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dc.contributor.authorGerding, Enrico H.
dc.contributor.authorRobu, Valentin
dc.contributor.authorStein, Sebastian
dc.contributor.authorParkes, David C.
dc.contributor.authorRogers, Alex
dc.contributor.authorJennings, Nicholas R.
dc.date.accessioned2012-11-28T19:46:31Z
dc.date.issued2011
dc.identifier.citationGerding, Enrico H., Valentin Robu, Sebastian Stein, David C. Parkes, Alex Rogers, and Nicholas R. Jennings. 2011. Online mechanism design for electric vehicle charging. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011): May, 2-6, 2011, Taipei, Taiwan, ed. Kagan Tumer, Pinar Yolum, Liz Sonenberg, and Peter Stone, 811-818. Richland, South Carolina: International Foundation for Autonomous Agents and Multiagent Systems.en_US
dc.identifier.isbn0-9826571-5-3en_US
dc.identifier.isbn978-0-9826571-5-7en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:9962006
dc.description.abstractPlug-in hybrid electric vehicles are expected to place a considerable strain on local electricity distribution networks, requiring charging to be coordinated in order to accommodate capacity constraints. We design a novel online auction protocol for this problem, wherein vehicle owners use agents to bid for power and also state time windows in which a vehicle is available for charging. This is a multi-dimensional mechanism design domain, with owners having non-increasing marginal valuations for each subsequent unit of electricity. In our design, we couple a greedy allocation algorithm with the occasional "burning" of allocated power, leaving it unallocated, in order to adjust an allocation and achieve monotonicity and thus truthfulness. We consider two variations: burning at each time step or on-departure. Both mechanisms are evaluated in depth, using data from a real-world trial of electric vehicles in the UK to simulate system dynamics and valuations. The mechanisms provide higher allocative efficiency than a fixed price system, are almost competitive with a standard scheduling heuristic which assumes non-strategic agents, and can sustain a substantially larger number of vehicles at the same per-owner fuel cost saving than a simple random scheme.en_US
dc.description.sponsorshipEngineering and Applied Sciencesen_US
dc.language.isoen_USen_US
dc.publisherInternational Foundation for Autonomous Agents and Multiagent Systemsen_US
dc.relation.isversionofhttp://www.ifaamas.org/Proceedings/aamas2011/papers/B6_B70.pdfen_US
dc.relation.hasversionhttp://www.eecs.harvard.edu/econcs/pubs/gerding-aamas11.pdfen_US
dc.relation.hasversionhttp://eprints.ecs.soton.ac.uk/21907/1/AAMAS440_cameraready.pdfen_US
dash.licenseOAP
dc.subjectelectric vehicleen_US
dc.subjectmechanism designen_US
dc.subjectpricingen_US
dc.subjectalgorithmsen_US
dc.subjectdesignen_US
dc.subjecteconomicsen_US
dc.subjectdistributed AIen_US
dc.subjectmultiagent systemsen_US
dc.titleOnline Mechanism Design for Electric Vehicle Chargingen_US
dc.typeMonograph or Booken_US
dc.description.versionAuthor's Originalen_US
dash.depositing.authorParkes, David C.
dc.date.available2012-11-28T19:46:31Z
dash.contributor.affiliatedParkes, David


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