Contract Design for Energy Demand Response

Reshef Meir, Hongyao Ma, Valentin Robu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Power companies such as Southern California Edison (SCE) uses Demand Response (DR) contracts to incentivize consumers to reduce their power consumption during periods when demand forecast exceeds supply. Current mechanisms in use offer contracts to consumers independent of one another, do not take into consideration consumers' heterogeneity in consumption profile or reliability, and fail to achieve high participation. We introduce DR-VCG, a new DR mechanism that offers a flexible set of contracts (which may include the standard SCE contracts) and uses VCG pricing. We prove that DR-VCG elicits truthful bids, incentivizes honest preparation efforts, and enables efficient computation of allocation and prices. With simple fixed-penalty contracts, the optimization goal of the mechanism is an upper bound on probability that the reduction target is missed. Extensive simulations show that compared to the current mechanism deployed by SCE, the DR-VCG mechanism achieves higher participation, increased reliability, and significantly reduced total expenses.
Original languageEnglish
Title of host publication26th International Joint Conference on Artificial Intelligence (IJCAI)
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1202-1208
Number of pages7
ISBN (Electronic)9780999241103
Publication statusPublished - 25 Aug 2017
Event26th international Joint Conference on Artificial Intelligence 2017 - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017
https://ijcai-17.org/

Conference

Conference26th international Joint Conference on Artificial Intelligence 2017
CountryAustralia
CityMelbourne
Period19/08/1725/08/17
Internet address

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    Meir, R., Ma, H., & Robu, V. (2017). Contract Design for Energy Demand Response. In 26th International Joint Conference on Artificial Intelligence (IJCAI) (pp. 1202-1208). International Joint Conferences on Artificial Intelligence.