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Conference Paper: Randomized auction design for electricity markets between grids and microgrids

TitleRandomized auction design for electricity markets between grids and microgrids
Authors
KeywordsApproximation Algorithms
Mechanism Design
Microgrids
Power Grid
Unit Commitment Problem
Issue Date2014
PublisherACM.
Citation
Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Austin, Texas, USA, 16-20 June 2014, p. 99-110 How to Cite?
AbstractThis work studies electricity markets between power grids and microgrids, an emerging paradigm of electric power generation and supply. It is among the first that addresses the economic challenges arising from such grid integration, and represents the first power auction mechanism design that explicitly handles the Unit Commitment Problem (UCP), a key challenge in power grid optimization previously investigated only for centralized cooperative algorithms. The proposed solution leverages a recent result in theoretical computer science that can decompose an optimal fractional (infeasible) solution to NP-hard problems into a convex combination of integral (feasible) solutions. The end result includes randomized power auctions that are (approximately) truthful and computationally efficient, and achieve small approximation ratios for grid-wide social welfare under UCP constraints and temporal demand correlations. Both power markets with grid-to-microgrid and microgrid-to-grid energy sales are studied, with an auction designed for each, under the same randomized power auction framework. Trace driven simulations are conducted to verify the efficacy of the two proposed inter-grid power auctions.
Persistent Identifierhttp://hdl.handle.net/10722/201098
ISBN

 

DC FieldValueLanguage
dc.contributor.authorZhang, Len_US
dc.contributor.authorLi, Zen_US
dc.contributor.authorWu, Cen_US
dc.date.accessioned2014-08-21T07:13:33Z-
dc.date.available2014-08-21T07:13:33Z-
dc.date.issued2014en_US
dc.identifier.citationProceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Austin, Texas, USA, 16-20 June 2014, p. 99-110en_US
dc.identifier.isbn9781450327893-
dc.identifier.urihttp://hdl.handle.net/10722/201098-
dc.description.abstractThis work studies electricity markets between power grids and microgrids, an emerging paradigm of electric power generation and supply. It is among the first that addresses the economic challenges arising from such grid integration, and represents the first power auction mechanism design that explicitly handles the Unit Commitment Problem (UCP), a key challenge in power grid optimization previously investigated only for centralized cooperative algorithms. The proposed solution leverages a recent result in theoretical computer science that can decompose an optimal fractional (infeasible) solution to NP-hard problems into a convex combination of integral (feasible) solutions. The end result includes randomized power auctions that are (approximately) truthful and computationally efficient, and achieve small approximation ratios for grid-wide social welfare under UCP constraints and temporal demand correlations. Both power markets with grid-to-microgrid and microgrid-to-grid energy sales are studied, with an auction designed for each, under the same randomized power auction framework. Trace driven simulations are conducted to verify the efficacy of the two proposed inter-grid power auctions.-
dc.languageengen_US
dc.publisherACM.-
dc.relation.ispartofProceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systemsen_US
dc.subjectApproximation Algorithms-
dc.subjectMechanism Design-
dc.subjectMicrogrids-
dc.subjectPower Grid-
dc.subjectUnit Commitment Problem-
dc.titleRandomized auction design for electricity markets between grids and microgridsen_US
dc.typeConference_Paperen_US
dc.identifier.emailWu, C: cwu@cs.hku.hken_US
dc.identifier.authorityWu, C=rp01397en_US
dc.identifier.doi10.1145/2591971.2591999-
dc.identifier.scopuseid_2-s2.0-84904362753-
dc.identifier.hkuros232127en_US
dc.identifier.spage99-
dc.identifier.epage110-
dc.publisher.placeNew York-

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