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

Coordination of Energy Efficiency and Demand Response

Energy Technology Data Exchange (ETDEWEB)

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

2010-01-29

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

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.

Review of current Southern California edison load management programs and proposal for a new market-driven, mass-market, demand-response program

Energy Technology Data Exchange (ETDEWEB)

Weller, G.H.

2002-01-01

Utility load management programs, including direct load control and interruptible load programs, constitute a large installed base of controllable loads that are employed by utilities as system reliability resources. In response to energy supply shortfalls expected during the summer of 2001, the California Public Utilities Commission in spring 2001 authorized new utility load management programs as well as revisions to existing programs. This report provides an independent review of the designs of these new programs for a large utility (Southern California Edison) and suggests possible improvements to enhance the price responsiveness of the customer actions influenced by these programs. The report also proposes a new program to elicit a mass-market demand response to utility price signals.

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)

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.

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.

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

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.

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

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.

Demand side management program evaluation based on industrial and commercial field data

International Nuclear Information System (INIS)

Eissa, M.M.

2011-01-01

Demand Response is increasingly viewed as an important tool for use by the electric utility industry in meeting the growing demand for electricity. There are two basic categories of demand response options: time varying retail tariffs and incentive Demand Response Programs. is applying the time varying retail tariffs program, which is not suitable according to the studied load curves captured from the industrial and commercial sectors. Different statistical studies on daily load curves for consumers connected to 22 kV lines are classified. The load curve criteria used for classification is based on peak ratio and night ratio. The data considered here is a set of 120 annual load curves corresponding to the electric power consumption (the western area in the King Saudi Arabia (KSA)) of many clients in winter and some months in the summer (peak period). The study is based on real data from several Saudi customer sectors in many geographical areas with larger commercial and industrial customers. The study proved that the suitable Demand Response for the ESC is the incentive program. - Highlights: → Study helps in selecting the proper demand side program. → A credit will be given for the customers during summer months. → Reduction in the electric bill. → Monthly bill credit is decreased based on customers' peak load reduction. → Guide for applying the proper demand side program suitable for the utility and customers.

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.

A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program

International Nuclear Information System (INIS)

Safamehr, Hossein; Rahimi-Kian, Ashkan

2015-01-01

Providing a cost-efficient and reliable energy is one of the main issues in human societies of the 21st century. In response to this demand, new features of micro grid technology have provided huge potentials, specifically by the capability of having an interactive coordination between energy suppliers and consumers. Accordingly, this paper offers an improved model for achieving an optimal Demand Response programing. To solve the proposed multi-objective optimization problem, Artificial Bee Colony algorithm and quasi-static technique are utilized. The considered objectives in this paper are minimizing the overall cost of energy consumption and also improving the technical parameters of micro grid over a time horizon. This optimization is subject to several constraints such as satisfying the energy balance and the operating constraints of each energy supply sources. Manageable load or load as source is another enabling feature existing in smart energy networks, which is considered in this paper and its effect on cost reduction and reliability improvement is studied. Trying to examine the performance of the proposed Demand Response Programing in real conditions, the uncertainties are also analyzed by stochastic methods. The results show significant improvements which are obtained by applying just intelligent programming and management. - Highlights: • This paper presents a cost-efficient and reliable energy management of a micro-grid. • New models of battery and manageable loads are formulated. • Artificial Bee Colony algorithm is used to solve the optimization problem. • Quasi-static technique is used to simplify the solving procedure. • The uncertainties are also analyzed by stochastic methods.

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.

Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs

International Nuclear Information System (INIS)

Nwulu, Nnamdi I.; Xia, Xiaohua

2015-01-01

Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model

Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs

OpenAIRE

Faria, Pedro; Spinola, Joao; Vale, Zita

2016-01-01

The use of distributed generation and demand-response (DR) programs is needed for improving business models, namely concerning the remuneration of these resources in the context of smart grids. In this paper, a methodology is proposed in which a virtual power player aggregates several small-sized resources, including consumers participating in DR programs. The global operation costs resulting from the resource scheduling are minimized. After scheduling the resources in several operation scena...

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 energy markets

International Nuclear Information System (INIS)

Skytte, K.; Birk Mortensen, J.

2004-11-01

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

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

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

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

International Nuclear Information System (INIS)

Wang, Yong; Li, Lin

2013-01-01

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

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

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.

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)

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.

Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program

International Nuclear Information System (INIS)

Nojavan, Sayyad; Zare, Kazem; Mohammadi-Ivatloo, Behnam

2017-01-01

Highlights: • Stochastic energy management of retailer under smart grid environment is proposed. • Optimal selling price is determined in the smart grid environment. • Fixed, time-of-use and real-time pricing are determined for selling to customers. • Charge/discharge of ESS is determined to increase the expected profit of retailer. • Demand response program is proposed to increase the expected profit of retailer. - Abstract: In this paper, bilateral contracting and selling price determination problems for an electricity retailer in the smart grid environment under uncertainties have been considered. Multiple energy procurement sources containing pool market (PM), bilateral contracts (BCs), distributed generation (DG) units, renewable energy sources (photovoltaic (PV) system and wind turbine (WT)) and energy storage system (ESS) as well as demand response program (DRP) as virtual generation unit are considered. The scenario-based stochastic framework is used for uncertainty modeling of pool market prices, client group demand and variable climate condition containing temperature, irradiation and wind speed. In the proposed model, the selling price is determined and compared by the retailer in the smart grid in three cases containing fixed pricing, time-of-use (TOU) pricing and real-time pricing (RTP). It is shown that the selling price determination based on RTP by the retailer leads to higher expected profit. Furthermore, demand response program (DRP) has been implemented to flatten the load profile to minimize the cost for end-user customers as well as increasing the retailer profit. To validate the proposed model, three case studies are used and the results are compared.

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

Optimal energy management of the smart parking lot under demand response program in the presence of the electrolyser and fuel cell as hydrogen storage system

International Nuclear Information System (INIS)

Jannati, Jamil; Nazarpour, Daryoosh

2017-01-01

Highlights: • Energy management of IPL is considered in the presence of wind turbine and PV system. • The optimal charge and discharge powers of EVs, dispatch power of LDG are determined. • Charging/discharging decisions of electrolyser and fuel cell are determined. • Demand response program is used to manage the peak load to reduce the operation cost. • Global optimal is guaranteed in proposed model by mixed-integer linear programming. - Abstract: Nowadays, utilization of distributed generation sources and electric vehicles (EVs) are increased to reduce air pollution and greenhouse gas emissions. Also, intelligent parking lots (IPL) are increased in response to the increase in the number of EVs. Therefore, optimal operation of distributed generation sources and IPL in the power market without technical scheduling will follow some economic problems for the owner of IPL and some technical problems for the operator of distribution network. Therefore, in this paper, an optimal energy management has been proposed for an IPL which includes renewable energy sources (wind turbine and photovoltaic system) and local dispatchable generators (micro-turbines). Also, determination of optimal charge and discharge powers of hydrogen storage system (HSS) containing electrolyser, hydrogen storage tanks and fuel cell has been considered in the proposed model. Furthermore, the time-of-use rates of demand response program are proposed to flatten the load curve to reduce the operation cost of IPL. The objective function includes minimizing the operation costs of upstream grid and local dispatchable generators as well as charging and discharging cost of IPL subject to the technical and physical constraints under demand response program in the presence of HSS. The proposed model is formulated as a mixed-integer linear programming and solved using GAMS optimization software under CPLEX solver. Four case studies are investigated to validate the proposed model to show the positive

Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

DEFF Research Database (Denmark)

Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza; Anvari-Moghaddam, Amjad

2017-01-01

In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response...

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

Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Directory of Open Access Journals (Sweden)

Alfred J. Hildreth

2013-01-01

Full Text Available Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

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...

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)

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

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

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

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)

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

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

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

Directory of Open Access Journals (Sweden)

Shengchun Yang

2016-01-01

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

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...

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

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

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...

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

International Nuclear Information System (INIS)

Clastres, Cedric; Khalfallah, Haikel

2015-01-01

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

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...

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.

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.

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

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

International Nuclear Information System (INIS)

Partovi, Farzad; Nikzad, Mehdi; Mozafari, Babak; Ranjbar, Ali Mohamad

2011-01-01

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software. -- Highlights: → Determination of optimal spinning reserve capacity requirement in order to satisfy desired security level set by system operator based on stochastic approach. → Scheduling energy and spinning reserve markets simultaneously. → Comparing the stochastic approach with deterministic approach to determine the advantages and disadvantages of each. → Examine the effect of demand response participation in reserve market to provide spinning reserve.

Smart Buildings and Demand Response

Science.gov (United States)

Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish

2011-11-01

Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto-DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components, systems, end-uses and whole building energy performance metrics. The paper presents a framework about when energy is used, levels of services by energy using systems, granularity of control, and speed of telemetry. DR, when defined as a discrete event, requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

The Integration of Energy Efficiency, Renewable Energy, DemandResponse and Climate Change: Challenges and Opportunities for Evaluatorsand Planners

Energy Technology Data Exchange (ETDEWEB)

Vine, Edward

2007-05-29

This paper explores the feasibility of integrating energyefficiency program evaluation with the emerging need for the evaluationof programs from different "energy cultures" (demand response, renewableenergy, and climate change). The paper reviews key features andinformation needs of the energy cultures and critically reviews theopportunities and challenges associated with integrating these withenergy efficiency program evaluation. There is a need to integrate thedifferent policy arenas where energy efficiency, demand response, andclimate change programs are developed, and there are positive signs thatthis integration is starting to occur.

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)

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

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 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.

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 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.

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...

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...

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)

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

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-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

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...

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...

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

International Nuclear Information System (INIS)

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

2007-06-01

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

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...

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.

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

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

Demand for pneumococcal vaccination under subsidy program for the elderly in Japan.

Science.gov (United States)

Kondo, Masahide; Yamamura, Mariko; Hoshi, Shu-Ling; Okubo, Ichiro

2012-09-12

Vaccination programs often organize subsidies and public relations in order to obtain high uptake rates and coverage. However, effects of subsidies and public relations have not been studied well in the literature. In this study, the demand function of pneumococcal vaccination among the elderly in Japan is estimated, incorporating effects of public relations and subsidy. Using a data from a questionnaire survey sent to municipalities, the varying and constant elasticity models were applied to estimate the demand function. The response variable is the uptake rate. Explanatory variables are: subsidy supported shot price, operating years of the program, target population size for vaccination, shot location intensity, income and various public relations tools. The best model is selected by c-AIC, and varying and constant price elasticities are calculated from estimation results. The vaccine uptake rate and the shot price have a negative relation. From the results of varying price elasticity, the demand for vaccination is elastic at municipalities with a shot price higher than 3,708 JPY (35.7 USD). Effects of public relations on the uptake rate are not found. It can be suggested that municipalities with a shot price higher than 3,708 JPY (35.7 USD) could subsidize more and reduce price to increase the demand for vaccination. Effects of public relations are not confirmed in this study, probably due to measurement errors of variables used for public relations, and studies at micro level exploring individual's response to public relations would be required.

Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

International Nuclear Information System (INIS)

Tabar, Vahid Sohrabi; Jirdehi, Mehdi Ahmadi; Hemmati, Reza

2017-01-01

Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. - Highlights: • Introducing portable renewable energy resource (PRER) and considering effect of them. • Considering reserve margin and sensitivity analysis for validate robustness. • Multi objective and stochastic management with considering various loads and sources. • Using augmented Epsilon-constraint method to solve multi objective program. • Highly decreasing total cost and pollution with PRER in stochastic state.

Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs

Directory of Open Access Journals (Sweden)

Pouria Sheikhahmadi

2018-03-01

Full Text Available The operation problem of a micro-grid (MG in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. The MGO can use incentive-based demand response programs (DRPs to pay an incentive to the consumers to change their demands in the peak hours. Moreover, the MGO forecasts the output power of renewable energy resources (RERs and models their uncertainties in its problem. In this paper, the operation problem of an MGO is modeled as a risk-based two-stage stochastic optimization problem. To model the uncertainties of RERs, two-stage stochastic programming is considered and conditional value at risk (CVaR index is used to manage the MGO’s risk-level. Moreover, the non-linear economic models of incentive-based DRPs are used by the MGO to change the peak load. The numerical studies are done to investigate the effect of incentive-based DRPs on the operation problem of the MGO. Moreover, to show the effect of the risk-averse parameter on MGO decisions, a sensitivity analysis is carried out.

Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

DEFF Research Database (Denmark)

Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

2015-01-01

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....

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...

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 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.

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 stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism

International Nuclear Information System (INIS)

Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat

2016-01-01

Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.

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)

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-31

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

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.

Potential transportation demand management programs and measures

Energy Technology Data Exchange (ETDEWEB)

Litman, T. [Victoria Transport Policy Institute, Victoria, BC (Canada)

1997-02-07

The advantages of transportation demand management (TDM) programs were discussed. TDM includes several policies, programs and measures designed to change travel patterns. TDM programs include commute trip reductions, pricing policies, land use management strategies, and programs to support alternative modes of transportation such as public transit, carpooling, bicycling, walking and telecommuting. TDM programs are designed to reduce traffic congestion and air pollution. Some other TDM programs and measures include: enabling programs, alternative mode encouragement, driving disincentives, parking programs, marginalizing user costs, reducing automobile ownership, and land use management.

Simulation-based Strategies for Smart Demand Response

Directory of Open Access Journals (Sweden)

Ines Leobner

2018-03-01

Full Text Available Demand Response can be seen as one effective way to harmonize demand and supply in order to achieve high self-coverage of energy consumption by means of renewable energy sources. This paper presents two different simulation-based concepts to integrate demand-response strategies into energy management systems in the customer domain of the Smart Grid. The first approach is a Model Predictive Control of the heating and cooling system of a low-energy office building. The second concept aims at industrial Demand Side Management by integrating energy use optimization into industrial automation systems. Both approaches are targeted at day-ahead planning. Furthermore, insights gained into the implications of the concepts onto the design of the model, simulation and optimization will be discussed. While both approaches share a similar architecture, different modelling and simulation approaches were required by the use cases.

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.

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.

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.

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)

Assessment of Industrial Load for Demand Response across Western Interconnect

Energy Technology Data Exchange (ETDEWEB)

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

2013-11-01

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

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

International Nuclear Information System (INIS)

2006-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

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

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

Stimulation of demand response through evaluation and training

International Nuclear Information System (INIS)

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

2004-01-01

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

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

International Nuclear Information System (INIS)

Barbose, Galen; Goldman, Charles; Neenan, Bernard

2005-01-01

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

Cost benefit analysis of the demand side management programs

International Nuclear Information System (INIS)

Schechtman, R.; Baum, M.

1989-01-01

The several cost and benefit components of the demand side management programs for the society groups, including the concessionaire, consumers and society as a whole are studied. The rule evaluations of management programs by demand side, used by North American concessionaire are also discussed. Finally, the numerical examples, that consolidating the concepts and rules evaluation are presented. (C.G.C.). 5 refs, 1 fig, 3 tabs

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. �

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.

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.

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.

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

Herter, Karen; Wayland, Seth; Rasin, Josh

2009-09-25

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

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

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

Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO

International Nuclear Information System (INIS)

Walawalkar, Rahul; Fernands, Stephen; Thakur, Netra; Chevva, Konda Reddy

2010-01-01

In electricity markets, traditional demand side management programs are slowly getting replaced with demand response (DR) programs. These programs have evolved since the early pilot programs launched in late 1990s. With the changes in market rules the opportunities have generally increased for DR for participating in emergency, economic and ancillary service programs. In recent times, various regulators have suggested that DR can also be used as a solution to meet supply - demand fluctuations in scenarios with significant penetration of variable renewable sources in grid. This paper provides an overview of the evolution of the DR programs in PJM and NYISO markets as well as analyzes current opportunities. Although DR participation has grown, most of the current participation is in the reliability programs, which are designed to provide load curtailment during peak days. This suggests that there is a significant gap between perception of ability of DR to mitigate variability of renewables and reality of current participation. DR in future can be scaled to play a more dynamic role in electricity markets, but that would require changes both on technology as well as policy front. Advances in building technologies and energy storage combined with appropriate price signals can lead to enhanced DR participation. (author)

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.

Demand response scheme based on lottery-like rebates

KAUST Repository

Schwartz, Galina A.; Tembine, Hamidou; Amin, Saurabh; Sastry, S. Shankar

2014-01-01

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

Demand response scheme based on lottery-like rebates

KAUST Repository

Schwartz, Galina A.

2014-08-24

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

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

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.

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%

Modeling, Analysis, and Control of Demand Response Resources

Energy Technology Data Exchange (ETDEWEB)

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

2012-05-01

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

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.

Review of US utility demand-side bidding programs

International Nuclear Information System (INIS)

Goldman, C.A.; Kito, M.S.

1995-01-01

In this study, we review utility experiences with demand-side management (DSM) bidding programs. Since 1987, about 35 US utilities have signed long-term contracts with developers of DSM resources (ie energy service companies and customers) to provide a quantity of demand and energy savings at specified prices. Total resource costs range between 5.4 and 8 cents/kWh for DSM bidding programs where complete information on program costs is available. Almost all DSM bidding programs have been cost-effective compared with the utility's own supply-side alternatives, although there is substantial disagreement regarding the value of these programs compared with the utility's own DSM programs. In most bidding programs, payments to bidders account for between 70 and 90% of total program costs. Variation in winning bid prices is influenced primarily by DSM bid ceiling prices, differences in the mix of measures and markets targeted by developers, and the degree of performance risk borne by the DSM developer. Bids targeting residential customers averaged 6.2 cents/kWh compared with about 5.0 cents/kWh for commercial/industrial bids. We also compared the costs of acquiring lighting savings in DSM bidding contracts with a sample of 20 utility sponsored commercial/industrial lighting programs. We found that, on average total resource costs were slightly higher in bidding programs (6.1 vs 5.6 cents/kWh), although ratepayers bear significantly less performance risk in bidding programs compared with traditional utility-sponsored DSM programs. (author)

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...

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.

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

Science.gov (United States)

Zhang, Xiao

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

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.

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.

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.

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.

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.

An assessment of the role mass market demand response could play in contributing to the management of variable generation integration issues

International Nuclear Information System (INIS)

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

2012-01-01

The penetration of wind and solar generating resources is expected to dramatically increase in the United States over the coming years. It is widely understood that large scale deployment of these types of renewable energy sources (e.g., wind, solar) that have variable and less predictable production characteristics than traditional thermal resources poses integration challenges for bulk power system operators. At present, bulk power system operators primarily utilize strategies that rely on existing thermal generation resources and improved wind and solar energy production forecasts to manage this uncertainty; a host of additional options are also envisioned for the near future including demand response (DR). There are well-established bodies of research that examine variable generation integration issues as well as demand response potential; but, the existing literature that provides a comparative assessment of the two neither treats this topic comprehensively nor in a highly integrated fashion. Thus, this paper seeks to address these missing pieces by considering the full range of opportunities and challenges for mass market DR rates and programs to support integration of variable renewable generation. - Highlights: ► Mass market demand response can help manage the integration of renewable resources. ► To be more effective, retail electricity rates must apply contemporaneous prices. ► Demand response programs will require shorter duration and more frequent events. ► Mass market customers will likely need to accept control technology. ► Market rules and regulatory policies must change to expand demand response's role.

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-...

Coordination of Retail Demand Response with Midwest ISO Markets

Energy Technology Data Exchange (ETDEWEB)

Bharvirkar, Ranjit; Bharvirkar, Ranjit; Goldman, Charles; Heffner, Grayson; Sedano, Richard

2008-05-27

The Organization of Midwest ISO States (OMS) launched the Midwest Demand Resource Initiative (MWDRI) in 2007 to identify barriers to deploying demand response (DR) resources in the Midwest Independent System Operator (MISO) region and develop policies to overcome them. The MWDRI stakeholders decided that a useful initial activity would be to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This additional detail could then be used to assess any"seams issues" affecting coordination and integration of retail DR resources with MISO's wholesale markets. Working with state regulatory agencies, we conducted a detailed survey of existing DR programs, dynamic pricing tariffs, and their features in MISO states. Utilities 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. This report describes the results of this comprehensive survey and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into organized wholesale markets. Survey responses from 37 MISO members and 4 non-members provided information on 141 DR programs and dynamic pricing tariffs with a peak load reduction potential of 4,727 MW of retail DR resource. Major findings of this study area:- About 72percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;18percent. Almost 90percent of the DR resources included in this survey are provided by investor-owned utilities. - Approximately, 90percent of the DR resources are available with less than

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.

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.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2004-08-01

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

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 �

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

International Nuclear Information System (INIS)

Malme, R. |; International Energy Agency, Paris

2006-01-01

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

Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power

International Nuclear Information System (INIS)

Wang Jianhui; Liu Cong; Ton, Dan; Zhou Yan; Kim, Jinho; Vyas, Anantray

2011-01-01

This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced. - Research highlights: → A unit commitment model is used to simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). → Different PHEV charging scenarios are simulated on the Illinois power system → Load shifting and shaving enabled by DR programs are also modeled. → The simulation results show that the operating cost can be reduced with DR and optimal PHEV charging.

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

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

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...

A Microcomputer Program that Simulates the Baumol-Tobin Transactions Demand for Money.

Science.gov (United States)

Beckman, Steven

1987-01-01

This article describes an economic model dealing with the demand for money and a microcomputer program which enables students to experiment with cash management techniques. By simulating personal experiences, the program teaches how changes in income, interest rates, and charges for exchanging bonds and cash affect money demand. (Author/JDH)

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...

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.

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

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

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 for programs for key populations in Africa from countries ...

African Journals Online (AJOL)

... a minority proposed programming for IDU (13%, 21 proposals). Demand for these programs was highly concentrated in a subset of countries. Epidemiological data for at least one key population was included in a majority of these proposals (63%, 67 proposals), but in many cases these data were not linked to programs.

Growth in Malaysian Demand for Business Education--the Australian Response.

Science.gov (United States)

Lewis, Philip E. T.; Pratt, Graham R.

1996-01-01

Increasing Malaysian demand for business education is examined from the perspective of Australia, one of the largest suppliers to the region. Topics discussed include: origins and nature of the demand; Malaysian enrollment patterns in Australia; "twinning programs," in which a Malaysian college and a foreign university collaborate to…

A Novel Technique to Enhance Demand Responsiveness

DEFF Research Database (Denmark)

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

2015-01-01

In this study, a new pricing approach is proposed to increase demand responsiveness. The proposed approach considers two well-known demand side management techniques, namely peak shaving and valley filling. This is done by incentivising consumers by magnifying price difference between peak and off......-peak hours. The usefulness of the suggested method is then investigated by its combination with an electric vehicle optimal scheduling methodology which captures both economic valuation and grid technical constraints. This case is chosen in this study to address network congestion issues, namely under...

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

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

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.

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.

Control for large scale demand response of thermostatic loads

DEFF Research Database (Denmark)

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

2013-01-01

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

Do 'enabling technologies' affect customer performance in price-responsive load programs?

International Nuclear Information System (INIS)

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-01-01

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and predictable load

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

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.

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.

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....

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

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.

Who should pay for demand-side management programs?

International Nuclear Information System (INIS)

Flaim, T.

1992-01-01

Traditional utility resource planning involves taking the load forecast as a given and then determining the additional supply resources expected to serve that load at minimum cost and optimal levels of reliability. With integrated planning, the goal is still to balance supply and demand, but in a way that is most cost effective given all possible ways to serve customers' energy service needs. The new element in integrated resource planning is demand side management (DSM) or activities aimed at altering the quantity of energy customers use and/or the timing of their consumption. This paper discusses how DSM works to accomplish energy conservation and how it affects the rate structure. It also goes on to discuss how a utility can optimize the participation in a conservation program so that no particular group might have to carry the brunt of a rate increase. These suggestions include aligning rates to accurately reflect marginal costs; require participating customers to pay as many program costs as are possible; where participating customers can't pay full cost of a program, restrict costs to those groups who are eligible to participate; and offer a 'reverse shared-savings' program to the largest customers. The paper goes on to discuss electric-to-gas fuel switching and what customers should carry the cost burden for this type of switching

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

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

Health promotion and disease prevention: a look at demand management programs.

Science.gov (United States)

Fronstin, P

1996-09-01

This Issue Brief describes employers' efforts to contain health expenditures through demand management programs. These programs are designed to reduce utilization by focusing on disease prevention and health promotion. Demand management includes work site health promotion, wellness programs, and access management. Work site health promotion is a comprehensive approach to improving health and includes awareness, health education, behavioral change, and organizational health initiatives. Wellness programs usually include stress management, smoking cessation, weight management, back care, health screenings, nutrition education, work place safety, prenatal and well baby care, CPR and first aid classes, and employee assistance programs (EAPs). These programs are often viewed positively by workers and can have long-term benefits for employers above and beyond health care cost containment. Demand management can benefit employers by increasing productivity, employee retention, and employee morale and by reducing turnover, absenteeism, future medical claims, and ultimately expenditures on health care. Even though a growing number of employers are offering wellness programs, only 37 percent of full-time workers employed in medium and large private establishments were eligible for wellness programs by 1993. However, a recent survey found that 88 percent of major employers have introduced some form of health promotion, disease prevention, or early intervention initiative to encourage healthy lifestyles among their salaried employees. Distinctions must be drawn between short- and long-term strategies. Demand management can be thought of as a short-term strategy when the focus of the program is on creating more appropriate and efficient health care utilization. Disease prevention is characterized by longer-term health improvement objectives. Whether the purpose is to reduce utilization in the short term or in the long term, the ultimate goal remains the same: to reduce health

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

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.

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)

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 Response Valuation Frameworks Paper

Energy Technology Data Exchange (ETDEWEB)

Heffner, Grayson

2009-02-01

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

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...

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

International Nuclear Information System (INIS)

Nakada, Tatsuhiro; Shin, Kongjoo; Managi, Shunsuke

2016-01-01

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

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.

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)

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.

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.

Evaluation of demand-side management programs

International Nuclear Information System (INIS)

Kolbe, A.L.; O'Loughlin, M.P.

1990-01-01

Over the past few years, the attention accorded to demand-side management (DSM) measures has called into question the traditional cost minimization approach for evaluating such programs. Two broad approaches to DSM seem to be generally used: one examining the problem from multiple perspectives and the other including various practical methods used in-house by utility planners. Whatever the standard used to evaluate DSM, there remains at least one problem which cannot be quantified. The customers who participate in a DSM program cannot only take into account the effects of DSM on their electricity bills; their comfort can also be affected. This lowering of comfort constitutes a legitimate cost which can explain why some apparently sensible DSM measures are not adopted. A method is proposed to incorporate this cost. It establishes a way to evaluate DSM program tradeoffs that, from the perspective of standard economic theory, maximizes social welfare; explains why at least one of the perspectives in the multiple perspective approach needs to be modified to incorporate all customer costs; and outlines how the proposed standard can be implemented. 8 refs

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

49 CFR 37.77 - Purchase or lease of new non-rail vehicles by public entities operating a demand responsive...

Science.gov (United States)

2010-10-01

... and days of service; (5) Restrictions or priorities based on trip purpose; (6) Availability of... disabilities. (c) For purposes of this section, a demand responsive system, when viewed in its entirety, shall... shall, before any procurement of an inaccessible vehicle, file with the appropriate state program office...

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

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

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)

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.

An EMD-ANN based prediction methodology for DR driven smart household load demand

NARCIS (Netherlands)

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

2015-01-01

This study proposes a model for the prediction of smart household load demand influenced by a dynamic pricing demand response (DR) program. Price-based DR programs have a considerable impact on household demand pattern due to the expected choice of customers or their home energy management systems

Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

International Nuclear Information System (INIS)

Morais, H.; Sousa, T.; Soares, J.; Faria, P.; Vale, Z.

2015-01-01

Highlights: • Definition fuel shifting demand response programs applied to the electric vehicles. • Integration of the proposed fuel shifting in energy resource management algorithm. • Analysis of fuel shifting contribution to support the consumption increasing. • Analysis of fuel shifting contribution to support the electric vehicles growing. • Sensitivity analysis considering different electric vehicles penetration levels. - Abstract: In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required

Designing cost effective water demand management programs in Australia.

Science.gov (United States)

White, S B; Fane, S A

2002-01-01

This paper describes recent experience with integrated resource planning (IRP) and the application of least cost planning (LCP) for the evaluation of demand management strategies in urban water. Two Australian case studies, Sydney and Northern New South Wales (NSW) are used in illustration. LCP can determine the most cost effective means of providing water services or alternatively the cheapest forms of water conservation. LCP contrasts to a traditional approach of evaluation which looks only at means of increasing supply. Detailed investigation of water usage, known as end-use analysis, is required for LCP. End-use analysis allows both rigorous demand forecasting, and the development and evaluation of conservation strategies. Strategies include education campaigns, increasing water use efficiency and promoting wastewater reuse or rainwater tanks. The optimal mix of conservation strategies and conventional capacity expansion is identified based on levelised unit cost. IRP uses LCP in the iterative process, evaluating and assessing options, investing in selected options, measuring the results, and then re-evaluating options. Key to this process is the design of cost effective demand management programs. IRP however includes a range of parameters beyond least economic cost in the planning process and program designs, including uncertainty, benefit partitioning and implementation considerations.

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...

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-03-01

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

The impact of family planning programs on unmet need and demand for contraception.

Science.gov (United States)

Bongaarts, John

2014-06-01

Much of the existing literature on the demographic impact of family planning programs focuses on their role in increasing contraceptive use, which, in turn, accelerates fertility decline. What is not clear, however, is whether this effect operates solely through a reduction in unmet need brought about by eliminating obstacles to use or whether and to what extent the programs also affect demand for contraception through messages concerning the benefits of family planning. This article aims to shed additional light on this issue by analyzing data drawn from recent Demographic and Health Surveys conducted in 63 developing countries. The first section reviews general levels and trends in unmet need, demand, and use over the course of the fertility transition. The second section presents different types of evidence of program effects, including results from a controlled experiment and from country case studies. The evidence indicates a program impact on both unmet need and demand. © 2013 The Population Council, Inc.

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.

A Generalized Formulation of Demand Response under Market Environments

Science.gov (United States)

Nguyen, Minh Y.; Nguyen, Duc M.

2015-06-01

This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.

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

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

Directory of Open Access Journals (Sweden)

Zhe Luo

2016-08-01

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

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.

Conservation programs impact in the industrial energetic demand of the Sao Paulo State

International Nuclear Information System (INIS)

Silva Walter, A.C. da; Bajay, S.V.

1987-01-01

This paper describes the evaluation methodology of the impacts of conservation and substitution programs on the industrial energy demand in the State of Sao Paulo. The main industrial sectors are investigated. An econometric energy demand forecasting model is used to project the demand in the planning period. After an analysis of the conservation and substitution possibilities in each industrial sector, a correction in the projected demand is made through adoption of assumptions oriented by these studies. (author)

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.

Province gets serious about demand management

International Nuclear Information System (INIS)

Anon

2003-01-01

Directives from the Minister to the Ontario Energy Board to review options for demand-side management and demand reduction activities, and discussion papers describing the policy framework needed to implement demand management, are indications of renewed interest by the provincial government in demand-side management of Ontario's electric power supply. This renewed interest comes on the hills of a 5.5 per cent increase in electricity use, a 33 per cent increase in imports, and consumption records broken in 10 of the last 12 months. A 117-page study was released in April by Navigant Consulting, entitled 'Demand response blueprint for Ontario' which estimates that if the Ontario market had 250 MW of additional demand response, customers providing the demand response would have saved $20 million by reducing their demand when HOEP was greater than $120/MWh, while other customers would have saved $170 million due to lower HOEP, and would have enjoyed greater reliability as a result of the increase in reserve margins. Other than price signals to induce customers to save, the Navigant report suggest paying customers not to consume during peak periods. The report estimates that such a policy could generate a total demand response of 350 MW and a $235 million reduction in revenue to generators. The Navigan report also includes a large number of detailed analysis and recommendations. One among them is for the extensive use of interval meters for customers with loads over 200 kW. The report tends to be critical of the recent price freeze ordered by the Ontario government, claiming that the freeze could increase consumption, making prices more volatile and increasing the cost to the government even more. Successful demand response programs from California, New York and the New England states are cited as examples for Ontario to emulate

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

The past, present, and future of U.S. utility demand-side management programs

International Nuclear Information System (INIS)

Eto, J.

1996-12-01

Demand-side management or DSM refers to active efforts by electric and gas utilities to modify customers' energy use patterns. The experience in the US shows that utilities, when provided with appropriate incentives, can provide a powerful stimulus to energy efficiency in the private sector. This paper describes the range and history of DSM programs offered by US electric utilities, with a focus on the political, economic, and regulatory events that have shaped their evolution. It also describes the changes these programs are undergoing as a result of US electricity industry restructuring. DSM programs began modestly in the 1970s in response to growing concerns about dependence on foreign sources of oil and environmental consequences of electricity generation, especially nuclear power. The foundation for the unique US partnership between government and utility interests can be traced first to the private-ownership structure of the vertically integrated electricity industry and second to the monopoly franchise granted by state regulators. Electricity industry restructuring calls into question both of these basic conditions, and thus the future of utility DSM programs for the public interest. Future policies guiding ratepayer-funded energy-efficiency DSM programs will need to pay close attention to the specific market objectives of the programs and to the balance between public and private interests

The past, present, and future of U.S. utility demand-side management programs

Energy Technology Data Exchange (ETDEWEB)

Eto, J. [Lawrence Berkeley National Lab., CA (United States). Environmental Energy Technologies Div.

1996-12-01

Demand-side management or DSM refers to active efforts by electric and gas utilities to modify customers` energy use patterns. The experience in the US shows that utilities, when provided with appropriate incentives, can provide a powerful stimulus to energy efficiency in the private sector. This paper describes the range and history of DSM programs offered by US electric utilities, with a focus on the political, economic, and regulatory events that have shaped their evolution. It also describes the changes these programs are undergoing as a result of US electricity industry restructuring. DSM programs began modestly in the 1970s in response to growing concerns about dependence on foreign sources of oil and environmental consequences of electricity generation, especially nuclear power. The foundation for the unique US partnership between government and utility interests can be traced first to the private-ownership structure of the vertically integrated electricity industry and second to the monopoly franchise granted by state regulators. Electricity industry restructuring calls into question both of these basic conditions, and thus the future of utility DSM programs for the public interest. Future policies guiding ratepayer-funded energy-efficiency DSM programs will need to pay close attention to the specific market objectives of the programs and to the balance between public and private interests.

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...

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.

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.)

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-03-01

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

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

DEFF Research Database (Denmark)

O'Connell, Niamh

. However, before the necessary investments can be made to establish and operate this novel resource, its value must be determined. As with all current power system resources, if distributed demand response is deployed on a large scale it will be required to interface with the power system and market...... investments will be made to establish and operate the resource. A positive commercial assessment will signal to investors that the resource can offer a return on their investment, and that it can thrive in a competitive environment. We consider both the social welfare and commercial value of demand response......This thesis deals with the development of operational models of demand response and the evaluation of this novel resource within existing frameworks for power system dispatch and market clearing. Increasing shares of power generation from variable renewable sources, and climate change policies...

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....

Demand participation in the restructured Electric Reliability Council of Texas market

International Nuclear Information System (INIS)

Zarnikau, Jay W.

2010-01-01

Does an electricity market which has been restructured to foster competition provide greater opportunities for demand response than a traditional regulated utility industry? The experiences of the restructured Electric Reliability Council of Texas (ERCOT) market over the past eight years provide some hope that it is possible to design a competitive market which will properly value and accommodate demand response. While the overall level of demand response in ERCOT is below the levels enjoyed prior to restructuring, there have nonetheless been some promising advances, including the integration of demand-side resources into competitive markets for ancillary services. ERCOT's experiences demonstrate that the degree of demand participation in a restructured market is highly sensitive to the market design. But even in a market which has been deregulated to a large degree, regulatory intervention and special demand-side programs may be needed in order to bolster demand response. (author)

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.

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

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...

Evaluation of Reliability in Risk-Constrained Scheduling of Autonomous Microgrids with Demand Response and Renewable Resources

DEFF Research Database (Denmark)

Vahedipour-Dahraie, Mostafa; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

2018-01-01

of microgrid. Moreover, the impacts of different VOLL and risk aversion parameter are illustrated on the system reliability. Extensive simulation results are also presented to illustrate the impact of risk aversion on system security issues with and without DR. Numerical results demonstrate the advantages......Uncertain natures of the renewable energy resources and consumers’ participation in demand response (DR) programs have introduced new challenges to the energy and reserve scheduling of microgrids, particularly in the autonomous mode. In this paper, a risk-constrained stochastic framework...... is presented to maximize the expected profit of a microgrid operator under uncertainties of renewable resources, demand load and electricity price. In the proposed model, the trade-off between maximizing the operator’s expected profit and the risk of getting low profits in undesired scenarios is modeled...

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

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 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...

Economic profitability analysis of demand side management program

International Nuclear Information System (INIS)

Sheen, J.N.

2005-01-01

This study considers both the internal and external costs of the utility in deriving the avoided capacity cost (ACC) and avoided operating cost (AOC) induced in an electric utility caused by the implementation of a demand side management program (DSM). In calculating the ACC, a multiple objective linear programming model is developed. Meanwhile, the AOC is calculated by considering the differences between the total and specific time period energy consumption ratios before and after the implementation of the DSM program. This study also develops an economic analysis method using Net Present Value and Pay Back Year models to assess the economic profitability of implementing a DSM program from a participant's point of view. The design and construction of a partial load leveling eutectic salt Cooling Energy Storage (CES) air conditioning system in a target office building in Kaohsiung, Taiwan, is discussed in order to simulate the cost benefit of the CES system from the perspective of the utility and from that of the participant. The results confirm the effectiveness of the developed models in simulating the economic benefits of implementing a DSM program from the perspectives of both the utility and the participant

Effects of utility demand-side management programs on uncertainty

International Nuclear Information System (INIS)

Hirst, E.

1994-01-01

Electric utilities face a variety of uncertainties that complicate their long-term resource planning. These uncertainties include future economic and load growths, fuel prices, environmental and economic regulations, performance of existing power plants, cost and availability of purchased power, and the costs and performance of new demand and supply resources. As utilities increasingly turn to demand-side management (DSM) programs to provide resources, it becomes more important to analyze the interactions between these programs and the uncertainties facing utilities. This paper uses a dynamic planning model to quantify the uncertainty effects of supply-only vs DSM + supply resource portfolios. The analysis considers four sets of uncertainties: economic growth, fuel prices, the costs to build new power plants, and the costs to operate DSM programs. The two types of portfolios are tested against these four sets of uncertainties for the period 1990 to 2010. Sensitivity, scenario, and worst-case analysis methods are used. The sensitivity analyses show that the DSM + supply resource portfolio is less sensitive to unanticipated changes in economic growth, fuel prices, and power-plant construction costs than is the supply-only portfolio. The supply-only resource mix is better only with respect to uncertainties about the costs of DSM programs. The base-case analysis shows that including DSM programs in the utility's resource portfolio reduces the net present value of revenue requirements (NPV-RR) by 490 million dollars. The scenario-analysis results show an additional 30 million dollars (6%) in benefits associated with reduction in these uncertainties. In the worst-case analysis, the DSM + supply portfolio again reduces the cost penalty associated with guessing wrong for both cases, when the utility plans for high needs and learns it has low needs and vice versa. 20 refs

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

Long-term evaluation of individualized marketing programs for travel demand management

Science.gov (United States)

2010-07-01

This research examines the use of individualized marketing as a transportation demand : management (TDM) strategy, using the City of Portlands SmartTrips program. This research : project has two specific aims: (1) to evaluate whether the benefits ...

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.

Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power

International Nuclear Information System (INIS)

Azizipanah-Abarghooee, Rasoul; Golestaneh, Faranak; Gooi, Hoay Beng; Lin, Jeremy; Bavafa, Farhad; Terzija, Vladimir

2016-01-01

Highlights: • Suggesting a new UC mixing a probabilistic security and incentive demand response. • Investigating the effects of uncertainty on UC using chance-constraint programming. • Proposing an efficient spinning reserve satisfaction based on a new ED correction. • Presenting a new operational cycles way to convert binary variable to discrete one. - Abstract: We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers’ benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n − 1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved Jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems.

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

Energy Technology Data Exchange (ETDEWEB)

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

2017-11-01

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

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.

A Multi-Objective Demand Side Management Considering ENS Cost in Smart Grids

DEFF Research Database (Denmark)

Yousefi Khanghah, Babak; Ghassemzadeh, Saeid; Hosseini, Seyed Hossein

2017-01-01

In this paper a new method is presented to achieve economic exploitation and proper usage of network capacity by exerting controlling actions over flexible loads and energy storage (ES) equipment. Multi-objective planning for demand response programs (DRP) and battery management policies is carried...... out by considering energy not supplied (ENS). In order to achieve an optimal scheduling, charge/discharge control for batteries, demand response programs and dispatch of controllable distributed generations (DGs) are also considered. Then, the balanced cost and benefits of participants are evaluated...

Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

DEFF Research Database (Denmark)

Morais, Hugo; Sousa, Tiago; Soares, J.

2015-01-01

In the smart grids context, distributed energy resources management plays an important role in the power systems' operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important...... to develop adequate methodologies to schedule the electric vehicles' charge and discharge processes, avoiding network congestions and providing ancillary services.This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed......, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting...

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-05-14

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

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

Definitional-mission report: Demand-side management program for the Tenaga Nasional Berhad in Malaysia. Export trade information

Energy Technology Data Exchange (ETDEWEB)

1992-03-01

A definitional mission evaluated the prospects of the US Trade and Development Program (TDP) funding a market demonstration of a Demand Side Management (DSM) program being developed by the Tenaga Nasional Berhad (TNB) in Malaysia. TNB is the national electric utility of Malaysia with the responsibility to promote economically efficient supply of electricity needed for the economic development of Peninsular Malaysia. DSM is a utility-financed program to affect energy savings at the enduse level thereby reducing peak and base loads. Historically, TNB has taken the peak load and the load duration curves as given in planning and implementing the least-cost generation expansion strategy. It has refrained from influencing the pattern of energy use by the customer through any means other than tariff structures and levels. The experience of many utilities with DSM in the U.S. offers TNB an opportunity to develop a suitable DSM program for Malaysia.

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.

Identification of Value Proposition and Development of Innovative Business Models for Demand Response Products and Services Enabled by the DR-BOB Solution

Directory of Open Access Journals (Sweden)

Mario Sisinni

2017-10-01

Full Text Available The work presented is the result of an ongoing European H2020 project entitled DR-BOB Demand Response in Blocks of Buildings (DR-BOB that seeks to integrate existing technologies to create a scalable solution for Demand Response (DR in blocks of buildings. In most EU countries, DR programs are currently limited to the industrial sector and to direct asset control. The DR-BOB solution extends applicability to the building sector, providing predictive building management in blocks of buildings, enabling facilities managers to respond to implicit and explicit DR schemes, and enabling the aggregation of the DR potential of many blocks of buildings for use in demand response markets. The solution consists of three main components: the Local Energy Manager (LEM, which adds intelligence and provides the capacity for predictive building management in blocks of buildings, a Consumer Portal (CP to enable building managers and building occupants to interact with the system and be engaged in demand response operations, and a Decentralized Energy Management System (DEMS®, Siemens plc, Nottingham, England, UK, which enables the aggregation of the DR potential of many blocks of buildings, thus allowing participation in incentive-based demand response with or without an aggregator. The paper reports the key results around Business Modelling development for demand response products and services enabled by the DR-BOB solution. The scope is threefold: (1 illustrate how the functionality of the demand response solution can provide value proposition to underpin its exploitation by four specific customer segments, namely aggregators and three types of Owners of Blocks of Buildings in different market conditions, (2 explore key aspects of the Business Model from the point of view of a demand response solution provider, in particular around most the suitable revenue stream and key partnership, and (3 assess the importance of key variables such as market maturity, user

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.

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.

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.

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.

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.

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...

Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

International Nuclear Information System (INIS)

Huang, Yun-Hsun; Wu, Jung-Hua; Hsu, Yu-Ju

2016-01-01

Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results. - Highlights: • A multi-region, two-stage stochastic programming model has been developed. • The decision tree and Monte Carlo simulation are integrated into the framework. • Taiwan's electricity sector is used to illustrate the applicability of the model. • The results under deterministic and stochastic cases are shown for comparison. • Optimal portfolios of regional generation technologies can be identified.

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...

Energy efficiency and demand respond programs play vital roles in short- and long-term system reliability

Energy Technology Data Exchange (ETDEWEB)

Mitola, J. P.

2003-12-01

The effects of deregulation of the electric power industry on the reliability of the power grid in the United States are examined. Three major factors -- customer load, utility infrastructure, and demand response -- together are suggested as being most important; the ability of the industry to maintain the equilibrium among these three factors will determine the success or failure of deregulation. Each of these factors are examined in turn, followed by recommendations encouraging demand response or energy efficiency innovations, particularly new demand response technologies that are reliable, measurable, competitive to end-users, and fully dispatchable to utilities.

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

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

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...

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

Development of demand functions and their inclusion in linear programming forecasting models

International Nuclear Information System (INIS)

Chamberlin, J.H.

1976-05-01

The purpose of the paper is to present a method for including demand directly within a linear programming model, and to use this method to analyze the effect of the Liquid Metal Fast Breeder Reactor upon the nuclear energy system

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.

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.

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...

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-06

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-07

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

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 Role of Public-Sector Family Planning Programs in Meeting the Demand for Contraception in Sub-Saharan Africa.

Science.gov (United States)

Bongaarts, John; Hardee, Karen

2017-06-01

Commonly used indicators of contraceptive behavior in a population-modern contraceptive prevalence (mCPR), unmet need for contraception, demand for contraception and demand satisfied-are not well-suited for evaluating the progress made by government family planning programs in helping women and men achieve their reproductive goals. Trends in these measures in 26 Sub-Saharan African countries between 1990 and 2014 were examined. Trends in a proposed new indicator, the public-sector family planning program impact score (PFPI), and its relationship to mCPR and the family planning effort score were also assessed. Case studies were used to review public family planning program development and implementation in four countries (Nigeria, Ethiopia, Rwanda and Kenya). The four commonly used indicators capture the extent to which women use family planning and to which demand is satisfied, but shed no direct light on the role of family planning programs. PFPI provides evidence that can be used to hold governments accountable for meeting the demand for family planning, and was closely related to policy developments in the four case-study countries. PFPI provides a useful addition to the indicators currently used to assess progress in reproductive health and family planning programs.

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.

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)

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

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)

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 ...

Electricity demand response in China: Status, feasible market schemes and pilots

International Nuclear Information System (INIS)

Li, Weilin; Xu, Peng; Lu, Xing; Wang, Huilong; Pang, Zhihong

2016-01-01

Demand Response (DR) has been extensively developed and implemented in the US and Europe. However, DR hardly exists in many developing countries for similar problems such as rigid power market and state monopoly. With the increasing imbalance between supply and demand in China's power industry, the government has issued new policies on DR and approved the first batch of pilot cities. China is setting a good example of how to encourage DR under monopolistic electric market and open up the market to aggregators and DR suppliers. This paper summarizes the current DR status, feasible DR market schemes and DR pilot projects in China. First, electric power system reform, renewable energy policies and power industry development are reviewed, highlighting the problems associated with the current dispatch mechanisms of DR policies and markets. New DR programs and DR-related policies are also introduced. On this basis, the driving forces and challenges associated with DR in China are analyzed. The major challenge is the lack of a suitable market mechanism for the current Chinese power industry. Hence, this paper presents six feasible strategies that fully utilize the existing policies. Additionally, the latest DR applications in different pilot cities are summarized and analyzed. - Highlights: • Summarize the status, feasible market schemes and pilot projects of DR in China. • Highlight the problems of the current dispatch mechanisms of DR policies and market. • Analyze the driving forces and challenges associated with DR in China. • Present six feasible strategies that fully utilize the existing policies. • Summarize and analyze the latest DR applications in different pilot cities.

Meeting the Demand for Accountability: Case Study of a Teacher Education Program in China

Directory of Open Access Journals (Sweden)

Tak Cheung CHAN

2009-02-01

Full Text Available To meet the demand for accountability, a teacher education program in a university located in South China has established processes at the college, the program, and the faculty levels to assure its program quality. Highlights of the processes are: involvement of stakeholders and the examination of program effectiveness. Although much has been done to help program candidates succeed, more effort is needed in the areas of program assessment and continuous improvement to assure program quality. An accountability implementation plan, a beginning teacher mentoring program, and a comparative study of beginning teacher performance were recommended to further enforce its strategies toward program accountability.

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

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 controllers with optimized programing; Controladores de demanda com programacao otimizada

Energy Technology Data Exchange (ETDEWEB)

Santos, A.H.M.; Haddad, J.; Almeida, A.T.L. [Escola Federal de Engenharia de Itajuba, MG (Brazil); Devienne, R.F. [Universidade de Taubate (UNITAU), SP (Brazil)

1995-12-31

This work presents a methodological proposal for load re-allocation strategy in opposition to the empiric methodology presently used by demand controllers. Through the utilization of dynamic programing techniques associated to fuzzy theory it is possible to modulate the electric power consumers load curve, incorporating different objectives resulting in the global energy consumption rationing 6 figs., 5 tabs., 8 refs.

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

DEFF Research Database (Denmark)

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

2017-01-01

Before restructuring in the electricity industry, the primary decision-makers of the electricity market were deemed to be power generation and transmission companies, market regulation boards, and power industry regulators. In this traditional structure, consumers were interested in receiving...... electricity at flat rates while paying no attention to the problems of this industry. This attitude was the source of many problems, sometimes leading to collapse of power systems and widespread blackouts. Restructuring of the electricity industry however provided a multitude of solutions to these problems....... The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...

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

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...

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-12-07

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

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.

Supply shortage forecast in Ontario: The significance of demand-side management (DSM); its tools and techniques

International Nuclear Information System (INIS)

Saini, S.

2004-01-01

Aspects of the recent report by the Ontario Electricity Conservation and Supply Task Force and Independent Market Operator which forecasts acute power supply shortages in Ontario, are discussed. Immediate action is recommended to avert the problem. The principal recommendation concerns the adoption of Demand Side Management as a tool to reduce the widening gap between supply and demand, citing supply shortage, imports, high prices, deregulated market and environmental concerns as the driving forces which push for the adoption of DSM. It is claimed that DSM, through its tools such as Demand/Load Response Programs and Time-of-Use rates has the capacity to create the necessary balance between supply and demand more efficiently, and in a more timely fashion than supply side management. The demand for adoption of DSM is justified on the basis of a careful examination of the magnitude and significance of each of the driving forces affecting the electricity supply in Ontario, as well as the benefits and techniques of DSM designed to manage power shortages. Energy Conservation and Efficiency and Demand/Load Response Programs are discussed as the principal DSM techniques, while Dynamic/Real Time Pricing, Time-of-Use Rates, Automated /Smart Metering, Web-based/Communication Systems, Reliability-based Programs, Market/Price-based programs, and Types of Load Control are described as the principal tools used by DSM. DSM program approaches and strategies are also reviewed, along with a brief list of successful examples of DSM applications. 3 figs

Supply shortage forecast in Ontario: The significance of demand-side management (DSM); its tools and techniques

Energy Technology Data Exchange (ETDEWEB)

Saini, S.

2004-06-01

Aspects of the recent report by the Ontario Electricity Conservation and Supply Task Force and Independent Market Operator which forecasts acute power supply shortages in Ontario, are discussed. Immediate action is recommended to avert the problem. The principal recommendation concerns the adoption of Demand Side Management as a tool to reduce the widening gap between supply and demand, citing supply shortage, imports, high prices, deregulated market and environmental concerns as the driving forces which push for the adoption of DSM. It is claimed that DSM, through its tools such as Demand/Load Response Programs and Time-of-Use rates has the capacity to create the necessary balance between supply and demand more efficiently, and in a more timely fashion than supply side management. The demand for adoption of DSM is justified on the basis of a careful examination of the magnitude and significance of each of the driving forces affecting the electricity supply in Ontario, as well as the benefits and techniques of DSM designed to manage power shortages. Energy Conservation and Efficiency and Demand/Load Response Programs are discussed as the principal DSM techniques, while Dynamic/Real Time Pricing, Time-of-Use Rates, Automated /Smart Metering, Web-based/Communication Systems, Reliability-based Programs, Market/Price-based programs, and Types of Load Control are described as the principal tools used by DSM. DSM program approaches and strategies are also reviewed, along with a brief list of successful examples of DSM applications. 3 figs.

Demand Shifting With Thermal Mass in Large Commercial Buildings:Field Tests, Simulation and Audits

Energy Technology Data Exchange (ETDEWEB)

Xu, Peng; Haves, Philip; Piette, Mary Ann; Zagreus, Leah

2005-09-01

The principle of pre-cooling and demand limiting is to pre-cool buildings at night or in the morning during off-peak hours, storing cooling in the building thermal mass and thereby reducing cooling loads and reducing or shedding related electrical demand during the peak periods. Cost savings are achieved by reducing on-peak energy and demand charges. The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies (Braun 1990, Ruud et al. 1990, Conniff 1991, Andresen and Brandemuehl 1992, Mahajan et al. 1993, Morris et al. 1994, Keeney and Braun 1997, Becker and Paciuk 2002, Xu et al. 2003). This technology appears to have significant potential for demand reduction if applied within an overall demand response program. The primary goal associated with this research is to develop information and tools necessary to assess the viability of and, where appropriate, implement demand response programs involving building thermal mass in buildings throughout California. The project involves evaluating the technology readiness, overall demand reduction potential, and customer acceptance for different classes of buildings. This information can be used along with estimates of the impact of the strategies on energy use to design appropriate incentives for customers.

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

Machine learning for identifying demand patterns of home energy management systems with dynamic electricity pricing

NARCIS (Netherlands)

Koolen, D. (Derck); Sadat-Razavi, N. (Navid); W. Ketter (Wolfgang)

2017-01-01

textabstractEnergy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR) programs enhance demand flexibility by communicating energy market price volatility to the end-consumer.

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

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.

Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids

Directory of Open Access Journals (Sweden)

Akhtar Hussain

2017-06-01

Full Text Available Integration of demand response (DR programs and battery energy storage system (BESS in microgrids are beneficial for both microgrid owners and consumers. The intensity of DR programs and BESS size can alter the operation of microgrids. Meanwhile, the optimal size for BESS units is linked with the uncertainties associated with renewable energy sources and load variations. Similarly, the participation of enrolled customers in DR programs is also uncertain and, among various other factors, uncertainty in market prices is a major cause. Therefore, in this paper, the impact of DR program intensity and BESS size on the operation of networked microgrids is analyzed while considering the prevailing uncertainties. The uncertainties associated with forecast load values, output of renewable generators, and market price are realized via the robust optimization method. Robust optimization has the capability to provide immunity against the worst-case scenario, provided the uncertainties lie within the specified bounds. The worst-case scenario of the prevailing uncertainties is considered for evaluating the feasibility of the proposed method. The two representative categories of DR programs, i.e., price-based and incentive-based DR programs are considered. The impact of change in DR intensity and BESS size on operation cost of the microgrid network, external power trading, internal power transfer, load profile of the network, and state-of-charge (SOC of battery energy storage system (BESS units is analyzed. Simulation results are analyzed to determine the integration of favorable DR program and/or BESS units for different microgrid networks with diverse objectives.

Market modeling for assessment of demand side programs using the marginal cost

International Nuclear Information System (INIS)

Papastamatiou, Panagiotis; Psarras, John

2000-01-01

Demand side management is nowadays considered as a functional step in the energy planning process. The criteria proposed for the assessment of the demand side programs (DSPs) are usually based on the balance between the marginal supply cost and the mean DSP cost. These criteria could not support the allotting of the invested capital to incentives for the consumers and advertising. This paper presents a methodology to support the utility planning at this point with more reliability. It proposes the expansion of the assessment criteria with the use of the marginal cost of the DSP. For the calculation of the DSP marginal cost, a dynamic model is developed and it is used for the simulation of the penetration of a DS Program. Using the 'least-cost' criterion as the decision rule for the simulation, the planner has a distribution of the available investment capital throughout the whole planning period. The use of the 'most-value' criterion supports the separation of the invested capital between incentives for the consumers and supportive expenses, e.g. advertising, marketing cost, etc. (Author)

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.

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.

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.

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...

Big Data Analytics for Demand Response: Clustering Over Space and Time

Energy Technology Data Exchange (ETDEWEB)

Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Kolte, Jahanvi [Nirma Univ., Gujarat (India); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

2015-10-29

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

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.

The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations

Energy Technology Data Exchange (ETDEWEB)

Kirby, Brendan J [ORNL

2006-07-01

, market and reliability rules have, understandably, been written around the capabilities and limitations of generators, the historic reliability resources. Responsive load limitations and capabilities are often not accommodated in markets or reliability criteria. Third, because of the institutional structure, demand response alternatives are treated as temporary solutions that can delay but not replace transmission enhancement. Financing has to be based on a three to five year project life as opposed to the twenty to fifty year life of transmission facilities. More can be done to integrate demand response options into transmission expansion planning. Given the societal benefits it may be appropriate for independent transmission planning organizations to take a more proactive role in drawing demand response alternatives into the resource mix. Existing demand response programs provide a technical basis to build from. Regulatory and market obstacles will have to be overcome if demand response alternatives are to be routinely considered in transmission expansion planning.

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.

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.

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

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

Assessment of the Impact of Teaching Demands on Research Productivity Among Doctoral Nursing Program Faculty.

Science.gov (United States)

Smeltzer, Suzanne C; Cantrell, Mary Ann; Sharts-Hopko, Nancy C; Heverly, Mary Ann; Jenkinson, Amanda; Nthenge, Serah

2016-01-01

This article reports the findings of a study that examined the research and scholarship productivity of doctorally prepared nursing faculty teaching and mentoring doctoral students and the conflicting demands on them to maintain programs of research and scholarship. The specific aims were to (a) examine the research productivity and scholarship of faculty members teaching in doctoral programs and mentoring doctoral students to examine the perceived effectiveness of existing institutional mechanisms to support scholarship, (b) explore institutional features and personal practices used by doctoral program faculty to develop and maintain research and scholarship productivity, and (c) analyze predictors of scholarship productivity. Data were collected via an on-line researcher-developed survey that examined doctoral faculty roles/responsibilities and their relationship to their scholarly productivity, overall research productivity, and institutional features and personal practices to support research/scholarship activities. Survey respondents reported spending a large amount of time engaged in research-related activities with 58.9% (n = 326) spending anywhere from 6 to 20 hours per week conducting research, writing research-based papers, giving presentations, grant writing, or conducting evidence-based improvement projects. Scholar productivity among the respondents was robust. Personal practices that most strongly supported faculty members' scholarship productivity were the belief that engaging in scholarship made them better teachers and the personal gratification in experiencing doctoral students' successes. A multiple regression analysis conducted to determine predictors of productivity indicated that the strongest predictor was the average number of hours spent on research/scholarship-related activities, followed by time bought out from teaching and other responsibilities of the faculty role for research. Copyright © 2016 Elsevier Inc. All rights reserved.

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...

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

Directory of Open Access Journals (Sweden)

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.

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

Decision support program for congestion management using demand side flexibility

DEFF Research Database (Denmark)

Esmat, Ayman; Pinson, Pierre; Usaola, Julio

2017-01-01

In the past decades, Distribution System Operators (DSOs) have been mitigating distribution networks (DNs) contingencies by opting to grid reinforcements. However, this approach is not always cost and time efficient. Demand Side Flexibility (DSF) is one of the recent alternatives used in DNs cong...... effect is taken into consideration as well as the uncertain behavior of customers. Finally, the distribution grid of the Danish Bornholm Island is used to illustrate the merits of the DSP. The total cost incurred by the DSO is calculated and presented.......In the past decades, Distribution System Operators (DSOs) have been mitigating distribution networks (DNs) contingencies by opting to grid reinforcements. However, this approach is not always cost and time efficient. Demand Side Flexibility (DSF) is one of the recent alternatives used in DNs...... congestion management. Consequently, new market players such as aggregators are needed to handle DSF transaction between customers and DSOs. This paper proposes and models a decision support program (DSP) to optimize the total cost charged by the DSO for using DSF services. Moreover, the energy rebound...

Responsive Space Program Brief

Energy Technology Data Exchange (ETDEWEB)

Dors, Eric E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2014-03-11

The goal of the Responsive Space program is to make significant, integrated science and technology contributions to the end-to-end missions of the U.S. Government that protect against global emerging and nuclear threats, from the earliest adversary planning through resilient event response report describes the LANL space program, mission, and other activities. The report describes some of their activities.

Demonstrating a small utility approach to demand-side program implementation

International Nuclear Information System (INIS)

1991-01-01

The US DOE awarded a grant to the Burlington Electric Department (B.E.D.) to test a demand-side management (DSM) demonstration program designed to quickly save a significant amount of power with little disruption to the utility's customers or its normal operations. B.E.D. is a small municipal utility located in northern Vermont, with a lengthy history of successful DSM involvement. In our grant application, we proposed to develop a replicable program and approach to DSM that might be useful to other small utilities and to write a report to enable such replication. We believe that this DSM program and/or individual program components are replicable. This report is designed to allow other utilities interested in DSM to replicate this program or specific program design features to meet their DSM goals. We also wanted to use the opportunity of this grant to test the waters of residential heating fuel-switching. We hoped to test the application of one fuel-switching technology, and to benefit from the lessons learned in developing a full-scale DSM program for this end- use. To this end the pilot effort has been very successful. In the pilot pressure we installed direct-vent gas fired space heaters sized as supplemental heating units in 44 residences heated solely by electric resistance heat. We installed the gas space heating units at no cost to the owners or residents. We surveyed participating customers. The results of those surveys are included in this report and preliminary estimates of winter peak capacity load reductions are also noted in this report

Demonstrating a small utility approach to demand-side program implementation

Energy Technology Data Exchange (ETDEWEB)

1991-10-01

The US DOE awarded a grant to the Burlington Electric Department (B.E.D.) to test a demand-side management (DSM) demonstration program designed to quickly save a significant amount of power with little disruption to the utility's customers or its normal operations. B.E.D. is a small municipal utility located in northern Vermont, with a lengthy history of successful DSM involvement. In our grant application, we proposed to develop a replicable program and approach to DSM that might be useful to other small utilities and to write a report to enable such replication. We believe that this DSM program and/or individual program components are replicable. This report is designed to allow other utilities interested in DSM to replicate this program or specific program design features to meet their DSM goals. We also wanted to use the opportunity of this grant to test the waters of residential heating fuel-switching. We hoped to test the application of one fuel-switching technology, and to benefit from the lessons learned in developing a full-scale DSM program for this end- use. To this end the pilot effort has been very successful. In the pilot pressure we installed direct-vent gas fired space heaters sized as supplemental heating units in 44 residences heated solely by electric resistance heat. We installed the gas space heating units at no cost to the owners or residents. We surveyed participating customers. The results of those surveys are included in this report and preliminary estimates of winter peak capacity load reductions are also noted in this report.

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)

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.