National Library of Energy BETA

Sample records for demand response provider

  1. Demand Response Providing Ancillary Services

    E-Print Network [OSTI]

    1 Demand Response Providing Ancillary Services: A Comparison of Opportunities and Challenges in US to operate (likely price takers) ­ Statistical reliability (property of large aggregations of small resources size based on Mid-Atlantic Reserve Zone #12;Market Rules: Resource Size Min. Size (MW) Aggregation

  2. Demand Response Providing Ancillary A Comparison of Opportunities and

    E-Print Network [OSTI]

    LBNL-5958E Demand Response Providing Ancillary Services A Comparison of Opportunities Government or any agency thereof or The Regents of the University of California. #12;Demand Response System Reliability, Demand Response (DR), Electricity Markets, Smart Grid Abstract Interest in using

  3. Opportunities for Mass Market Demand Response to Provide Ancillary Services

    SciTech Connect (OSTI)

    Pratt, Rob; Najewicz, Dave

    2011-10-01

    Discusses what is meant by mass market demand response to provide ancillary services and outlines opportunities for adoption, and barriers to adoption.

  4. Market and Policy Barriers for Demand Response Providing Ancillary Services

    Office of Energy Efficiency and Renewable Energy (EERE)

    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. The barriers were identified through examinations of regulatory structures, market environments, and product offerings; and discussions with industry stakeholders and regulators.

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

    E-Print Network [OSTI]

    Cappers, Peter

    2014-01-01

    Response for Wholesale Ancillary Services. November 2009.Demand Response Providing Ancillary Services. Presented atManual 11: Energy & Ancillary Services Market Operations.

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

    E-Print Network [OSTI]

    Cappers, Peter

    2014-01-01

    Wholesale Electricity Demand Response Program Comparison,J. (2009) Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services.

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

    SciTech Connect (OSTI)

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

    2009-02-01

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

  8. Advanced Demand Responsive Lighting

    E-Print Network [OSTI]

    Advanced Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center demand responsive lighting systems ­ Importance of dimming ­ New wireless controls technologies · Advanced Demand Responsive Lighting (commenced March 2007) #12;Objectives · Provide up-to-date information

  9. Demand Response Assessment INTRODUCTION

    E-Print Network [OSTI]

    Demand Response Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "Demand Response" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demand response (price mechanisms

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

    SciTech Connect (OSTI)

    Cappers, Peter; MacDonald, Jason; Goldman, Charles

    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.

  11. Demand Response and Open Automated Demand Response

    E-Print Network [OSTI]

    LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

  12. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

  13. Demand Response Technology Roadmap A

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    meetings and workshops convened to develop content for the Demand Response Technology Roadmap. The project team has developed this companion document in the interest of providing...

  14. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    2007-10-15

    The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

  15. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R

    2013-01-01

    Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

  16. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-01-01

    Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities”

  17. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    F) Enhanced ACP Date RAA ACP Demand Response – SpinningReserve Demonstration Demand Response – Spinning Reservesupply spinning reserve. Demand Response – Spinning Reserve

  18. Demand Response Programs for Oregon

    E-Print Network [OSTI]

    Demand Response Programs for Oregon Utilities Public Utility Commission May 2003 Public Utility ....................................................................................................................... 1 Types of Demand Response Programs............................................................................ 3 Demand Response Programs in Oregon

  19. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

  20. Optimal Demand Response Libin Jiang

    E-Print Network [OSTI]

    Optimal Demand Response Libin Jiang Steven Low Computing + Math Sciences Electrical Engineering Caltech Oct 2011 #12;Outline Caltech smart grid research Optimal demand response #12;Global trends 1

  1. Demand Response Spinning Reserve Demonstration

    SciTech Connect (OSTI)

    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.

  2. ERCOT Demand Response Paul Wattles

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    ERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre;Definitions of Demand Response · `The short-term adjustment of energy use by consumers in response to price to market or reliability conditions.' (NAESB) #12;Definitions of Demand Response · The common threads

  3. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    DECC aggregator managed portfolio automated demand responseaggregator designs their own programs, and offers demand responseaggregator is responsible for designing and implementing their own demand response

  4. Assessment of Demand Response Resource

    E-Print Network [OSTI]

    Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

  5. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    2 2.0 Demand ResponseFully Automated Demand Response Tests in Large Facilities,was coordinated by the Demand Response Research Center and

  6. Demand Response: Load Management Programs 

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01

    Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs V. Residential Discussion... Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off-peak period or from high-price periods...

  7. Demand Response Aggregated Demand Response Pilot

    E-Print Network [OSTI]

    · Owns and operates over 1,300 megawatts of nuclear, hydroelectric, solar, and wind generation assets · Increasingly less capacity and flexibility of its hydroelectric resources · EN's Pilot provides BPA 35 MW

  8. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01

    their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

  9. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01

    Fully Automated Demand Response Tests in Large Facilities”of Fully Automated Demand Response in Large Facilities”,was coordinated by the Demand Response Research Center and

  10. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

  11. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17  

  12. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

  13. Demand Response - Policy | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Coordination of Energy Efficiency and Demand Response Demand Response in U.S. Electricity Markets: Empirical Evidence 2009 Retail Demand Response in Southwest Power Pool (January...

  14. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning Reserveand B. Kirby. 2012. The Demand Response Spinning Reserve

  15. Honeywell Demonstrates Automated Demand Response Benefits for...

    Office of Environmental Management (EM)

    Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility,...

  16. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01

    LBNL Commercial and Residential Demand Response Overview ofmarket [5]. Residential demand reduction programs have beenin the domain of residential demand response. There are a

  17. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    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.

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01

    hydro facility or demand response aggregator to provide theOperator Demand Response Mass-Market Customers Aggregator ofDemand Response Resources Mass Market Customers Aggregator

  19. Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann

    2005-01-01

    Fully Automated Demand Response Tests in Large Facilities”.also provided through the Demand Response Research Center (of Fully Automated Demand Response in Large Facilities”

  20. Automated Demand Response Technologies and Demonstration in New York City using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01

    C. McParland, "Open Automated Demand Response Communications2011. Utility & Demand Response Programs Energy ProviderAnnual Consumption (kWh) Demand Response Program Curtailment

  1. Demand Response for Ancillary Services

    Broader source: Energy.gov [DOE]

    Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and implement a methodology to construct detailed temporal and spatial representations of demand response resources and to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to assess economic value of the realizable potential of demand response for ancillary services.

  2. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

    Donnelly, Matt; Trudnowski, Daniel J.; Mattix, S.; Dagle, Jeffery E.

    2012-02-28

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

  3. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    Energy Efficiency, Demand Response, and Peak Load Managementdemand response, and load management programs in the Ebefore they undertake load management and demand response

  4. Demand Response Programs Oregon Public Utility Commission

    E-Print Network [OSTI]

    Demand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director;Demand Response Results, 2004 Load Control ­ Cool Keeper ­ ID Irrigation Load Control Price Responsive

  5. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01

    Monitoring in an Agent-Based Smart Home, Proceedings of theConference on Smart Homes and Health Telematics, September,Smart Meter Motion sensors Figure 1: Schematic of the Demand Response Electrical Appliance Manager in a Home.

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

  7. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01

    Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

  8. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

  9. Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis

    E-Print Network [OSTI]

    Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis CERTH, University Hegde, Laurent Massouli´e Technicolor Paris Research Lab Paris, France Abstract-- Demand response (DR the alternative option of dynamic demand adaptation. In this direction, demand response (DR) programs provide

  10. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

  11. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    retail regulatory authority prohibit such activity. Demand response integration into US wholesale power marketsretail or wholesale level. 17 While demand response began participating at scale in wholesale power markets

  12. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    demand response: ? Distribution utility ? ISO ? Aggregator (demand response less obstructive and inconvenient for the customer (particularly if DR resources are aggregated by a load aggregator).

  13. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

  14. Demand Response and Energy Efficiency 

    E-Print Network [OSTI]

    2009-01-01

    stream_source_info ESL-IC-09-11-05.pdf.txt stream_content_type text/plain stream_size 14615 Content-Encoding ISO-8859-1 stream_name ESL-IC-09-11-05.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Demand Response... 4 An Innovative Solution to Get the Ball Rolling ? Demand Response (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

  15. Optimal Demand Response and Power Flow

    E-Print Network [OSTI]

    Willett, Rebecca

    Optimal Demand Response and Power Flow Steven Low Computing + Math Sciences Electrical Engineering #12;Outline Optimal demand response n With L. Chen, L. Jiang, N. Li Optimal power flow n With S. Bose;Optimal demand response Model Results n Uncorrelated demand: distributed alg n Correlated demand

  16. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

  17. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01

    Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

  18. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

    and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

  20. Incorporating Demand Response into Western Interconnection Transmission Planning

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01

    Aggregator Programs. Demand Response Measurement andIncorporating Demand Response into Western Interconnection13 Demand Response Dispatch

  1. Assessment of Demand Response and Advanced Metering

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    #12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

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

    SciTech Connect (OSTI)

    Shen, Bo; Ghatikar, Girish; Ni, Chun Chun; Dudley, Junqiao; Martin, Phil; 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).

  3. Adaptive Demand Response: Online Learning of Restless and Controlled Bandits

    E-Print Network [OSTI]

    Liu, Mingyan

    Adaptive Demand Response: Online Learning of Restless and Controlled Bandits Qingsi Wang, Mingyan realized curtailment, not the curtailment of each load. We develop an adaptive demand response learning like UCB1. I. INTRODUCTION Electric loads participating in demand response programs provide a variety

  4. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    > B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Responseand integration is: Energy efficiency, energy conservation,

  5. Demand Response For Power System Reliability: FAQ

    SciTech Connect (OSTI)

    Kirby, Brendan J [ORNL

    2006-12-01

    Demand response is the most underutilized power system reliability resource in North America. Technological advances now make it possible to tap this resource to both reduce costs and improve. Misconceptions concerning response capabilities tend to force loads to provide responses that they are less able to provide and often prohibit them from providing the most valuable reliability services. Fortunately this is beginning to change with some ISOs making more extensive use of load response. This report is structured as a series of short questions and answers that address load response capabilities and power system reliability needs. Its objective is to further the use of responsive load as a bulk power system reliability resource in providing the fastest and most valuable ancillary services.

  6. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    none,

    2010-01-01

    Summarizes existing research and discusses current practices, opportunities, and barriers to coordinating energy efficiency and demand response programs.

  7. Demand And Response Transportation Rider's Guide

    E-Print Network [OSTI]

    Acton, Scott

    Demand And Response Transportation Rider's Guide http://www.virginia.edu/parking/disabilities/dart Version 14.5 (8/13/14) Welcome DART Rider: The Demand and Response Transportation (DART) Service rides: #12;Demand And Response Transportation Rider's Guide http

  8. INTEGRATION OF PV IN DEMAND RESPONSE

    E-Print Network [OSTI]

    Perez, Richard R.

    INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract the case that distributed PV generation deserves a substantial portion of the credit allotted to demand response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing

  9. Demand Response for Computing Jerey S. Chase

    E-Print Network [OSTI]

    Chase, Jeffrey S.

    Chapter 1 Demand Response for Computing Centers Jerey S. Chase Duke University 1.1 Introduction ............................................................... 3 1.2 Demand Response in the Emerging Smart Grid .......................... 5 1.2.1 Importance of Demand Response for Energy E ciency .......... 6 1.2.2 The Role of Renewable Energy

  10. Demand Response and Ancillary Services September 2008

    E-Print Network [OSTI]

    Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

  11. THE STATE OF DEMAND RESPONSE IN CALIFORNIA

    E-Print Network [OSTI]

    THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

  12. Demand Response Resources in Pacific Northwest

    E-Print Network [OSTI]

    Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

  13. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

  14. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    LBNL-2294E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J Ann Piette of Lawrence Berkeley National Laboratory's (LBNL) Demand Response Research Center (DRRC and Environment's (CIEE) Demand Response Emerging Technologies Development (DRETD) Program, under Work for Others

  15. THE STATE OF DEMAND RESPONSE IN CALIFORNIA

    E-Print Network [OSTI]

    THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

  16. Demand Response in the ERCOT Markets

    SciTech Connect (OSTI)

    Patterson, Mark

    2011-10-25

    ERCOT grid serves 85% of Texas load over 40K+ miles transmission line. Demand response: voluntary load response, load resources, controllable load resources, and emergency interruptible load service.

  17. Installation and Commissioning Automated Demand Response Systems

    SciTech Connect (OSTI)

    Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

    2008-04-21

    Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

  18. Direct versus Facility Centric Load Control for Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01

    Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

  19. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01

    of Fully Automated Demand  Response in Large Facilities.  Fully Automated Demand Response Tests in Large Facilities.  Open Automated  Demand Response Communication Standards: 

  20. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01

    Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

  1. Rates and technologies for mass-market demand response

    E-Print Network [OSTI]

    Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

    2002-01-01

    Roger. 2002. Using Demand Response to Link Wholesale andfor advanced metering, demand response, and dynamic pricing.EPRI. 2001. Managing Demand-Response To Achieve Multiple

  2. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01

    Goodin. 2009. “Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. ” InOpen Automated Demand Response Demonstration Project. LBNL-

  3. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

    A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

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

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01

    Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

  5. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01

    C. McParland, Open Automated Demand Response Communicationsand Open Automated Demand Response", Grid Interop Forum,Testing of Automated Demand Response for Integration of

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

    and Techniques for Demand Response. May 2007. LBNL-59975.to facilitate automating  demand response actions at the Interoperable Automated Demand Response Infrastructure,

  7. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Goli, Sasank

    2012-01-01

    and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

  8. Results and commissioning issues from an automated demand response pilot

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

    2004-01-01

    of Fully Automated Demand Response in Large Facilities"Management and Demand Response in Commercial Buildings", L Band Commissioning Issues from an Automated Demand Response.

  9. National Action Plan on Demand Response | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    Working Group (FUPWG) Fall 2008 meeting-discusses the National Assessment of Demand Response study, the National Action Plan for Demand Response, and demand response as...

  10. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

    2008-11-19

    Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

  11. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    3 3.0 Previous Experience with Demand Responsive Lighting11 4.3. Prevalence of Lighting13 4.4. Impact of Title 24 on Lighting

  12. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at*** ...

  13. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    National Action Plan for Energy Efficiency Energy efficiency programson energy efficiency program types, see National Action PlanNational Action Plan for Energy Efficiency Most demand response programs

  14. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    Demand  Response  Roadmap  Project   Final  Report  39   5.   Developing a Roadmap Actionproject was to develop a “roadmap” to guide the Hawaiian

  15. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19

    Jun 19, 2013 ... efficient linear programming formulation for the demand response of such a consumer who could be a price taker, industrial or commercial user ...

  16. BPA, Energy Northwest launch demand response pilot

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    BPA-Energy-Northwest-launch-demand-response-pilot Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand...

  17. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01

    conditioning. Figure 2: Wireless discharge air temperatureWireless Demand Response Controls for HVAC Systems Cliffordcontrol software and wireless hardware that could enable

  18. Using Partnerships to Drive Demand and Provide Services in Communities...

    Broader source: Energy.gov (indexed) [DOE]

    Program Multifamily and Low-Income Peer Exchange Call: Using Partnerships to Drive Demand and Provide Services in Communities, February 2, 2012. Call Slides and Discussion...

  19. Response to changes in demand/supply

    E-Print Network [OSTI]

    Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

  20. Response to changes in demand/supply

    E-Print Network [OSTI]

    Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

  1. Demand response in adjustment markets for electricity

    E-Print Network [OSTI]

    : electricity consumption, adjustment market, demand response, information asymmetry JEL codes: D11, D21, Q41 in the consumption of electric energy by retail customers from their expected consumption inDemand response in adjustment markets for electricity Claude Crampes and Thomas-Olivier Léautier

  2. Progress toward Producing Demand-Response-Ready Appliances

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.; Sastry, Chellury

    2009-12-01

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

  3. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    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.

  4. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    using existing utility load-management assets can provide anhow existing utility load-management assets can provide anutility load-management asset can be repositioned as a

  5. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    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 sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

  6. Response to several FOIA requests - Renewable Energy. Demand...

    Energy Savers [EERE]

    Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA...

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

    SciTech Connect (OSTI)

    Rochlin, Cliff

    2009-11-15

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

  8. PIER: Demand Response Research Center Director, Mary Ann Piette

    E-Print Network [OSTI]

    1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

  9. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    This study is a multi-national laboratory effort to assess the potential value of demand response and energy storage to electricity systems with different penetration levels of variable renewable...

  10. Capitalize on Existing Assets with Demand Response 

    E-Print Network [OSTI]

    Collins, J.

    2008-01-01

    Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demand response, the voluntary...

  11. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    and technology options should have general application across systems. However, MECO has unprecedented levels of wind energywind, solar, and clean energy initiatives have introduced many changes and created uncertainties that complicate utility demand response technology

  12. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    and Retails Electricity Markets in SPP The Southwest Powerand Retails Electricity Markets in SPP.3 2.1 Wholesale Markets in the Southwest PowerRetail Demand Response in SPP Wholesale Markets in the Southwest Power

  13. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

    Earle, Robert; Kahn, Edward P.; Macan, Edo

    2009-07-15

    Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

  14. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    using existing utility load-management assets can provide anhow existing utility load-management assets can provide anshow how a traditional utility load-management asset can be

  15. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    congestion or less-costly ancillary services provision; (4)economic, reliability and ancillary DR applications. Can theattributed to DR in providing ancillary services, improving

  16. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    Within 10 Minutes After Sudden Failure Of Two Generators inafter sudden failure of two generators in Texas. SpinningIn contrast, failure of a large generator to provide

  17. Commercial & Industrial Demand Response

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit the following comments response NAESB Business Practice

  18. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    NWS NYISO OAT PG&E PIER RAA SCADA SCE SDG&E SOAP UCLT WAPAControl and Data Acquisition (SCADA) rate at least partiallyFeeder Loads SCE provided SCADA load data for the targeted

  19. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01

    4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

  20. Analysis of Open Automated Demand Response Deployments in California

    E-Print Network [OSTI]

    LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

  1. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

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

    2011-04-29

    Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

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

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R; Ma, Ookie

    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.

  3. Demand Response and Electric Grid Reliability 

    E-Print Network [OSTI]

    Wattles, P.

    2012-01-01

    and Regional Transmission Organizations are the ?air traffic controllers? of the bulk electric power grids 4 Power supply (generation) must match load (demand) CATEE Conference October 10, 2012 ? The fundamental concept behind ERCOT operations... changes or incentives.? (FERC) ? ?Changes in electric use by demand-side resources from their normal consumption patterns in response to changes in the price of electricity, or to incentive payments designed to induce lower electricity use at times...

  4. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    2010-04-15

    The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

  5. FERC Presendation: Demand Response as Power System Resources...

    Broader source: Energy.gov (indexed) [DOE]

    Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as...

  6. SGDP Report Now Available: Interoperability of Demand Response...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response...

  7. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01

    efficiency, daily peak load management and demand response.Loads Efficiency, Daily Load Management and Demand ResponseOperations Peak Load Management (Daily) - TOU Savings - Peak

  8. Robust Unit Commitment Problem with Demand Response and ...

    E-Print Network [OSTI]

    2010-10-31

    Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... Key Words: unit commitment, demand response, wind energy, robust ...

  9. Demand Response and Smart Metering Policy Actions Since the Energy...

    Office of Environmental Management (EM)

    Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the...

  10. Demand Response and Energy Storage Integration Study - Past Workshops...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response and Energy Storage Integration Study - Past Workshops Demand Response and Energy Storage Integration Study - Past Workshops The project was initiated and informed...

  11. SGDP Report: Interoperability of Demand Response Resources Demonstrati...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February...

  12. ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES

    E-Print Network [OSTI]

    Gross, George

    ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

  13. SGDP Report Now Available: Interoperability of Demand Response...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response Resources...

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

    SciTech Connect (OSTI)

    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.

  15. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30

    The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

  16. ERCOT's Weather Sensitive Demand Response Pilot 

    E-Print Network [OSTI]

    Carter, T.

    2013-01-01

    Demand Response Pilot CATEE 12-17-13 ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Disclaimer The information contained in this report has been obtained from sources which Constellation New... services along with other information about our business is available online at constellation.com. ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Demand Response in ERCOT CATEE 121313 - Tim Carter...

  17. Demand Response Initiatives at CPS Energy 

    E-Print Network [OSTI]

    Luna, R.

    2013-01-01

    stream_source_info ESL-KT-13-12-53.pdf.txt stream_content_type text/plain stream_size 4780 Content-Encoding UTF-8 stream_name ESL-KT-13-12-53.pdf.txt Content-Type text/plain; charset=UTF-8 Demand Response Initiatives... and Toyota combined. • Schools & Universities contributed 6 MW’s of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168,572 ESL-KT-13-12-53 CATEE 2013...

  18. Retail Demand Response in Southwest Power Pool

    SciTech Connect (OSTI)

    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 among SPP members. For these entities, investment in DR is often driven by the need to reduce summer peak demand that is used to set demand charges for each distribution cooperative. o About 65-70percent of the interruptible/curtailable tariffs and DLC programs are routinely triggered based on market conditions, not just for system emergencies. Approximately, 53percent of the DR resources are available with less than two hours advance notice and 447 MW can be dispatched with less than thirty minutes notice. o Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels ranged from $0.40 to $8.30/kW-month for interruptible rate tariffs and $0.30 to $4.60/kW-month for DLC programs. A few interruptible programs offered incentive payments which were explicitly linkedto actual load reductions during events; payments ranged from 2 to 40 cents/kWh for load curtailed.

  19. An Operational Model for Optimal NonDispatchable Demand Response

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    An Operational Model for Optimal NonDispatchable Demand Response for Continuous PowerintensiveFACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power: To balance supply and demand of a power system, one can manipulate both: supply and demand demand response

  20. Demand Response Enabling Technologies and Approaches for Industrial Facilities 

    E-Print Network [OSTI]

    Epstein, G.; D'Antonio, M.; Schmidt, C.; Seryak, J.; Smith, C.

    2005-01-01

    , there are also huge opportunities for demand response in the industrial sector. This paper describes some of the demand response initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

  1. Demand Response Projects: Technical and Market Demonstrations

    E-Print Network [OSTI]

    signal · Reinforces conservation program efforts in areas such as insulation and heat pumps Voluntary DR Commercial & Industrial DR Pilot ­ Internet communication/control of imbedded load control devices on up storage Commercial & Industrial DR Pilot (8 customers)* · Open Automated Demand Response Communication

  2. Demand Response This is the first of the Council's power plans to treat demand response as a resource.1

    E-Print Network [OSTI]

    . WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding. Demand response as defined here does not include involuntary curtailment imposed on electricity users to conditions in wholesale power markets, its electricity demand is not. This situation has a number of adverse

  3. Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes

    E-Print Network [OSTI]

    Sastry, S. Shankar

    Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

  4. Risk Management and Combinatorial Optimization for Large-Scale Demand Response and Renewable Energy Integration

    E-Print Network [OSTI]

    Yang, Insoon

    2015-01-01

    results: demand response . . . . . . . . . . . . . . . . . .Institute. “Automated Demand Response Today”. In: (2012). [Energy. “Benefits of demand response in electricity markets

  5. Autonomous Demand Response in Heterogeneous Smart Grid Topologies

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    1 Autonomous Demand Response in Heterogeneous Smart Grid Topologies Hamed Narimani and Hamed-mails: narimani-hh@ec.iut.ac.ir and hamed@ee.ucr.edu Abstract--Autonomous demand response (DR) is scalable and has demand response systems in heterogeneous smart grid topologies. Keywords: Autonomous demand response

  6. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03

    The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

  7. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14

    Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

  8. Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids

    E-Print Network [OSTI]

    Trumpf, Jochen

    Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids Paul Scott Methodologies]: Artificial Intelligence Keywords OPF; ADMM; demand response; distributed control; micro- grid-coupled behaviours. In this new regime demand response (DR) techniques will play a central role in providing

  9. (2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via

    E-Print Network [OSTI]

    Wierman, Adam

    2013-01-01

    (2013) 1­28 Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting.chen@hp.com Abstract Demand response is a crucial aspect of the future smart grid. It has the potential to provide centers' participation in demand response is becoming increasingly important given their high

  10. The Role of Demand Response Policy Forum Series

    E-Print Network [OSTI]

    California at Davis, University of

    The Role of Demand Response Policy Forum Series Beyond 33 Percent: California's Renewable Future and Demand Response #12;Historic focus on Seasonal Grid Stress PG&E Demand Bid Test Day 0 2000 4000 6000 8000 Communication Latency #12;Bottom Up Review of End-Use Loads for Demand Response 5 Commercial Residential

  11. Price-responsive demand management for a smart grid world

    SciTech Connect (OSTI)

    Chao, Hung-po

    2010-01-15

    Price-responsive demand is essential for the success of a smart grid. However, existing demand-response programs run the risk of causing inefficient price formation. This problem can be solved if each retail customer could establish a contract-based baseline through demand subscription before joining a demand-response program. (author)

  12. A Simulation Study of Demand Responsive Transit System Design

    E-Print Network [OSTI]

    Dessouky, Maged

    A Simulation Study of Demand Responsive Transit System Design Luca Quadrifoglio, Maged M. Dessouky changed the landscape for demand responsive transit systems. First, the demand for this type of transit experiencing increased usage for demand responsive transit systems. The National Transit Summaries and Trends

  13. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

  14. Optimal Design of Demand-Responsive Feeder Transit Services 

    E-Print Network [OSTI]

    Li, Xiugang

    2010-10-12

    The general public considers Fixed-Route Transit (FRT) to be inconvenient while Demand-Responsive Transit (DRT) provides much of the desired flexibility with a door-to-door type of service. However, FRT is typically more cost efficient than DRT...

  15. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

  16. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect (OSTI)

    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

  17. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    electricity. In this manner, demand side management is directly integrated into the wholesale capacity marketcapacity market U.S. Federal Energy Regulatory Commission Florida Reliability Coordinating Council incremental auctions independent electricity

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

    SciTech Connect (OSTI)

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

    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.

  19. 2014 Navigant Consulting, Inc. Assessing Demand Response (DR)

    E-Print Network [OSTI]

    © 2014 Navigant Consulting, Inc. Assessing Demand Response (DR) Program Potential for the Seventh;Assessing Demand Response (DR) Program Potential for the Seventh Power Plan Page i Updated Final Report

  20. Demand Response: Lessons Learned with an Eye to the Future |...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Demand Response: Lessons Learned with an Eye to the Future Demand Response: Lessons Learned with an Eye to the Future July 11, 2013 - 11:56am Addthis Patricia A. Hoffman Patricia...

  1. Optimization of Demand Response Through Peak Shaving , D. Craigie

    E-Print Network [OSTI]

    Todd, Michael J.

    Optimization of Demand Response Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demand response of such a consumer. We will establish a monotonicity result that indicates fuel supply

  2. Grid Integration of Aggregated Demand Response, Part I: Load Availability

    E-Print Network [OSTI]

    LBNL-6417E Grid Integration of Aggregated Demand Response, Part I: Load Availability Profiles Resources 4 #12;#12;#12;CHAPTER 3: Results: DR Profiles 3.1 Projected Demand Response Availability in 2020

  3. A National Forum on Demand Response: Results on What Remains...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Forum on Demand Response: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group A National Forum on Demand Response: Results on What...

  4. Quantifying the Variable Effects of Systems with Demand Response Resources

    E-Print Network [OSTI]

    Gross, George

    Quantifying the Variable Effects of Systems with Demand Response Resources Anupama Kowli and George in the electricity industry. In particular, there is a new class of consumers, called demand response resources (DRRs

  5. Demand Response Opportunities and Enabling Technologies for Data

    E-Print Network [OSTI]

    LBNL-5763E Demand Response Opportunities and Enabling Technologies for Data Centers: Findings from in this report was coordinated by the Lawrence Berkeley National Laboratory (LBNL) Demand Response Research

  6. Provide Virtual Distributed Environments for Grid Computing on Demand

    E-Print Network [OSTI]

    The eect of compression on performance in a demand paging operating system Allen Wynn, Jie Wu the eciency of I/O in order to improve overall system performance. In a demand paging operating system: Demand paging; Compression; Operating system; Page-replacement policy 1. Introduction 1.1. Motivation

  7. A First Look at Colocation Demand Response Shaolei Ren

    E-Print Network [OSTI]

    Ren, Shaolei

    A First Look at Colocation Demand Response Shaolei Ren Florida International University Mohammad A. Islam Florida International University ABSTRACT Large data centers can participate in demand response, the existing research has only considered demand response by owner-operated data centers (e.g., Google

  8. Consumer Targeting in Residential Demand Response James C. Holyhead

    E-Print Network [OSTI]

    Molinari, Marc

    Consumer Targeting in Residential Demand Response Programmes James C. Holyhead Agents, Interaction and Computer Science University of Southampton, UK acr@ecs.soton.ac.uk ABSTRACT Demand response refers. In this paper we propose a novel approach to residential demand response, in which incentives are targeted

  9. Optimal Power Flow Based Demand Response Offer Price Optimization

    E-Print Network [OSTI]

    Lavaei, Javad

    Optimal Power Flow Based Demand Response Offer Price Optimization Zhen Qiu 1 Introduction-time energy balance. Demand response programs are offered by the utility companies to reduce the load response cost in exchange for load reduction. A considerable amount of papers have discussed the demand

  10. Optimal Demand Response Based on Utility Maximization in Power Networks

    E-Print Network [OSTI]

    Wierman, Adam

    Optimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen different appliances including PHEVs and batteries and propose a demand response approach based on utility. The utility company can thus use dynamic pricing to coordinate demand responses to the benefit of the overall

  11. Optimal Demand Response Capacity of Automatic Lighting Control

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    1 Optimal Demand Response Capacity of Automatic Lighting Control Seyed Ataollah Raziei and Hamed-mails: razieis1@udayton.edu and hamed@ee.ucr.edu Abstract--Demand response programs seek to ad- just the normal prior studies have extensively studied the capacity of offering demand response in buildings

  12. Opportunities and Challenges for Data Center Demand Response

    E-Print Network [OSTI]

    Low, Steven H.

    Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

  13. Two Market Models for Demand Response in Power Networks

    E-Print Network [OSTI]

    Wierman, Adam

    Two Market Models for Demand Response in Power Networks Lijun Chen, Na Li, Steven H. Low and John C-- In this paper, we consider two abstract market models for designing demand response to match power supply as oligopolistic markets, and propose distributed demand response algorithms to achieve the equilibria. The models

  14. A Visualization Aid for Demand Response Studies in the Smart

    E-Print Network [OSTI]

    Maciejewski, Anthony A. "Tony"

    A Visualization Aid for Demand Response Studies in the Smart Grid With the influx of data in the emerging smart grid due to technologies such as smart meters and demand response programs, it is more for quantifying and comparing the effectiveness and profitability of a given set of solutions to a demand response

  15. Optimal demand response: problem formulation and deterministic case

    E-Print Network [OSTI]

    Low, Steven H.

    Optimal demand response: problem formulation and deterministic case Lijun Chen, Na Li, Libin Jiang load through real-time demand response and purchases balancing power on the spot market to meet, optimal demand response reduces to joint scheduling of the procurement and consumption decisions

  16. Greening Multi-Tenant Data Center Demand Response Niangjun Chen

    E-Print Network [OSTI]

    Ren, Shaolei

    Greening Multi-Tenant Data Center Demand Response Niangjun Chen , Xiaoqi Ren , Shaolei Ren , Adam resources for emergency demand response (EDR). However, currently, data centers typically participate in EDR. In this paper, we focus on "greening" demand response in multi-tenant data centers by incentivizing ten- ants

  17. Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson University of California an efficient demand response HVAC control strategy, actual room usage must be considered. Temperature and CO2 are used for simulations but not for predictive demand response strategies. In this paper, we develop

  18. Date: June 12, 2007 To: Pacific Northwest Demand Response Project

    E-Print Network [OSTI]

    Date: June 12, 2007 To: Pacific Northwest Demand Response Project From: Rich Sedano/RAP and Chuck, 2007 meeting of the Pacific Northwest Demand Response Project, we agreed to form three Working Groups for the evaluation of cost-effectiveness of Demand Response resources. One potential outcome would be for state

  19. Demand Response Opportunities in Industrial Refrigerated Warehouses in

    E-Print Network [OSTI]

    LBNL-4837E Demand Response Opportunities in Industrial Refrigerated Warehouses in California Sasank thereof or The Regents of the University of California. #12;Demand Response Opportunities in Industrial centralized control systems can be excellent candidates for Automated Demand Response (Auto- DR) due

  20. A Successful Implementation with the Smart Grid: Demand Response Resources

    E-Print Network [OSTI]

    Gross, George

    1 A Successful Implementation with the Smart Grid: Demand Response Resources Contribution of intelligent line switching, demand response resources (DRRs), FACTS devices and PMUs is key in the smart grid events as a result of voluntary load curtailments. Index Terms--Electricity Markets, Demand Response re

  1. Opportunities, Barriers and Actions for Industrial Demand Response in

    E-Print Network [OSTI]

    LBNL-1335E Opportunities, Barriers and Actions for Industrial Demand Response in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the Demand Response Demand Response in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

  2. Examining Uncertainty in Demand Response Baseline Models and

    E-Print Network [OSTI]

    LBNL-5096E Examining Uncertainty in Demand Response Baseline Models and Variability in Automated of California. #12;Examining Uncertainty in Demand Response Baseline Models and Variability in Automated.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR

  3. An Integrated Architecture for Demand Response Communications and Control

    E-Print Network [OSTI]

    Gross, George

    An Integrated Architecture for Demand Response Communications and Control Michael LeMay, Rajesh for the MGA and ZigBee wireless communications. Index Terms Demand Response, Advanced Meter Infrastructure. In principle this can be done with demand response techniques in which electricity users take measures

  4. EnerNOC Inc. Commercial & Industrial Demand Response

    E-Print Network [OSTI]

    © EnerNOC Inc. Commercial & Industrial Demand Response: An Overview of the Utility/Aggregator Business Model Pacific Northwest Demand Response Project April 28, 2011 #12;22 Agenda Introduction Ener #12;77 Whos EnerNOC? Market Leader in C&I Demand Response and Industrial Energy Efficiency More than

  5. 2008-2010 Research Summary: Analysis of Demand Response

    E-Print Network [OSTI]

    LBNL-5680E 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California. · #12;· · · 1.1. Role of the Demand Response Research Center · · · · · · #12;Figure 2: Discovery Process Treatment Facility Controls #12;2.1.2. Automated Demand Response Strategies #12;2.1.3. San Luis Rey

  6. Assessing the Control Systems Capacity for Demand Response in

    E-Print Network [OSTI]

    LBNL-5319E Assessing the Control Systems Capacity for Demand Response in California Industries in this report was coordinated by the Demand Response Research Center and funded by the California Energy of the Demand Response Research Center Industrial Controls Experts Working Group: · Jim Filanc, Southern

  7. Examining Synergies between Energy Management and Demand Response: A

    E-Print Network [OSTI]

    LBNL-5719E Examining Synergies between Energy Management and Demand Response: A Case Study at Two Summary #12;Introduction Energy Management · · · · · · · · · · #12;Demand Response #12;#12;Bentley Prince-Project Personnel Changes #12;Enablement of Demand Response Capabilities due to Energy Management Improvement

  8. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    LBNL-6014E LEED Demand Response Credit: A Plan for Research towards Implementation Sila Kiliccote thereof or The Regents of the University of California. #12;LEED Demand Response Credit: A Plan H. Dudley1 , Heather Langford3 1 Demand Response Research Center, Lawrence Berkeley National

  9. Fast Automated Demand Response to Enable the Integration of Renewable

    E-Print Network [OSTI]

    LBNL-5555E Fast Automated Demand Response to Enable the Integration of Renewable Resources David S The work described in this report was coordinated by the Demand Response Research Center and funded ABSTRACT This study examines how fast automated demand response (AutoDR) can help mitigate grid balancing

  10. Opportunities for Energy Efficiency and Demand Response in the California

    E-Print Network [OSTI]

    LBNL-4849E Opportunities for Energy Efficiency and Demand Response in the California Cement in this report was coordinated by the Demand Response Research Center and funded by the California Energy. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry. PIER Industrial

  11. Opportunities for Demand Response in California Agricultural Irrigation: A

    E-Print Network [OSTI]

    LBNL-6108E Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study was sponsored in part by the Demand Response Research Center which is funded by the California .................................. 2 Best Opportunities for Demand Response and Permanent Load Shifting Programs.............. 3

  12. Field Demonstration of Automated Demand Response for Both Winter and

    E-Print Network [OSTI]

    LBNL-6216E Field Demonstration of Automated Demand Response for Both Winter and Summer Events;1 Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings of a series of field test of automated demand response systems in large buildings in the Pacific Northwest

  13. Factors Influencing Productivity and Operating Cost of Demand Responsive Transit

    E-Print Network [OSTI]

    Dessouky, Maged

    Factors Influencing Productivity and Operating Cost of Demand Responsive Transit Kurt Palmer Maged of the Americans with Disabilities Act in 1991 operating expenses for Demand Responsive Transit have more than and practices upon productivity and operating cost. ii #12;1 Introduction Demand Responsive Transit (DRT

  14. Optimal Demand Response with Energy Storage Management

    E-Print Network [OSTI]

    Huang, Longbo; Ramchandran, Kannan

    2012-01-01

    In this paper, we consider the problem of optimal demand response and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic programming, which is often complex in computation and requires substantial statistical information of the system dynamics. We instead develop a low-complexity algorithm called Demand Response with Energy Storage Management (DR-ESM). DR-ESM does not require any statistical knowledge of the system dynamics, including the renewable energy and the power prices. It only requires the entity to solve a small convex optimization pr...

  15. Overview of Demand Side Response | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    Partnership Working Group (FUPWG) Fall 2008 meeting-discusses the utility PJM's demand side response (DSR) capabilities, including emergency and economic responses....

  16. Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Kalsi, Karanjit; Fuller, Jason C.; Elizondo, Marcelo A.; Chassin, David P.

    2012-07-22

    Due to the potentially large number of Distributed Energy Resources (DERs) – demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the fast transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies. On the other hand, a less complex model is more amenable to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop aggregated models for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response and other time varying effects of the system. The aggregated model efficiently includes statistical information of the population and accounts for a second order effect necessary to accurately capture the collective dynamic behavior. The developed aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions caused due to temperature set point changes.

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

    SciTech Connect (OSTI)

    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.

  18. Towards Continuous Policy-driven Demand Response in Data Centers

    E-Print Network [OSTI]

    Shenoy, Prashant

    Towards Continuous Policy-driven Demand Response in Data Centers David Irwin, Navin Sharma, and Prashant Shenoy University of Massachusetts, Amherst {irwin,nksharma,shenoy}@cs.umass.edu ABSTRACT Demand response (DR) is a technique for balancing electricity sup- ply and demand by regulating power consumption

  19. Measurement and evaluation techniques for automated demand response demonstration

    SciTech Connect (OSTI)

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

    2004-08-01

    The recent electricity crisis in California and elsewhere has prompted new research to evaluate demand response strategies in large facilities. This paper describes an evaluation of fully automated demand response technologies (Auto-DR) in five large facilities. Auto-DR does not involve human intervention, but is initiated at a facility through receipt of an external communications signal. This paper summarizes the measurement and evaluation of the performance of demand response technologies and strategies in five large facilities. All the sites have data trending systems such as energy management and control systems (EMCS) and/or energy information systems (EIS). Additional sub-metering was applied where necessary to evaluate the facility's demand response performance. This paper reviews the control responses during the test period, and analyzes demand savings achieved at each site. Occupant comfort issues are investigated where data are available. This paper discusses methods to estimate demand savings and results from demand response strategies at five large facilities.

  20. The Pacific Northwest Demand Response Market Demonstration

    SciTech Connect (OSTI)

    Chassin, David P.; Hammerstrom, Donald J.; DeSteese, John G.

    2008-07-20

    This paper describes the implementation and results of a field demonstration wherein residential electric water heaters and thermostats, commercial building space conditioning, municipal water pump loads, and several distributed generators were coordinated to manage constrained feeder electrical distribution through the two-way communication of load status and electric price signals. The field demonstration took place in Washington and Oregon and was paid for by the U.S. Department of Energy and several northwest utilities. Price is found to be an effective control signal for managing transmission or distribution congestion. Real-time signals at 5-minute intervals are shown to shift controlled load in time. The behaviors of customers and their responses under fixed, time-ofuse, and real-time price contracts are compared. Peak loads are effectively reduced on the experimental feeder. A novel application of portfolio theory is applied to the selection of an optimal mix of customer contract types. Index Terms—demand response, power markets, retail markets, distribution automation, distributed resources, load control.

  1. Risk Management and Combinatorial Optimization for Large-Scale Demand Response and Renewable Energy Integration

    E-Print Network [OSTI]

    Yang, Insoon

    2015-01-01

    Demand Response and Renewable Energy Integration by InsoonDemand Response and Renewable Energy Integration CopyrightDemand Response and Renewable Energy Integration by Insoon

  2. California DREAMing: the design of residential demand responsive technology with people in mind

    E-Print Network [OSTI]

    Peffer, Therese E.

    2009-01-01

    majority of existing residential demand response programs inas evidence that residential demand response can “empowerthat facilitates residential demand response in order to

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01

    to  Automated  Demand   Response  and  the  OpenADR  ®  Automated  Demand  Response  Program.   https://Data  for  Automated  Demand  Response  in  Commercial  

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01

    and Open Automated Demand Response. In Grid Interop Forum.Berkeley National Laboratory. Demand Response ResearchCenter, Demand Response Research Center PIER Team Briefing,

  5. Unlocking the potential for efficiency and demand response through advanced metering

    E-Print Network [OSTI]

    Levy, Roger; Herter, Karen; Wilson, John

    2004-01-01

    Advanced Metering, Demand Response, and Dynamic Pricing. ”for Efficiency and Demand Response through Advanced Meteringenergy efficiency and demand response programs. Without

  6. When it comes to Demand Response, is FERC its Own Worst Enemy?

    E-Print Network [OSTI]

    Bushnell, James; Hobbs, Benjamin; Wolak, Frank A.

    2009-01-01

    made between traditional demand response (DR) programs andpricing. Traditional demand response programs typically payFor overviews of demand response technologies and program

  7. Design and Implementation of an Open, Interoperable Automated Demand Response Infrastructure

    E-Print Network [OSTI]

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

    2008-01-01

    of Fully Automated Demand Response in Large Facilities. CEC-Fully Automated Demand Response Tests in Large Facilities.Management and Demand Response in Commercial Building. ,

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

    E-Print Network [OSTI]

    Piette, Mary Ann; Kiliccote, Sila

    2006-01-01

    Energy. “Benefits of Demand Response in Electricity MarketsEnergy Efficiency and Demand Response?7 3.1.Demand Response in Commercial

  9. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01

    S.  Kiliccote.   Estimating Demand Response Load  Impacts: in California.   Demand Response Research Center, Lawrence and Techniques for Demand Response.  LBNL Report 59975.  

  10. 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry

    E-Print Network [OSTI]

    Goli, Sasank

    2013-01-01

    K.C. Mares, D. Shroyer. 2010. Demand Response andOpen Automated Demand Response Opportunities for Dataand the Role of Automated Demand Response. Lawrence Berkeley

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

    E-Print Network [OSTI]

    Page, Janie

    2012-01-01

    2010 Assessment of Demand Response and  Advanced Metering:  Development for Demand Response  Calculation ? Findings and Energy  Efficiency and  Demand Response with Communicating 

  12. Estimating Demand Response Market Potential Among Large Commercial and Industrial Customers: A Scoping Study

    E-Print Network [OSTI]

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

    2007-01-01

    of Program Participation Rates on Demand Response MarketTable 3-1. Methods of Estimating Demand Response PenetrationDemand Response

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01

    for Automated Demand Response in Commercial Buildings. ” In2010. “Open Automated Demand Response Dynamic Pricing2009. “Open Automated Demand Response Communications

  14. Analytical Frameworks to Incorporate Demand Response in Long-term Resource Planning

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01

    Cost- effectiveness of Demand Response. ” Prepared for theon the National Action Plan on Demand Response, February.Role of Automated Demand Response. ” LBNL-4189E, November.

  15. What China Can Learn from International Experiences in Developing a Demand Response Program

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    K.C. Mares, D. Shroyer. , 2010. Demand Response andOpen Automated Demand Response Opportunities for DataProcessing Industry Demand Response Participation: A Scoping

  16. A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats

    E-Print Network [OSTI]

    Herter, Karen

    2010-01-01

    to everyone at the Demand Response Research Center, theEnergy Efficiency and Demand Response with CommunicatingEnergy Efficiency and Demand Response with Communicating

  17. Fast Automated Demand Response to Enable the Integration of Renewable Resources

    E-Print Network [OSTI]

    Watson, David S.

    2013-01-01

    Consulting), and Dave Shroyer (SCG). Demand Response andOpen Automated Demand Response Opportunities for DataIAW Research Team, Demand Response Research Center, Lawrence

  18. Cooperative Demand Response Using Repeated Game for Price-Anticipating Buildings in Smart Grid

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    E. El-Saadany, “A summary of demand response in electricityYang, and X. Guan, “Optimal demand response scheduling withwith application to demand response,” IEEE Transactions on

  19. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01

    Energy Resources and Demand Response under Uncertainty AfzalEnergy Resources and Demand Response under Uncertainty ?DER in conjunction with demand response (DR): the expected

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

    E-Print Network [OSTI]

    Marks, Gary

    2014-01-01

    Grower Acceptance of Demand Response and Permanent LoadCommission. (n.d. ). Demand Response. Retrieved fromLead Product Manager, Demand Response Department, Pacific

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01

    Laboratory. Berkeley. Demand Response Research Center,and Automated Demand Response in Wastewater TreatmentLaboratory. Berkeley. Demand Response Research Center,

  2. Field Test Results of Automated Demand Response in a Large Office Building

    E-Print Network [OSTI]

    Han, Junqiao

    2008-01-01

    and Techniques for Demand Response, LBNL-59975, May 2007 [Protocol Development for Demand Response Calculation – Findsand S. Kiliccote, Estimating Demand Response Load Impacts:

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

    E-Print Network [OSTI]

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

    2004-01-01

    Development for Demand Response Calculation - Findings and2003. “Dividends with Demand Response. ” ASHRAE Journal,Management and Demand Response in Commercial Buildings. ”

  4. Architecture Concepts and Technical Issues for an Open, Interoperable Automated Demand Response Infrastructure

    E-Print Network [OSTI]

    Koch, Ed; Piette, Mary Ann

    2008-01-01

    energy efficiency and demand response in large facilities.was sponsored by the Demand Response Research Center whichInteroperable Automated Demand Response Infrastructure Ed

  5. Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann; Hansen, David

    2006-01-01

    of Fully Automated Demand Response in Large Facilities”NYSERDA) and the Demand Response Research Center (LLC “Working Group 2 Demand Response Program Evaluation –

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01

    Goldman, G. (2009) Retail demand response in Southwest PowerCoordination of retail demand response with Midwest ISO2010. 110 pages. Demand Response and Variable Generation

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

    E-Print Network [OSTI]

    Lekov, Alex

    2009-01-01

    your Power. (2008). "Demand Response Programs." RetrievedS. (2008). Automated Demand Response Results from Multi-Yearusing Open Automated Demand Response, California Energy

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    Open Automated Demand Response Demonstration Project” LBNL-2009a). “Open Automated Demand Response Communications inand Actions for Industrial Demand Response in California. ”

  9. California DREAMing: the design of residential demand responsive technology with people in mind

    E-Print Network [OSTI]

    Peffer, Therese E.

    2009-01-01

    Advanced Metering and Demand Response in ElectricityChen, X. (2008). Demand Response-enabled Autonomous Controlfor Thermal Comfort, Demand Response, and Reduced Annual

  10. Price Responsive Demand in New York Wholesale Electricity Market using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01

    Advanced Metering, and Demand Response in Electricity2006. Benefits of Demand Response in Electricity Markets and2010. Open Automated Demand Response Technologies for

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

    E-Print Network [OSTI]

    Herter, Karen

    2010-01-01

    Martin Aspen. 2006. Demand Response Enabling TechnologiesDon. 2007. “Pricing for Demand Response from Residential andthe Level of Demand Response,” Power Point Presentation, 24

  12. A Cooperative Demand Response Scheme Using Punishment Mechanism and Application to Industrial Refrigerated Warehouses

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    Z. Yang, and Y. Zhang, “Demand response man- agement withwith application to demand response,” IEEE Transactions onand automated demand response in industrial refrigerated

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01

    to  Automated  Demand   Response  and  the  OpenADR  ®  Automated  Demand  Response  Program.   https://2009a.   Open  Automated  Demand  Response  Communications  

  14. Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01

    2008. Estimating Demand Response Load Impacts: Evaluation ofK. C. Mares, and D. Shroyer. 2010. Demand Response andOpen Automated Demand Response Opportunities for Data

  15. Intelligent Building Energy Information and Control Systems for Low-Energy Operations and Optimal Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2014-01-01

    Open  Automated  Demand  Response  Communications from  7 Years of Automated Demand Response in Commercial Management and Demand Response in Commercial  Buildings. , 

  16. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Chuck; Neenan, Bernie

    2006-03-10

    Dynamic retail electricity pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response often appears to be an afterthought. But that may be changing as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period, during which utilities were required to offer a default or ''standard offer'' generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached, or are nearing, the end of their transitional period and several states have adopted an RTP-type default service for large commercial and industrial (C&I) customers. Are these initiatives motivated by the desire to induce greater demand response, or is RTP being called upon to serve a different role in competitive markets? Surprisingly, we found that in most cases, the primary reason for adopting RTP as the default service was not to encourage demand response, but rather to advance policy objectives related to the development of competitive retail markets. However, we also find that, if efforts are made in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This paper, which draws from a lengthier report, describes the experience to date with default RTP in the U.S., identifying findings related to its actual and potential role as an instrument for cultivating price responsive demand [1]. For each of the five states currently with default RTP, we conducted a detailed review of the regulatory proceedings leading to its adoption. To further understand the intentions and expectations of those involved in its design and implementation, we also interviewed regulatory staff and utilities in each state, as well as eight of the most prominent competitive retail suppliers operating in these markets which, together, comprised about 60-65% of competitive C&I sales in the U.S. in 2004 [2].

  17. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    for decades. In the US, load management and interruptible/primary interest in load management was driven in part byresponse (DR) is a load management tool which provides a

  18. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2005-11-09

    Dynamic retail pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response has been an afterthought, and in some cases not given any weight at all. But that may be changing, as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period during which utilities were required to offer a default or standard offer generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached the end of their transitional period, and several have adopted or are actively considering an RTP-type default service for large commercial and industrial (C&I) customers. In most cases, the primary reason for adopting RTP as the default service has been to advance policy objectives related to the development of competitive retail markets. However, if attention is paid in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This article, which draws from a lengthier report, describes experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price responsive demand.1 As of summer 2005, default service RTP was in place or approved for future implementation in five U.S. states: New Jersey, Maryland, Pennsylvania, New York, and Illinois. For each of these states, we conducted a detailed review of the regulatory proceedings leading to adoption of default RTP and interviewed regulatory staff and utilities in these states, as well as eight competitive retail suppliers active in these markets.

  19. Demand Response in the West: Lessons for States and Provinces

    SciTech Connect (OSTI)

    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.

  20. SGDP Report: Interoperability of Demand Response Resources Demonstrati...

    Broader source: Energy.gov (indexed) [DOE]

    Interoperability of Demand Response Resources Demonstration in NY was awarded to Con Edison in 2009 as part of DOE's Smart Grid Demonstration Project (SGDP) grants funded by the...

  1. Robust Unit Commitment Problem with Demand Response and ...

    E-Print Network [OSTI]

    Oct 31, 2010 ... Robust Unit Commitment Problem with Demand Response and Wind Energy. Long Zhao(longzhao ***at*** mail.usf.edu) Bo Zeng(bozeng ...

  2. Coordination of Energy Efficiency and Demand Response: A Resource...

    Open Energy Info (EERE)

    Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

  3. The Role of Demand Response in Default Service Pricing

    E-Print Network [OSTI]

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2008-01-01

    service for competitive retail markets, demand response hasimportant juncture in retail market design. Most states withof competitive retail markets. However, if attention is paid

  4. The Role of Demand Response in Default Service Pricing

    E-Print Network [OSTI]

    Barbose, Galen; Goldman, Chuck; Neenan, Bernie

    2006-01-01

    for competitive retail markets, demand response oftenimportant juncture in retail market design. Most states withdevelopment of competitive retail markets. However, we also

  5. Retail Demand Response in Southwest Power Pool | Department of...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region. Retail Demand Response in Southwest Power Pool More Documents &...

  6. Robust Unit Commitment Problem with Demand Response and ...

    E-Print Network [OSTI]

    Long Zhao

    2010-10-31

    Oct 31, 2010 ... Abstract: To improve the efficiency in power generation and to reduce the greenhouse gas emission, both Demand Response (DR) strategy ...

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

    for demand response and metal castings, food processing,industrial gases, metal casting, petroleum refining, pulpMetal plating, finishing Metal casting of specialized parts

  8. Benefits of Demand Response in Electricity Markets and Recommendations...

    Office of Environmental Management (EM)

    incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized. Benefits of Demand Response in Electricity...

  9. National Action Plan on Demand Response, June 2010 | Department...

    Broader source: Energy.gov (indexed) [DOE]

    Energy Regulatory Commission (FERC) is required to develop the National Action Plan on Demand Response (National Action Plan) as outlined in section 529 of the Energy...

  10. Demand Response Resources for Energy and Ancillary Services (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01

    2009. Open Automated Demand Response Communications2010. Open Automated Demand Response Technologies forenergy efficiency and demand response: Framework concepts

  12. The Impact of Control Technology on the Demand Response Potential of California Industrial Refrigerated Facilities Final Report

    E-Print Network [OSTI]

    Scott, Doug

    2014-01-01

    and Automated Demand Response in Industrial RefrigeratedDemand Response .. ..Technology on the Demand Response Potential of California

  13. Value of Demand Response -Introduction Klaus Skytte

    E-Print Network [OSTI]

    -of-supply and DR 15 minutes DaysHoursSeconds Adjustments of planned production Prognosis errors Excess capacity in demand to prices. Similar to Least-cost planning and demand-side management. DR differs by using prices: Curtailment of load, Direct load control, e.g. central control of electric comfort heating. Reservation prices

  14. Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnection

    Broader source: Energy.gov [DOE]

    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.

  15. Optimal Demand Response Based on Utility Maximization in Power Networks

    E-Print Network [OSTI]

    Low, Steven H.

    -- Demand side management will be a key component of future smart grid that can help reduce peak load interesting properties of the proposed scheme. I. INTRODUCTION Demand side management will be a key componentOptimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen

  16. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01

    program, demand  response aggregator, demand response  vii WITH AN AGGREGATOR USING OPEN AUTOMATED DEMAND RESPONSE ThisWith an Aggregator Using Open Automated Demand Response is 

  17. PIER Demand Response Research Center SCOPING STUDY ROUNDTABLE RESEARCH TARGET AREAS

    E-Print Network [OSTI]

    PIER Demand Response Research Center SCOPING STUDY ROUNDTABLE ­ RESEARCH TARGET AREAS (Draft Areas #12;PIER Demand Response Research Center SCOPING STUDY ROUNDTABLE ­ RESEARCH TARGET AREAS (Draft the Value of Demand Response: Develop an Integrated Efficiency / Demand Response Framework Introduction

  18. What China Can Learn from International Experiences in Developing a Demand Response Program

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    2012. Addressing Electricity Demand through Demand Response:has been driving up the electricity demand while widespreadexperiences in addressing electricity demand This section is

  19. Integration of Renewables Via Demand Management: Highly Dispatchable and Distributed Demand Response for the Integration of Distributed Generation

    SciTech Connect (OSTI)

    2012-02-11

    GENI Project: AutoGrid, in conjunction with Lawrence Berkeley National Laboratory and Columbia University, will design and demonstrate automated control software that helps manage real-time demand for energy across the electric grid. Known as the Demand Response Optimization and Management System - Real-Time (DROMS-RT), the software will enable personalized price signal to be sent to millions of customers in extremely short timeframes—incentivizing them to alter their electricity use in response to grid conditions. This will help grid operators better manage unpredictable demand and supply fluctuations in short time-scales —making the power generation process more efficient and cost effective for both suppliers and consumers. DROMS-RT is expected to provide a 90% reduction in the cost of operating demand response and dynamic pricing Projects in the U.S.

  20. A DISTRIBUTED INTELLIGENT AUTOMATED DEMAND RESPONSE BUILDING MANAGEMENT SYSTEM

    SciTech Connect (OSTI)

    Auslander, David; Culler, David; Wright, Paul; Lu, Yan; Piette, Mary

    2013-12-30

    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 during the study period was 1175 kW. Several new tools facilitated this work, such as the Smart Energy Box, the distributed load controller or Energy Information Gateway, the web-­based DR controller (dubbed the Central Load-­Shed Coordinator or CLSC), and the Demand Response Capacity Assessment & Operation Assistance Tool (DRCAOT). In addition, an innovative data aggregator called sMAP (simple Measurement and Actuation Profile) allowed data from different sources collected in a compact form and facilitated detailed analysis of the building systems operation. A smart phone application (RAP or Rapid Audit Protocol) facilitated an inventory of the building’s plug loads. Carbon dioxide sensors located in conference rooms and classrooms allowed demand controlled ventilation. The extensive submetering and nimble access to this data provided great insight into the details of the building operation as well as quick diagnostics and analyses of tests. For example, students discovered a short-­cycling chiller, a stuck damper, and a leaking cooling coil in the first field tests. For our final field tests, we were able to see how each zone was affected by the DR strategies (e.g., the offices on the 7th floor grew very warm quickly) and fine-­tune the strategies accordingly.

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

    Broader source: Energy.gov [DOE]

    Renewable integration studies have evaluated many challenges associated with deploying large amounts of variable wind and solar generation technologies. These studies can evaluate operational impacts associated with variable generation, benefits of improved wind and solar resource forecasting, and trade-offs between institutional changes, including increasing balancing area cooperation and technical changes such as installing new flexible generation. Demand response (DR) resources present a potentially important source of grid flexibility and can aid in integrating variable generation; however, integration analyses have not yet incorporated these resources explicitly into grid simulation models as part of a standard toolkit for resource planners.

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

    SciTech Connect (OSTI)

    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.

  3. ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS

    E-Print Network [OSTI]

    Chuah, Chen-Nee

    ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS Howard CheHao Chang1, Haining Du2. Using VMesh to connect disjoint sensor networks One of our expectations for VMesh is to enable demand response (DR) [1] for automatic utility usage retrievals and price dispatching. DR is a project in- itiated

  4. Interoperability of Demand Response Resources Demonstration in NY

    SciTech Connect (OSTI)

    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.

  5. The Impact of Uncertain Physical Parameters on HVAC Demand Response

    SciTech Connect (OSTI)

    Sun, Yannan; Elizondo, Marcelo A.; Lu, Shuai; Fuller, Jason C.

    2014-03-01

    HVAC units are currently one of the major resources providing demand response (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units. These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demand response.

  6. Demand response compensation, net Benefits and cost allocation: comments

    SciTech Connect (OSTI)

    Hogan, William W.

    2010-11-15

    FERC's Supplemental Notice of Public Rulemaking addresses the question of proper compensation for demand response in organized wholesale electricity markets. Assuming that the Commission would proceed with the proposal ''to require tariff provisions allowing demand response resources to participate in wholesale energy markets by reducing consumption of electricity from expected levels in response to price signals, to pay those demand response resources, in all hours, the market price of energy for such reductions,'' the Commission posed questions about applying a net benefits test and rules for cost allocation. This article summarizes critical points and poses implications for the issues of net benefit tests and cost allocation. (author)

  7. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    response, distributed generation, and renewable energycontrol, distributed generation, renewable energy systems,

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

    SciTech Connect (OSTI)

    Aghajanzadeh, Arian; Wray, Craig; McKane, Aimee

    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.

  9. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    California Energy Commission curtailment service providerwith retail energy competition, retail service providers maywith retail energy competition, retail service providers may

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

    SciTech Connect (OSTI)

    Cappers, Peter; Goldman, Charles; Kathan, David

    2009-06-01

    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.

  11. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

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

    2010-03-17

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

  12. Program Strategies and Results for California’s Energy Efficiency and Demand Response Markets 

    E-Print Network [OSTI]

    Ehrhard, R.; Hamilton, G.

    2008-01-01

    Global Energy Partners provides a review of California’s strategic approach to energy efficiency and demand response implementation, with a focus on the industrial sector. The official role of the state, through the California Energy Commission (CEC...

  13. Analysis of Residential Demand Response and Double-Auction Markets

    SciTech Connect (OSTI)

    Fuller, Jason C.; Schneider, Kevin P.; Chassin, David P.

    2011-10-10

    Demand response and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

  14. Demand-Side Response from Industrial Loads

    SciTech Connect (OSTI)

    Starke, Michael R; Alkadi, Nasr E; Letto, Daryl; Johnson, Brandon; Dowling, Kevin; George, Raoule; Khan, Saqib

    2013-01-01

    Through a research study funded by the Department of Energy, Smart Grid solutions company ENBALA Power Networks along with the Oak Ridge National Laboratory (ORNL) have geospatially quantified the potential flexibility within industrial loads to leverage their inherent process storage to help support the management of the electricity grid. The study found that there is an excess of 12 GW of demand-side load flexibility available in a select list of top industrial facilities in the United States. Future studies will expand on this quantity of flexibility as more in-depth analysis of different industries is conducted and demonstrations are completed.

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

    SciTech Connect (OSTI)

    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 controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term.

  16. Summary of the 2006 Automated Demand Response Pilot 

    E-Print Network [OSTI]

    Piette, M.; Kiliccote, S.

    2007-01-01

    This paper discusses the specific concept for, design of, and results from a pilot program to automate demand response with critical peak pricing. California utilities have been exploring the use of critical peak pricing (CPP) to help reduce peak...

  17. Optimal demand response: problem formulation and deterministic case

    E-Print Network [OSTI]

    Wierman, Adam

    load through real-time demand response and purchases balancing power on the spot market to meet generation [17]. Indeed, [12, 18, 19] advocates the creation of a distribution/retail market to encourage

  18. Benefits of Demand Response in Electricity Markets and Recommendations...

    Broader source: Energy.gov (indexed) [DOE]

    bear little relation to the true production costs of electricity as they vary over time. Demand response is a tariff or program established to motivate changes in electric use by...

  19. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01

    Version 1.0), , 2009. CEC-500-2009-063. 13. LEED libraryDR credit LEED DR Pilot Credit: http://www.usgbc.org/LEED Demand Response Credit: A Plan for Research towards

  20. Retrofitting Existing Buildings for Demand Response & Energy Efficiency

    E-Print Network [OSTI]

    California at Los Angeles, University of

    Retrofitting Existing Buildings for Demand Response & Energy Efficiency www rate periods to avoid high charges. · Assembly Bill 1103 ­ Building Energy Efficiency Disclosure - Starting January 1, 2010, all commercial building lease transactions must disclose the energy efficiency

  1. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2006-04-15

    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)

  2. (2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via

    E-Print Network [OSTI]

    Low, Steven H.

    2013-01-01

    significant peak demand reduction and to ease the incorporation of renewable energy into the grid. Data has the potential to significantly ease the adoption of renewable energy into the grid. Data centers.chen@hp.com Abstract Demand response is a crucial aspect of the future smart grid. It has the potential to provide

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

    SciTech Connect (OSTI)

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

    2013-07-01

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

  4. A Look Ahead at Demand Response in New England

    SciTech Connect (OSTI)

    Burke, Robert B.; Henderson, Michael I.; Widergren, Steven E.

    2008-08-01

    The paper describes the demand response programs developed and in operation in New England, and the revised designs for participation in the forward capacity market. This description will include how energy efficiency, demand-side resources, and distributed generation are eligible to participate in this new forward capacity market. The paper will also discuss various methods that can be used to configure and communicate with demand response resources and important concerns in specifying interfaces that accommodate multiple technologies and allow technology choice and evolution.

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

    SciTech Connect (OSTI)

    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.

  6. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

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

    2009-05-01

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

  7. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    SciTech Connect (OSTI)

    Ghatikar, Girish; Piette, Mary Ann; Fujita, Sydny; McKane, Aimee; Dudley, Junqiao Han; Radspieler, Anthony; Mares, K.C.; Shroyer, Dave

    2009-12-30

    This study examines data center characteristics, loads, control systems, and technologies to identify demand response (DR) and automated DR (Open Auto-DR) opportunities and challenges. The study was performed in collaboration with technology experts, industrial partners, and data center facility managers and existing research on commercial and industrial DR was collected and analyzed. The results suggest that data centers, with significant and rapidly growing energy use, have significant DR potential. Because data centers are highly automated, they are excellent candidates for Open Auto-DR. 'Non-mission-critical' data centers are the most likely candidates for early adoption of DR. Data center site infrastructure DR strategies have been well studied for other commercial buildings; however, DR strategies for information technology (IT) infrastructure have not been studied extensively. The largest opportunity for DR or load reduction in data centers is in the use of virtualization to reduce IT equipment energy use, which correspondingly reduces facility cooling loads. DR strategies could also be deployed for data center lighting, and heating, ventilation, and air conditioning. Additional studies and demonstrations are needed to quantify benefits to data centers of participating in DR and to address concerns about DR's possible impact on data center performance or quality of service and equipment life span.

  8. Value of Demand Response: Quantities from Production Cost Modeling (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

  9. Barrier Immune Radio Communications for Demand Response

    SciTech Connect (OSTI)

    Rubinstein, Francis; Ghatikar, Girish; Granderson, Jessica; Haugen, Paul; Romero, Carlos; Watson, David

    2009-02-01

    Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.

  10. Field Testing of Automated Demand Response for Integration of Renewable

    E-Print Network [OSTI]

    LBNL-5556E Field Testing of Automated Demand Response for Integration of Renewable Resources responsibility for the accuracy, completeness, or usefulness of any information TCP/IP over CDMA CAISO Utility Aggregator NOC Proprietary Comm. EMS GridLink Loads Interval Meter

  11. Intelligent Office Lighting: Demand-Responsive Conditioning and Increased User Satisfaction

    E-Print Network [OSTI]

    Agogino, Alice M.

    Intelligent Office Lighting: Demand-Responsive Conditioning and Increased User Satisfaction Jessica diagram decision framework is used to optimize demand responsive actuation decisions, resulting with retrofitting. Keywords: Daylighting, energy efficiency, influence diagrams, intelligence, demand response, user

  12. Sixth Northwest Conservation and Electric Power Plan Chapter 5: Demand Response

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Chapter 5: Demand Response Summary of Key.............................................................................................................. 1 Demand Response in the Fifth Power Plan........................................................................................... 3 Demand Response in the Sixth Power Plan

  13. Sixth Northwest Conservation and Electric Power Plan Appendix H: Demand Response

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix H: Demand Response Introduction consumers' levels of service unchanged, demand response is a change in use of electricity at particular..................................................................................................................................... 1 Demand Response in the Council's Fifth Power Plan

  14. Dispatching Demand ResponseTransit Service: Maximizing Productivity and Service Quality Guidebook

    E-Print Network [OSTI]

    Dispatching Demand ResponseTransit Service: Maximizing Productivity and Service Quality Guidebook and Subtitle Dispatching Demand Response Transit Service Maximizing Productivity and Service Quality Guidebook while maintaining service quality. Researchers collected data from 42 demand response rural and small

  15. The Summer of 2006: A Milestone in the Ongoing Maturation of Demand Response

    E-Print Network [OSTI]

    Hopper, Nicole; Goldman, Charles; Bharvirkar, Ranjit; Engel, Dan

    2007-01-01

    2007) Figure 7. U.S. Demand Response Resources in 2005Proposals to Augment 2007 Demand Response Programs, Aug. 22,Efforts to Improve Demand Response Programs for State to

  16. A Cooperative Demand Response Scheme Using Punishment Mechanism and Application to Industrial Refrigerated Warehouses

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    aggregated loads for demand response,” in Proceedings of TheS. H. Low, “Optimal demand response: Problem formulation andZ. Yang, and Y. Zhang, “Demand response man- agement with

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01

    Power System Operator Demand Response Mass-Market Customers Aggregator of RetailPower System Operator Demand Response Resources Mass Market Customers Aggregator of Retailmarket customers, retail entities offering demand response opportunities, and bulk power

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

    E-Print Network [OSTI]

    Herter, Karen

    2014-01-01

    of the Open Automated Demand Response Standard for theOpen Automated Demand Response (OpenADR) Price Schedule Time3.3.2. General Electric Demand Response Module Figure 7. GE’

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

    SciTech Connect (OSTI)

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

    2012-01-18

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

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    Response for Wholesale Ancillary Services Sila Kiliccote,Response for Wholesale Ancillary Services Sila Kiliccotedemand response, OpenADR, ancillary services Abstract The

  1. Real-time Pricing Demand Response in Operations

    SciTech Connect (OSTI)

    Widergren, Steven E.; Marinovici, Maria C.; Berliner, Teri; Graves, Alan

    2012-07-26

    Abstract—Dynamic pricing schemes have been implemented in commercial and industrial application settings, and recently they are getting attention for application to residential customers. Time-of-use and critical-peak-pricing rates are in place in various regions and are being piloted in many more. These programs are proving themselves useful for balancing energy during peak periods; however, real-time (5 minute) pricing signals combined with automation in end-use systems have the potential to deliver even more benefits to operators and consumers. Besides system peak shaving, a real-time pricing system can contribute demand response based on the locational marginal price of electricity, reduce load in response to a generator outage, and respond to local distribution system capacity limiting situations. The US Department of Energy (DOE) is teaming with a mid-west electricity service provider to run a distribution feeder-based retail electricity market that negotiates with residential automation equipment and clears every 5 minutes, thus providing a signal for lowering or raising electric consumption based on operational objectives of economic efficiency and reliability. This paper outlines the capability of the real-time pricing system and the operational scenarios being tested as the system is rolled-out starting in the first half of 2012.

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

    E-Print Network [OSTI]

    Olsen, Daniel

    2012-01-01

    Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

  3. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01

    Protocol for Building Automation and Control  Networks.  Protocol for Building Automation and Control  Networks, Demand Response Automation Server  Demand Response Research 

  4. Price Responsive Demand in New York Wholesale Electricity Market using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01

    and Demand Response in Electricity Markets." University ofDemand Response in Electricity Markets and Recommendationsof Wholesale Electricity Markets for NYC in Summer

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01

    chain such as daily load management and demand response.more effective load management or a permanent reduction inother actions such as load management and demand response (

  6. Jointly Optimizing Cost, Service, and Environmental Performance in Demand-Responsive Transit Scheduling

    E-Print Network [OSTI]

    Dessouky, Maged

    Jointly Optimizing Cost, Service, and Environmental Performance in Demand-Responsive Transit-cycle environmental consequences in vehicle routing and scheduling, which we develop for a demand- responsive

  7. The Impact of Control Technology on the Demand Response Potential of

    E-Print Network [OSTI]

    LBNL-5750E The Impact of Control Technology on the Demand Response Potential of California was sponsored in part by the Demand Response Research Center which is funded

  8. Solutions for Summer Electric Power Shortages: Demand Response and its Applications in Air Conditioning and Refrigerating Systems

    E-Print Network [OSTI]

    Han, Junqiao; Piette, Mary Ann

    2008-01-01

    Research Director, PIER Demand Response Research CenterAssessment of Demand Response & Advanced Metering, staffPower Shortages: Demand Response and its Applications in Air

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

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01

    your Power. (2008). "Demand Response Programs." RetrievedUsing Open Automated Demand Response, Lawrence Berkeley2008). "What is Demand Response?" Retrieved 10/10/2008, from

  10. Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

    2006-01-01

    of Fully Automated Demand Response in Large Facilities.for Energy Efficiency and Demand Response”, Proceedings ofAuthority (NYSERDA), the Demand Response Research Center (

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

    E-Print Network [OSTI]

    Olsen, Daniel J.

    2014-01-01

    is estimated. Keywords: Demand response, ancillary services,of Aggregated Demand Response, Part 1: Load Availabilityof Energy (DOE) Demand Response and Energy Storage

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2014-01-01

    of fully automated demand response in large facilities,2009). Open Automated Demand Response CommunicationsOpen Automated Demand Response Technology Demonstration

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

    SciTech Connect (OSTI)

    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.

  14. Demand Response in Quebec's CI Buildings: Potentioal and Strategies 

    E-Print Network [OSTI]

    Daoud, A.; Leduc, M. A.; Baribeault, J.; Lavigne, K.; Chenard, S.; Poulin, A.; Martel, S.; Bendaoud, A.

    2013-01-01

    ? ICEBO2013 Demand response in Quebec?s CI buildings: potential and strategies Team: Ahmed Daoud, Ph.D, project manager Marie-Andr?e Leduc, MSc., ing, task manager Jean Baribeault, ing, researcher Karine Lavigne, MSc.A., ing, researcher Sylvain... Proceedings of the 13th International Conference for Enhanced Building Operations, Montreal, Quebec, October 8-11, 2013 Demand response in CI buildings ESL-IC-13-10-20a Proceedings of the 13th International Conference for Enhanced Building Operations...

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

    SciTech Connect (OSTI)

    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.

  16. Smart (In-home) Power Scheduling for Demand Response on the Smart Grid

    E-Print Network [OSTI]

    Yener, Aylin

    1 Smart (In-home) Power Scheduling for Demand Response on the Smart Grid Gang Xiong, Chen Chen consumption are part of demand response, which relies on varying price of electricity to reduce peak demand

  17. Intelligent Building Automation: A Demand Response Management Perspective 

    E-Print Network [OSTI]

    Qazi, T.

    2010-01-01

    ? Would it be more effective if the consumer were to be part of the efficiency process? What about if the energy savings could be passed on to the consumer directly depending on how efficient he was? Demand response is a mechanism by which consumers change...

  18. Demand Response and Energy Storage Integration Study- Past Workshops

    Office of Energy Efficiency and Renewable Energy (EERE)

    The project was initiated and informed by the results of two DOE workshops; one on energy storage and the other on demand response. The workshops were attended by members of the electric power industry, researchers, and policy makers; and the study design and goals reflect their contributions to the collective thinking of the project team.

  19. 00 (2015) 130 Greening Multi-Tenant Data Center Demand Response$

    E-Print Network [OSTI]

    Ren, Shaolei

    2015-01-01

    00 (2015) 1­30 Greening Multi-Tenant Data Center Demand Response$ Niangjun Chena , Xiaoqi Rena for demand response, particularly for emergency demand response (EDR), which saves the power grid from. In this paper, we focus on "greening" demand response in multi-tenant data centers, i.e., colocation data

  20. A Methodology to Evaluate Demand Response Communication Protocols for the Smart Grid

    E-Print Network [OSTI]

    Tronci, Enrico

    A Methodology to Evaluate Demand Response Communication Protocols for the Smart Grid Emad Ebeid between the consumer and the grid operator. Currently, there exist many evaluations of demand response of demand response protocols for the Smart Grid in combination with a demand response strategy

  1. Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging

    E-Print Network [OSTI]

    Bahk, Saewoong

    1 Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging Sung-Guk Yoon Member, which is called demand response. Under demand response, retailers determine their electricity prices cost solution and the result of the equal- charging scheme. Index Terms--demand response, electric

  2. Distributed Demand Response and User Adaptation in Smart Grids

    E-Print Network [OSTI]

    Fan, Zhong

    2010-01-01

    This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm.

  3. Providing Interactive Functions for Staggered Multicast Near VideoOnDemand Systems

    E-Print Network [OSTI]

    Fei, Zongming

    Providing Interactive Functions for Staggered Multicast Near Video­On­Demand Systems (Extended In this paper we propose a scheme to provide inter­ active functions through active buffer management at the client side for staggered multicast near VOD sys­ tems. The scheme uses client side buffering in a novel

  4. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01

    Control of Distributed Energy Resources and Demand ResponseControl of Distributed Energy Resources and Demand Responseinstalled distribution energy resources (DER) in the form of

  5. What China Can Learn from International Experiences in Developing a Demand Response Program

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    of preferred resources, placing energy efficiency and demandPromoting Energy Efficiency as a Cost-Effective Resource infor energy efficiency and demand response resources. Peak

  6. Examining Synergies between Energy Management and Demand Response: A Case Study at Two California Industrial Facilities

    E-Print Network [OSTI]

    Olsen, Daniel

    2013-01-01

    Capabilities due to Energy Management Improvement inSummary Introduction Energy Management Demand Responseand Processes Energy Management and Demand Response History

  7. Distributed Algorithms for Control of Demand Response and Distributed Energy Resources

    E-Print Network [OSTI]

    Dominguez-Garcia, Alejandro

    Distributed Algorithms for Control of Demand Response and Distributed Energy Resources Alejandro D networks. These algorithms are relevant for load curtailment control in demand response programs, and also is currently achieved through demand response programs in which participants, i.e., demand re- sponse resources

  8. Demand Response Design based on a Stackelberg Game in Smart Grid

    E-Print Network [OSTI]

    Bahk, Saewoong

    Demand Response Design based on a Stackelberg Game in Smart Grid Sung-Guk Yoon, Young-June Choi- time demand response can be applied. A smart grid network consisting of one retailer and many customers, demand response (DR) [3] is an indirect way to control the demand through hourly pricing information

  9. Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging

    E-Print Network [OSTI]

    Bahk, Saewoong

    1 Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging Sung-Guk Yoon Member, which is called demand response. Under demand response, retailers determine their electricity prices and customers respond accordingly with their electricity consumption levels. In particular, the demands

  10. Recouping Energy Costs from Cloud Tenants: Tenant Demand Response Aware Pricing Design

    E-Print Network [OSTI]

    Giles, C. Lee

    Recouping Energy Costs from Cloud Tenants: Tenant Demand Response Aware Pricing Design Cheng Wang. The poor predictability of real-world tenants' demand and demand responses (DRs) make such pricing design Cloud Tenant; Pricing Design; Game; Demand Response 1. INTRODUCTION The electric utility bills of data

  11. Real-Time Demand Response with Uncertain Renewable Energy in Smart Grid

    E-Print Network [OSTI]

    Wierman, Adam

    Real-Time Demand Response with Uncertain Renewable Energy in Smart Grid Libin Jiang and Steven Low manages user load through real-time demand response and purchases balancing power on the spot market and demand response in the presence of uncertain renewable supply and time-correlated demand. The overall

  12. A methodology for comparing distances traveled by performance-equivalent fixed-route and demand responsive

    E-Print Network [OSTI]

    Quadrifoglio, Luca

    -route and a demand responsive service, while ensuring a comparable service to the same set of customers. We consider to our findings, demand responsive transit services perform better for high- quality service levels and low demand density scenarios. Keywords: transit; bus lines; demand responsive services; service level

  13. A Truthful Incentive Mechanism for Emergency Demand Response in Colocation Data Centers

    E-Print Network [OSTI]

    Li, Zongpeng

    A Truthful Incentive Mechanism for Emergency Demand Response in Colocation Data Centers Linquan--Data centers are key participants in demand re- sponse programs, including emergency demand response (EDR grids, demand response programs are adopted in many countries for exploiting flexibility of electricity

  14. POWERTECH 2009, JUNE 28 -JULY 2, 2009, BUCHAREST, ROMANIA 1 Incorporation of Demand Response Resources in

    E-Print Network [OSTI]

    Gross, George

    POWERTECH 2009, JUNE 28 - JULY 2, 2009, BUCHAREST, ROMANIA 1 Incorporation of Demand Response, IEEE, Abstract--The use of demand-side resources, in general, and demand response resources (DRRs concerns. Integration of demand response resources in the competitive electricity markets impacts resource

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

    SciTech Connect (OSTI)

    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.

  16. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01

    to provide for energy and grid security and reliability.allowed to run and grid security and higher energy prices

  17. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  18. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

    13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

  20. Coordination of Retail Demand Response with Midwest ISO Markets

    SciTech Connect (OSTI)

    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 two hours advance notice and over 1,900 MW can be dispatched on less than thirty minutes notice. These legacy DR programs are increasingly used by utilities for economic in addition to reliability purposes, with over two-thirds (68percent) of these programs callable based on market conditions. - Approximately 60percent of DLC programs and 30percent of interruptible rate programs called ten or more DR events in 2006. Despite the high frequency of DR events, customer complaints remained low. The use of economic criteria to trigger DR events and the flexibility to trigger a large number of events suggests that DR resources can help improve the efficiency of MISO wholesale markets. - Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels averaged about $5/kW-month for interruptible rate tariffs and $6/kW-month for DLC programs. Few programs offered incentive payments that were explicitly linked to actual load reductions during events and at least 27 DR programs do not have penalties for non-performance. - Measurement and verification (M&V) protocols to estimate load impacts vary significantly across MISO states. Almost half of the DR programs have not been evaluated in recent times and thus performance data for DR events is not available. For many DLC programs, M&V protocols may need to be enhancedin order to allow participation in MISO's proposed EDR schedule. System operators and planners will need to develop more accurate estimates of the load reduced capability and actual performance.

  1. Semantic Information Integration and Processing for Demand Response Optimization Qunzhi Zhou, Sreedhar Natarajan, Yogesh Simmhan and Viktor Prasanna

    E-Print Network [OSTI]

    Hwang, Kai

    Semantic Information Integration and Processing for Demand Response Optimization Qunzhi Zhou Demand response optimization (DR) deals with curtailing power consumption when peak demand on the power for Dynamic Demand Response Optimization Existing DR programs are typically based on static planning

  2. Price Responsive Demand in New York Wholesale Electricity Market using OpenADR

    SciTech Connect (OSTI)

    Kim, Joyce Jihyun; Kiliccote, Sila

    2012-06-01

    In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated Demand Response (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demand response in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsive demand for large commercial customers in New York City.

  3. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    SciTech Connect (OSTI)

    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.

  4. Commercial Building Loads Providing Ancillary Services in PJM

    E-Print Network [OSTI]

    MacDonald, Jason

    2014-01-01

    and Communications for Demand Response and Energy EfficiencyM. Hummon et al. "Demand Response for Ancillary Services." (and S. Kiliccote. 2012. “Demand Response Providing Ancillary

  5. Estimating Demand Response Market Potential | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoopButtePowerEdisto Electric Coop,Erosion Flume Jump to: navigation,NewDemand Response

  6. An Online Procurement Auction for Power Demand Response in Storage-Assisted Smart Grids

    E-Print Network [OSTI]

    Li, Zongpeng

    An Online Procurement Auction for Power Demand Response in Storage-Assisted Smart Grids Ruiting discharging at times when supply is tight. This work aims at a systematic study of such demand response

  7. Field Test Results of Automated Demand Response in a Large Office Building

    E-Print Network [OSTI]

    Han, Junqiao

    2008-01-01

    operation of the power grid. Keywords Demand Response,ensures stability of the power grid. Auto-DR implementations

  8. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

  9. Role of Standard Demand Response Signals for Advanced Automated Aggregation

    SciTech Connect (OSTI)

    Lawrence Berkeley National Laboratory; Kiliccote, Sila

    2011-11-18

    Emerging standards such as OpenADR enable Demand Response (DR) Resources to interact directly with Utilities and Independent System Operators to allow their facility automation equipment to respond to a variety of DR signals ranging from day ahead to real time ancillary services. In addition, there are Aggregators in today’s markets who are capable of bringing together collections of aggregated DR assets and selling them to the grid as a single resource. However, in most cases these aggregated resources are not automated and when they are, they typically use proprietary technologies. There is a need for a framework for dealing with aggregated resources that supports the following requirements: • Allows demand-side resources to participate in multiple DR markets ranging from wholesale ancillary services to retail tariffs without being completely committed to a single entity like an Aggregator; • Allow aggregated groups of demand-side resources to be formed in an ad hoc fashion to address specific grid-side issues and support the optimization of the collective response of an aggregated group along a number of different dimensions. This is important in order to taylor the aggregated performance envelope to the needs to of the grid; • Allow aggregated groups to be formed in a hierarchical fashion so that each group can participate in variety of markets from wholesale ancillary services to distribution level retail tariffs. This paper explores the issues of aggregated groups of DR resources as described above especially within the context of emerging smart grid standards and the role they will play in both the management and interaction of various grid-side entities with those resources.

  10. Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

    E-Print Network [OSTI]

    Zhang, Wei

    Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response Wei Zhang, Jianming Lian, Chin-Yao Chang, Karanjit Kalsi and Yannan Sun Abstract-- Demand Response is playing population of appliances under demand response is especially important to evaluate the effec- tiveness

  11. Towards Building an Optimal Demand Response Framework for DC Distribution Networks

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    Towards Building an Optimal Demand Response Framework for DC Distribution Networks Hamed Mohsenian, an optimization-based foundation is proposed for demand response in DC distribution networks in presence to assess the performance and to gain insights into the proposed demand-response paradigm. Keywords: DC

  12. An Autonomous Demand Response Program in Smart Grid with Foresighted Users

    E-Print Network [OSTI]

    Wong, Vincent

    An Autonomous Demand Response Program in Smart Grid with Foresighted Users Shahab Bahrami, Vancouver, Canada email: {bahramis, vincentw}@ece.ubc.ca Abstract--In smart grid, demand response also benefit by reducing its total cost. In most of the existing studies, the demand response program

  13. A Privacy-Aware Architecture For Demand Response Systems Stephen Wicker, Robert Thomas

    E-Print Network [OSTI]

    Wicker, Stephen

    A Privacy-Aware Architecture For Demand Response Systems Stephen Wicker, Robert Thomas School architectures that realize the benefits of demand response without requiring that AMI data be centrally-based demand response efforts in the face of public outcry. We also show that Trusted Platform Modules can

  14. A Cheat-Proof Game Theoretic Demand Response Scheme for Smart Grids

    E-Print Network [OSTI]

    Liu, K. J. Ray

    A Cheat-Proof Game Theoretic Demand Response Scheme for Smart Grids Yan Chen, W. Sabrina Lin, Feng}@umd.edu Abstract--While demand response has achieved promising results on making the power grid more efficient and reliable, the additional dynamics and flexibility brought by demand response also increase the uncertainty

  15. Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Mechanisms

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    1 Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Member, IEEE, and Hamed Mohsenian-Rad, Member, IEEE Abstract--Autonomous demand response (DR) programs in autonomous DR systems in a decentralized fashion. Keywords: Autonomous demand response, optimality, fairness

  16. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    E-Print Network [OSTI]

    Zhang, Wei

    1 Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Wei Zhang, Member, IEEE Abstract--Demand response is playing an increasingly impor- tant role in the efficient loads is especially important to evaluate the effec- tiveness of various demand response strategies

  17. Real-Time Pricing for Demand Response Based on Stochastic Approximation

    E-Print Network [OSTI]

    Wong, Vincent

    1 Real-Time Pricing for Demand Response Based on Stochastic Approximation Pedram Samadi, Student to reduce their energy expenses. Keywords: Demand response, real-time pricing, PAR minimiza- tion, stochastic approximation, simultaneous perturbation. I. INTRODUCTION Demand response (DR) is an important

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

    E-Print Network [OSTI]

    de Weerdt, Mathijs

    Impact of Competition on Quality of Service in Demand Responsive Transit Ferdi Grootenboers1@inrets.fr Abstract. Demand responsive transportation has the potential to pro- vide efficient public door-company, quality of service, auction 1 Introduction Demand-Responsive Transit (DRT) services are a form

  19. Abstract --Due to the potentially large number of Distributed Energy Resources (DERs) demand response, distributed

    E-Print Network [OSTI]

    Zhang, Wei

    to accurately estimate the transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies, where dynamics on time scales of seconds to minutes demand response. The aggregated model efficiently includes statistical information of the population

  20. Pricing Data Center Demand Response Zhenhua Liu, Iris Liu, Steven Low, Adam Wierman

    E-Print Network [OSTI]

    Low, Steven H.

    Pricing Data Center Demand Response Zhenhua Liu, Iris Liu, Steven Low, Adam Wierman California Institute of Technology Pasadena, CA, USA {zliu2,iliu,slow,adamw}@caltech.edu ABSTRACT Demand response- ularly promising industry for demand response: data centers. We use simulations to show that, not only

  1. Comfort-Aware Home Energy Management Under Market-Based Demand-Response

    E-Print Network [OSTI]

    Boutaba, Raouf

    Comfort-Aware Home Energy Management Under Market-Based Demand-Response Jin Xiao, Jian Li, Raouf-compatible with market-based Demand-Response programs under explicit user comfort constraints. Theoretical analysis aside pricing and consumption data in South Korea. Index Terms--smart grid, demand-response, energy management I

  2. When Smart Grid Meets Geo-distributed Cloud: An Auction Approach to Datacenter Demand Response

    E-Print Network [OSTI]

    Li, Zongpeng

    When Smart Grid Meets Geo-distributed Cloud: An Auction Approach to Datacenter Demand Response Zhi--Datacenter demand response is envisioned as a promising tool for mitigating operational stability issues faced in escalating electricity cost. However, the current demand response paradigm is inefficient towards

  3. Energy-Agile Laptops: Demand Response of Mobile Plug Loads Using Sensor/Actuator Networks

    E-Print Network [OSTI]

    California at Berkeley, University of

    Energy-Agile Laptops: Demand Response of Mobile Plug Loads Using Sensor/Actuator Networks Nathan@me.berkeley.edu Abstract--This paper explores demand response techniques for managing mobile, distributed loads with on observed. Our first simulation study explores a classic demand response scenario in which a large number

  4. Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems

    E-Print Network [OSTI]

    Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems with Variable Resources Electric Energy System #12;#12;Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems benefits correspond to a real-world power system, as we use actual data on demand-response and wind

  5. Multi-period Optimal Procurement and Demand Responses in the Presence of Uncertain Supply

    E-Print Network [OSTI]

    Wierman, Adam

    Multi-period Optimal Procurement and Demand Responses in the Presence of Uncertain Supply Libin markets, uncertainty in renewable generation, and real-time dynamic demand response. A load-serving entity day-ahead decision, propose real-time demand response algorithm, and study the effect of volume

  6. Design and Valuation of Demand Response Mechanisms and Instruments for Integrating

    E-Print Network [OSTI]

    Design and Valuation of Demand Response Mechanisms and Instruments for Integrating Renewable) research project titled "Design and Valuation of Demand Response Mechanisms and Instruments for Integrating resources. The increased reserve requirement can be met using the so-called demand response resources (DRRs

  7. A Privacy-Preserving Scheme for Incentive-Based Demand Response in the Smart Grid

    E-Print Network [OSTI]

    Fang, Yuguang "Michael"

    1 A Privacy-Preserving Scheme for Incentive-Based Demand Response in the Smart Grid Yanmin Gong to both grid operators and customers, exploiting the full potential of demand response. However to be attributable to individuals. However, this assumption does not hold in incentive-based demand response (IDR

  8. Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation

    E-Print Network [OSTI]

    Wierman, Adam

    Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local facilities. In this extended abstract we briefly de- scribe recent work in [1] on two demand response schemes Keywords Demand response, coincident peak pricing, data center, work- load shifting, online algorithm 1

  9. Optimal Power Procurement and Demand Response with Quality-of-Usage Guarantees

    E-Print Network [OSTI]

    Huang, Longbo

    1 Optimal Power Procurement and Demand Response with Quality-of-Usage Guarantees Longbo Huang, Jean the utility company to jointly perform power procurement and demand response so as to maximize the social are the inte- gration of renewable energy technologies [1] and the design of efficient user demand-response

  10. Bet and Energy -From Load Forecasting to Demand Response in a Web of Things

    E-Print Network [OSTI]

    Beigl, Michael

    Bet and Energy - From Load Forecasting to Demand Response in a Web of Things Yong Ding TECO (DSM) [7, 19]. Within DSM, mainly two principal activities i.e. load shifting (demand response programs) and load reduction (energy efficiency and conser- vation programs) can be realized [4]. 1.1 Demand Response

  11. Residential Demand Response under Uncertainty Paul Scott and Sylvie Thiebaux and

    E-Print Network [OSTI]

    Thiébaux, Sylvie

    Residential Demand Response under Uncertainty Paul Scott and Sylvie Thi´ebaux and Menkes van den stochastic optimisation in residential demand response. 1 Introduction Electricity consumption in residential participate in smart grid activities such as demand response where loads are shifted to times favourable

  12. A Hierarchical Task Model for Dispatching in Computer-Assisted Demand-Responsive Paratransit Operation

    E-Print Network [OSTI]

    Dessouky, Maged

    A Hierarchical Task Model for Dispatching in Computer- Assisted Demand-Responsive Paratransit Model for Dispatching in Computer-Assisted Demand-Responsive Paratransit Operation ABSTRACT, Dispatch Training #12;1 INTRODUCTION Demand-responsive paratransit service is on the rise. For example

  13. A Multi-Resolution Large Population Game Framework for Smart Grid Demand Response Management

    E-Print Network [OSTI]

    Boyer, Edmond

    A Multi-Resolution Large Population Game Framework for Smart Grid Demand Response Management Quanyan Zhu and Tamer Bas¸ar Abstract--Dynamic demand response (DR) management is becoming an integral, active operation, and efficient demand response. A reliable and efficient communication and networking

  14. Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager

    E-Print Network [OSTI]

    Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager February 14 utilities to invest in DR Regional situational analysis ­ issues to address #12;Nationally ­ Demand ResponseSource: FERC Demand Response & Advanced Metering Report, February 2011 Peak DR 65,000 MW 1,062 MW Peak DR

  15. A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS

    E-Print Network [OSTI]

    Dessouky, Maged

    A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS Marco a demand responsive transit service with a predetermined quality for the user in terms of waiting time models; Continuous approximation models; Paratransit services; Demand responsive transit systems. #12;3 1

  16. Findings from the 2004 Fully Automated Demand Response Tests in Large

    E-Print Network [OSTI]

    LBNL-58178 Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities M;Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities September 7, 2005 Mary Ann Manager Dave Michel Contract 500-03-026 Sponsored by the California Energy Commission PIER Demand Response

  17. Memorandum: Cost-effectiveness valuation framework for Demand Response Resources: Guidelines and Suggestions (DRAFT)

    E-Print Network [OSTI]

    Memorandum: Cost-effectiveness valuation framework for Demand Response Resources: Guidelines and Suggestions (DRAFT) To: Pacific Northwest Demand Response Project Cost-Effectiveness Working Group From: Chuck Northwest Demand Response Project agreed to form three Working Groups to explore DR issues in more detail

  18. ScopingStudyReport-AppxC-Homework-013105.doc -1 -DEMAND RESPONSE RESEARCH CENTER SCOPING

    E-Print Network [OSTI]

    ScopingStudyReport-AppxC-Homework-013105.doc - 1 - DEMAND RESPONSE RESEARCH CENTER SCOPING STUDYStudyReport-AppxC-Homework-013105.doc - 2 - Preparing for the Roundtable Session (HOMEWORK ASSIGNMENT) The PIER Demand Response that advances the near-term adoption of Demand Response technologies, policies, programs, strategies

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

    SciTech Connect (OSTI)

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

    2011-11-11

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

  20. Demand-response (DR) programs, in which facilities reduce their electric loads in response to a utility signal, represent a

    E-Print Network [OSTI]

    The Issue Demand-response (DR) programs, in which facilities reduce their electric loads (Figure 1). The testing covered four Lighting the Way to Demand ResponseLighting the Way to Demand Response California Energy Commission's Public Interest Energy Research Program Technical Brief PIER

  1. Direct versus Facility Centric Load Control for Automated Demand Response

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2009-11-06

    Direct load control (DLC) refers to the scenario where third party entities outside the home or facility are responsible for deciding how and when specific customer loads will be controlled in response to Demand Response (DR) events on the electric grid. Examples of third parties responsible for performing DLC may be Utilities, Independent System Operators (ISO), Aggregators, or third party control companies. DLC can be contrasted with facility centric load control (FCLC) where the decisions for how loads are controlled are made entirely within the facility or enterprise control systems. In FCLC the facility owner has more freedom of choice in how to respond to DR events on the grid. Both approaches are in use today in automation of DR and both will continue to be used in future market segments including industrial, commercial and residential facilities. This paper will present a framework which can be used to differentiate between DLC and FCLC based upon where decisions are made on how specific loads are controlled in response to DR events. This differentiation is then used to compare and contrast the differences between DLC and FCLC to identify the impact each has on:(1)Utility/ISO and third party systems for managing demand response, (2)Facility systems for implementing load control, (3)Communications networks for interacting with the facility and (4)Facility operators and managers. Finally a survey of some of the existing DR related specifications and communications standards is given and their applicability to DLC or FCLC. In general FCLC adds more cost and responsibilities to the facilities whereas DLC represents higher costs and complexity for the Utility/ISO. This difference is primarily due to where the DR Logic is implemented and the consequences that creates. DLC may be more certain than FCLC because it is more predictable - however as more loads have the capability to respond to DR signals, people may prefer to have their own control of end-use loads and FCLC systems. Research is needed to understand the predictability of FCLC which is related to the perceived value of the DR from the facility manager or home owner's perspective.

  2. Advanced Control Technologies and Strategies Linking DemandResponse and Energy Efficiency

    SciTech Connect (OSTI)

    Kiliccote, Sila; Piette, Mary Ann

    2005-09-02

    This paper presents a preliminary framework to describe how advanced controls can support multiple modes of operations including both energy efficiency and demand response (DR). A general description of DR, its benefits, and nationwide status is outlined. The role of energy management and control systems for DR is described. Building systems such as HVAC and lighting that utilize control technologies and strategies for energy efficiency are mapped on to DR and demand shedding strategies are developed. Past research projects are presented to provide a context for the current projects. The economic case for implementing DR from a building owner perspective is also explored.

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

    SciTech Connect (OSTI)

    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, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).

  4. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit

    2013-06-21

    Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.

  5. Field Testing of Automated Demand Response for Integration of Renewable Resources in California's Ancillary Services Market for Regulation Products

    E-Print Network [OSTI]

    Kiliccote, Sila

    2013-01-01

    and Techniques for Demand Response”, May 2007. LBNL-59975 38the Role of Automated Demand Response, 2010. Watson, D. , N.Fast Automated Demand Response to Enable Integration of

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

    E-Print Network [OSTI]

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

    2004-01-01

    of Fully Automated Demand Response in Large Facilities”Learned from an Automated Demand Response Test in the SummerLearned from an Automated Demand Response Test in the Summer

  7. Resource Allocation with Unknown Constraints: An Extremum Seeking Control Approach and Applications to Demand Response

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas

    2014-01-01

    Z. Yang, and Y. Zhang, “Demand response manage- ment withS. H. Low, “Optimal demand response: Problem formulation andYang, and X. Guan, “Optimal demand response scheduling with

  8. Pilot Testing of Commercial Refrigeration-Based Demand Response

    SciTech Connect (OSTI)

    Hirsch, Adam; Clark, Jordan; Deru, Michael; Trenbath, Kim; Doebber, Ian; Studer, Daniel

    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.

  9. Scenarios for Consuming Standardized Automated Demand Response Signals

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2008-10-03

    Automated Demand Response (DR) programs require that Utility/ISO's deliver DR signals to participants via a machine to machine communications channel. Typically these DR signals constitute business logic information (e.g. prices and reliability/shed levels) as opposed to commands to control specific loads in the facility. At some point in the chain from the Utility/ISO to the loads in a facility, the business level information sent by the Utility/ISO must be processed and used to execute a DR strategy for the facility. This paper explores the various scenarios and types of participants that may utilize DR signals from the Utility/ISO. Specifically it explores scenarios ranging from single end user facility, to third party facility managers and DR Aggregators. In each of these scenarios it is pointed out where the DR signal sent from the Utility/ISO is processed and turned into the specific load control commands that are part of a DR strategy for a facility. The information in these signals is discussed. In some cases the DR strategy will be completely embedded in the facility while in others it may be centralized at a third party (e.g. Aggregator) and part of an aggregated set of facilities. This paper also discusses the pros and cons of the various scenarios and discusses how the Utility/ISO can use an open standardized method (e.g. Open Automated Demand Response Communication Standards) for delivering DR signals that will promote interoperability and insure that the widest range of end user facilities can participate in DR programs regardless of which scenario they belong to.

  10. Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost Uncertainty

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost framework for supply chain networks with global outsourcing and quick-response production under demand, and multiple demand markets. Using variational inequality theory, we formulate the governing equilibrium

  11. The response of world energy and oil demand to income growth and changes in oil prices

    SciTech Connect (OSTI)

    Dargay, J. [Oxford Univ. (United Kingdom). Transport Studies Unit; Gately, D. [New York Univ., NY (United States). Economics Dept.

    1995-11-01

    This paper reviews the path of world oil demand over the past three decades, and the effects of both the oil price increases of the 1970s and the oil price decreases of the 1980s. Compared with demand in the industrialized countries, demand in the Less Developed Countries (LDC) has been more responsive to income growth, less responsive to price increases, and more responsive to price decreases. The LDC has also exhibited much greater heterogeneity in income growth and is effect on demand. The authors expect a smaller demand response to future price increases than to those of the 1970s. The demand response to future income growth will be not substantially smaller than in the past. Finally, given the prospect of growing dependence on OPEC oil, in the event of a major disruption the lessened price-responsiveness of demand could cause dramatic price increases and serious macroeconomic effects.

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

    SciTech Connect (OSTI)

    Ghatikar, Girish; Riess, David; Piette, Mary Ann

    2014-01-02

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

  13. A demand responsive bidding mechanism with price elasticity matrix in wholesale electricity pools

    E-Print Network [OSTI]

    Wang, Jiankang, Ph. D. Massachusetts Institute of Technology

    2009-01-01

    In the past several decades, many demand-side participation features have been applied in the electricity power systems. These features, such as distributed generation, on-site storage and demand response, add uncertainties ...

  14. Climate control : smart thermostats, demand response, and energy efficiency in Austin, Texas

    E-Print Network [OSTI]

    Bowen, Brian (Brian Richard)

    2015-01-01

    Energy efficiency and demand response are critical resources for the transition to a cleaner electricity grid. Demand-side management programs can reduce electricity use during peak times when power is scarce and expensive, ...

  15. A new wholesale bidding mechanism for enhanced demand response in smart grids

    E-Print Network [OSTI]

    Wang, Jiankang

    Calls to improve customer participation as a key element of smart grids have reinvigorated interest in demand-side features such as distributed generation, on-site storage and demand response. In the context of deregulated ...

  16. Three Case Studues of the Application of Energy Systems Optimization Best Prectices for Automatic Demand Response 

    E-Print Network [OSTI]

    Shi, Y.; Guiberteau, K.; Yagua, C.; Watt, J.

    2013-01-01

    of the Application of Energy Systems Optimization Best Practices for Automatic Demand Response Yifu Shi Kelly Guiberteau Carlos Yagua, P.E. James Watt, P.E. Energy Systems Laboratory, Texas A&M University College Station, Texas Austin Energy... of the demand response program is to reduce facilities peak energy demand to reduce the cost of electricity for both Austin Energy and their customer. Reducing the demand mitigates the need to construct additional generation, transmission, and distribution...

  17. A tale of two houses: the human dimension of demand response enabling technology from a case study of an adaptive wireless thermostat.

    E-Print Network [OSTI]

    Peffer, Therese; Arens, Edward A; Chen, Xue; Jang, Jaehwi; Auslander, David M.

    2008-01-01

    technology to enable residential Demand Response (DR) is aalternative model for a residential demand response enablinguse it. Existing Residential Demand Response (DR) Programs

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

    E-Print Network [OSTI]

    Thompson, Lisa

    2010-01-01

    your Power. (2008). "Demand Response Programs." RetrievedTool Berkeley, CA, Demand Response Research Center.2008). "What is Demand Response?" Retrieved 10/10/2008, from

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

    SciTech Connect (OSTI)

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

    2007-01-01

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

  20. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

    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 conducted using three different baseline models for estimation peak load reductions. One was three-in-ten baseline, which is based on the site electricity consumption from 7 am to 10 am for the three days with the highest consumption of the previous ten business days. The second model, the LBNL outside air temperature (OAT) regression baseline model, is based on OAT data and site electricity consumption from the previous ten days, adjusted using weather regressions from the fifteen-minute electric load data during each DR test event for each site. A third baseline that simply averages the available load data was used for sites less with less than 10 days of historical meter data. The evaluation also included surveying sites regarding any problems or issues that arose during the DR test events. Question covered occupant comfort, control issues and other potential problems.

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

    SciTech Connect (OSTI)

    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.

  2. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    SciTech Connect (OSTI)

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

    2010-08-02

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

  3. Fair Rewarding in Colocation Data Centers: Truthful Mechanism for Emergency Demand Response

    E-Print Network [OSTI]

    Ren, Shaolei

    emergency events (e.g., extreme weather) that result in electricity production shortage and put the grid response, especially for emergency demand response (EDR) where the power grid coordinates large electricity as a valuable demand response resource for enhancing power grid's efficiency and reliability, especially during

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

    SciTech Connect (OSTI)

    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.

  5. California DREAMing: the design of residential demand responsive technology with people in mind

    E-Print Network [OSTI]

    Peffer, Therese E.

    2009-01-01

    to inform people of their energy usage. We tested the systemcertain quality and energy usage standards of variousprice and household energy usage to enable demand response

  6. Comments of the Demand Response and Smart Grid Coalition on DOE...

    Office of Environmental Management (EM)

    the Demand Response and Smart Grid Coalition on DOE's Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy...

  7. Chilled Water Thermal Storage System and Demand Response at the University of California at Merced

    E-Print Network [OSTI]

    Granderson, Jessica

    2010-01-01

    Chilled Water Thermal Storage System and Demand Response atCalifornia. Chilled Water Thermal Storage System and Demandin the presence of thermal energy storage (TES) and the

  8. A National Forum on Demand Response: What Remains to Be Done...

    Office of Environmental Management (EM)

    needs are changing as additional opportunities have opened up in wholesale and retail electricity markets for demand response resources. The working group focused on two key...

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01

    National Laboratory ABSTRACT In 2006, the Public Interest Energy ResearchEnergy Research Program Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory

  10. Greening the Grid: The Role of Storage and Demand Response, Greening...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    STORAGE AND DEMAND RESPONSE GREENING THE GRID THE NEED FOR FLEXIBILITY Affordably integrating high levels of variable renewable energy (VRE) sources such as wind and solar requires...

  11. The Summer of 2006: A Milestone in the Ongoing Maturation of Demand Response

    E-Print Network [OSTI]

    Hopper, Nicole; Goldman, Charles; Bharvirkar, Ranjit; Engel, Dan

    2007-01-01

    presentation to Peak Load Management Alliance Fall Meeting,Midwest ISO 2006 Load Management Response Survey Summary,appeals, demand-side management, utility load conservation,

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

    E-Print Network [OSTI]

    Lekov, Alex

    2009-01-01

    energy efficiency, load management, and demand response caseenergy efficiency and load management purposes can often bein place controls for load management programs as well as

  13. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01

    Solution Procedure for SDP Energy Prices We use electricityLondon for assistance with energy price modeling. Siddiquiof DER under uncertain energy prices with demand response

  14. Introduction to Commercial Building Control Strategies and Techniques for Demand Response -- Appendices

    SciTech Connect (OSTI)

    Motegi, N.; Piette, M.A.; Watson, D.S.; Kiliccote, S.; Xu, P.

    2007-05-01

    There are 3 appendices listed: (A) DR strategies for HVAC systems; (B) Summary of DR strategies; and (C) Case study of advanced demand response.

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

  17. Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing

    E-Print Network [OSTI]

    Boutaba, Raouf

    1999 when abnormal hot weather combined with electricity generation shortage resulted in unheard management and is a major con- tributor of electric grid faults. Although peak demand happens very infrastructure (Figure 1): technology upgrade of the electric grid system, all-digital management infrastructure

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,min) Rebound (kW) Daily peak demand (%) Daily energy (%)

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,min) Rebound (kW) Daily peak demand (%) Daily energy (%)

  20. Demand Response Spinning Reserve Demonstration -- Phase 2 Findings from the Summer of 2008

    SciTech Connect (OSTI)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Parker, Eric; Bernier, Clark; Young, Paul; Sheehan, Dave; Kueck, John; Kirby, Brendan

    2009-04-30

    The Demand Response Spinning Reserve project is a pioneering demonstration showing that existing utility load-management assets can provide an important electricity system reliability resource known as spinning reserve. Using aggregated demand-side resources to provide spinning reserve as demonstrated in this project will give grid operators at the California Independent System Operator (CA ISO) and Southern California Edison (SCE) a powerful new tool to improve reliability, prevent rolling blackouts, and lower grid operating costs.In the first phase of this demonstration project, we target marketed SCE?s air-conditioning (AC) load-cycling program, called the Summer Discount Plan (SDP), to customers on a single SCE distribution feederand developed an external website with real-time telemetry for the aggregated loads on this feeder and conducted a large number of short-duration curtailments of participating customers? air-conditioning units to simulate provision of spinning reserve. In this second phase of the demonstration project, we explored four major elements that would be critical for this demonstration to make the transition to a commercial activity:1. We conducted load curtailments within four geographically distinct feeders to determine the transferability of target marketing approaches and better understand the performance of SCE?s load management dispatch system as well as variations in the AC use of SCE?s participating customers;2. We deployed specialized, near-real-time AC monitoring devices to improve our understanding of the aggregated load curtailments we observe on the feeders;3. We integrated information provided by the AC monitoring devices with information from SCE?s load management dispatch system to measure the time required for each step in the curtailment process; and4. We established connectivity with the CA ISO to explore the steps involved in responding to CA ISO-initiated requests for dispatch of spinning reserve.The major findings from the second phase of this demonstration are:1. Demand-response resources can provide full response significantly faster than required by NERC and WECC reliability rules.2. The aggregate impact of demand response from many small, individual sources can be estimated with varying degrees of reliability through analysis of distribution feeder loads.3. Monitoring individual AC units helps to evaluate the efficacy of the SCE load management dispatch system and better understand AC energy use by participating customers.4. Monitoring individual AC units provides an independent data source to corroborate the estimates of the magnitude of aggregate load curtailments and gives insight into results from estimation methods that rely solely on distribution feeder data.

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

    E-Print Network [OSTI]

    Hwang, Kai

    Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid Yogesh Simmhan-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los An- geles Smart Grid consumer in Los Angeles, is serving as a campus microgrid testbed and ex- ploring informatics

  2. Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost Uncertainty

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost and computational framework for supply chain networks with global outsourcing and quick-response production under demand and cost uncertainty. Our model considers multiple off-shore suppliers, multiple manufacturers

  3. Demand Response Design based on a Stackelberg Game in Smart Grid

    E-Print Network [OSTI]

    Bahk, Saewoong

    of a real-time two-way communication system. This is called demand-side management (DSM) [2]. Among DSMDemand Response Design based on a Stackelberg Game in Smart Grid Sung-Guk Yoon, Young-June Choi- time demand response can be applied. A smart grid network consisting of one retailer and many customers

  4. Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

    2006-01-01

    energy efficiency, peak load management and demand response.minimization); peak load management (for daily operations);Energy Efficiency, Daily Load Management and DR Demand-Side

  5. Hazard consistent structural demands and in-structure design response spectra

    SciTech Connect (OSTI)

    Houston, Thomas W [Los Alamos National Laboratory; Costantino, Michael C [Los Alamos National Laboratory; Costantino, Carl J [Los Alamos National Laboratory

    2009-01-01

    Current analysis methodology for the Soil Structure Interaction (SSI) analysis of nuclear facilities is specified in ASCE Standard 4. This methodology is based on the use of deterministic procedures with the intention that enough conservatism is included in the specified procedures to achieve an 80% probability of non-exceedance in the computed response of a Structure, System. or Component for given a mean seismic design input. Recently developed standards are aimed at achieving performance-based, risk consistent seismic designs that meet specified target performance goals. These design approaches rely upon accurately characterizing the probability (hazard) level of system demands due to seismic loads consistent with Probabilistic Seismic Hazard Analyses. This paper examines the adequacy of the deterministic SSI procedures described in ASCE 4-98 to achieve an 80th percentile of Non-Exceedance Probability (NEP) in structural demand, given a mean seismic input motion. The study demonstrates that the deterministic procedures provide computed in-structure response spectra that are near or greater than the target 80th percentile NEP for site profiles other than those resulting in high levels of radiation damping. The deterministic procedures do not appear to be as robust in predicting peak accelerations, which correlate to structural demands within the structure.

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

    SciTech Connect (OSTI)

    Wenzel, Mike

    2013-10-14

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

  7. Side-payment profitability and interacting eyeball ISPs under convex demand-response modeling congestion-sensitive applications

    E-Print Network [OSTI]

    Kesidis, George

    2011-01-01

    This paper is concerned with the issue of side payments between content providers (CPs) and Internet service (access bandwidth) providers (ISPs) in an Internet that is potentially not neutral. We herein generalize past results modeling the ISP and CP interaction as a noncooperative game in two directions. We consider different demand response models (price sensitivities) for different provider types in order to explore when side payments are profitable to the ISP. Also, we consider convex (non-linear) demand response to model demand triggered by traffic which is sensitive to access bandwidth congestion, particularly delay-sensitive interactive real-time applications. Finally, we consider a model with two competing "eyeball" ISPs with transit pricing of net traffic at their peering point to study the effects of caching remote content.

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

    E-Print Network [OSTI]

    Kim, J. J.; Yin, R.; Kiliccote, S.

    2013-01-01

    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...

  9. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  10. A Full Demand Response Model in Co-Optimized Energy and

    SciTech Connect (OSTI)

    Liu, Guodong; Tomsovic, Kevin

    2014-01-01

    It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

  11. Opportunities for Automated Demand Response in Wastewater Treatment

    E-Print Network [OSTI]

    for North Shore Pumping Station shutdowns Cogeneration Plant Active #12;Figure 16: Demand from utility meter, solar generation, and cogeneration during days where cogeneration unit is running throughout the day Figure 17: Cogeneration unit ramp-up profile #12;CHAPTER 7: Conclusions #12;#12;References #12;Glossary

  12. Chilled Water Thermal Storage System and Demand Response at the University of California at Merced

    SciTech Connect (OSTI)

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

    2009-10-08

    The University of California at Merced is a unique campus that has benefited from intensive efforts to maximize energy efficiency, and has participated in a demand response program for the past two years. Campus demand response evaluations are often difficult because of the complexities introduced by central heating and cooling, non-coincident and diverse building loads, and existence of a single electrical meter for the entire campus. At the University of California at Merced, a two million gallon chilled water storage system is charged daily during off-peak price periods and used to flatten the load profile during peak demand periods. This makes demand response more subtle and challenges typical evaluation protocols. The goal of this research is to study demand response savings in the presence of storage systems in a campus setting. First, University of California at Merced summer electric loads are characterized; second, its participation in two demand response events is detailed. In each event a set of strategies were pre-programmed into the campus control system to enable semi-automated response. Finally, demand savings results are applied to the utility's DR incentives structure to calculate the financial savings under various DR programs and tariffs. A key conclusion to this research is that there is significant demand reduction using a zone temperature set point change event with the full off peak storage cooling in use.

  13. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    SciTech Connect (OSTI)

    Kiliccote, Sila; Piette, Mary Ann

    2008-10-01

    This report summarizes San Diego Gas& Electric Company?s collaboration with the Demand Response Research Center to develop and test automation capability for the Capacity Bidding Program in 2007. The report describes the Open Automated Demand Response architecture, summarizes the history of technology development and pilot studies. It also outlines the Capacity Bidding Program and technology being used by an aggregator that participated in this demand response program. Due to delays, the program was not fully operational for summer 2007. However, a test event on October 3, 2007, showed that the project successfully achieved the objective to develop and demonstrate how an open, Web?based interoperable automated notification system for capacity bidding can be used by aggregators for demand response. The system was effective in initiating a fully automated demand response shed at the aggregated sites. This project also demonstrated how aggregators can integrate their demand response automation systems with San Diego Gas& Electric Company?s Demand Response Automation Server and capacity bidding program.

  14. Demand Response and Peak Load Management; Programs, Products and Technology 

    E-Print Network [OSTI]

    Barth, A.

    2015-01-01

    Management: Programs, Products, and Technology IETC 2015 ESL-IE-15-06-13 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 2Supply & Demand Power Demand Grid Stability Reliability Risk Price Availability... ESL-IE-15-06-13 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 What Should We Expect? 0 1000 2000 3000 4000 5000 6000 2 0 1 1 2 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 2 0 1 6 2 0 1 7 2 0 1 8 2 0 1 9 2 0...

  15. Demand Response - Policy: More Information | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department8, 20153Daniel BoffDepartment ofConditionDelmarva Power -Demand

  16. Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan, Zhiyun Lin, and Minyue Fu

    E-Print Network [OSTI]

    Zhang, Wei

    Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan of residential responsive loads for vari- ous demand response applications. We propose a general hybrid system and effectively reduce the peak power consumption. I. INTRODUCTION Demand response has the potential to shift

  17. IEEE TRANSACTIONS ON SMART GRID, VOL. 4, NO. 4, DECEMBER 2013 2089 Scalable and Robust Demand Response With

    E-Print Network [OSTI]

    Giannakis, Georgios

    Response With Mixed-Integer Constraints Seung-Jun Kim and Georgios B. Giannakis Abstract--A demand response--Lagrange relaxation, mixed-integer programs, parallel and distributed algorithms, real-time demand response, robust of piecewise linear convex . I. INTRODUCTION DEMAND response (DR) is a key component of the smart grid, which

  18. A Market-Based Mechanism for Providing Demand-Side Regulation Service Ioannis Ch. Paschalidis, Binbin Li, Michael C. Caramanis

    E-Print Network [OSTI]

    Caramanis, Michael

    A Market-Based Mechanism for Providing Demand-Side Regulation Service Reserves Ioannis Ch a building Smart Microgrid Operator (SMO) to offer regulation service reserves and meet the associated utility. We study an asymptotic regime in which this upper bound is tight and the static policy provides

  19. Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

    2012-01-04

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

  20. A Truthful Incentive Mechanism for Emergency Demand Response in Colocation Data Centers

    E-Print Network [OSTI]

    Ren, Shaolei

    program, the operator has to rely on the highly expensive and/or environmentally-unfriendly on-site energy--Data centers are key participants in demand re- sponse programs, including emergency demand response (EDR of incentives to reduce energy consumption by tenants who control their servers and are typically on fixed power

  1. EnergySolve Demand Response | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTIONRobertsdale, AlabamaETEC GmbH JumpEllenville, NewLtd EILEnergyInformationEnergySolve Demand

  2. Demand Response Performance and Communication Strategy: AHRI and CEE

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department8, 20153Daniel BoffDepartment ofConditionDelmarva Power1 Demand

  3. A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing

    E-Print Network [OSTI]

    Giles, C. Lee

    1 A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real bills. Our focus is on a subset of this work that carries out demand response (DR) by modulating

  4. A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing

    E-Print Network [OSTI]

    Urgaonkar, Bhuvan

    1 A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real for optimizing their utility bills. Our focus is on a subset of this work that carries out demand response (DR

  5. A Dynamic Market Mechanism for Integration of Renewables and Demand Response

    E-Print Network [OSTI]

    Knudsen, Jesper

    2015-04-21

    The most formidable challenge in assembling a Smart Grid is the integration of a high penetration of renewables. Demand Response, a largely promising concept, is increasingly discussed as a means to cope with the intermittent ...

  6. Smart finite state devices: A modeling framework for demand response technologies

    E-Print Network [OSTI]

    Turitsyn, Konstantin

    We introduce and analyze Markov Decision Process (MDP) machines to model individual devices which are expected to participate in future demand-response markets on distribution grids. We differentiate devices into the ...

  7. Design and Optimization of a Feeder Demand Responsive Transit System in El Cenizo,TX 

    E-Print Network [OSTI]

    Chandra, Shailesh

    2010-10-12

    time interval of a new demand responsive transit "feeder" service within one representative colonia, El Cenizo. A comprehensive analysis of the results of a survey conducted through a questionnaire is presented to explain the existing travel patterns...

  8. Power system balancing with high renewable penetration : the potential of demand response

    E-Print Network [OSTI]

    Critz, David Karl

    2012-01-01

    This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model was used to represent a version of ...

  9. Subverting value hierarchies : essays on the causes and responses to shifts in demand for authenticity

    E-Print Network [OSTI]

    Hahl, Oliver (Oliver Douglas)

    2013-01-01

    This dissertation includes three essays on the causes and responses to shifts in demand for authenticity. In the first chapter, I answer the question: why do previously cast-off products, practices, or styles abruptly ...

  10. Price Responsive Demand in New York Wholesale Electricity Market using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01

    and Demand Response in Electricity Markets." University ofRates and Tariffs /Schedule for Electricity Service, P.S.C.no. 10- Electricity/Rules 24 (Riders)/Leaf No. 177-327."

  11. Cooperative Demand Response Using Repeated Game for Price-Anticipating Buildings in Smart Grid

    E-Print Network [OSTI]

    Ma, Kai; Hu, Guoqiang; Spanos, Costas J

    2014-01-01

    Price-Anticipating Buildings in Smart Grid Kai Ma Guoqiangprice-anticipating buildings in smart grid. The cooperativebuilding electricity use, with application to demand response,” IEEE Transactions on Smart

  12. Integrating short-term demand response into long-term investment planning

    E-Print Network [OSTI]

    De Jonghe, Cedric; Hobbs, Benjamin F.; Belmans, Ronnie

    2011-03-20

    the importance of integrating short-term demand response to time-varying prices into those investment models. Three different methodologies are suggested to integrate short-term responsiveness into a long-term model assuming that consumer response can be modelled...

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

    SciTech Connect (OSTI)

    Marks, Gary; Wilcox, Edmund; Olsen, Daniel; Goli, Sasank

    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 conducting a more comprehensive survey of California growers.

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

    SciTech Connect (OSTI)

    Herter, Karen; Rasin, Josh; Perry, Tim

    2009-11-30

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

  15. Response to several FOIA requests - Renewable Energy. Demand for Fossil

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematicsEnergyInterestedReplacement-2-A Wholesale PowerNatural GasBreakoutResponseResponseFuels |

  16. IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 2, MARCH 2014 861 An Optimal and Distributed Demand Response

    E-Print Network [OSTI]

    Nehorai, Arye

    of demand response management for the future smart grid that integrates plug-in electric vehicles for augmented Lagrangian. I. INTRODUCTION I N THE electricity market, demand response [1] is a mech- anism to manage users' consumption behavior under spe- cific supply conditions. The goal of demand response

  17. Why Urban Mass Demand Responsive Transport? Jani-Pekka Jokinen, Teemu Sihvola, Esa Hyytia and Reijo Sulonen

    E-Print Network [OSTI]

    Hyytiä, Esa

    Why Urban Mass Demand Responsive Transport? Jani-Pekka Jokinen, Teemu Sihvola, Esa Hyyti that a large-scale demand responsive system is the missing element from the spectrum of the urban transport. In each case, we are able to give sound arguments why a mass demand responsive transport (DRT) service can

  18. IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 4, JULY 2014 2075 A Distributed Demand Response Control Strategy

    E-Print Network [OSTI]

    Cai, Lin

    IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 4, JULY 2014 2075 A Distributed Demand Response) systems in demand response (DR), we propose a distributed DR control strategy to dispatch the HVAC loads and demonstrate the effectiveness and efficiency of the proposed control algorithm. Index Terms--Demand response

  19. Topic 4: Demand Response A.H. MohsenianRad (U of T) 1Networking and Distributed Systems

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    Topic 4: Demand Response A.H. MohsenianRad (U of T) 1Networking and Distributed Systems Department;Definition of Demand Response Dr. Hamed Mohsenian-Rad Texas Tech UniversityCommunications and Control in Smart Grid · According to the U.S. Department of Energy: Demand response (DR) is defined as changes

  20. Managing Plug-Loads for Demand Response within Buildings Thomas Weng, Bharathan Balaji, Seemanta Dutta, Rajesh Gupta, Yuvraj Agarwal

    E-Print Network [OSTI]

    Gupta, Rajesh

    Managing Plug-Loads for Demand Response within Buildings Thomas Weng, Bharathan Balaji, Seemanta managers can per- form active energy management, especially during demand response situations that require, allowing them to deal with demand response situations through user- specified actuation policies. At its

  1. Deep Demand Response: The Case Study of the CITRIS Building at the University of California-Berkeley

    E-Print Network [OSTI]

    California at Berkeley, University of

    Deep Demand Response: The Case Study of the CITRIS Building at the University of California quality. We have made progress towards achieving deep demand response of 30% reduction of peak loads modeling expertise), and UC Berkeley (related demand response research including distributed wireless

  2. Optimal Demand Response in DC Distribution Networks Hamed Mohsenian-Rad, Member, IEEE and Ali Davoudi, Member, IEEE

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    Optimal Demand Response in DC Distribution Networks Hamed Mohsenian-Rad, Member, IEEE and Ali first present an optimization-based foundation for demand response in DC distribution networks. Then, we devise a pricing mechanism to enforce optimal demand response in a distributed fashion. Simulation

  3. Abstract --Demand Response (DR) programs are not a new concept; moreover, the key technologies for their implementation

    E-Print Network [OSTI]

    Catholic University of Chile (Universidad Católica de Chile)

    1 Abstract -- Demand Response (DR) programs are not a new concept; moreover, the key technologies migrate to active and dynamic demand response, under reliability criteria based on the smart grid paradigm. This article formulates a new perspective of demand response in emerging countries, based on the US

  4. Solving a Dial-a-Ride Problem with a Hybrid Evolutionary Multi-objective Application to Demand Responsive Transport

    E-Print Network [OSTI]

    Boyer, Edmond

    to Demand Responsive Transport R´emy Chevrier,a , Arnaud Liefoogheb,c , Laetitia Jourdanb,c , Clarisse, 59650 Villeneuve d'Ascq, France Abstract Demand responsive transport allows customers to be carried to improve the quality of service, demand responsive transport needs more flexibility. This paper tries

  5. Design and Implementation of an Open, Interoperable AutomatedDemand Response Infrastructure

    SciTech Connect (OSTI)

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

    2007-10-01

    This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automating demand response (DR). Automating DR allows greater levels of participation and improved reliability and repeatability of the demand response and customer facilities. Automated DR systems have been deployed for critical peak pricing and demand bidding and are being designed for real time pricing. The system is designed to generate, manage, and track DR signals between utilities and Independent System Operators (ISOs) to aggregators and end-use customers and their control systems.

  6. Export demand response in the Ontario electricity market

    SciTech Connect (OSTI)

    Peerbocus, Nash; Melino, Angelo

    2007-11-15

    Export responses to unanticipated price shocks can be a key contributing factor to the rapid mean reversion of electricity prices. The authors use event analysis - a technique more familiar from financial applications - to demonstrate how hourly export transactions respond to negative supply shocks in the Ontario electricity market. (author)

  7. An Integrated Architecture for Demand Response Communications and Control

    E-Print Network [OSTI]

    and deployment of Advanced Meter Infrastructures (AMIs), Building Automation Systems (BASs), and var- ious, AMI, ZigBee, Building Automation System, BAS, Home Automation, Meter Data Management 1. Introduction Automation Systems (BASs), and embedded control systems. AMI provides intelligent metering based on data net

  8. Scalable, Secure Energy Information Management for Demand-Response Analysis Yogesh Simmhan1,2

    E-Print Network [OSTI]

    Hwang, Kai

    Scalable, Secure Energy Information Management for Demand-Response Analysis Yogesh Simmhan1 and optimize energy usage to meet sustainability goals. Managing the energy information lifecycle ­ from, feedback, and query/response interactions, which are transmitted across a widely distributed infrastructure

  9. When it comes to demand response, is FERC its own worst enemy?

    SciTech Connect (OSTI)

    Bushnell, James; Hobbs, Benjamin F.; Wolak, Frank A.

    2009-10-15

    There is a significant risk of creating conditions that will crowd out true price response by focusing too much on demand response programs with unverifiable baselines and reliability-based rather than price-based mechanisms for obtaining consumption reductions. (author)

  10. Testing The Effects Of Price Responsive Demand On Uniform Price And Soft-Cap Electricity Auctions

    E-Print Network [OSTI]

    Testing The Effects Of Price Responsive Demand On Uniform Price And Soft-Cap Electricity Auctions R describes a framework for testing the efficacy of a price-responsive load on a uniform price last accepted offer and a soft-cap market. Experimental evidence to date based on uniform price market testing has

  11. Configuring load as a resource for competitive electricity markets--Review of demand response programs in the U.S. and around the world

    E-Print Network [OSTI]

    Heffner, Grayson C.

    2002-01-01

    MARKETS – REVIEW OF DEMAND RESPONSE PROGRAMS IN THE U.S. ANDMARKETS – REVIEW OF DEMAND RESPONSE PROGRAMS IN THE U.S. ANDend-users they serve. Demand Response Programs, once called

  12. Evaluation of the Demand Response Performance of Electric Water Heaters

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Widder, Sarah H.; Parker, Steven A.; Pratt, Richard M.; Chassin, Forrest S.

    2015-03-17

    The purpose of this project is to verify or refute many of the concerns raised by utilities regarding the ability of large tank HPWHs to perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. This project was divided into three phases. Phase 1 consisted of week-long laboratory experiments designed to demonstrate technical feasibility of individual large-tank HPWHs in providing DR services compared to large-tank ERWHs. In Phase 2, the individual behaviors of the water heaters were then extrapolated to a population by first calibrating readily available water heater models developed in GridLAB-D simulation software to experimental results obtained in Phase 1. These models were used to simulate a population of water heaters and generate annual load profiles to assess the impacts on system-level power and residential load curves. Such population modeling allows for the inherent and permanent load reduction accomplished by the more efficient HPWHs to be considered, in addition to the temporal DR services the water heater can provide by switching ON or OFF as needed by utilities. The economic and emissions impacts of using large-tank water heaters in DR programs are then analyzed from the utility and consumer perspective, based on National Impacts Analysis in Phase 3. Phase 1 is discussed in this report. Details on Phases 2 and 3 can be found in the companion report (Cooke et al. 2014).

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

    SciTech Connect (OSTI)

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

    2003-04-18

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

  14. Quantifying Changes in Building Electricity Use, with Application to Demand Response

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Price, Phillip N.; Kiliccote, Sila; Piette, Mary Ann

    2010-11-17

    We present methods for analyzing commercial and industrial facility 15-minute-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence, and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.

  15. Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Chassin, Forrest S.; Chassin, David P.

    2011-12-12

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

  16. AMI Communication Requirements to Implement Demand-Response: Applicability of Hybrid Spread Spectrum Wireless

    SciTech Connect (OSTI)

    Hadley, Mark D.; Clements, Samuel L.; Carroll, Thomas E.

    2011-09-30

    While holistically defining the smart grid is a challenge, one area of interest is demand-response. In 2009, the Department of Energy announced over $4 billion in grant and project funding for the Smart Grid. A significant amount of this funding was allotted to utilities for cost sharing projects to deploy Smart Grid technologies, many of whom have deployed and are deploying advanced metering infrastructure (AMI). AMI is an enabler to increase the efficiency of utilities and the bulk power grid. The bulk electrical system is unique in that it produces electricity as it is consumed. Most other industries have a delay between generation and consumption. This aspect of the power grid means that there must be enough generation capacity to meet the highest demand whereas other industries could over produce during off-peak times. This requires significant investment in generation capacity to cover the few days a year of peak consumption. Since bulk electrical storage doesn't yet exist at scale another way to curb the need for new peak period generation is through demand-response; that is to incentivize consumers (demand) to curtail (respond) electrical usage during peak periods. Of the various methods proposed for enabling demand-response, this paper will focus on the communication requirements for creating an energy market using transactional controls. More specifically, the paper will focus on the communication requirements needed to send the peak period notices and receive the response back from the consumers.

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

    SciTech Connect (OSTI)

    Lincoln, Donald; Evans, Christoper

    2012-01-01

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

  18. Commercial Building Loads Providing Ancillary Services in PJM

    E-Print Network [OSTI]

    MacDonald, Jason

    2014-01-01

    P. Barooah, and S. Meyn. "Ancillary service for the grid viaet al. "Demand Response for Ancillary Services." (2013): 1-8Demand Response Providing Ancillary Services: A Comparison

  19. Architecture Concepts and Technical Issues for an Open,Interoperable Automated Demand Response Infrastructure

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2007-10-01

    This paper presents the technical and architectural issues associated with automating Demand Response (DR) programs. The paper focuses on a description of the Demand Response Automation Server (DRAS), which is the main component used to automate the interactions between the Utilities and their customers for DR programs. Use cases are presented that show the role of the DRAS in automating various aspects of DR programs. This paper also describes the various technical aspects of the DRAS including its interfaces and major modes of operation. This includes how the DRAS supports automating such Utility/Customer interactions as automated DR bidding, automated DR event handling, and finally real-time pricing.

  20. Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency 

    E-Print Network [OSTI]

    Kiliccote, S.; Piette, M. A.

    2005-01-01

    stream_source_info ESL-IE-15-06-13.pdf.txt stream_content_type text/plain stream_size 7608 Content-Encoding UTF-8 stream_name ESL-IE-15-06-13.pdf.txt Content-Type text/plain; charset=UTF-8 Demand Response & Peak Load... additional generation resources • Hurdles to adding additional resources Why Demand Response Exists ESL-IE-15-06-13 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 What are my Options? • Efficiency...

  1. Killing Two Birds with One Stone: Can Real-Time Pricing SupportRetail Competition and Demand Response?

    SciTech Connect (OSTI)

    Barbose, Galen; Bharvirkar, Ranjit; Goldman, Charles; Hopper,Nicole; Neenan, Bernie

    2006-04-25

    As retail choice states reach the end of their transitional, rate-cap periods, state regulators must decide what type of default supply service to provide to customers that have not switched to a competitive retail supplier. In a growing number of states, regulators have adopted real-time pricing (RTP) as the default service for large commercial and industrial (C&I) customers. Although this trend is driven chiefly by policy objectives related to retail competition, default service RTP may have the added benefit of stimulating demand response. To evaluate the potential role of RTP as a means to both ends--retail market development and demand response--we conducted a comprehensive review of experience with default RTP in the U.S. and examined the emergence of RTP as a product offering by competitive retail suppliers. Across the ten utilities with default RTP in place in 2005, between 5% and 35% of the applicable load remained on the rate. Based on interviews with competitive retailers, we find evidence to suggest that a comparable amount of load in these states has switched to hourly pricing arrangements with competitive retailers. Many customers on default or competitive hourly pricing are paying prices indexed to the real-time spot market, and thus have no advance knowledge of prices. Because the price responsiveness of customers under these conditions has yet to be formally analyzed, and relatively few efforts have been undertaken to help these customers become price responsive, the actual demand response impacts from hourly pricing in retail choice states remains largely an open question. However, we find that policymakers and other stakeholders in retail choice states have various strategies at their disposal to capture the potential demand response benefits from hourly pricing, while simultaneously supporting retail competition.

  2. Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit; Sun, Yannan

    2012-12-12

    Demand Response is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demand response is especially important to evaluate the effectiveness of these demand response programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demand response, aggregated model, ancillary

  3. Demand Response

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department8, 20153Daniel BoffDepartment ofConditionDelmarva Power -

  4. Enabling Efficient, Responsive, and Resilient Buildings: Collaboration Between the United States and India

    E-Print Network [OSTI]

    Basu, Chandrayee

    2014-01-01

    Fast Automated Demand Response to Enable the Integration ofCallaway, S. Kiliccote. “Demand Response Providing Ancillaryand Open Automated Demand Response. ” Grid Interop Forum.

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

    SciTech Connect (OSTI)

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

    2009-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

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

    SciTech Connect (OSTI)

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

    2008-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

  7. Distributed Algorithms for Control of Demand Response and Distributed Energy Resources

    E-Print Network [OSTI]

    Liberzon, Daniel

    Distributed Algorithms for Control of Demand Response and Distributed Energy Resources Alejandro D algorithms for control and coordination of loads and distributed energy resources (DERs) in distribution) integration of distributed energy resources (DERs), e.g., photovoltaics (PV); and iii) new storage

  8. Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids

    E-Print Network [OSTI]

    Yeoh, William

    Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids Paul Scott1 direction method of multipliers (ADMM), can be adapted to remain practical in this challenging microgrid discrete decisions. Our experiments on a suburb-sized microgrid show that the AC power flows and a simple

  9. On Using Complex Event Processing for Dynamic Demand Response Optimization in Microgrid

    E-Print Network [OSTI]

    Hwang, Kai

    On Using Complex Event Processing for Dynamic Demand Response Optimization in Microgrid Qunzhi Zhou Processing (CEP) patterns to model and detect dynamic situations in a campus microgrid to facilitate adaptive these patterns on realtime events in the USC Campus microgrid using our CEP framework. Index Terms

  10. Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    scheduled for implementation) in the midwest (MISO), New England (ISO-NE), New York (NYISO), the mid1 Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios Hongyan Li protocols I. INTRODUCTION IN April 2003 the U.S. Federal Energy Regulatory Commis- sion issued a white paper

  11. Effects of Price-Responsive Residential Demand on Retail and Wholesale Power Market Operations

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    1 Effects of Price-Responsive Residential Demand on Retail and Wholesale Power Market Operations/C) on integrated retail and wholesale power market operations. The physical operations of the A/C sys- tem, and distribution of electric power was mo- nopolistically controlled by vertically integrated utilities with retail

  12. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01

    follows: • EDemand t : electricity demand during day t (incost of reducing electricity demand (in $/MWh e ) • HRDCost:maximum fraction of electricity demand to be met by demand

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

    SciTech Connect (OSTI)

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

    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 operation of sludge-processing equipment besides centrifuges, and utilizing schedulable self-generation.

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

    SciTech Connect (OSTI)

    Piette, Mary Ann; Kiliccote, Sila

    2006-09-01

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

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

    SciTech Connect (OSTI)

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

    2014-01-31

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

  16. Optimal Power Procurement and Demand Response with Quality-of-Usage Guarantees

    E-Print Network [OSTI]

    Huang, Longbo; Ramchandran, Kannan

    2011-01-01

    In this paper, we propose a general operating scheme which allows the utility company to jointly perform power procurement and demand response so as to maximize the social welfare. Our model takes into consideration the effect of the renewable energy and the multi-stage feature of the power procurement process. It also enables the utility company to provide quality-of-usage (QoU) guarantee to the power consumers, which ensures that the average power usage level meets the target value for each user. To maximize the social welfare, we develop a low-complexity algorithm called the \\emph{welfare maximization algorithm} (WMA), which performs joint power procurement and dynamic pricing. WMA is constructed based on a two-timescale Lyapunov optimization technique. We prove that WMA achieves a close-to-optimal utility and ensures that the QoU requirement is met with bounded deficit. WMA can be implemented in a distributed manner and is robust with respect to system dynamics uncertainty.

  17. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,kW) Rebound (kW) Daily Peak Demand (kW) Daily Energy (kWh) a

  18. Impacts of Providing Inertial Response on Dynamic Loads of Wind Turbine Drivetrains: Preprint

    SciTech Connect (OSTI)

    Girsang, I. P.; Dhupia, J.; Singh, M.; Gevorgian, V.; Muljadi, E.; Jonkman, J.

    2014-09-01

    There has been growing demand from the power industry for wind power plants to support power system operations. One such requirement is for wind turbines to provide ancillary services in the form of inertial response. When the grid frequency drops, it is essential for wind turbine generators (WTGs) to inject kinetic energy stored in their inertia into the grid to help arrest the frequency decline. However, the impacts of inertial response on the structural loads of the wind turbine have not been given much attention. To bridge this gap, this paper utilizes a holistic model for both fixed-speed and variable-speed WTGs by integrating the aeroelastic wind turbine model in FAST, developed by the National Renewable Energy Laboratory, with the electromechanical drivetrain model in SimDriveline and SimPowerSystems.

  19. 1822 IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 4, DECEMBER 2012 Real-Time Price-Based Demand Response

    E-Print Network [OSTI]

    Fu, Yong

    , real-time price-based demand response management, residential appli- ances, robust optimization1822 IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 4, DECEMBER 2012 Real-Time Price-Based Demand Response Management for Residential Appliances via Stochastic Optimization and Robust Optimization Zhi Chen

  20. The Impact of Energy Efficiency and Demand Response Programs on the U.S. Electricity Market

    SciTech Connect (OSTI)

    Baek, Young Sun; Hadley, Stanton W

    2012-01-01

    This study analyzes the impact of the energy efficiency (EE) and demand response (DR) programs on the grid and the consequent level of production. Changes in demand caused by EE and DR programs affect not only the dispatch of existing plants and new generation technologies, the retirements of old plants, and the finances of the market. To find the new equilibrium in the market, we use the Oak Ridge Competitive Electricity Dispatch Model (ORCED) developed to simulate the operations and costs of regional power markets depending on various factors including fuel prices, initial mix of generation capacity, and customer response to electricity prices. In ORCED, over 19,000 plant units in the nation are aggregated into up to 200 plant groups per region. Then, ORCED dispatches the power plant groups in each region to meet the electricity demands for a given year up to 2035. In our analysis, we show various demand, supply, and dispatch patterns affected by EE and DR programs across regions.