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Optimal planning strategy for EV charging stations considering travel demands based on non‐cooperative game theory

Authors :
Yongsheng Zhu
Mingming Zhang
Yan Dong
Qunfang Chang
Bin Chen
Caijing Nie
Source :
IET Generation, Transmission & Distribution, Vol 17, Iss 3, Pp 684-695 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract In this paper, an optimal planning strategy is proposed for EV charging stations by considering travel demand based on non‐cooperative game theory. In the proposed methodology, a realistic and stochastic charging demand distribution was obtained with the travel chain of an EV and the associated probability density function. Based on the charging demand of EV owners and a multi‐operator scenario, a two‐stage effective and practical charging station planning model was established. The first stage of the planning model optimized the location of charging stations to decrease the total deadhead mileage of the EVs with the cooperation of the charging station operators. In the second stage, the operators were committed to increasing their economic benefits by developing a charging station capacity strategy in the framework of the non‐cooperative game. Furthermore, the combination of an adaptive mutation particle swarm optimization algorithm (AMPSO) and approximate Nash equilibrium had a better effect in reducing the difficulty of solving the game model and obtaining an optimal planning strategy. Finally, the results of the case study demonstrated the effectiveness of the proposed methodology for improving the charging experience of the EV owners and achieving a balance of benefits among multiple charging station operators.

Details

Language :
English
ISSN :
17518695 and 17518687
Volume :
17
Issue :
3
Database :
Directory of Open Access Journals
Journal :
IET Generation, Transmission & Distribution
Publication Type :
Academic Journal
Accession number :
edsdoj.1c46919f588948c288d74f6a15112124
Document Type :
article
Full Text :
https://doi.org/10.1049/gtd2.12697