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A temporal–spatial charging coordination scheme incorporating probability of EV charging availability

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  • Li, Zhikang
  • Ma, Chengbin

Abstract

The charging coordination of electric vehicle (EV) fleets in both temporal domain and spatial domain has attracted growing attention in recent years. Meanwhile, the uncertainties in EV arrival time and total available charging power from charging stations make the coordination problem highly dynamic and challenging. This paper develops a new temporal–spatial EV charging coordination scheme that jointly considers the above two major uncertainties. Firstly, EV charging scheduling (i.e., temporal coordination) is treated as a generalized Nash equilibrium game, in which each EV (including an upcoming EV) prefers to meet its own charging demand with minimized charging cost. The probability of EV charging availability is especially proposed to incorporate the charging demands of the upcoming EVs into the coordination scheme. In order to provide flexibility and private information protection, a distributed receding horizon optimization-based solution is developed, through which the Lagrange multipliers to reach the social equilibrium are determined via an iterative manner. The charging station selection is then recommended that minimizes the objective function over the entire optimization horizon. Finally, simulations under both small-scale and large-scale scenarios effectively demonstrate improved service quality of the EV charging, both in temporal and spatial domains, and avoidance of overload in charging stations. Results in a 150-EV scenario show that, averagely, the proposed method reduces battery SoC mismatch by 43% and increases degree of consistency by 5.9%.

Suggested Citation

  • Li, Zhikang & Ma, Chengbin, 2022. "A temporal–spatial charging coordination scheme incorporating probability of EV charging availability," Applied Energy, Elsevier, vol. 325(C).
    • Handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011072
    DOI: 10.1016/j.apenergy.2022.119838
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    References listed on IDEAS

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    1. Francisco Facchinei & Christian Kanzow, 2010. "Generalized Nash Equilibrium Problems," Annals of Operations Research, Springer, vol. 175(1), pages 177-211, March.
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    Cited by:

    1. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
    2. Feng, Jian & Yao, Yifan & Liu, Zhenfeng & Liu, Zhenling, 2024. "Electric vehicle charging stations' installing strategies: Considering government subsidies," Applied Energy, Elsevier, vol. 370(C).
    3. Etedadi, Farshad & Kelouwani, Sousso & Agbossou, Kodjo & Henao, Nilson & Laurencelle, François, 2023. "Consensus and sharing based distributed coordination of home energy management systems with demand response enabled baseboard heaters," Applied Energy, Elsevier, vol. 336(C).

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