Hao Ming, Bainan Xia, Ki-Yeob Lee, et al. Prediction and assessment of demandresponse potential with coupon incentivesin highly renewable power systems[J]. Protection and Control of Modern Power Systems, 2020, 5(2): 1-14.
DOI:
Hao Ming, Bainan Xia, Ki-Yeob Lee, et al. Prediction and assessment of demandresponse potential with coupon incentivesin highly renewable power systems[J]. Protection and Control of Modern Power Systems, 2020, 5(2): 1-14.DOI: 10.1186/s41601-020-00155-x.
Prediction and assessment of demandresponse potential with coupon incentivesin highly renewable power systems
Demand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example
in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT)
load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore
incentivizing end-consumers' load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR)
the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements
individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets
as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction
individualized target setting and a lottery mechanism. This paper summarizes the methodologies
design
critical findings
as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries
the effective cost for demand response providers in EnergyCoupon can be substantially reduced
while achieving a similar level of demand reduction as conventional DR programs.
Abstract
Demand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example
in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT)
load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore
incentivizing end-consumers’ load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR)
the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements
individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets
as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction
individualized target setting and a lottery mechanism. This paper summarizes the methodologies
design
critical findings
as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries
the effective cost for demand response providers in EnergyCoupon can be substantially reduced
while achieving a similar level of demand reduction as conventional DR programs.
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references
1. Electric Reliability Council of Texas. ( 2020 ). ERCOT.com , [online ] Available: http://www.ercot.com/.
2. Green the Grid, Green the Grid: the role of storage and demand response. ( 2015 ) [online] Available: https://www.nrel.gov/docs/fy150sti/63041.pdf.
3. U.S. Department of Energy. ( 2006 ). Benefit of demand response in electricity market and recommendations for achieving them, [online] Available: http://www.caiso.com/Documents/DemandResponseandProxyDemandResourcesFrequentlyAskedQuestions.pdf.
4. New York Independent System Operator (NYISO). ( 2009 ). Day-ahead demand response program manual , [online ] Available: http://www.nyiso.com/public/webdocs/markets_operations/documents/Manuals_and_Guides/Manuals/Operations/dadrp_mnl.pdf.
5. California ISO. ( 2015 ). Demand response user guide , [online ] Available: http://www.caiso.com/Documents/July20_2009InitialCommentsonPDAdoptingDRActivities_Budgets_2009–2011inDocketNos_A_08-06-001_etal_.pdf.