DATA-DRIVEN MEAN-FIELD GAME APPROXIMATION FOR A POPULATION OF ELECTRIC VEHICLES

Dario Bauso, Toru Namerikawa

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

Abstract

For a population of electric vehicles (EVs) we design a datadriven mean-field game and provide analysis of approximated
mean-field equilibrium points based on a receding horizon approach. The model involves stochastic disturbances on the
data that drive the game. Some numerical studies illustrate
the efficacy of the proposed strategies.
Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE Data Science Workshop (DSW)
PublisherIEEE
Pages285-289
ISBN (Print)978-1-7281-0708-0
DOIs
Publication statusPublished - 2019
Event2019 IEEE Data Science Workshop (DSW) - Minneapolis, United States
Duration: 2-Jun-20195-Jun-2019

Workshop

Workshop2019 IEEE Data Science Workshop (DSW)
CountryUnited States
CityMinneapolis
Period02/06/201905/06/2019

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