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Optimization of electric vehicle charging station layout considering the improvement of distribution network resilience under extreme disasters

Author

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  • Mei, Haozhou
  • Wu, Qiong
  • Ren, Hongbo
  • Zhang, Jinli
  • Li, Qifen

Abstract

The challenge posed by extreme natural disasters to the resilience of power distribution networks is growing increasingly severe. Electric vehicles, as distributed and mobile energy storage devices, have the potential to enhance the resilience of distribution networks through vehicle to grid technology. In this study, resilience is integrated into the evaluation metrics for charging station layout planning, and a methodology for the layout of electric vehicle charging stations is proposed, balancing both economy and resilience. After constructing a typical extreme disaster scenario model using typhoons as an example, a resilience deployment model for charging stations is developed, which comprehensively considers the resilience of the distribution network and traffic flow. The objective function is designed to minimize the annual total social cost, which includes factors such as construction and operation costs, user usage costs, charging loss costs, and resilience configuration costs. A joint solution algorithm, combining the Voronoi diagram and particle swarm optimization algorithm, is proposed to solve the model. According to the simulation results of an illustrative example, the resilience optimization scenario performs well in terms of load loss penalty. This indicates that, in extreme disaster situations, this planning approach can effectively mitigate losses caused by power outages and improve the reliability and stability of the power system.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:323:y:2025:i:c:s0360544225014732
    DOI: 10.1016/j.energy.2025.135831
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