Sample records for demand response estimation

  1. A Methodology for Estimating Large-Customer Demand Response Market Potential

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    Estimating Large-Customer Demand Response Market PotentialEstimating Large-Customer Demand Response Market PotentialSyracuse, NY ABSTRACT Demand response (DR) is increasingly

  2. 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

    2007-01-01T23:59:59.000Z

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

  3. Estimating Large-Customer Demand Response Market Potential: Integrating Price and Customer Behavior

    E-Print Network [OSTI]

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

    2007-01-01T23:59:59.000Z

    Estimating Large-Customer Demand Response Market Potential:Syracuse, NY ABSTRACT Demand response (DR) is increasinglyestimated. Introduction Demand response (DR) is increasingly

  4. 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision|LLCInsulation IncentivesEshone EnergyEstero,Demand

  5. 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

  6. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

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

  7. 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

    2007-01-01T23:59:59.000Z

    demand response options, or benchmarking, are probably not all that meaningful. The “best practices”

  8. 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

    2007-01-01T23:59:59.000Z

    demand response, participation can imply: (1) customer enrollment in voluntary programs and tariffs, or (2) the retention

  9. 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

  10. 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

    2007-01-01T23:59:59.000Z

    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.

  11. Estimating Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Buildings in California

    E-Print Network [OSTI]

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote, Sila

    2008-01-01T23:59:59.000Z

    commercial buildings participating in a demand?response (buildings participating in an Automated Demand Response buildings  participating  in  an  event?driven  demand?response  (

  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

    2007-01-01T23:59:59.000Z

    choices in the face of real options, or surveys can beoptions may differ from their actual behavior when faced with realReal-Time Demand Response (RTDR) program offers customers two advance-notice options:

  13. Demand response enabling technology development

    E-Print Network [OSTI]

    Arens, Edward; Auslander, David; Huizenga, Charlie

    2008-01-01T23:59:59.000Z

    behavior in developing a demand response future. Phase_II_Demand Response Enabling Technology Development Phase IIYi Yuan The goal of the Demand Response Enabling Technology

  14. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

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

  15. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    Demand Response Enabling Technology Development Phase IEfficiency and Demand Response Programs for 2005/2006,Application to Demand Response Energy Pricing” SenSys 2003,

  16. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings”, Lawrencesystems. Demand Response using HVAC in Commercial BuildingsDemand Response Test in Large Facilities13 National Conference on Building

  17. Demand Response In California

    Broader source: Energy.gov [DOE]

    Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

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

  19. 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

    2007-01-01T23:59:59.000Z

    2001. “Electricity Demand Side Management Study: Review ofEpping/North Ryde Demand Side Management Scoping Study:Energy Agency Demand Side Management (IEA DSM) Programme:

  20. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    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

  1. 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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Data for Automated Demand Response in Commercial Buildings,Demand Response Infrastructure for Commercial Buildings",demand response and energy efficiency functions into the design of buildings,

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    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

  5. Demand Response: Load Management Programs 

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01T23:59:59.000Z

    CenterPoint Load 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...

  6. 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

  7. 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..................................................................................................................................... 1 Demand Response in the Council's Fifth Power Plan......................................................................................................................... 3 Estimate of Potential Demand Response

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

    E-Print Network [OSTI]

    Han, Junqiao

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

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

  10. Demand Response: Load Management Programs

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01T23:59:59.000Z

    CenterPoint Load 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...

  11. 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

    2007-01-01T23:59:59.000Z

    of Residential Response in Time of Use Pricing Experiments”,as critical-peak pricing, time-of-use rates, and real-timebusinesses. Time-of-use and real-time-pricing (RTP)-type

  12. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

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

  13. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

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

  14. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    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

  15. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    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

  16. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01T23:59:59.000Z

    and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

  17. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    Rubinstein, Francis

    2010-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities,”Fully Automated Demand Response Tests in Large Facilities.for Automated Demand Response. Technical Document to

  18. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    Strategies Linking Demand Response and Energy Efficiency,”Fully Automated Demand Response Tests in Large Facilities,technical support from the Demand Response Research Center (

  19. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    integrating HECO and Hawaii Energy demand response relatedpotential. Energy efficiency and demand response efforts areBoth  energy  efficiency  and  demand  response  should  

  20. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    Strategies for Demand Response in Commercial Buildings DavidStrategies for Demand Response in Commercial Buildings Davidadjusted for demand response in commercial buildings. The

  1. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    Demand Response Systems National Conference on BuildingDemand Response Systems National Conference on BuildingDemand Response Systems National Conference on Building

  2. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    In terms of demand response capability, building operatorsautomated demand response and improve building energy andand demand response features directly into building design

  3. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    NONE

    2007-10-15T23:59:59.000Z

    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.

  4. Demand Response and Energy Efficiency

    E-Print Network [OSTI]

    Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5... for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 5 What is Demand Response? ?The temporary reduction of electricity demanded from the grid by an end-user in response to capacity shortages, system reliability events, or high wholesale...

  5. Demand Response Technology Roadmap A

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

    workshop agendas, presentation materials, and transcripts. For the background to the Demand Response Technology Roadmap and to make use of individual roadmaps, the reader is...

  6. Demand Response Technology Roadmap M

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

    between May 2014 and February 2015. The Bonneville Power Administration (BPA) Demand Response Executive Sponsor Team decided upon the scope of the project in May. Two subsequent...

  7. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL

    2013-01-01T23:59:59.000Z

    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.

  8. Overview of Demand Side Response

    Broader source: Energy.gov [DOE]

    Presentation—given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008 meeting—discusses the utility PJM's demand side response (DSR) capabilities, including emergency and economic responses.

  9. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    and best practices to guide HECO demand response developmentbest practices for DR renewable integration – Technically demand responseof best practices. This is partially because demand response

  10. ERCOT Demand Response Paul Wattles

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    changes or incentives.' (FERC) · `Changes in electric use by demand-side resources from their normalERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre thermostats -- Other DLC Possible triggers: Real-time prices, congestion management, 4CP response paid

  11. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

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

    2005-04-01T23:59:59.000Z

    This paper describes the results from the second season of research 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 the electric grid reliability and manage electricity costs. 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. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

  12. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

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

    2010-01-29T23:59:59.000Z

    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.

  13. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    sector, the demand response potential of California buildinga demand response event prohibit a building’s participationdemand response strategies in California buildings are

  14. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    Conference on Building Commissioning: May 4-6, 2005 Motegi,National Conference on Building Commissioning: May 4-6, 2005Demand Response and Commissioning Mary Ann Piette, David S.

  15. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01T23:59:59.000Z

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

  18. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

  19. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

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

  20. Demand response-enabled residential thermostat controls.

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    human dimension of demand response technology from a caseArens, E. , et al. 2008. Demand Response Enabling TechnologyArens, E. , et al. 2006. Demand Response Enabling Technology

  1. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01T23:59:59.000Z

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

  2. National Action Plan on Demand Response

    Broader source: Energy.gov [DOE]

    Presentation—given at the Federal Utility Partnership 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 related to the energy outlook.

  3. 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.

    2007-05-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    BEST PRACTICES AND RESULTS OF DR IMPLEMENTATION . 31 Encouraging End-User Participation: The Role of Incentives 16 Demand Response

  5. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    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

  6. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    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).

  7. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    al: Installation and Commissioning Automated Demand ResponseConference on Building Commissioning: April 22 – 24, 2008al: Installation and Commissioning Automated Demand Response

  8. Sandia National Laboratories: demand response inverter

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

    demand response inverter ECIS-Princeton Power Systems, Inc.: Demand Response Inverter On March 19, 2013, in DETL, Distribution Grid Integration, Energy, Energy Surety, Facilities,...

  9. Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

    SciTech Connect (OSTI)

    Denholm, P.; Ong, S.; Booten, C.

    2012-05-01T23:59:59.000Z

    This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

  10. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    NONE

    2010-04-15T23:59:59.000Z

    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.

  11. Demand Response Programs for Oregon

    E-Print Network [OSTI]

    wholesale prices and looming shortages in Western power markets in 2000-01, Portland General Electric programs for large customers remain, though they are not active at current wholesale prices. Other programs demand response for the wholesale market -- by passing through real-time prices for usage above a set

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

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

  13. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01T23:59:59.000Z

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

  14. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

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

  15. 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

  16. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    temperature-based demand response in buildings that havedemand response advantages of global zone temperature setup in buildings

  17. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    DEMAND RESPONSE .7 Wholesale Marketuse at times of high wholesale market prices or when systemenergy expenditure. In wholesale markets, spot energy prices

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    in Demand Response for Wholesale Ancillary Services Silain Demand Response for Wholesale Ancillary Services Silasuccessfully in the wholesale non- spinning ancillary

  20. 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

    2004-08-01T23:59:59.000Z

    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.

  1. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    renewable integration capability. Coordinating and integrating HECO and Hawaii Energy demand response related activities has the potential

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01T23:59:59.000Z

    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.

  9. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    Response Controls for HVAC Systems Clifford Federspiel,tests. Figure 5: Specific HVAC electric power consumptioncontrol, demand response, HVAC, wireless Executive Summary

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2013-01-01T23:59:59.000Z

    for the Open Automated Demand Response (OpenADR) StandardsControl for Automated Demand Response, Grid Interop, 2009. [C. McParland, Open Automated Demand Response Communications

  12. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    reliability signals for demand response GTA HTTPS HVAC IT kWand Commissioning Automated Demand Response Systems. ”and Techniques for Demand Response. California Energy

  13. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

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

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01T23:59:59.000Z

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

  15. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Goli, Sasank

    2012-01-01T23:59:59.000Z

    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).

  16. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    advanced metering and demand response in electricityGoldman, and D. Kathan. “Demand response in U.S. electricity29] DOE. Benefits of demand response in electricity markets

  18. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

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

  20. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

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

  1. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

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

  2. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response.Building Systems and DR Strategies 16 Demand ResponseDemand Response Systems. ” Proceedings, 16 th National Conference on Building

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01T23:59:59.000Z

    in California. DEMAND RESPONSE AND COMMERCIAL BUILDINGSload and demand response against other buildings and alsoDemand Response and Energy Efficiency in Commercial Buildings",

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Keywords: demand response, buildings, electricity use, Interface  Automated Demand Response  Building Automation of demand response in  commercial buildings.   One key 

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

    E-Print Network [OSTI]

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

    2004-01-01T23:59:59.000Z

    Management and Demand Response in Commercial Buildings", L BAutomated Demand Response National Conference on BuildingAutomated Demand Response National Conference on Building

  6. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  7. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    Demand  Response for Small Commercial Buildings.   CEC?500?automated demand response  For small commercial buildings, AUTOMATED DEMAND RESPONSE FOR SMALL COMMERCIAL BUILDINGS

  8. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    for Demand Response in New and Existing Commercial BuildingsDemand Response Strategies and National Conference on BuildingDemand Response Strategies and Commissioning Commercial Building

  9. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. Inbased demand response information to building controlDemand Response Standard for the Residential Sector. California Energy Commission, PIER Buildings

  10. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    is manual demand response where building staff receive acommercial buildings’ demand response technologies andBuilding Control Strategies and Techniques for Demand Response.

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  12. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters March 10, 2015 -...

  13. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    Commission (FERC) 2008a. “Wholesale Competition in RegionsDemand Response into Wholesale Electricity Markets,” (URL:1 2. Wholesale and Retails Electricity Markets in

  14. Demand Response - Policy | Department of Energy

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

    prices or when grid reliability is jeopardized. In regions with centrally organized wholesale electricity markets, demand response can help stabilize volatile electricity prices...

  15. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19T23:59:59.000Z

    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. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

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

  17. Wastewater plant takes plunge into demand response

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

    Commission and the Bonneville Power Administration, the Eugene-Springfield Water Pollution Control Facility in Eugene, Ore., was put through a series of demand response tests....

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

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

    Honeywell's Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardwaresoftware platform for automated demand response (ADR). This project...

  19. Demand Response and Electric Grid Reliability

    E-Print Network [OSTI]

    Wattles, P.

    2012-01-01T23:59:59.000Z

    Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

  20. INTEGRATION OF PV IN DEMAND RESPONSE

    E-Print Network [OSTI]

    Perez, Richard R.

    . It may also be implemented by means of customer-sited emergency power generation (e.g., diesel generators 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

  1. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

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

    2012-02-28T23:59:59.000Z

    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.

  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]

    Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

  3. Demand Response Programs Oregon Public Utility Commission

    E-Print Network [OSTI]

    , Demand Side Management #12;Current Programs/Tariffs ­ Load Control Programs Cool Keeper, Utah (currentlyDemand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director 33 MW, building to 90 MW) Irrigation load control, Idaho (35 MW summer, 2004) Lighting load control

  4. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    37 3.8.1. Impacts of DR programs on Wholesale MarketPrice Response on Wholesale Markets.in Organized Wholesale Markets .19

  5. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    Pepco.6: Comparison of SCE, BGE and Pepco Maryland AMI Business3.6.2. Maryland: BGE and Pepco In response to the federal

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

    Office of Environmental Management (EM)

    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. Market Response ModelsMarket Response Models Demand CreationDemand Creation

    E-Print Network [OSTI]

    Brock, David

    Market Response ModelsMarket Response Models andand Demand CreationDemand Creation Dominique MImportance of Marketing Investments Need for a Market Response focusNeed for a Market Response focus Digital data enriched acquisition and retention costsasymmetry between acquisition and retention costs In both cases, longIn both

  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. Capitalize on Existing Assets with Demand Response

    E-Print Network [OSTI]

    Collins, J.

    2008-01-01T23:59:59.000Z

    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...

  10. 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 operating by some Korean paper companies for acquiring needed pulpwood as a first step for the construction

  11. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

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

    2009-07-15T23:59:59.000Z

    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)

  12. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    12: Market Impacts of Price Responsive Load in PJM and ISO-44 Figure 15: PJM Synchronized Reserve Scheduled MW:particularly those in PJM’s service territory, have begun

  13. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

  14. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration would like submit the following comments response NAESB

  15. 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

  16. 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

  17. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    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"

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01T23:59:59.000Z

    El-Saadany. “A summary of demand response in electricityadvanced metering and demand response in electricityWolak. When it comes to demand response is FERC is own worst

  19. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    for Demand Response in a New Commercial Building in NewDemand Response and Energy Efficiency in Commercial Buildings.Demand Response Mary Ann Piette, Sila Kiliccote, and Girish Ghatikar Lawrence Berkeley National Laboratory Building

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

    E-Print Network [OSTI]

    Boutaba, Raouf

    Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing Jin Xiao, Jae--In this paper, we present demand-side energy manage- ment under real-time demand-response pricing as a task, demand-response, energy management I. INTRODUCTION The growing awareness of global climate change has

  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

    2011-04-29T23:59:59.000Z

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    demand response and energy ef?ciency in commercial buildings,”building control strategies and techniques for demand response,”building electricity use with application to demand response,”

  3. 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...

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

    E-Print Network [OSTI]

    2010-10-31T23:59:59.000Z

    Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... On the other hand, demand response, which enables customers to ...

  5. 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

  6. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30T23:59:59.000Z

    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.

  7. ERCOT's Weather Sensitive Demand Response Pilot

    E-Print Network [OSTI]

    Carter, T.

    2013-01-01T23:59:59.000Z

    ERCOT’s Weather Sensitive 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... 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...

  8. Demand Response Initiatives at CPS Energy

    E-Print Network [OSTI]

    Luna, R.

    2013-01-01T23:59:59.000Z

    Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSE’s DR Program • DR... than the military bases 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...

  9. 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

    2008-04-21T23:59:59.000Z

    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.

  10. Smart Buildings Using Demand Response March 6, 2011

    E-Print Network [OSTI]

    Kammen, Daniel M.

    Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Research Center Program Manager, Building Technologies Department Environmental Energy Technologies only as needed) · Energy Efficiency strategies are permanent (occur daily) 4 #12;Demand-Side

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

    SciTech Connect (OSTI)

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

    2012-02-14T23:59:59.000Z

    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.

  12. 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

  13. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03T23:59:59.000Z

    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.

  14. Demand Response For Power System Reliability: FAQ

    SciTech Connect (OSTI)

    Kirby, Brendan J [ORNL

    2006-12-01T23:59:59.000Z

    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.

  15. 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

  16. 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

  17. Measurement and evaluation techniques for automated demand response demonstration

    E-Print Network [OSTI]

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

    2004-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings. ” Highdemand-response technologies in large commercial and institutional buildings.building method California Independent System Operator (Cal ISO)’s Demand Response

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

    SciTech Connect (OSTI)

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

    2009-02-01T23:59:59.000Z

    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.

  19. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

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

  20. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01T23:59:59.000Z

    Automated  Demand  Response  in  Commercial  Buildings.  Demand  Response  Infrastructure  for   Commercial  Buildings.  

  2. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    McParland, Charles

    2009-12-01T23:59:59.000Z

    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.

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

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

    This report represents a review of policy developments on demand response and other related areas such as smart meters and smart grid. It has been prepared by the Demand Response...

  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. 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

  6. 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

  7. 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...

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    demand response programs identifies three clusters of industries as the key participants: • petroleum, plastic,Demand Response Potential from Audit Database Top 25 Industries by Average kW Table 1 3344 Semiconductors & Electronics 3261 Plastic

  9. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    January 2008. Biography Mary Ann Piette is a Staff ScientistAutomated Demand Response Mary Ann Piette, Sila Kiliccote,

  10. An Operational Model for Optimal NonDispatchable Demand Response

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    FACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power

  11. 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

  12. 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

  13. 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

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

    E-Print Network [OSTI]

    Low, Steven H.

    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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Opportunities and Challenges for Data Center Demand Response

    E-Print Network [OSTI]

    Wierman, Adam

    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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. Two Market Models for Demand Response in Power Networks

    E-Print Network [OSTI]

    Low, Steven H.

    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

  8. 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

  9. Graphical language for identification of control strategies allowing Demand Response

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Graphical language for identification of control strategies allowing Demand Response David DA SILVA. This will allow the identification of the electric appliance availability for demand response control strategies to be implemented in terms of demand response for electrical appliances. Introduction An important part

  10. Optimal Demand Response with Energy Storage Management

    E-Print Network [OSTI]

    Huang, Longbo; Ramchandran, Kannan

    2012-01-01T23:59:59.000Z

    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...

  11. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    M T E P 06 - The Midwest ISO Transmission Expansion Plan,Demand Response in Midwest ISO Market," Presentation at MISODemand Response with Midwest ISO Wholesale Markets Ranjit

  12. Retail Demand Response in Southwest Power Pool

    SciTech Connect (OSTI)

    Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

    2009-01-30T23:59:59.000Z

    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.

  13. Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective

    E-Print Network [OSTI]

    Metaxoglou, Konstantinos

    We document the numerical challenges we experienced estimating random-coefficient demand models as in Berry, Levinsohn, and Pakes (1995) using two well-known data sets and a thorough optimization design. The optimization ...

  14. 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

  15. Intelligent Building Automation: A Demand Response Management Perspective

    E-Print Network [OSTI]

    Qazi, T.

    2010-01-01T23:59:59.000Z

    the energy consumption in response to energy price fluctuations, demand charges, or a direct request to reduce demand when the power grid reaches critical levels. However, in order for a demand response regime to be effective the building will need to have a...

  16. Optimal Demand Response Capacity of Automatic Lighting Control

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    . To remedy this problem, different demand side management programs have been proposed to shape the energy prior studies have extensively studied the capacity of offering demand response in buildings and office buildings. Keywords: Demand response, automatic lighting control, commercial and office buildings

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

    E-Print Network [OSTI]

    ) is a demand-side management strategy to reduce electricity use during times of high peak electric loads;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

  18. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

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

    2008-11-19T23:59:59.000Z

    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.

  19. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    demand-side management (DSM) framework presented in Table x provides three major areas for changing electric loads in buildings:

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01T23:59:59.000Z

    Goldman, G. (2009) Retail demand response in Southwest PowerL. (2009) Renewable Demand Response (RDR): Financial &Northwest GridWise™ Demand Response and Variable Generation

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01T23:59:59.000Z

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

  6. Demand response-enabled autonomous control for interior space conditioning in residential buildings.

    E-Print Network [OSTI]

    Chen, Xue

    2008-01-01T23:59:59.000Z

    Demand Response Autonomous Controlssystem under the context of demand response for residential10] E. Arens et al. , Demand response enabling technology

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

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

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

    E-Print Network [OSTI]

    Page, Janie

    2012-01-01T23:59:59.000Z

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

  9. Quantifying Changes in Building Electricity Use, with Application to Demand Response

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    and techniques for demand response,” Lawrence BerkeleyNational action plan on demand response,” Prepared with the3] G. He?ner, “Demand response valuation frameworks paper,”

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

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Koch, Ed; Piette, Mary Ann

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Herter, Karen

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Watson, David S.

    2013-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Eto, Joseph H.

    2010-01-01T23:59:59.000Z

    A. Barat, D. Watson. 2007. Demand Response Spinning ReserveN ATIONAL L ABORATORY Demand Response Spinning Reserveemployer. LBNL-XXXXX Demand Response Spinning Reserve

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

    E-Print Network [OSTI]

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

    2009-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01T23:59:59.000Z

    of Distributed Energy Resources and Demand Response underof Distributed Energy Resources and Demand Response underof Distributed Energy Resources and Demand Response under

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

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01T23:59:59.000Z

    Integration of Energy Efficiency and Demand Response Intohttp://www.cpuc.ca.gov/PUC/energy/Demand+Response/Cost-Utilization of Energy Efficiency and Demand Response as

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

    E-Print Network [OSTI]

    Piette, Mary Ann; Kiliccote, Sila

    2006-01-01T23:59:59.000Z

    Demand Response in Commercial Buildings 3.1. Demand Response in Commercial Buildings ElectricityDemand Response: Understanding the DR potential in commercial buildings

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. ” InAutomated Demand Response for Small Commercial Buildings. ”in automated demand response programs with building control

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2014-01-01T23:59:59.000Z

    account  demand  response  signals,  building?integrated of Automated Demand Response in Commercial Buildings.  and Demand Response in Commercial  Buildings. , LBNL 

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

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    PA. 3. DEMAND RESPONSE IN COMMERCIAL BUILDINGS ElectricityDemand Response and Energy Efficiency in Commercial BuildingsDemand Response and Energy Efficiency in Commercial Buildings

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

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    is manual demand response -- where building staff receives aand Demand Response in Commercial Building. ,April, LBNL-Keywords: Demand response, automation, commercial buildings,

  4. 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

    2004-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings. ” LBNL Reportautomated Demand Response (DR) technologies in buildings.Automated Demand Response is initiated at a building or

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

    high.  Demand response helps to manage building electricity Building  Control Strategies and Techniques for Demand Response.  Non?Residential Building in California.   Demand Response 

  6. Machine to machine (M2M) technology in demand responsive commercial buildings

    E-Print Network [OSTI]

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

    2004-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings. ” Highoperate buildings to maximize demand response and minimizeDemand Response Demonstration”, 2004 ACEEE Summer Study on Energy Efficiency in Buildings.

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

    E-Print Network [OSTI]

    Koch, Ed; Piette, Mary Ann

    2008-01-01T23:59:59.000Z

    is manual demand response -- where building staff receives aKeywords: Demand response, automation, commercial buildings,buildings, especially as it applies to Demand Response

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

    E-Print Network [OSTI]

    Page, Janie

    2012-01-01T23:59:59.000Z

    Demand Response for Small Commercial Buildings.   Lawrence small?medium buildings’ roles in demand response  efforts.  demand response for small? medium commercial buildings 

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

    E-Print Network [OSTI]

    Granderson, Jessica

    2010-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response.of Automated Demand Response in a Large Office Building.there demand response potential in commercial building that

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    and Demand Response in Commercial Building,” Report No.Demand Response Infrastructure for Commercial Buildings MaryDemand Response Infrastructure for Commercial Buildings Mary

  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

    2014-01-01T23:59:59.000Z

    1. Demand response with price-anticipating buildings. C.one-stage demand response because all the building managersbuilding electricity use, with application to demand response,”

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

    E-Print Network [OSTI]

    Motegi, N.

    2011-01-01T23:59:59.000Z

    for Demand Response in New and Existing Commercial BuildingsBuilding Control Strategies and Techniques for Demand Response -Building Control Strategies and Techniques for Demand Response

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Automated Demand Response for Small Commercial Buildings. ”Demand Response Strategies and Commissioning Commercial Buildingfor Automated Demand Response in Commercial Buildings Sila

  14. Opportunities for Automated Demand Response in Wastewater Treatment

    E-Print Network [OSTI]

    ;CHAPTER 4: Facility Baseline Analysis Net Plant Demand Figure 5: Average load profile for net plant demand characteristics and estimated shed potential for six submetered centrifuge Lift Pumps #12;Figure 7: Daily profile on event days compared to average dry season demand Partial-day complete plant shutdown Table 5: Load sheds

  15. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    peak demand management. Photo sensors for daylight drivenare done by local photo-sensors and control hardwaresensing device in a photo sensor is typically a photodiode,

  16. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    in peak demand. This definition of energy efficiency makesthe following definitions are used: Energy efficiency refersThis definition implicitly distinguishes energy efficiency

  17. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    in Demand Response for Wholesale Ancillary Services. ” Incan be used to link wholesale and retail real-time prices.11 Wholesale Electricity Market Information

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

    E-Print Network [OSTI]

    Long Zhao

    2010-10-31T23:59:59.000Z

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

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

    Open Energy Info (EERE)

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

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

    Office of Environmental Management (EM)

    and demonstrate methodologies to enhance the ability of customer sited demand response resources, both conventional and renewable, to integrate more effectively with electric...

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

    Office of Environmental Management (EM)

    and demonstrate methodologies to enhance the ability of customer sited demand response resources, both conventional and renewable, to integrate more effectively with electric...

  2. The Role of Enabling Technologies in Demand Response

    SciTech Connect (OSTI)

    NONE

    2007-09-15T23:59:59.000Z

    The report provides a study of the technologies that are crucial to the success of demand response programs. It takes a look at the historical development of demand response programs and analyzes how new technology is needed to enable demand response to make the transition from a small scale pilot operation to a mass market means of improving grid reliability. Additionally, the report discusses the key technologies needed to enable a large scale demand response effort and evaluates current efforts to develop and integrate these technologies. Finally, the report provides profiles of leading developers of these key technologies.

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

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

  4. Progress toward Producing Demand-Response-Ready Appliances

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.; Sastry, Chellury

    2009-12-01T23:59:59.000Z

    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.

  5. Interoperability of Demand Response Resources Demonstration in NY

    SciTech Connect (OSTI)

    Wellington, Andre

    2014-03-31T23:59:59.000Z

    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.

  6. 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

    2009-11-06T23:59:59.000Z

    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.

  7. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    SciTech Connect (OSTI)

    Goli, Sasank; McKane, Aimee; Olsen, Daniel

    2011-06-14T23:59:59.000Z

    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.

  8. A DISTRIBUTED INTELLIGENT AUTOMATED DEMAND RESPONSE BUILDING MANAGEMENT SYSTEM

    SciTech Connect (OSTI)

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

    2013-12-30T23:59:59.000Z

    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.

  9. Estimation and specification tests of count data recreation demand functions

    E-Print Network [OSTI]

    Gomez, Irma Adriana

    1991-01-01T23:59:59.000Z

    is ultimately used to compute consumer surplus for natural resource policy analysis. Data from population-wide surveys, although not collected quite as frequently as user survey data, are also useful for estimating recreation demand functions. However, data... of distributions. They specify the mean and variance of the Katz distribution under the alternative to be p. ; and (lt; + u p. ; ), 2-k respectively. In this case, the Poisson estimator is obtain when u = 0. This suggest that a test for the null against...

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

    SciTech Connect (OSTI)

    Hogan, William W.

    2010-11-15T23:59:59.000Z

    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)

  11. Response to changes in demand/supply

    E-Print Network [OSTI]

    , distribution channels, differentiation of quality, price, specification, etc., of the products. Primary wood with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board;112 distribution channels, differentiation of quality, price, specification, etc., of the products. Primary wood

  12. Value of Demand Response -Introduction Klaus Skytte

    E-Print Network [OSTI]

    of wind power. #12;Perspectives ­ The System Operator Keep the balance Demand reduction = increased as indicator. #12;Motivations We want more wind power in the system. This require more flexibility of the rest plants and better use of wind power. Public goods / Externalities not measured in the markets #12

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

    SciTech Connect (OSTI)

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

    2013-11-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2011-10-10T23:59:59.000Z

    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.

  15. 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

    2009-02-28T23:59:59.000Z

    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.

  16. Nordic TSOs' Action Plans in enhancing and monitoring Demand Response

    E-Print Network [OSTI]

    THE OPERATIONAL SECURITY OF THE POWER SYSTEM AND TO MAINTAIN THE NATIONAL MOMENTARY BALANCE for the Nordic market model functioning. The importance of demand re- sponse is increasing while the powerNordic TSOs' Action Plans in enhancing and monitoring Demand Response Nordel Market Committee

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

    E-Print Network [OSTI]

    the need and methods for commercial building sector involvement in demand response (DR). We summarize, including architects, engineers, consultants, contractors, and building owners and managers. Finally, we in the US increased the focus on the need for flexible demand-side resources to address four major

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01T23:59:59.000Z

    commercial building, demand response, dynamic pricing,demand response (Auto-DR) in large commercial buildingsdemand response (Auto-DR) in large commercial buildings

  19. Demand-Side Response from Industrial Loads

    SciTech Connect (OSTI)

    Starke, Michael R [ORNL; Alkadi, Nasr E [ORNL; Letto, Daryl [Enbala Power Networks; Johnson, Brandon [University of Tennessee, Knoxville (UTK); Dowling, Kevin [University of Tennessee, Knoxville (UTK); George, Raoule [Enbala Power Networks; Khan, Saqib [University of Texas, Austin

    2013-01-01T23:59:59.000Z

    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.

  20. Demand Response (transactional control) - Energy Innovation Portal

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration wouldDECOMPOSITIONPortal DecisionRichlandDelegations,DemandEnergy

  1. 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...

  2. Summary of the 2006 Automated Demand Response Pilot

    E-Print Network [OSTI]

    Piette, M.; Kiliccote, S.

    2007-01-01T23:59:59.000Z

    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...

  3. 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

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    energy cost for DR; The packaging of DR offerings is perceived as inadequate; A business’energy costs. o Several demand response programs offer financial and other benefits to businesses

  5. Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response 

    E-Print Network [OSTI]

    Tyra, K.; Hanel, J.

    2012-01-01T23:59:59.000Z

    Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response October 10, 2012 ENERGY EFFICIENCY PROGRAMS OVERVIEW ?Program rules and guidelines established by Public Utility Commission of Texas (PUCT) ?All Texas investor...

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

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann

    2005-01-01T23:59:59.000Z

    driven building response. Demand Side Management Energybuildings. Table 1 outlines how DR fits into historical demand side management (

  7. 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

    2011-08-15T23:59:59.000Z

    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.

  8. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

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

    2009-05-01T23:59:59.000Z

    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.

  9. 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

    2009-12-30T23:59:59.000Z

    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.

  10. 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

  11. 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

  12. 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

  13. 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

    2007-01-01T23:59:59.000Z

    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

  14. 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

    2014-01-01T23:59:59.000Z

    ? min . [1] U. D. of Energy, “Benefits of demand response inHong, and X. Li, “A demand response energy management schemefor energy efficiency and automated demand response in

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2014-01-01T23:59:59.000Z

    Systems for  Energy Management and Demand Response in 7.  Linking energy efficiency and demand response.   In for Low-Energy Operations and Optimal Demand Response Mary

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01T23:59:59.000Z

    centers. 4. Demand Response Strategies Building from theBuilding Control Strategies and Techniques for Demand Response.Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Building

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

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann

    2005-01-01T23:59:59.000Z

    and individuals. DEMAND RESPONSE BUILDINGS RESEARCH Recentand event driven building response. Demand Side ManagementDemand Response does not involve human intervention, but is initiated at a home, building,

  18. Quantifying Changes in Building Electricity Use, with Application to Demand Response

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    building control strategies and techniques for demand response,”demand response systems,” in Proceedings of 16th National Conference on BuildingBuilding Electricity Use, with Application to Demand Response

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

    E-Print Network [OSTI]

    Stadler, Michael

    2009-01-01T23:59:59.000Z

    Net- Energy Buildings with Demand Response Michael Stadler,Net-Energy Buildings with Demand Response 1 Michael Stadlerbuilding simulation tools, e.g. , EnergyPlus, require specification of the demand response

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

    E-Print Network [OSTI]

    Han, Junqiao

    2008-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response,Automated Demand Response in a Large Office Building JunqiaoDemand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Building

  1. Demand response-enabled autonomous control for interior space conditioning in residential buildings.

    E-Print Network [OSTI]

    Chen, Xue

    2008-01-01T23:59:59.000Z

    of demand response for residential buildings. ProfessorDemand Response-enabled Autonomous Control for Interior Space Conditioning in Residential BuildingsDemand Response-enabled Autonomous Control for Interior Space Conditioning in Residential Buildings

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01T23:59:59.000Z

    and provide demand response (DR) through building controland provide demand response (DR) through building controlDemand Response Automation Server (DRAS) in a 15-minute interval. This allows the continuous monitoring of the building's

  3. A First Look at Colocation Demand Response Shaolei Ren

    E-Print Network [OSTI]

    Ren, Shaolei

    programs and receive financial benefits by reducing energy consumption upon utility's request. However, on the other hand, can reduce server energy consumption but may not desire demand response unless response by using a trace-based simulation to show that iCODE can significantly reduce energy consumption

  4. 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

  5. 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 compared to their counterparts such as laptops in nomad computing or sensor networks. First, vehicles response (DR) [1] for automatic utility usage retrievals and price dispatching. DR is a project in- itiated

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Olsen, Daniel

    2012-01-01T23:59:59.000Z

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

  8. 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

  9. 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

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

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

    The Demand Response and Smart Grid Coalition (DRSG), the trade association for companies that provide products and services in the areas of demand response and smart grid...

  11. 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

    2006-01-01T23:59:59.000Z

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

  12. Killing Two Birds with One Stone: Can Real-Time Pricing Support Retail Competition and Demand Response?

    E-Print Network [OSTI]

    Barbose, Galen; Bharvirkar, Ranjit; Goldman, Charles; Hopper, Nicole; Neenan, Bernie

    2006-01-01T23:59:59.000Z

    Competition and Demand Response? Galen Barbose, Ranjitbenefit of stimulating demand response. To evaluate themarket development and demand response – we conducted a

  13. 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

    2006-01-01T23:59:59.000Z

    potential demand response in commercial buildings with EMCSbuildings for integrated energy efficiency and demand response (buildings provide an excellent resource for demand response.

  14. 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

    2014-01-01T23:59:59.000Z

    automated demand response systems in large buildings in theBuilding Control Strategies and Techniques for Demand Response,buildings were able to provide significant demand response

  15. 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.

    2013-01-01T23:59:59.000Z

    1 October 10th 2013 ? 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...-10-20 Proceedings of the 13th International Conference for Enhanced Building Operations, Montreal, Quebec, October 8-11, 2013 4 Demand response in CI buildings ESL-IC-13-10-20 Proceedings of the 13th International Conference for Enhanced Building Operations...

  16. Optimal Design of Demand-Responsive Feeder Transit Services

    E-Print Network [OSTI]

    Li, Xiugang

    2010-10-12T23:59:59.000Z

    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...

  17. Autonomous Demand Response in Heterogeneous Smart Grid Topologies

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    , heterogeneous grid, locational marginal price, game theory, Nash equilibrium. I. INTRODUCTION Demand response on locational marginal prices (LMPs), which depend on parameters such as the line c appliances such as air-conditioners and water-heaters [2]. An alternative for DLC is smart pricing, where

  18. 2008-2010 Research Summary: Analysis of Demand Response

    E-Print Network [OSTI]

    ;#12;Figure 4: Energy end-uses for a sample of wastewater treatment plants in New York State 2.1.1. Wastewater · · · · · #12;#12;Figure 6: Energy performance of a refrigerated warehouse during a demand response event compared to baseline energy usage #12;Figure 7: Energy performance of a refrigerated warehouse which

  19. Ris-R-1565(EN) Analyses of Demand Response

    E-Print Network [OSTI]

    of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many in Denmark and the Nordic Power Market..........................21 4.2 Prices and demand response options in Denmark Department: Systems Analysis Department Risø-R-1565(EN) October 2006 ISSN 0106-2840 ISBN 87

  20. automated demand response: Topics by E-print Network

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

    automated demand response First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 Analysis of Open Automated...

  1. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

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

    2009-08-01T23:59:59.000Z

    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.

  2. 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.

    2012-07-22T23:59:59.000Z

    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

  3. 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

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

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01T23:59:59.000Z

    Potential Role of Demand Response Resources in Maintaining Grid Stability and Integrating Variable Renewable Energy

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

    SciTech Connect (OSTI)

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

    2008-11-19T23:59:59.000Z

    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.

  6. Distributed Demand Response and User Adaptation in Smart Grids

    E-Print Network [OSTI]

    Fan, Zhong

    2010-01-01T23:59:59.000Z

    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.

  7. Coordination of Retail Demand Response with Midwest ISO Markets

    SciTech Connect (OSTI)

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

    2008-05-27T23:59:59.000Z

    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.

  8. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Chuck; Neenan, Bernie

    2006-03-10T23:59:59.000Z

    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].

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

    E-Print Network [OSTI]

    Scott, Doug

    2014-01-01T23:59:59.000Z

    detailed the energy efficiency and demand response measuresto control both their energy usage and demand in order torequires balancing energy efficiency and demand response.

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

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Lekov, Alex

    2009-01-01T23:59:59.000Z

    Best Practices. Kiliccote, S. (2008). Automated Demand Responsebest operation practices and behaviors to enhance the impact of DR activities. 1.0 Introduction Background and Overview Demand Response (

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

    E-Print Network [OSTI]

    Olsen, Daniel

    2013-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Low, Steven H.

    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

  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. Demand responsive programs - an emerging resource for competitive electricity markets?

    SciTech Connect (OSTI)

    Heffner, Grayson C. Dr.; Goldman, Charles A.

    2001-06-25T23:59:59.000Z

    The restructuring of regional electricity markets in the U.S. has been accompanied by numerous problems, including generation capacity shortages, transmission congestion, wholesale price volatility, and reduced system reliability. These problems have created significant new opportunities for technologies and business approaches that allow load serving entities and other aggregators, to control and manage the load patterns of their wholesale or retail end-users. These technologies and business approaches for manipulating end-user load shapes are known as Load Management or, more recently, Demand Responsive programs. Lawrence Berkeley National Laboratory (LBNL) is conducting case studies on innovative demand responsive programs and presents preliminary results for five case studies in this paper. These case studies illustrate the diversity of market participants and range of technologies and business approaches and focus on key program elements such as target markets, market segmentation and participation results; pricing scheme; dispatch and coordination; measurement, verification, and settlement; and operational results where available.

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

    SciTech Connect (OSTI)

    Chassin, David P.; Kalsi, Karanjit

    2012-07-26T23:59:59.000Z

    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.

  17. Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response

    E-Print Network [OSTI]

    Tyra, K.; Hanel, J.

    2012-01-01T23:59:59.000Z

    Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response October 10, 2012 ENERGY EFFICIENCY PROGRAMS OVERVIEW ?Program rules and guidelines established by Public Utility Commission of Texas (PUCT) ?All Texas investor... to be administered by transmission-distribution utilities ?Programs are implemented by Energy Efficiency Services Providers and Retail Electric Providers 1 WHY DOES ONCOR DO SOLAR PV? ?Helps meet our energy efficiency goals ?Helps customers reduce...

  18. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2005-11-09T23:59:59.000Z

    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. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2014-03-01T23:59:59.000Z

    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.

  2. Workshop on Demand Response, Ballerup, 7. February 2006 1 Monte Carlo Simulations of the Nordic Power System

    E-Print Network [OSTI]

    Power System · How to estimate the value of demand response? · Method · Model · Setup · Results Stine the value of extreme events and not only averages Estimates the benefit of DR in the Nordic power system 2006 9 The Nordic power system · Total available power capacity is 80,000 MW. Interconnections exist

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

    SciTech Connect (OSTI)

    Douglas C. Larson; Matt Lowry; Sharon Irwin

    2004-06-29T23:59:59.000Z

    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.

  4. The Integration of Energy Efficiency, Renewable Energy, Demand Response and Climate Change: Challenges and Opportunities for Evaluators and Planners

    E-Print Network [OSTI]

    Vine, Edward

    2007-01-01T23:59:59.000Z

    to inform projected energy and demand reductions in regionaldown to reflect energy and demand savings due to spillover (market and estimate the energy and demand savings associated

  5. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

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

    2010-03-17T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01T23:59:59.000Z

    and demand response for large commercial buildings in Newdemand response and energy efficiency in commercial buildings.demand response participation for large commercial buildings

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

    E-Print Network [OSTI]

    Granderson, J.; Dudley, J. H.; Kiliccote, S.; Piette, M. A.

    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...

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

    E-Print Network [OSTI]

    Watson, David S.

    2013-01-01T23:59:59.000Z

    demand response is more environmentally friendly than fossil fueldemand response (DR) used in the commercial and industrial sectors is more environmentally friendly than fossil fuelfossil fuels are the predominant heating fuels for California’s commercial buildings, heating electricity demand

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

    E-Print Network [OSTI]

    Watson, David S.

    2013-01-01T23:59:59.000Z

    Sodium Sulfur (NaS) Zinc- Air Battery Demand Response CostsSodium Sulfur (NaS) Zinc- Air Battery Low High AverageSodium Sulfur (NaS) Zinc- Air Battery Demand Response Costs

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

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01T23:59:59.000Z

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

    Office of Environmental Management (EM)

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic2 OPAM615_CostNSAR -DepartmentRetail Demand Response in Southwest Power Pool

  12. Confidence Intervals for OD Demand Estimation Yingying Chen, Fernando Ordo~nez

    E-Print Network [OSTI]

    Ordóñez, Fernando

    Confidence Intervals for OD Demand Estimation Yingying Chen, Fernando Ord´o~nez , and Kurt Palmer Representative origin-destination (OD) demand tables are a crucial part of making many transportation models relevant to practice. However estimating these OD tables is a challenging problem, even more so determining

  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 this problem by applying privacy-aware design practices to the development of demand response architectures

  14. 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

  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. 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

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

    E-Print Network [OSTI]

    Wierman, Adam

    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

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

    E-Print Network [OSTI]

    Culler, David E.

    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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. (2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via

    E-Print Network [OSTI]

    Wierman, Adam

    (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

  11. 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

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

    E-Print Network [OSTI]

    Liberzon, Daniel

    (DRRs), sign a contract with an aggregating entity--the demand response provider--so as their load canDistributed 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

  13. RisNyt NO2 2005 1313 Demand response er som at kbe benzin

    E-Print Network [OSTI]

    RisøNyt NO2 2005 1313 Demand response er som at købe benzin når den er billigst Af Leif Sønderberg tankstationen og købe mest muligt benzin når prisen er lavest. Sådan er Demand Response, som vi også vil opleve at ændre på dette er Demand Response (DR), hvor man inden for korte tids- intervaller skal agere på

  14. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Lawrence Berkeley National Laboratory; Kiliccote, Sila

    2011-11-18T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Cappers, Peter; Goldman, Charles; Kathan, David

    2009-06-01T23:59:59.000Z

    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.

  17. 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.

    2013-07-01T23:59:59.000Z

    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.

  18. 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

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

    SciTech Connect (OSTI)

    Piette, Mary Ann; Kiliccote, Sila

    2006-09-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2009-11-06T23:59:59.000Z

    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.

  1. Nonlinear estimation of water network demands form limited measurement information

    E-Print Network [OSTI]

    Rabie, Ahmed Ibrahim El Said

    2009-05-15T23:59:59.000Z

    the simulator EPANET using 3 case studies. In the second phase, the estimation formulation was tested using the same 3 case studies with different sensor configurations. In each of the case studies, estimation results are reasonable with fewer sensors than...

  2. 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

    2008-01-31T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    None

    2012-02-11T23:59:59.000Z

    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.

  4. 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

    2013-01-01T23:59:59.000Z

    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

  5. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01T23:59:59.000Z

    of Automated Demand Response in a Large Office Building”, inBuilding Control Strategies and Techniques for Demand Response.Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

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

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01T23:59:59.000Z

    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.

  7. Scenarios for Consuming Standardized Automated Demand Response Signals

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2008-10-03T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    Demand Side Management Framework for Industrial Facilities provides three major areas for changing electric loads in industrial buildings:

  9. 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 ...

  10. 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

    2009-01-01T23:59:59.000Z

    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 ...

  11. Empirical Analysis of the Spot Market Implications of Price-Responsive Demand

    E-Print Network [OSTI]

    Siddiqui, Afzal S.; Bartholomew, Emily S.; Marnay, Chris

    2008-01-01T23:59:59.000Z

    and Demand Response in Electricity Markets,” CSEM Working Paper CSEM-WP-105, University of California Energy Institute, Berkeley, CA, USA.USA. Siddiqui, AS (2004), “Price-Elastic Demand in Deregulated Electricity

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

    E-Print Network [OSTI]

    Bowen, Brian (Brian Richard)

    2015-01-01T23:59:59.000Z

    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, ...

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

    E-Print Network [OSTI]

    Stadler, Michael

    2009-01-01T23:59:59.000Z

    Operation in Zero-Net- Energy Buildings with Demand ResponseOperation in Zero-Net-Energy Buildings with Demand Responsemicrogrid, storage, zero- net energy buildings, zero-carbon

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01T23:59:59.000Z

    demand-side management activities and commercial buildings’demand-side management (DSM) framework presented in Figure 1 provides continuous energy management concepts for shaping electric loads in buildings,demand-side management activities, DR methods and levels of automation. We highlight OpenADR as a standard for commercial buildings

  15. Real-time Pricing Demand Response in Operations

    SciTech Connect (OSTI)

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

    2012-07-26T23:59:59.000Z

    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.

  16. 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.

    2008-01-01T23:59:59.000Z

    and Ed Arens. 2008. Demand Response-Enabled ResidentialEfficiency and Demand Response Programs for 2005/2006.The Human Dimension of Demand Response Enabling Technology

  17. 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

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01T23:59:59.000Z

    produce the greatest energy and demand savings. Aeration andand C.Y. Chang (2005). "Energy Demand in Sludge Dewatering."be modified to reduce energy demand during demand response

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

    E-Print Network [OSTI]

    Olsen, Daniel J.

    2014-01-01T23:59:59.000Z

    U.S. Department of Energy (DOE) Demand Response and Energy2006-005. California Energy Commission, Demand ForecastingPart 2: Modeling Energy—Limited Demand Response in a

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01T23:59:59.000Z

    Dynamic controls for energy efficiency and demand response:to evaluate continuous energy management and demand responseBldg Energy (kWh) Energy (kWh) Demand (kW) Office Bldg Of f

  1. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    SciTech Connect (OSTI)

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

    2010-08-02T23:59:59.000Z

    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.

  2. NWPPA showcases demand response in Port Angeles, upgrades at...

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

    commitment to demand-side management and recent improvements at the Dworshak National Fish Hatchery that's saving energy and benefiting fish. A pair of BPA-supported projects...

  3. Empirical Analysis of the Spot Market Implications ofPrice-Responsive Demand

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Bartholomew, Emily S.; Marnay, Chris

    2005-08-01T23:59:59.000Z

    Regardless of the form of restructuring, deregulatedelectricity industries share one common feature: the absence of anysignificant, rapid demand-side response to the wholesale (or, spotmarket) price. For a variety of reasons, most electricity consumers stillpay an average cost based regulated retail tariff held over from the eraof vertical integration, even as the retailers themselves are oftenforced to purchase electricity at volatile wholesale prices set in openmarkets. This results in considerable price risk for retailers, who aresometimes additionally forbidden by regulators from signing hedgingcontracts. More importantly, because end-users do not perceive real-time(or even hourly or daily) fluctuations in the wholesale price ofelectricity, they have no incentive to adjust their consumptionaccordingly. Consequently, demand for electricity is highly inelastic,which together with the non storability of electricity that requiresmarket clearing over very short time steps spawn many other problemsassociated with electricity markets, such as exercise of market power andprice volatility. Indeed, electricity generation resources can bestretched to the point where system adequacy is threatened. Economictheory suggests that even modest price responsiveness can relieve thestress on generation resources and decrease spot prices. To quantify thiseffect, actual generator bid data from the New York control area is usedto construct supply stacks and intersect them with demand curves ofvarious slopes to approximate the effect of different levels of demandresponse. The potential impact of real-time pricing (RTP) on theequilibrium spot price and quantity is then estimated. These resultsindicate the immediate benefits that could be derived from a moreprice-responsive demand providing policymakers with a measure of howprices can be potentially reduced and consumption maintained within thecapability of generation assets.

  4. 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

    2009-04-30T23:59:59.000Z

    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.

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

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

    submitted to Congress a required "Implementation Proposal for the National Action Plan on Demand Response." The Implementation Proposal was for FERC's June 2010 National Action...

  6. 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.

    2007-05-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01T23:59:59.000Z

    Reliability Corporation National Institute of Standards and Technology Open Access Transmission Tariff Open Automated Demand Response Protocol Public Utility Commission Photovoltaic

  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

    2008-01-01T23:59:59.000Z

    Demand Response Research Center Staff Scientist, Lawrence Berkeley National Laboratory 1 Cyclotron, Building

  9. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    congress_1252d.pdf. EPRI. 2009. Automated DemandProject – Revision 1. EPRI. Palo Alto, California: 2009.DOE DR DRAS DRRC EIS EMCS EPRI FERC FM HASP ISO ISONE LBNL

  10. Demand Response Enabling Technologies and Approaches for Industrial Facilities

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    There are numerous programs sponsored by Independent System Operators (ISOs) and utility or state efficiency programs that have an objective of reducing peak demand. Most of these programs have targeted the residential and commercial sector, however...

  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

    2007-01-01T23:59:59.000Z

    Response – What’s Happening in PJM? Demand Response: CaseEdison (ConEd) Mid-Atlantic • PJM Interconnection • PEPCOERCOT, ISO-NE, NYISO and PJM—offered a range of economic and

  12. 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

  13. 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.

    2013-01-01T23:59:59.000Z

    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...

  14. 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.

    2013-01-01T23:59:59.000Z

    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...

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

    SciTech Connect (OSTI)

    Herter, Karen; Wayland, Seth; Rasin, Josh

    2009-08-12T23:59:59.000Z

    This report documents a field study of 78 small commercial customers in the Sacramento Municipal Utility District service territory who volunteered for an integrated energy-efficiency/demand-response (EE-DR) program in the summer of 2008. The original objective for the pilot was to provide a better understanding of demand response issues in the small commercial sector. Early findings justified a focus on offering small businesses (1) help with the energy efficiency of their buildings in exchange for occasional load shed, and (2) a portfolio of options to meet the needs of a diverse customer sector. To meet these expressed needs, the research pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. Overall results show that pilot participants had energy savings of 20%, and the potential for an additional 14% to 20% load drop during a 100 F demand response event. In addition to the efficiency-related bill savings, participants on the dynamic rate saved an estimated 5% on their energy costs compared to the standard rate. About 80% of participants said that the program met or surpassed their expectations, and three-quarters said they would probably or definitely participate again without the $120 participation incentive. These results provide evidence that energy efficiency programs, dynamic rates and load control programs can be used concurrently and effectively in the small business sector, and that communicating thermostats are a reliable tool for providing air-conditioning load shed and enhancing the ability of customers on dynamic rates to respond to intermittent price events.

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

    SciTech Connect (OSTI)

    Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

    2014-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Han, Junqiao; Piette, Mary Ann

    2007-11-30T23:59:59.000Z

    Demand response (DR) is an effective tool which resolves inconsistencies between electric power supply and demand. It further provides a reliable and credible resource that ensures stable and economical operation of the power grid. This paper introduces systematic definitions for DR and demand side management, along with operational differences between these two methods. A classification is provided for DR programs, and various DR strategies are provided for application in air conditioning and refrigerating systems. The reliability of DR is demonstrated through discussion of successful overseas examples. Finally, suggestions as to the implementation of demand response in China are provided.

  18. 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

    2009-10-08T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    ) programs motivate home users through dynamic pricing to shift electricity consumption from peak demand incentives to the users, usually in the form of dynamic pricing, to reduce their electricity consumption. For example, the residential sector in UK accounts for 31% of the total electricity consumption

  20. OPUC Flexibility Planning Guidelines Pacific Northwest Demand Response Project

    E-Print Network [OSTI]

    ) · Demand management ­ smart grid controllable "withdrawal" and "recharge" #12;Jim Hicks Energy Strategies Jim Hicks Energy Strategies West, LLC #12;OPUC's New IRP Guidelines* · Integrated Resource Plans operational view of planning, including comprehensive multi-faceted VER integration strategy #12;Daily Wind

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

    SciTech Connect (OSTI)

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

    2012-01-18T23:59:59.000Z

    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.

  2. 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

    2009-05-11T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Kiliccote, Sila; Piette, Mary Ann

    2008-10-01T23:59:59.000Z

    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.

  4. 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

  5. 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

  6. Paying for demand-side response at the wholesale level

    SciTech Connect (OSTI)

    Falk, Jonathan

    2010-11-15T23:59:59.000Z

    The recent FERC Notice of Public Rulemaking regarding the payment to demand-side resources in wholesale markets has engendered a great deal of comments including FERC's obligation to ensure just and reasonable rates in the wholesale market and criteria for what FERC should do (on grounds of economic efficiency) without any real focus on what that commitment would really mean if FERC actually pursued it. (author)

  7. 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 for the home and produces a demand that is more level over time. Index Terms--Smart grid, power management to control power usage across the home. The EMC may be standalone or embedded either in the smart meter

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

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01T23:59:59.000Z

    the second half of the wholesale electric market equation.response with Midwest ISO wholesale markets, report no.DR Programs in Wholesale Markets 18

  9. Demand response medium sized industry consumers (Smart Grid Project) | Open

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A Potential Microhydro SiteDayton Power & LightDemand

  10. 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 bills. Our focus is on a subset of this work that carries out demand response (DR) by modulating

  11. 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

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01T23:59:59.000Z

    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."

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

    E-Print Network [OSTI]

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

    2014-01-01T23:59:59.000Z

    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

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

    E-Print Network [OSTI]

    Chandra, Shailesh

    2010-10-12T23:59:59.000Z

    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...

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

    E-Print Network [OSTI]

    Ehrhard, R.; Hamilton, G.

    2008-01-01T23:59:59.000Z

    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...

  16. 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 ...

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

    E-Print Network [OSTI]

    Critz, David Karl

    2012-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Hahl, Oliver (Oliver Douglas)

    2013-01-01T23:59:59.000Z

    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 ...

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

    E-Print Network [OSTI]

    Knudsen, Jesper

    2015-04-21T23:59:59.000Z

    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 ...

  20. Demand Response in the U.S.- Key trends and federal facility participation

    Broader source: Energy.gov [DOE]

    Presentation—given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008 meeting—provides demand response (DR) definition, current status of DR in the United States, key DR trends, and federal participation issues.

  1. OFWAR: Reducing SSD Response Time Using On-Demand Fast-Write-and-Rewrite

    E-Print Network [OSTI]

    Zhang, Tong

    OFWAR: Reducing SSD Response Time Using On-Demand Fast-Write-and-Rewrite Qi Wu and Tong Zhang to degrade SSD response time, we speed up memory programming at the penalty of shorter data retention time the average SSD response time by up to 52.3%. Index Terms--Solid-state drive, data retention, workload

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

    E-Print Network [OSTI]

    Olsen, Daniel J.

    2014-01-01T23:59:59.000Z

    potential value of demand response and energy storage to electricity systems with different penetration levels of variable renewable

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

    SciTech Connect (OSTI)

    Marks, Gary; Wilcox, Edmund; Olsen, Daniel; Goli, Sasank

    2013-01-02T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    applications. Mary Ann Piette is a Staff Scientist atResponse Ed Koch, Akuacom Mary Ann Piette, Lawrence BerkeleyCA 94903 ed@akuacom.com Mary Ann Piette Lawrence Berkeley

  5. 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

  6. 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

  7. 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

  8. Deep Demand Response: The Case Study of the CITRIS Building at the University of California-Berkeley

    E-Print Network [OSTI]

    Culler, David E.

    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

  9. 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

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

    SciTech Connect (OSTI)

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

    2008-10-20T23:59:59.000Z

    Demand response (DR) is an emerging research field and an effective tool that improves grid reliability and prevents the price of electricity from rising, especially in deregulated markets. This paper introduces the definition of DR and Automated Demand Response (Auto-DR). It describes the Auto-DR technology utilized at a commercial building in the summer of 2006 and the methodologies to evaluate associated demand savings. On the basis of field tests in a large office building, Auto-DR is proven to be a reliable and credible resource that ensures a stable and economical operation of the power grid.

  11. Design and Implementation of an Open, Interoperable AutomatedDemand Response Infrastructure

    SciTech Connect (OSTI)

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

    2007-10-01T23:59:59.000Z

    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.

  12. Examining Uncertainty in Demand Response Baseline Models and

    E-Print Network [OSTI]

    , changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated;DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency

  13. Export demand response in the Ontario electricity market

    SciTech Connect (OSTI)

    Peerbocus, Nash; Melino, Angelo

    2007-11-15T23:59:59.000Z

    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)

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

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    . There- fore, in this paper, the first steps are taken towards designing de- mand response programs, such as photovoltaic (PV) systems, batteries, and fuel cells, that are natively DC sources. H. MohsenianTowards Building an Optimal Demand Response Framework for DC Distribution Networks Hamed Mohsenian

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

    E-Print Network [OSTI]

    Kiliccote, S.; Piette, M. A.

    2005-01-01T23:59:59.000Z

    ICEBO 2005 Conference Paper September 1, 2005 LBNL # 58179 ADVANCED CONTROL TECHNOLOGIES AND STRATEGIES LINKING DEMAND RESPONSE AND ENERGY EFFICIENCY Sila Kiliccote Mary Ann Piette Lawrence Berkeley National Laboratory Berkeley..., 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...

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

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01T23:59:59.000Z

    best practices that could be applicable in improving the energy efficiency and demand responsebest practices that could be applied to form the basis for demand responsedemand response activities. The following case studies illustrate best practices

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

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01T23:59:59.000Z

    best practices that could be applied to form the basis for demand responsebest practices that could be applicable in improving the energy efficiency and demand responsedemand response activities. The following case studies illustrate best practices

  18. 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

    2010-11-17T23:59:59.000Z

    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.

  19. 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.

    2011-09-30T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Lincoln, Donald; Evans, Christoper

    2012-01-01T23:59:59.000Z

    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.

  1. 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

    2013-10-01T23:59:59.000Z

    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.

  2. Opportunities for Energy Efficiency and Demand Response in Corrugated Cardboard Manufacturing Facilities

    E-Print Network [OSTI]

    Chow, S.; Hackett, B.; Ganji, A. R.

    2005-01-01T23:59:59.000Z

    OPPORTUNITIES FOR ENERGY EFFICIENCY AND DEMAND RESPONSE IN CORRUGATED CARDBOARD MANUFACTURING FACILITIES Sandra Chow BASE Energy, Inc.* San Francisco, CA 94103 Ahmad R. Ganji, Ph.D., P.E. San Francisco State University San Francisco, CA....6 Plant F 7 53,307 0.7 Plant G 14 294,544 0.3 Plant H 13 61,553 0.8 Plant I 9 28,945 1.1 Plant J 9 24,759 2.9 Plant K 12 124,854 0.8 Plant L 18 113,640 1.2 MAJOR OPPORTUNITIES IN DEMAND RESPONSE In recent years, due...

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

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2007-10-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2012-12-12T23:59:59.000Z

    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

  5. Optimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model Predictive Control

    E-Print Network [OSTI]

    Mittelmann, Hans D.

    is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model

  6. 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

    2004-03-30T23:59:59.000Z

    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).

  7. Estimate of federal relighting potential and demand for efficient lighting products

    SciTech Connect (OSTI)

    Shankle, S.A.; Dirks, J.A.; Elliott, D.B.; Richman, E.E.; Grover, S.E.

    1993-11-01T23:59:59.000Z

    The increasing level of electric utility rebates for energy-efficient lighting retrofits has recently prompted concern over the adequacy of the market supply of energy-efficient lighting products (Energy User News 1991). In support of the U.S. Department of Energy`s Federal Energy Management Program, Pacific Northwest Laboratory (PNL) has developed an estimate of the total potential for energy-efficient lighting retrofits in federally owned buildings. This estimate can be used to address the issue of the impact of federal relighting projects on the supply of energy-efficient lighting products. The estimate was developed in 1992, using 1991 data. Any investments in energy-efficient lighting products that occurred in 1992 will reduce the potential estimated here. This analysis proceeds by estimating the existing stock of lighting fixtures in federally owned buildings. The lighting technology screening matrix is then used to determine the minimum life-cycle cost retrofit for each type of existing lighting fixture. Estimates of the existing stock are developed for (1) four types of fluorescent lighting fixtures (2-, 3-, and 4-lamp, F40 4-foot fixtures, and 2-lamp, F96 8-foot fixtures, all with standard magnetic ballasts); (2) one type of incandescent fixture (a 75-watt single bulb fixture); and (3) one type of exit sign (containing two 20-watt incandescent bulbs). Estimates of the existing stock of lighting fixtures in federally owned buildings, estimates of the total potential demand for energy-efficient lighting products if all cost-effective retrofits were undertaken immediately, and total potential annual energy savings (in MWh and dollars), the total investment required to obtain the energy savings and the present value of the efficiency investment, are presented.

  8. 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 DataDepartment of Energy Your Density Isn't Your Destiny:Revised Finding of No53197 This workDayton:|

  9. 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

    2008-08-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2009-08-01T23:59:59.000Z

    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.

  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 at wholesale conditional on A/C load, and the retail energy prices offered to residential A/C consumers

  12. Facility Location under Demand Uncertainty: Response to a Large-scale Bioterror Attack

    E-Print Network [OSTI]

    Dessouky, Maged

    Facility Location under Demand Uncertainty: Response to a Large-scale Bioterror Attack Abstract In the event of a catastrophic bio-terror attack, major urban centers need to effi- ciently distribute large of a hypothetical anthrax attack in Los Angeles County. Keywords: Capacitated facility location, distance

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

    E-Print Network [OSTI]

    Boutaba, Raouf

    pricing and consumption data in South Korea. Index Terms--smart grid, demand-response, energy management I-based pricing. In peak capping, each home is allocated an energy quota. In market-based pricing, the price-term viable way of regulating energy consumptions. We work with day-ahead market pricing in this paper

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

    E-Print Network [OSTI]

    Prasanna, Viktor K.

    -driven demand response optimization (DR) in the USC campus microgrid, as part of the Los An- geles Smart Grid to interact with the consumers (or their software/hardware proxies). The Los Angeles Smart Grid Demonstration can later be scaled to a city power grid. Here, we describe our prototype software architecture

  15. 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

    2012-12-20T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Lekov, Alex

    2009-01-01T23:59:59.000Z

    in significant energy and demand savings for refrigeratedbe modified to reduce energy demand during demand responsein refrigerated warehouse energy demand if they are not

  17. 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

    2014-01-31T23:59:59.000Z

    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.

  18. 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

  19. The Impact of Energy Efficiency and Demand Response Programs on the U.S. Electricity Market

    SciTech Connect (OSTI)

    Baek, Young Sun [ORNL; Hadley, Stanton W [ORNL

    2012-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2009-05-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2010-06-02T23:59:59.000Z

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

  2. 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.

    2011-09-10T23:59:59.000Z

    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.

  3. 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

    2014-01-02T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01T23:59:59.000Z

    customers need to reduce energy demand during expensiveadditive) $11.42 / kW-max demand Energy Delivery Charges Alltype, floor space, peak demand, energy supplier, DR program

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

    E-Print Network [OSTI]

    Piette, Mary Ann; Kiliccote, Sila

    2006-01-01T23:59:59.000Z

    perspective, a demand-side management framework with threethe integration of DR in demand-side management activitiesdevelopments. The demand-side management (DSM) framework

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

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    buildings. A demand-side management framework from buildingthe integration of DR in demand-side management activitiesdevelopments. The demand-side management (DSM) framework

  7. 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.

    2011-11-11T23:59:59.000Z

    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.

  8. A Probabilistic Deformation Demand Model and Fragility Estimates for Asymmetric Offshore Jacket Platforms

    E-Print Network [OSTI]

    Fallon, Michael Brooks

    2012-11-12T23:59:59.000Z

    to assess the deformation demand on asymmetric offshore jacket platforms subject to wave and current loadings. The probabilistic model is constructed by adding correction terms and a model error to an existing deterministic deformation demand model...

  9. 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

    2010-05-14T23:59:59.000Z

    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.

  10. 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

    2009-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Wenzel, Mike

    2013-10-14T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2011-07-01T23:59:59.000Z

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

  13. Efficient Estimation in a Regression Model with Missing Responses

    E-Print Network [OSTI]

    Crawford, Scott

    2012-10-19T23:59:59.000Z

    This article examines methods to efficiently estimate the mean response in a linear model with an unknown error distribution under the assumption that the responses are missing at random. We show how the asymptotic variance is affected...

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

    SciTech Connect (OSTI)

    Herter, Karen; Wayland, Seth; Rasin, Josh

    2009-09-25T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2009-05-26T23:59:59.000Z

    The US Department of Energy has launched the Zero-Net-Energy (ZNE) Commercial Building Initiative (CBI) in order to develop commercial buildings that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge energy-efficient technologies and meet their remaining energy needs through on-site renewable energy generation. We examine how such buildings may be implemented within the context of a cost- or carbon-minimizing microgrid that is able to adopt and operate various technologies, such as photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive / demand-response technologies. We use a mixed-integer linear program (MILP) that has a multi-criteria objective function: the minimization of a weighted average of the building's annual energy costs and carbon / CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the CBI. Using a nursing home in northern California and New York with existing tariff rates and technology data, we find that a ZNE building requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve ZNE. For comparison, we analyze a nursing home facility in New York to examine the effects of a flatter tariff structure and different load profiles. It has trouble reaching ZNE status and its load reductions as well as efficiency measures need to be more effective than those in the CA case. Finally, we illustrate that the multi-criteria frontier that considers costs and carbon emissions in the presence of demand response dominates the one without it.

  16. 2012 CERTS LAAR Program Peer Review - Frequency Response Demand - Jeff Dagle, PNNL

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

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015ofDepartment ofCBFO-13-3322(EE) | Department1TheDepartment ofResponsive Demand

  17. Selye originally described stress as a nonspecific response of the body to any demand placed upon it1

    E-Print Network [OSTI]

    Yan, Zhen

    Selye originally described stress as a nonspecific response of the body to any demand placed upon controlling extinction of conditioned fear13,14 . Moreover, impaired PFC function and plasticity is thought

  18. DOE and FERC Jointly Submit Implementation Proposal for The National Action Plan on Demand Response to Congress

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy and the Federal Energy Regulatory Commission (FERC) jointly submitted to Congress a required “Implementation Proposal for The National Action Plan on Demand Response.”

  19. Calibration of an EnergyPlus Building Energy Model to Assess the Impact of Demand Response Measures

    E-Print Network [OSTI]

    Lavigne, K.; Sansregret, S.; Daoud, A.; Leclair, L. A.

    2013-01-01T23:59:59.000Z

    1 Karine Lavigne Simon Sansregret Ahmed DaoudLouis-Alexandre Leclaire CALIBRATION OF AN ENERGYPLUS BUILDING ENERGY MODEL TO ASSESS THE IMPACT OF DEMAND RESPONSE MEASURES ICEBO 2013, Montr?al Groupe ? Technologie2 ICEBO-2013 Contextualization... ICEBO-2013 Groupe ? Technologie Calibrated Results 22 ICEBO-2013 12 Groupe ? Technologie Conclusion 23 ICEBO-2013 > Calibrating model for a demand response objective : Challenging and High Effort > Capturing building and human erratic behaviour...

  20. Estimation of the urban household demand for water in the United States

    E-Print Network [OSTI]

    Foster, Henry Sessam

    1977-01-01T23:59:59.000Z

    only apparenl: fa&. tor in septic 'ark area S?para ie demarrd equal;i ons for sums&sr prinkling &tom&'nstrated that sp:insLing demand ha. s significaritly greater: price elasticity Lhr-n domo;tic demand. 77ry r&estorn areas oxhibite0 a, price ela. r...

  1. 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

    2009-04-01T23:59:59.000Z

    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.

  2. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 31, NO. 7, JULY 2013 1 Demand Response Management via Real-time

    E-Print Network [OSTI]

    Huang, Jianwei

    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 31, NO. 7, JULY 2013 1 Demand Response through demand response management in smart grid systems. The proposed scheme solves a two. Index Terms--Real-time pricing, Demand response manage- ment, Payoff maximization, Profit maximization

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    the ongoing pilot demand-side management (DSM) programs ina comprehensive demand-side management (DSM) pilot program,a directive on demand-side management (DSM) in late 2010.

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

    SciTech Connect (OSTI)

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

    2010-12-22T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Herter, Karen; Rasin, Josh; Perry, Tim

    2009-11-30T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Herter, Karen

    2010-01-01T23:59:59.000Z

    Case Study of Small Business Energy Efficiency and DemandCase Study of Small Business Energy Efficiency and DemandSolutions Participant Energy Savings Business Type Program

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

    E-Print Network [OSTI]

    Cappers, Peter

    2012-01-01T23:59:59.000Z

    diverse set of flexible traditional generation resourcessufficient flexible demand or generation capacity exists tosufficient flexible demand or generation capacity exists to

  8. AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)

    SciTech Connect (OSTI)

    FERRIES SR; KLINK KL; OSTAPKOWICZ B

    2012-01-30T23:59:59.000Z

    Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.

  9. 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

    2003-04-18T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2010-06-01T23:59:59.000Z

    We take the perspective of a microgrid that has installed distribution energy resources (DER) in the form of distributed generation with combined heat and power applications. Given uncertain electricity and fuel prices, the microgrid minimizes its expected annual energy bill for various capacity sizes. In almost all cases, there is an economic and environmental advantage to using DER in conjunction with demand response (DR): the expected annualized energy bill is reduced by 9percent while CO2 emissions decline by 25percent. Furthermore, the microgrid's risk is diminished as DER may be deployed depending on prevailing market conditions and local demand. In order to test a policy measure that would place a weight on CO2 emissions, we use a multi-criteria objective function that minimizes a weighted average of expected costs and emissions. We find that greater emphasis on CO2 emissions has a beneficial environmental impact only if DR is available and enough reserve generation capacity exists. Finally, greater uncertainty results in higher expected costs and risk exposure, the effects of which may be mitigated by selecting a larger capacity.

  11. Modeling of Electric Water Heaters for Demand Response: A Baseline PDE Model

    SciTech Connect (OSTI)

    Xu, Zhijie; Diao, Ruisheng; Lu, Shuai; Lian, Jianming; Zhang, Yu

    2014-09-05T23:59:59.000Z

    Demand response (DR)control can effectively relieve balancing and frequency regulation burdens on conventional generators, facilitate integrating more renewable energy, and reduce generation and transmission investments needed to meet peak demands. Electric water heaters (EWHs) have a great potential in implementing DR control strategies because: (a) the EWH power consumption has a high correlation with daily load patterns; (b) they constitute a significant percentage of domestic electrical load; (c) the heating element is a resistor, without reactive power consumption; and (d) they can be used as energy storage devices when needed. Accurately modeling the dynamic behavior of EWHs is essential for designing DR controls. Various water heater models, simplified to different extents, were published in the literature; however, few of them were validated against field measurements, which may result in inaccuracy when implementing DR controls. In this paper, a partial differential equation physics-based model, developed to capture detailed temperature profiles at different tank locations, is validated against field test data for more than 10 days. The developed model shows very good performance in capturing water thermal dynamics for benchmark testing purposes

  12. Workshop on Demand Response, Ballerup, 7. February 2006 www.risoe.dk Curtailment of Household Equipments A Danish Case Study

    E-Print Network [OSTI]

    Workshop on Demand Response, Ballerup, 7. February 2006 www.risoe.dk Curtailment of Household Frame · 189 Respondents · Power consumption: 5000 ­ 6000 kWh per year · No electrical heating · Products hours 3 hours 3 hours Question 9 Question 10 Question 13 Price(DKK/kWh) 0% 5% 10% 15% 20% 25% Response

  13. Smart Finite State Devices: A Modeling Framework for Demand Response Technologies

    E-Print Network [OSTI]

    Turitsyn, Konstantin; Ananyev, Maxim; Chertkov, Michael

    2011-01-01T23:59:59.000Z

    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 following four types: (a) optional loads that can be shed, e.g. light dimming; (b) deferrable loads that can be delayed, e.g. dishwashers; (c) controllable loads with inertia, e.g. thermostatically-controlled loads, whose task is to maintain an auxiliary characteristic (temperature) within pre-defined margins; and (d) storage devices that can alternate between charging and generating. Our analysis of the devices seeks to find their optimal price-taking control strategy under a given stochastic model of the distribution market.

  14. Japan's Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2010-01-01T23:59:59.000Z

    industrial sector, oil demand will decrease due particularlyand commercial sectors, oil demand will decline on a shifttransportation sector, oil demand will shrink on a fall in

  15. On Using Complex Event Processing for Dynamic Demand Response Optimization in Microgrid

    E-Print Network [OSTI]

    Prasanna, Viktor K.

    DR. Our focus is on demand-side management rather than supply-side constraints. Continuous data from that can benefit demand-side management in DR, an accessible means to define them at a higher level California Los Angeles, CA 90089, USA Email: {simmhan, prasanna}@usc.edu Abstract--Demand-side load reduction

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

    E-Print Network [OSTI]

    Low, Steven H.

    Smart Grid involves changes in both the demand side and supply side. On the supply side, more renewable energy will be integrated to reduce greenhouse gas emissions and other pollution. On the demand side, smarter demand management systems will be available to respond to the electricity price and improve

  17. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

  18. Demand Dispatch-Intelligent

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

    CA Control Areas CO 2 Carbon Dioxide CHP Combined Heat and Power CPP Critical Peak Pricing DG Distributed Generation DOE Department of Energy DR Demand Response DRCC Demand...

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

    E-Print Network [OSTI]

    Kesidis, George

    2011-01-01T23:59:59.000Z

    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.

  20. Estimation of a supply and demand model for the hired farm labor market in Texas

    E-Print Network [OSTI]

    Turley, Keith Pool

    1977-01-01T23:59:59.000Z

    labor in Texas increased from -0. 8 in 1951 to -2. 8 in 1975, while the long run wage elasticity of demand increased from -1. 0 to -3. 5 during the same time period. The hypothesis that Mexican immigration has had a direct influence on the supply... be expected to cause a 0. 3 per- cent short-run increase in the supply of hired farm labor in Texas, and a 0. 1 percent short-run decrease in the farm wage rate, while the long-run effect on the wage rate would be a 0. 4 percent decrease from the 1975...