{"type":"ScholarlyArticle","title":"Contract Design for Energy Demand Response","authors":[{"name":"Reshef Meir","slug":"reshef-meir","given":"Reshef","family":"Meir","affiliation":"Technion -Israel Institute of Technology Haifa , Israel"},{"name":"Hongyao Ma","slug":"hongyao-ma","given":"Hongyao","family":"Ma","affiliation":"Harvard University Cambridge , MA , US"},{"name":"Valentin Robu","slug":"valentin-robu","given":"Valentin","family":"Robu","affiliation":"Heriot-Watt University Edinburgh , UK"}],"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. \r\nCurrent 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. \r\n\r\nWe 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.\r\n\r\n 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.","doi":"10.24963/ijcai.2017/167","url":"https://ijcai.org/proceedings/2017/167","pdf":"https://ijcai.org/proceedings/2017/0167.pdf","markdown":"https://ijcai.org/proceedings/2017/167.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/167","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra, IIIA-CSIC","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Knowledge Representation, Reasoning, and Logic","track":"Main track","number":167,"pages":{"first":1202,"last":1208},"keywords":["Knowledge Representation, Reasoning, and Logic: Game Theory","Agent-based and Multi-agent Systems: Economic paradigms, auctions and market-based systems","Multidisciplinary Topics and Applications: Computational Sustainability"],"videos":[],"references":[{"position":1,"raw":"[Akasiadis and Chalkiadakis, 2013] Charilaos Akasiadis and Georgios Chalkiadakis. 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