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Impact of electric vehicles on post-disaster power supply restoration of urban distribution systems

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  • Du, Ying
  • Zhang, Junxiang
  • Chen, Yuntian
  • Liu, Zhengguang
  • Zhang, Haoran
  • Ji, Haoran
  • Wang, Chengshan
  • Yan, Jinyue

Abstract

The resilience of the urban distribution system is crucial for resisting increasingly frequent disasters under climate change. In the context of extensive penetration of Electric Vehicles (EVs) into the distribution system, this study investigates the potential of EVs as an auxiliary power source for post-disaster power supply restoration using actual data from Shanghai. A coupling system comprising the traffic network and the urban distribution system was established, where the travel and charging patterns of EVs were modeled using actual data. Based on that, the spatio-temporal available EV power at different Vehicle to Grid (V2G) stations can be estimated after calculating EVs’ on-road power consumption and considering the V2G response policy. A post-disaster power supply restoration scheme that incorporates V2G participation was proposed, leading to a better restoration strategy that fully utilizes V2G capabilities. It can be found that V2G based restoration scheme demonstrates superior performance in enhancing grid resilience during disaster scenarios, as quantified by various resilience indicators including power loss, response speed, and recovery degree. Additionally, the model offers spatio-temporal insights for disaster prevention by leveraging V2G technology, identifying critical times and locations for effective defense during disasters. This paper also predicted the benefits of V2G under varying future EV penetration rates and response rates.

Suggested Citation

  • Du, Ying & Zhang, Junxiang & Chen, Yuntian & Liu, Zhengguang & Zhang, Haoran & Ji, Haoran & Wang, Chengshan & Yan, Jinyue, 2025. "Impact of electric vehicles on post-disaster power supply restoration of urban distribution systems," Applied Energy, Elsevier, vol. 383(C).
    • Handle: RePEc:eee:appene:v:383:y:2025:i:c:s0306261925000327
    DOI: 10.1016/j.apenergy.2025.125302
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    References listed on IDEAS

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    1. Shen, Yueqing & Qian, Tong & Li, Weiwei & Zhao, Wei & Tang, Wenhu & Chen, Xingyu & Yu, Zeyuan, 2023. "Mobile energy storage systems with spatial–temporal flexibility for post-disaster recovery of power distribution systems: A bilevel optimization approach," Energy, Elsevier, vol. 282(C).
    2. Chung, Yu-Wei & Khaki, Behnam & Li, Tianyi & Chu, Chicheng & Gadh, Rajit, 2019. "Ensemble machine learning-based algorithm for electric vehicle user behavior prediction," Applied Energy, Elsevier, vol. 254(C).
    3. Mehrjerdi, Hasan, 2021. "Resilience oriented vehicle-to-home operation based on battery swapping mechanism," Energy, Elsevier, vol. 218(C).
    Full references (including those not matched with items on IDEAS)

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    1. Mei, Haozhou & Wu, Qiong & Ren, Hongbo & Zhang, Jinli & Li, Qifen, 2025. "Optimization of electric vehicle charging station layout considering the improvement of distribution network resilience under extreme disasters," Energy, Elsevier, vol. 323(C).

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