Congestion games for V2G-enabled EV charging

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations

    Abstract

    A model of the problem of charging and discharging electrical vehicles as a congestion game is presented. A generalization of congestion games - feedback congestion games (FCG) - is introduced. The charging of grid- integrated vehicles, which can also discharge energy back to the grid, is a natural FCG application. FCGs are proven to be exact potential games and therefore converge to a pure-strategy Nash equilibrium by an iterated better-response process. A compact representation and an algorithm that enable efficient best-response search are presented. A detailed empirical evaluation assesses the performance of the iterated best-response process. The evaluation considers the quality of the resulting solutions and the rate of convergence to a stable state. The effect of allowing to also discharge batteries using FCG is compared to scenarios that only include charging and is found to dramatically improve the predictability of the achieved solutions as well as the balancing of load.

    Original languageEnglish
    Title of host publicationProceedings of the National Conference on Artificial Intelligence
    PublisherAI Access Foundation
    Pages1440-1446
    Number of pages7
    ISBN (Electronic)9781577356783
    StatePublished - 1 Jan 2014
    Event28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014 - Quebec City, Canada
    Duration: 27 Jul 201431 Jul 2014

    Publication series

    NameProceedings of the National Conference on Artificial Intelligence
    Volume2

    Conference

    Conference28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014
    Country/TerritoryCanada
    CityQuebec City
    Period27/07/1431/07/14

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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