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Optimal planning for charging stations within multi-coupled networks considering load-balance effects

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Listed:
  • Yang, Nan
  • Lin, Dongrui
  • Ding, Li
  • Yang, Chuyuan
  • Zhang, Lei
  • Yang, Yi
  • Ye, Xuecheng
  • Xiong, Zhi
  • Huang, Yuehua

Abstract

With the rapid proliferation of electric vehicles (EVs), operational challenges such as traffic congestion and power system overload have become increasingly prominent. To address these issues and effectively guide the operation of charging stations (CSs) managed by grid companies (GCs), this paper proposes an optimized CS planning method within multi-coupled networks considering load-balance effects. Firstly, a multi-coupled network topology model is developed by integrating the EV charging network, the transportation network (TN), and the power distribution network (PDN). Then, on the TN level, a load clustering-based method for delineating service areas is proposed, considering the impact of real-time traffic conditions on user charging decisions. On the PDN level, the impact of spatially distributed charging loads on voltage fluctuations is analyzed, and a CS planning model considering load-balancing effects is developed. Finally, an immune genetic algorithm (IGA) is employed to solve the proposed model. Case studies demonstrate that the proposed model can reduce total time by 69.26 %, voltage fluctuation rate by 155.09 %, and network loss cost by 45.82 %, thereby validating its economic efficiency and practical effectiveness.

Suggested Citation

  • Yang, Nan & Lin, Dongrui & Ding, Li & Yang, Chuyuan & Zhang, Lei & Yang, Yi & Ye, Xuecheng & Xiong, Zhi & Huang, Yuehua, 2025. "Optimal planning for charging stations within multi-coupled networks considering load-balance effects," Energy, Elsevier, vol. 336(C).
    • Handle: RePEc:eee:energy:v:336:y:2025:i:c:s0360544225041234
    DOI: 10.1016/j.energy.2025.138481
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