email: fredrik.wallin@mdh.se, email: erik.dahlquist@mdh.se

2011-07-01

When new price strategies and other demand-response measures are being established, it is important that amounts of electricity consumed and the potential for consumer participation be given serious consideration. It is important to encourage consumers to use less electricity if sustainable use of energy is to be achieved. Demand-response is a key component of the smart grids concept. So it is vital to get a comprehensive understanding of how different processes and factors influence the end use of energy. This paper presents an in-depth analysis of questionnaire responses from 2000 households in Vaxjo, Sweden. It sheds new light on the energy consumption behaviors of Swedish householders. Since 2008 Vaxjo householder customers have been able to check their own daily electricity consumption and get advice and tips, via a website provided by the local energy company, on how to lower the use of electricity. At the present time, of those responding to the questionnaire, this website is visited more frequently by people who live in houses than in apartments.

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.

Market architecture and power demand management

International Nuclear Information System (INIS)

Rious, Vincent; Roques, Fabien

2014-12-01

Demand response is a cornerstone problem in electricity markets considering climate change constraint. Most liberalized electricity markets have a poor track record at developing demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper, focusing on demand response for mid-size and small consumers, we investigate which types of market signals should be sent to demand response aggregators to see demand response emerge as a competitive activity. Using data from the French power system over eight years, we compare the possible market design options to allow demand response to develop. Our simulations demonstrate that with the current market rules, demand response is not a profitable activity in the French electricity industry. Introducing a capacity remuneration could bring additional revenues to demand response aggregators if the power system has no over-capacity

Demand side management scheme in smart grid with cloud computing approach using stochastic dynamic programming

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S. Sofana Reka

2016-09-01

Full Text Available This paper proposes a cloud computing framework in smart grid environment by creating small integrated energy hub supporting real time computing for handling huge storage of data. A stochastic programming approach model is developed with cloud computing scheme for effective demand side management (DSM in smart grid. Simulation results are obtained using GUI interface and Gurobi optimizer in Matlab in order to reduce the electricity demand by creating energy networks in a smart hub approach.

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)

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

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

Demand Response in U.S. Electricity Markets: Empirical Evidence

OpenAIRE

Cappers, Peter

2009-01-01

Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in ...

Demand-Side Management and European environmental and energy goals. An optimal complementary approach

International Nuclear Information System (INIS)

Bergaentzle, Claire; Clastres, Cedric; Khalfallah, Haikel

2013-12-01

Demand side management (DSM) in electricity markets could improve energy efficiency and achieve environmental targets through controlled consumption. For the past 10 years or so DSM programs have registered significant results. However, detailed analysis of its real impact as observed by a large number of pilot studies suggests that such programs need to be fine-tuned to suit clearly identified conditions. This study aims to provide recommendations for the instruments to be used to prompt demand response with a view to maximizing energy and environmental efficiencies of various countries. The present study suggests that different DSM models should be deployed depending on the specific generation mix in any given country. Beside the natural benefits from cross-borders infrastructures, DSM improves the flexibility and reliability of the energy system, absorbing some shock on generation mix. We show efficiency increases with demand response but at a decreasing rate. So, according to rebound and report effects, simple DSM tools could be preferred. (authors)

A new proposal for greenhouse gas emissions responsibility allocation: best available technologies approach.

Science.gov (United States)

Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo

2014-01-01

In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.

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

Data model for Demand Side Management

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Simona-Vasilica OPREA

2017-08-01

Full Text Available Demand Side Management (DSM is a portfolio of measures to improve the energy system mainly at the consumption level. In this paper we propose a data model for DSM stating from the optimization methods approach in SMARTRADE project from different perspectives of several entities that include: Transmission System Operator (TSO/Distribution System Operators (DSOs perspectives in case of security/reliability concerns: minimum amount of load (or generation shedding; aggregators perspective in case of demand or generation shedding request: Which demand (or generators should be shed?; consumers perspective: load shifting (time-of-use (ToU tariffs and optimum contract strategies with the aggregators (also known as balancing responsible parties- BRP for load shedding.

A multi-scale relevance vector regression approach for daily urban water demand forecasting

Science.gov (United States)

Bai, Yun; Wang, Pu; Li, Chuan; Xie, Jingjing; Wang, Yin

2014-09-01

Water is one of the most important resources for economic and social developments. Daily water demand forecasting is an effective measure for scheduling urban water facilities. This work proposes a multi-scale relevance vector regression (MSRVR) approach to forecast daily urban water demand. The approach uses the stationary wavelet transform to decompose historical time series of daily water supplies into different scales. At each scale, the wavelet coefficients are used to train a machine-learning model using the relevance vector regression (RVR) method. The estimated coefficients of the RVR outputs for all of the scales are employed to reconstruct the forecasting result through the inverse wavelet transform. To better facilitate the MSRVR forecasting, the chaos features of the daily water supply series are analyzed to determine the input variables of the RVR model. In addition, an adaptive chaos particle swarm optimization algorithm is used to find the optimal combination of the RVR model parameters. The MSRVR approach is evaluated using real data collected from two waterworks and is compared with recently reported methods. The results show that the proposed MSRVR method can forecast daily urban water demand much more precisely in terms of the normalized root-mean-square error, correlation coefficient, and mean absolute percentage error criteria.

Evaluation of a fast power demand response strategy using active and passive building cold storages for smart grid applications

International Nuclear Information System (INIS)

Cui, Borui; Wang, Shengwei; Yan, Chengchu; Xue, Xue

2015-01-01

Highlights: • A fast power demand response strategy is developed for smart grid applications. • The developed strategy can provide immediate and stepped power demand reduction. • The demand reduction and building indoor temperature can be predicted accurately. • The demand reduction during the DR event is stable. - Abstract: Smart grid is considered as a promising solution in improving the power reliability and sustainability where demand response is one important ingredient. Demand response (DR) is a set of demand-side activities to reduce or shift electricity use to improve the electric grid efficiency and reliability. This paper presents the investigations on the power demand alternation potential for buildings involving both active and passive cold storages to support the demand response of buildings connected to smart grids. A control strategy is developed to provide immediate and stepped power demand reduction through shutting chiller(s) down when requested. The primary control objective of the developed control strategy is to restrain the building indoor temperature rise as to maintain indoor thermal comfort within certain level during the DR event. The chiller power reduction is also controlled under certain power reduction set-point. The results show that stepped and significant power reduction can be achieved through shutting chiller(s) down when requested. The power demand reduction and indoor temperature during the DR event can be also predicted accurately. The power demand reduction is stable which is predictable for the system operators

Demand response in U.S. electricity markets: Empirical evidence

International Nuclear Information System (INIS)

Cappers, Peter; Goldman, Charles; Kathan, David

2010-01-01

Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in existing wholesale and retail DR programs were capable of providing ∝38,000 MW of potential peak load reductions in the United States. Participants in organized wholesale market DR programs, though, have historically overestimated their likely performance during declared curtailments events, but appear to be getting better as they and their agents gain experience. In places with less developed organized wholesale market DR programs, utilities are learning how to create more flexible DR resources by adapting legacy load management programs to fit into existing wholesale market constructs. Overall, the development of open and organized wholesale markets coupled with direct policy support by the Federal Energy Regulatory Commission has facilitated new entry by curtailment service providers, which has likely expanded the demand response industry and led to product and service innovation. (author)

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

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...

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.

Demand response strategy management with active and reactive power incentive in the smart grid: a two-level optimization approach

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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.

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).

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...... before DR implementation. This paper critically examines the present practices of the DR in the various electricity markets existing in the world including Europe. The prospect of DR in various market levels such as day-ahead (spot) market, hour-ahead market, real time/regulating market and ancillary...... market is analyzed. This paper also addresses the key issues and challenges in the implementation of DR in the electricity markets....

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

Methodical Approach to Assessment of the Structure of Demand on the Products of the Restaurant Industry Enterprises

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Chorna Maryna V.

2013-11-01

Full Text Available The article presents a methodical approach to assessment of the structure of demand on the products (services of the restaurant industry enterprises and results of its approval. A characteristic feature of this approach is clear identification of stages and their logical consequence in the process of assessment (identification of the period of assessment – day, week, holidays, seasons; formation and systematisation of the information base by cost, quantitative and qualitative indicators; calculation of relative indicators of demand and income; building a matrix; and interpretation of results and application of the “demand level / income level” matrix. Use of the proposed approach allows identification of an assortment structure of the restaurant industry enterprise by correlation of the realised demand and obtained income, which gives a possibility to form managerial decisions on its improvement and also allows assessment of efficiency of these measures.

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...

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

reasons, that is, to help find solutions to California's energy problems. They have provided support in workmen, access to sites and vendors, and money to participate. Their efforts have revealed organizational and technical system barriers to the implementation of a wide scale program. This paper examines those barriers and provides possible avenues of approach for a future launch of a regional or statewide Automatic Demand Response Program.

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

Science.gov (United States)

2010-03-29

.... We propose that Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs) \\3... resource means a resource capable of providing demand response. 18 CFR 35.28(b)(5). \\3\\ The following RTOs... and RTOs administer for reliability or emergency conditions, such as, for instance, Midwest ISO's...

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.

Impact of Demand Side Response on a Commercial Retail Refrigeration System

Directory of Open Access Journals (Sweden)

Ibrahim M. Saleh

2018-02-01

Full Text Available The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system.

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

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

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

Estimation of demand function on natural gas and study of demand analysis

Energy Technology Data Exchange (ETDEWEB)

Kim, Y.D. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

1998-04-01

Demand Function is estimated with several methods about the demand on natural gas, and analyzed per usage. Since the demand on natural gas, which has big share of heating use, has a close relationship with temperature, the inter-season trend of price and income elasticity is estimated considering temperature and economic formation. Per usage response of natural gas demand on the changes of price and income is also estimated. It was estimated that the response of gas demand on the changes of price and income occurs by the change of number of users in long term. In case of the response of unit consumption, only industrial use shows long-term response to price. Since gas price barely responds to the change of exchange rate, it seems to express the price-making mechanism that does not reflect timely the import condition such as exchange rate, etc. 16 refs., 12 figs., 13 tabs.

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

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.

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

Joint Real-Time Energy and Demand-Response Management using a Hybrid Coalitional-Noncooperative Game

Energy Technology Data Exchange (ETDEWEB)

He, Fulin; Gu, Yi; Hao, Jun; Zhang, Jun Jason; Wei, Jiaolong; Zhang, Yingchen

2015-11-11

In order to model the interactions among utility companies, building demands and renewable energy generators (REGs), a hybrid coalitional-noncooperative game framework has been proposed. We formulate a dynamic non-cooperative game to study the energy dispatch within multiple utility companies, while we take a coalitional perspective on REGs and buildings demands through a hedonic coalition formation game approach. In this case, building demands request different power supply from REGs, then the building demands can be organized into an ultimate coalition structure through a distributed hedonic shift algorithm. At the same time, utility companies can also obtain a stable power generation profile. In addition, the interactive progress among the utility companies and building demands which cannot be supplied by REGs is implemented by distributed game theoretic algorithms. Numerical results illustrate that the proposed hybrid coalitional-noncooperative game scheme reduces the cost of both building demands and utility companies compared with the initial scene.

California DREAMing: The design of residential demand responsive technology with people in mind

Science.gov (United States)

Peffer, Therese Evelyn

Electrical utilities worldwide are exploring "demand response" programs to reduce electricity consumption during peak periods. Californian electrical utilities would like to pass the higher cost of peak demand to customers to offset costs, increase reliability, and reduce peak consumption. Variable pricing strategies require technology to communicate a dynamic price to customers and respond to that price. However, evidence from thermostat and energy display studies as well as research regarding energy-saving behaviors suggests that devices cannot effect residential demand response without the sanction and participation of people. This study developed several technologies to promote or enable residential demand response. First, along with a team of students and professors, I designed and tested the Demand Response Electrical Appliance Manager (DREAM). This wireless network of sensors, actuators, and controller with a user interface provides information to intelligently control a residential heating and cooling system and to inform people of their energy usage. We tested the system with computer simulation and in the laboratory and field. Secondly, as part of my contribution to the team, I evaluated machine-learning to predict a person's seasonal temperature preferences by analyzing existing data from office workers. The third part of the research involved developing an algorithm that generated temperature setpoints based on outdoor temperature. My study compared the simulated energy use using these setpoints to that using the setpoints of a programmable thermostat. Finally, I developed and tested a user interface for a thermostat and in-home energy display. This research tested the effects of both energy versus price information and the context of sponsorship on the behavior of subjects. I also surveyed subjects on the usefulness of various displays. The wireless network succeeded in providing detailed data to enable an intelligent controller and provide feedback to

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, M.A.; Kiliccote, S.; Dudley, J.H. [Lawrence Berkeley National Laboratory, Berkeley, CA (United States)

2013-11-15

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 twofold. 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.

8 Different approaches needed to manage ED demand among different age-groups.

Science.gov (United States)

Rimmer, Melanie; Ablard, Suzanne; O'Keeffe, Colin; Mason, Suzanne

2017-12-01

A variety of interventions have been proposed to manage rising demand for Emergency and Urgent Care, described by an NHS England review as unsustainable in the long term. However it is unlikely that any suggested approach will be equally suitable for the diverse population of ED users.We aimed to understand the patterns of demand amongst different types of patients attending ED. We also sought to understand the intended and unintended effects of demand management initiatives. Our study combined insights from routine data, a survey of ED patients, and qualitative interviews with ED staff. This paper describes the results of our analysis of the interviews. We conducted semi-structured interviews with 25 ED and Urgent Care Centre staff across 7 hospital sites in Yorkshire and Humber between 25 April and 11 July 2016. The interview topic guide asked about 4 broad areas; job role, description of patients and their impact on demand, description of inappropriate attendance, and current/future initiatives to deal with rising demand. Interviews were transcribed verbatim and analysed using framework analysis. We analysed the results to identify groups of patients with different patterns of use of ED services. We also explored ED staff experiences of demand management initiatives, and their suggestions for future initiatives. Although we did not ask specifically about patients' age, our analysis revealed that ED staff categorised attenders as children and young people, working age people, and older people. These groups had different reasons for attendance, different routes to the ED, different rate of non-urgent attendance, and different issues driving demand. Staff also described variation in the time taken to treat patients of different ages, with the oldest and youngest patients described as requiring the most time.There was no consensus amongst staff about the effectiveness of initiatives for managing demand. A strikingly wide variety of initiatives were mentioned

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

Science.gov (United States)

2011-03-24

... 13, 2010 Comments at 11; Viridity June 18, 2010 Comments at 5. [Demand response] is in all essential...; Potomac Economics; PG&E; Ohio Commission; Robert L. Borlick; Roy Shanker; and RRI Energy. \\58\\ See... at 6; PSEG at 5; and Potomac Economics at 6-8. \\60\\ Attachment to Answer of EPSA, Providing...

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...... 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...

Dramatic Demand Reduction In The Desert Southwest

Energy Technology Data Exchange (ETDEWEB)

Boehm, Robert [Univ. of Nevada, Las Vegas, NV (United States); Hsieh, Sean [Univ. of Nevada, Las Vegas, NV (United States); Lee, Joon [Univ. of Nevada, Las Vegas, NV (United States); Baghzouz, Yahia [Univ. of Nevada, Las Vegas, NV (United States); Cross, Andrew [Univ. of Nevada, Las Vegas, NV (United States); Chatterjee, Sarah [NV Energy, Las Vegas, NV (United States)

2015-07-06

This report summarizes a project that was funded to the University of Nevada Las Vegas (UNLV), with subcontractors Pulte Homes and NV Energy. The project was motivated by the fact that locations in the Desert Southwest portion of the US demonstrate very high peak electrical demands, typically in the late afternoons in the summer. These high demands often require high priced power to supply the needs, and the large loads can cause grid supply problems. An approach was proposed through this contact that would reduce the peak electrical demands to an anticipated 65% of what code-built houses of the similar size would have. It was proposed to achieve energy reduction through four approaches applied to a development of 185 homes in northwest part of Las Vegas named Villa Trieste. First, the homes would all be highly energy efficient. Secondly, each house would have a PV array installed on it. Third, an advanced demand response technique would be developed to allow the resident to have some control over the energy used. Finally, some type of battery storage would be used in the project. Pulte Homes designed the houses. The company considered initial cost vs. long-term savings and chose options that had relatively short paybacks. HERS (Home Energy Rating Service) ratings for the homes are approximately 43 on this scale. On this scale, code-built homes rate at 100, zero energy homes rate a 0, and Energy Star homes are 85. In addition a 1.764 Wp (peak Watt) rated PV array was used on each house. This was made up of solar shakes that were in visual harmony with the roofing material used. A demand response tool was developed to control the amount of electricity used during times of peak demand. While demand response techniques have been used in the utility industry for some time, this particular approach is designed to allow the customer to decide the degree of participation in the response activity. The temperature change in the residence can be decided by the residents by

Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study

Directory of Open Access Journals (Sweden)

Chi-Chun Lo

2016-02-01

Full Text Available This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.

Prediction of a service demand using combined forecasting approach

Science.gov (United States)

Zhou, Ling

2017-08-01

Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

The Demand Side Response to Multi-zone Tariffs. Consumer Test Results

Directory of Open Access Journals (Sweden)

Adam Olszewski

2015-12-01

Full Text Available Advanced Metering Infrastructure (AMI is a technologically advanced solution currently implemented by the most innovative distribution system operators. ENERGA-OPERATOR SA set about preparing for smart metering implementation in 2010. So far the company has installed over 400,000 meters in its area, and plans to install a further 450,000 in 2015. Kalisz, the first fully AMI-covered city in Poland, was chosen for an in-depth analysis of the system. In particular, a consumer test was conducted there with the intention of answering the question about the strength of the demand side response to multi-zone tariffs and power reduction. Conclusions from the year-long test show the demand side response to multi-zone tariffs – i.e. the maximum temporary percentage reduction of energy consumption in the time zone with the tariff raised by a min. of 80% – stays within the 5–15% range. In the case of power reduction (the maximum temporary reduction of energy consumption in the time zone when the power available to a household is limited to 1 kW – the demand side response stays within the 10–30% range. An additional effect of tariff diversification and smart metering is a reduction in electricity consumption by 1–4% on working days (i.e. this is the effect of either the consumption reduction or shifting it to weekends. During the test energy consumers were subjected to both price incentives and education. Due to the fact that it is difficult to separate the effects of education and tariff structures, the company plans to continue the research related to verifying the effectiveness of individual activation tools in reducing electricity consumption by households.

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)

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.

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.

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

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

Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response

International Nuclear Information System (INIS)

Vahid-Pakdel, M.J.; Nojavan, Sayyad; Mohammadi-ivatloo, B.; Zare, Kazem

2017-01-01

Highlights: • Studying heating market impact on energy hub operation considering price uncertainty. • Investigating impact of implementation of heat demand response on hub operation. • Presenting stochastic method to consider wind generation and prices uncertainties. - Abstract: Multi carrier energy systems or energy hubs has provided more flexibility for energy management systems. On the other hand, due to mutual impact of different energy carriers in energy hubs, energy management studies become more challengeable. The initial patterns of energy demands from grids point of view can be modified by optimal scheduling of energy hubs. In this work, optimal operation of multi carrier energy system has been studied in the presence of wind farm, electrical and thermal storage systems, electrical and thermal demand response programs, electricity market and thermal energy market. Stochastic programming is implemented for modeling the system uncertainties such as demands, market prices and wind speed. It is shown that adding new source of heat energy for providing demand of consumers with market mechanism changes the optimal operation point of multi carrier energy system. Presented mixed integer linear formulation for the problem has been solved by executing CPLEX solver of GAMS optimization software. Simulation results shows that hub’s operation cost reduces up to 4.8% by enabling the option of using thermal energy market for meeting heat demand.

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.

Demand response with locational dynamic pricing to support the integration of renewables

International Nuclear Information System (INIS)

Dupont, B.; De Jonghe, C.; Olmos, L.; Belmans, R.

2014-01-01

Electricity production from centralised and decentralised renewable energy resources in Europe is gaining significance, resulting in operational challenges in the electricity system. Although these challenges add to the locational and time dependency of the underlying cost of operating the system, this variability in time and location is not reflected in residential tariff schemes. Consequently, residential users are not incentivised to react to varying system conditions and to help the integration of renewable energy resources. Therefore, this paper provides a theoretical framework for designing a locational dynamic pricing scheme. This can be used to assess existing tariff structures for consumption and injection, and can serve as a theoretical background for developing new tariff schemes. Starting from the underlying costs, this paper shows that the potential for locational dynamic pricing depends on the locational and time dependency of its cost drivers. When converting costs into tariffs, the tariff design should be determined. This includes the advance notice of sending tariffs to users, and the length of price blocks and price patterns. This tariff design should find a balance between tariff principles related to costs, practicality and social acceptability on the one hand, and the resulting demand response incentive on the other. - Highlights: • The integration of renewables affects the locational and time dependency of costs. • Locational dynamic pricing reflects cost variability and allows demand response. • A theoretical framework for designing and assessing tariff schemes is proposed. • Tariff variability depends on the locational and time dependency of its cost drivers. • The tariff design should consider the resulting demand response incentive

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

Northwest Open Automated Demand Response Technology Demonstration Project

Energy Technology Data Exchange (ETDEWEB)

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

2009-08-01

Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology demonstration and evaluation for Bonneville Power Administration (BPA) in Seattle City Light's (SCL) service territory. This report summarizes the process and results of deploying open automated demand response (OpenADR) in Seattle area with winter morning peaking commercial buildings. The field tests were designed to evaluate the feasibility of deploying fully automated demand response (DR) in four to six sites in the winter and the savings from various building systems. The project started in November of 2008 and lasted 6 months. The methodology for the study included site recruitment, control strategy development, automation system deployment and enhancements, and evaluation of sites participation in DR test events. LBNL subcontracted McKinstry and Akuacom for this project. McKinstry assisted with recruitment, site survey collection, strategy development and overall participant and control vendor management. Akuacom established a new server and enhanced its operations to allow for scheduling winter morning day-of and day-ahead events. Each site signed a Memorandum of Agreement with SCL. SCL offered each site $3,000 for agreeing to participate in the study and an additional $1,000 for each event they participated. Each facility and their control vendor worked with LBNL and McKinstry to select and implement control strategies for DR and developed their automation based on the existing Internet connectivity and building control system. Once the DR strategies were programmed, McKinstry commissioned them before actual test events. McKinstry worked with LBNL to identify control points that can be archived at each facility. For each site LBNL collected meter data and trend logs from the energy management and control system. The communication system allowed the sites to receive day-ahead as well as day-of DR test event signals. Measurement of DR was

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

A review of the costs and benefits of demand response for electricity in the UK

International Nuclear Information System (INIS)

Bradley, Peter; Leach, Matthew; Torriti, Jacopo

2013-01-01

The recent policy discussion in the UK on the economic case for demand response (DR) calls for a reflection on available evidence regarding its costs and benefits. Existing studies tend to consider the size of investments and returns of certain forms of DR in isolation and do not consider economic welfare effects. From review of existing studies, policy documents, and some simple modelling of benefits of DR in providing reserve for unforeseen events, we demonstrate that the economic case for DR in UK electricity markets is positive. Consideration of economic welfare gains is provided. - Highlights: ► The paper clearly articulates the range of benefits and costs from demand response. ► Estimates for benefits and costs are converted into a broadly comparable basis. ► It is found that a positive case exists for demand response in the UK. ► New quantitative modelling is provided for one UK benefit not found in the literature. ► Economic welfare gain is considered in assessment; other UK papers do not consider such effects.

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.

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

OpenAIRE

Cha, Hee-Jun; Won, Dong-Jun; Kim, Sang-Hyuk; Chung, Il-Yop; Han, Byung-Moon

2015-01-01

The microgrid and demand response (DR) are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS) has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS) and an intelligent load. A...

Energy Saving in Greenhouse Horticulture as a response to changing societal demands

NARCIS (Netherlands)

Verstegen, J.A.A.M.; Westerman, A.D.; Bremmer, J.; Ravensbergen, P.

2004-01-01

In response to societal demands, the Dutch government implemented policy measures to reduce the use of fossil energy in greenhouse horticulture. A survey study was conducted to analyse behavioural aspects of horticultural growers to see 1) if they know about the policy measures and know what they

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

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.

Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings

Energy Technology Data Exchange (ETDEWEB)

Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Watson, David; Koch, Ed; Hennage, Dan

2009-05-01

This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automated demand response (auto-DR). Automating DR allows greater levels of participation, improved reliability, and repeatability of the DR in participating facilities. This paper also presents the technical and architectural issues associated with auto-DR and description of the demand response automation server (DRAS), the client/server architecture-based middle-ware used to automate the interactions between the utilities or any DR serving entity and their customers for DR programs. Use case diagrams are presented to show the role of the DRAS between utility/ISO and the clients at the facilities.

Demand Response on domestic thermostatically controlled loads

DEFF Research Database (Denmark)

Lakshmanan, Venkatachalam

. For a safe and reliable operation of electric power systems, the balance between electricity generation and consumption has to be maintained. The conventional fossil fuel based power generation achieves this balance by adjusting the generation to follow the consumption. In the electric power system......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....... In general, the electricity consumers are classified as industrial, commercial and domestic. In this dissertation, only the thermostatically controlled loads (TCLs) in the domestic segment are considered for the demand response study. The study is funded by Danish Council for Strategic Research (DCSR...

Demand Response in the West: Lessons for States and Provinces

Energy Technology Data Exchange (ETDEWEB)

Douglas C. Larson; Matt Lowry; Sharon Irwin

2004-06-29

OAK-B135 This paper is submitted in fulfillment of DOE Grant No. DE-FG03-015F22369 on the experience of western states/provinces with demand response (DR) in the electricity sector. Demand-side resources are often overlooked as a viable option for meeting load growth and addressing the challenges posed by the region's aging transmission system. Western states should work together with utilities and grid operators to facilitate the further deployment of DR programs which can provide benefits in the form of decreased grid congestion, improved system reliability, market efficiency, price stabilization, hedging against volatile fuel prices and reduced environmental impacts of energy production. This report describes the various types of DR programs; provides a survey of DR programs currently in place in the West; considers the benefits, drawbacks and barriers to DR; and presents lessons learned and recommendations for states/provinces.

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

Energy Technology Data Exchange (ETDEWEB)

Dargay, Joyce M. [Institute for Transport Studies, University of Leeds, Leeds LS2 9JT (United Kingdom); Gately, Dermot [Dept. of Economics, New York University, 19W. 4 St., New York, NY 10012 (United States)

2010-10-15

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)

An economic approach to abortion demand.

Science.gov (United States)

Rothstein, D S

1992-01-01

"This paper uses econometric multiple regression techniques in order to analyze the socioeconomic factors affecting the demand for abortion for the year 1985. A cross-section of the 50 [U.S.] states and Washington D.C. is examined and a household choice theoretical framework is utilized. The results suggest that average price of abortion, disposable personal per capita income, percentage of single women, whether abortions are state funded, unemployment rate, divorce rate, and if the state is located in the far West, are statistically significant factors in the determination of the demand for abortion." excerpt

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.

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

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.

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

Energy Technology Data Exchange (ETDEWEB)

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

A complex bid model and strategy for dispatchable loads in real-time market-based demand response

NARCIS (Netherlands)

Babar, M.; Nguyen, P.H.; Cuk, V.; Kamphuis, I.G.; Kling, W.L.

2014-01-01

The power system is moving into the new era of Smart Grid with the help of advance ICT and other developed technologies. These advancements made the demand response as an integral part of power and energy systems. Nowadays, the concept of Energy bidding is emerging in the Market-based Demand

Assessment of demand-response-driven load pattern elasticity using a combined approach for smart households

NARCIS (Netherlands)

Paterakis, N.G.; Tascikaraoglu, A.; Erdinç, O.; Bakirtzis, A.G.; Catalaõ, J.P.S.

2016-01-01

The recent interest in the smart grid vision and the technological advancement in the communication and control infrastructure enable several smart applications at different levels of the power grid structure, while specific importance is given to the demand side. As a result, changes in load

Demand-Side Flexibility for Energy Transitions: Policy Recommendations for Developing Demand Response

OpenAIRE

Nursimulu, Anjali; Florin, Marie-Valentine; Vuille, François

2016-01-01

As a follow-up to IRGC's report on demand-side flexibility for energy transitions, this Policy Brief highlights that increasing flexibility in power systems is needed to accommodate higher shares of non-controllable and intermittent renewable generation, and that this requires changes to the market design and regulatory framework, to facilitate the development and deployment of appropriate technologies and market-based instruments (e.g. taxes and subsidies). The Policy Brief focuses on demand...

Criteria for demand response systems

NARCIS (Netherlands)

Lampropoulos, I.; Kling, W.L.; Bosch, van den P.P.J.; Ribeiro, P.F.; Berg, van den J.

2013-01-01

The topic of demand side management is currently becoming more important than ever, in parallel with the further deregulation of the electricity sector, and the increasing integration of renewable energy sources. A historical review of automation integration in power system control assists in

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)

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

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...... with respect to external conditions. Such characteristics dictate the services DR is capable of offering, like primary frequency reserves, peak load shaving, and system balancing. In this paper, we develop methods to characterise price-responsive demand from the EcoGrid EU demonstration in a way that was bid...... 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...

Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method

Directory of Open Access Journals (Sweden)

Jun Dong

2018-04-01

Full Text Available For better utilizing renewable energy resources and improving the sustainability of power systems, demand response is widely applied in China, especially in recent decades. Considering the massive potential flexible resources in the residential sector, demand response programs are able to achieve significant benefits. This paper proposes an effective performance evaluation framework for such programs aimed at residential customers. In general, the evaluation process will face multiple criteria and some uncertain factors. Therefore, we combine the multi-criteria decision making concept and fuzzy set theory to accomplish the model establishment. By introducing trapezoidal fuzzy numbers into the Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR method, the evaluation model can effectively deal with the subjection and fuzziness of experts’ opinions. Furthermore, we ameliorate the criteria weight determination procedure of traditional models via combining the fuzzy Analytic Hierarchy Process and Shannon entropy method, which can incorporate objective information and subjective judgments. Finally, the proposed evaluation framework is verified by the empirical analysis of five demand response projects in Chinese residential areas. The results give a valid performance ranking of the five alternatives and indicate that more attention should be paid to the criteria affiliated with technology level and economy benefits. In addition, a series of sensitivity analyses are conducted to examine the validity and effectiveness of the established evaluation framework and results. The study improves traditional multi-criteria decision making method VIKOR by introducing trapezoidal fuzzy numbers and combination weighing technique, which can provide an effective mean for performance evaluation of residential demand response programs in a fuzzy environment.

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

not only to maximize the expected profit of MG operator (MGO), but also to minimize the energy payments of customers. To study the effect of uncertain parameters and demand-side participation on system operating conditions, an AC-optimal power flow (AC-OPF) approach is also applied. The proposed stochastic...

Short- and long-run demand for energy in Mexico: a cointegration approach

International Nuclear Information System (INIS)

Galindo, L.M.

2005-01-01

The objective of this paper is to estimate the demands for the different types of energy consumption for the Mexican economy over the period 1965-2001. These demands are modeled as a function of output and the own real price. The Johansen (J. Econ. Dynamics Control 12 (1988) 231) procedure and the likelihood ratio tests indicate the existence of long-run and stable relationships between each type of energy demand and income with the exception of the industrial sector where the cointegrating vector also includes the relative prices. The weak exogeneity tests indicate that energy consumption and income do not reject the null hypothesis of weak exogeneity when relative prices are weak exogenous. The final econometric models show that relative prices in the short run are relevant in all cases, with the exception of the residential sector. These results indicate that in Mexico the demand for energy is fundamentally driven by income and that the effect of the relative prices is basically concentrated on the short run with the exception of the industrial sector, which also shows a long-term price impact. The strong dependence of energy consumption with respect to income and the price inelastic response indicates that it is necessary to introduce strong measures to decouple energy consumption from output in order to obtain sustainable economic growth in Mexico

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.

The Effects of Demand-Responsive Parking on Transit Usage and Congestion: Evidence From Sfpark

Science.gov (United States)

2017-09-01

Parking is a serious issue in many urban areas, especially those experiencing rapid population growth. To address this problem, some cities have implemented demand-responsive pricing programs, where parking prices vary depending on the occupancy rate...

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.

Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China

International Nuclear Information System (INIS)

Wang Yuanyuan; Wang Jianzhou; Zhao Ge; Dong Yao

2012-01-01

Electricity demand forecasting could prove to be a useful policy tool for decision-makers; thus, accurate forecasting of electricity demand is valuable in allowing both power generators and consumers to make their plans. Although a seasonal ARIMA model is widely used in electricity demand analysis and is a high-precision approach for seasonal data forecasting, errors are unavoidable in the forecasting process. Consequently, a significant research goal is to further improve forecasting precision. To help people in the electricity sectors make more sensible decisions, this study proposes residual modification models to improve the precision of seasonal ARIMA for electricity demand forecasting. In this study, PSO optimal Fourier method, seasonal ARIMA model and combined models of PSO optimal Fourier method with seasonal ARIMA are applied in the Northwest electricity grid of China to correct the forecasting results of seasonal ARIMA. The modification models forecasting of the electricity demand appears to be more workable than that of the single seasonal ARIMA. The results indicate that the prediction accuracy of the three residual modification models is higher than the single seasonal ARIMA model and that the combined model is the most satisfactory of the three models. - Highlights: ► Three residual modification models are proposed to improve the precision of seasonal ARIMA. ► Accurate electricity demand forecast is helpful for a power production sector to come to a correct and reasonable decision. ► The results conclude that the residual modification approaches could enhance the prediction accuracy of seasonal ARIMA. ► The modification models could be applied to forecast electricity demand.

Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers

International Nuclear Information System (INIS)

Jang, Dongsik; Eom, Jiyong; Jae Park, Min; Jeung Rho, Jae

2016-01-01

To the extent that demand response represents an intentional electricity usage adjustment to price changes or incentive payments, consumers who exhibit more-variable load patterns on normal days may be capable of altering their loads more significantly in response to dynamic pricing plans. This study investigates the variation in the pre-enrollment load patterns of Korean commercial and industrial electricity customers and their impact on event-day loads during a critical peak pricing experiment in the winter of 2013. Contrary to conventional approaches to profiling electricity loads, this study proposes a new clustering technique based on variability indices that collectively represent the potential demand–response resource that these customers would supply. Our analysis reveals that variability in pre-enrollment load patterns does indeed have great predictive power for estimating their impact on demand–response loads. Customers in relatively low-variability clusters provided limited or no response, whereas customers in relatively high-variability clusters consistently presented large load impacts, accounting for most of the program-level peak reductions. This study suggests that dynamic pricing programs themselves may not offer adequate motivation for meaningful adjustments in load patterns, particularly for customers in low-variability clusters. - Highlights: • A method of clustering customers by variability indices is developed. • Customers in high-variability clusters provide substantial peak reductions. • Low-variability clusters exhibit limited reductions. • For low-variability customers, alternative policy instruments is well advised. • A model of discerning customer's demand response potential is suggested.

Distributed control system for demand response by servers

Science.gov (United States)

Hall, Joseph Edward

Within the broad topical designation of smart grid, research in demand response, or demand-side management, focuses on investigating possibilities for electrically powered devices to adapt their power consumption patterns to better match generation and more efficiently integrate intermittent renewable energy sources, especially wind. Devices such as battery chargers, heating and cooling systems, and computers can be controlled to change the time, duration, and magnitude of their power consumption while still meeting workload constraints such as deadlines and rate of throughput. This thesis presents a system by which a computer server, or multiple servers in a data center, can estimate the power imbalance on the electrical grid and use that information to dynamically change the power consumption as a service to the grid. Implementation on a testbed demonstrates the system with a hypothetical but realistic usage case scenario of an online video streaming service in which there are workloads with deadlines (high-priority) and workloads without deadlines (low-priority). The testbed is implemented with real servers, estimates the power imbalance from the grid frequency with real-time measurements of the live outlet, and uses a distributed, real-time algorithm to dynamically adjust the power consumption of the servers based on the frequency estimate and the throughput of video transcoder workloads. Analysis of the system explains and justifies multiple design choices, compares the significance of the system in relation to similar publications in the literature, and explores the potential impact of the system.

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.

Temperature Effect on Energy Demand

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Duk [Korea Energy Economics Institute, Euiwang (Korea)

1999-03-01

We provide various estimates of temperature effect for accommodating seasonality in energy demand, particularly natural gas demand. We exploit temperature response and monthly temperature distribution to estimate the temperature effect on natural gas demand. Both local and global smoothed temperature responses are estimated from empirical relationship between hourly temperature and hourly energy consumption data during the sample period (1990 - 1996). Monthly temperature distribution estimates are obtained by kernel density estimation from temperature dispersion within a month. We integrate temperature response and monthly temperature density over all the temperatures in the sample period to estimate temperature effect on energy demand. Then, estimates of temperature effect are compared between global and local smoothing methods. (author). 15 refs., 14 figs., 2 tabs.

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.

Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

International Nuclear Information System (INIS)

Amusa, Hammed; Amusa, Kafayat; Mabugu, Ramos

2009-01-01

Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960-2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use.

Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

Energy Technology Data Exchange (ETDEWEB)

Amusa, Hammed; Mabugu, Ramos [Financial and Fiscal Commission, Private Bag X69, Halfway Gardens, 1685 Midrand (South Africa); Amusa, Kafayat [Department of Economics, University of South Africa, P.O. Box 392, UNISA 0003 (South Africa)

2009-10-15

Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960-2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use. (author)

Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

International Nuclear Information System (INIS)

Toksari, M. Duran

2009-01-01

This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

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.

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.

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.

Modelling transport energy demand: A socio-technical approach

International Nuclear Information System (INIS)

Anable, Jillian; Brand, Christian; Tran, Martino; Eyre, Nick

2012-01-01

Despite an emerging consensus that societal energy consumption and related emissions are not only influenced by technical efficiency but also by lifestyles and socio-cultural factors, few attempts have been made to operationalise these insights in models of energy demand. This paper addresses that gap by presenting a scenario exercise using an integrated suite of sectoral and whole systems models to explore potential energy pathways in the UK transport sector. Techno-economic driven scenarios are contrasted with one in which social change is strongly influenced by concerns about energy use, the environment and well-being. The ‘what if’ Lifestyle scenario reveals a future in which distance travelled by car is reduced by 74% by 2050 and final energy demand from transport is halved compared to the reference case. Despite the more rapid uptake of electric vehicles and the larger share of electricity in final energy demand, it shows a future where electricity decarbonisation could be delayed. The paper illustrates the key trade-off between the more aggressive pursuit of purely technological fixes and demand reduction in the transport sector and concludes there are strong arguments for pursuing both demand and supply side solutions in the pursuit of emissions reduction and energy security.

Characterization of the elastic displacement demand: Case study - Sofia city

International Nuclear Information System (INIS)

Paskaleva, I.; Kouteva, M.; Vaccari, F.; Panza, G.F.

2008-02-01

The results of the study on the seismic site response in a part of the metropolitan Sofia are discussed. The neo-deterministic seismic hazard assessment procedure has been used to compute realistic synthetic waveforms considering four earthquake scenarios, with magnitudes M = 3.7, M = 6.3 and M = 7.0. Source and site specific ground motion time histories are computed along three investigated cross sections, making use of the hybrid approach, combining the modal summation technique and the finite differences scheme. Displacement and acceleration response spectra are considered. These results are validated against the design elastic displacement response spectra and displacement demand, recommended in Eurocode 8. The elastic response design spectrum from the standard pseudo-acceleration, versus natural period, Tn, format is converted to the Sa - Sd format. The elastic displacement response spectra and displacement demand are discussed with respect to the earthquake magnitude, the seismic source-to-site distance, seismic source mechanism, and the local geological site conditions. (author)

Climate change and peak demand for electricity: Evaluating policies for reducing peak demand under different climate change scenarios

Science.gov (United States)

Anthony, Abigail Walker

This research focuses on the relative advantages and disadvantages of using price-based and quantity-based controls for electricity markets. It also presents a detailed analysis of one specific approach to quantity based controls: the SmartAC program implemented in Stockton, California. Finally, the research forecasts electricity demand under various climate scenarios, and estimates potential cost savings that could result from a direct quantity control program over the next 50 years in each scenario. The traditional approach to dealing with the problem of peak demand for electricity is to invest in a large stock of excess capital that is rarely used, thereby greatly increasing production costs. Because this approach has proved so expensive, there has been a focus on identifying alternative approaches for dealing with peak demand problems. This research focuses on two approaches: price based approaches, such as real time pricing, and quantity based approaches, whereby the utility directly controls at least some elements of electricity used by consumers. This research suggests that well-designed policies for reducing peak demand might include both price and quantity controls. In theory, sufficiently high peak prices occurring during periods of peak demand and/or low supply can cause the quantity of electricity demanded to decline until demand is in balance with system capacity, potentially reducing the total amount of generation capacity needed to meet demand and helping meet electricity demand at the lowest cost. However, consumers need to be well informed about real-time prices for the pricing strategy to work as well as theory suggests. While this might be an appropriate assumption for large industrial and commercial users who have potentially large economic incentives, there is not yet enough research on whether households will fully understand and respond to real-time prices. Thus, while real-time pricing can be an effective tool for addressing the peak load