Online Mechanism Design for Electric Vehicle Charging

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Online Mechanism Design for Electric Vehicle Charging

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dc.contributor.author Gerding, Enrico H.
dc.contributor.author Robu, Valentin
dc.contributor.author Stein, Sebastian
dc.contributor.author Parkes, David C.
dc.contributor.author Rogers, Alex
dc.contributor.author Jennings, Nicholas R.
dc.date.accessioned 2012-11-28T19:46:31Z
dc.date.issued 2011
dc.identifier.citation Gerding, 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.isbn 0-9826571-5-3 en_US
dc.identifier.isbn 978-0-9826571-5-7 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:9962006
dc.description.abstract Plug-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.sponsorship Engineering and Applied Sciences en_US
dc.language.iso en_US en_US
dc.publisher International Foundation for Autonomous Agents and Multiagent Systems en_US
dc.relation.isversionof http://www.ifaamas.org/Proceedings/aamas2011/papers/B6_B70.pdf en_US
dc.relation.hasversion http://www.eecs.harvard.edu/econcs/pubs/gerding-aamas11.pdf en_US
dc.relation.hasversion http://eprints.ecs.soton.ac.uk/21907/1/AAMAS440_cameraready.pdf en_US
dash.license OAP
dc.subject electric vehicle en_US
dc.subject mechanism design en_US
dc.subject pricing en_US
dc.subject algorithms en_US
dc.subject design en_US
dc.subject economics en_US
dc.subject distributed AI en_US
dc.subject multiagent systems en_US
dc.title Online Mechanism Design for Electric Vehicle Charging en_US
dc.type Monograph or Book en_US
dc.description.version Author's Original en_US
dash.depositing.author Parkes, David C.
dc.date.available 2012-11-28T19:46:31Z

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  • FAS Scholarly Articles [7374]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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