Electric vehicle charging simulation framework considering traffic, user, and power grid

Research output: Contribution to journalArticlepeer-review

Authors

Colleges, School and Institutes

Abstract

The traffic and user have significant impacts on the electric vehicle (EV) charging load but are not considered in the existing research. We propose a novel integrated simulation framework considering the traffic, the user, and power grid as well as the EV traveling, parking and charging based on cellular automaton (CA). The traffic is modeled by the traffic module of the proposed framework based on CA, while the power grid and user are modeled in the EV charging module. The traffic flow, user's charging preference, user's charging satisfaction, and the total supply capability (TSC) in the surveyed region are considered in the proposed framework. Two cases are carried out to show the interactions between the user and power grid. It is shown that the proposed framework can accurately simulate the interactions among traffic situation, user's behavior and TSC, which are significantly lacking in the existing research. The proposed framework is scalable in considering additional interrelated elements.

Bibliographic note

Funding Information: Manuscript received: April 1, 2020; accepted: August 12, 2020. Date of Cross‐ Check: August 12, 2020. Date of online publication: November 19, 2020. This work was supported by the National Natural Science Foundation of Chi‐ na (No. 51936003). This article is distributed under the terms of the Creative Commons Attribu‐ tion 4.0 International License (http://creativecommons.org/licenses/by/4.0/). W. Liu, X. Shi, and J. Zhao are with the School of Electrical Engineering, Southeast University, Nanjing 210096, China (e-mail: 220182666@seu. edu. cn; 220182649@seu.edu.cn; jianfeng\_zhao@seu.edu.cn). X. Zhang and Y. Xue (corresponding author) are with the Department of Elec‐ tronic, Electrical and System Engineering, School of Engineering, University of Birmingham, Birmingham, UK (e-mail: X. P. Zhang@bham. ac. uk; xue237039454@gmail.com). DOI: 10.35833/MPCE.2020.000208 Publisher Copyright: © 2013 State Grid Electric Power Research Institute.

Details

Original languageEnglish
Article number9282060
Pages (from-to)602-611
Number of pages10
JournalJournal of Modern Power Systems and Clean Energy
Volume9
Issue number3
Early online date19 Nov 2020
Publication statusPublished - May 2021

Keywords

  • Electric vehicle (EV), cellular automaton, integrated simulation framework, power grid, traffic, user

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