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A mean field game theoretic approach to electric vehicles charging

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journal contribution
posted on 2016-08-11, 14:00 authored by Ziming Zhu, Sangarapillai LambotharanSangarapillai Lambotharan, Woon Hau Chin, Zhong Fan
Electric vehicles (EVs) provide environmentally friendly transport and they are considered to be an important component of distributed and mobile electric energy storage and supply system. It is possible that EVs can be used to store and transport energy from one geographical area to another as a supportive energy supply. Electricity consumption management should consider carefully the inclusion of EVs. One critical challenge in the consumption management for EVs is the optimization of battery charging. This paper provides a dynamic game theoretic optimization framework to formulate the optimal charging problem. The optimization considers a charging scenario where a large number of EVs charge simultaneously during a flexible period of time. Based on stochastic mean field game theory, the optimization will provide an optimal charging strategy for the EVs to proactively control their charging speed in order to minimize the cost of charging. Numerical results are presented to demonstrate the performance of the proposed framework.

Funding

This work was supported by the U.K. Engineering and Physical Science Research Council, under Grant EP/M015475, and a funding from the SUNSEED Project, an European Commission’s 7th Framework Programme under Grant Agreement number 619437.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Access

Volume

4

Pages

3501 - 3510

Citation

ZHU, Z. ... et al., 2016. A mean field game theoretic approach to electric vehicles charging. IEEE Access, 4, pp. 3501 - 3510.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Acceptance date

2016-06-15

Publication date

2016

Notes

This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/

ISSN

2169-3536

Language

  • en

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