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Uncertain scheduling potential of charging stations under multi-attribute uncertain charging decisions of electric vehicles

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  • Wu, Fuzhang
  • Yang, Jun
  • Li, Bin
  • Crisostomi, Emanuele
  • Rafiq, Hogir
  • Rashed, Ghamgeen Izat

Abstract

A method for analyzing the uncertain adjustability of charging stations (CSs) under the influence of multi-attribute group decision-makings of electric vehicles (EVs) is proposed. Firstly, considering physical constraints of parameters such as charging power and energy stored, a model for characterizing the schedulability of a single EV under different charging modes including rated power charging, adjustable charging, and flexible charging and discharging is constructed. Secondly, since the charging mode selection of EVs is a comprehensive decision considering charging cost, charging time and other attributes, and individual decision-making is often affected by group users, an EV charging mode selection probability model is developed based on the multi-attribute group decision-making theory. Further, scheduling potential boundary parameters of CSs affected by the scheduling potential of all EVs in the station are derived based on the Minkowski sum theory, and their probability characteristics are calculated by combining the charging mode selection probability of single EVs and the schedulability under each mode. Finally, case studies prove the superiority of the proposed theory.

Suggested Citation

  • Wu, Fuzhang & Yang, Jun & Li, Bin & Crisostomi, Emanuele & Rafiq, Hogir & Rashed, Ghamgeen Izat, 2024. "Uncertain scheduling potential of charging stations under multi-attribute uncertain charging decisions of electric vehicles," Applied Energy, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:appene:v:374:y:2024:i:c:s0306261924014193
    DOI: 10.1016/j.apenergy.2024.124036
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    Cited by:

    1. Qingyuan Yan & Zhaoyi Wang & Ling Xing & Chenchen Zhu, 2024. "Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System," Sustainability, MDPI, vol. 16(19), pages 1-44, September.

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