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A two-stage optimization framework for EV charging station planning considering investment cost and service satisfaction

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  • Meng, Yunfan
  • Sun, Yonghui
  • Xie, Dongliang
  • Xiao, Min
  • Yin, Chenxu
  • Zhao, Liang

Abstract

A two-stage optimization framework combining macroscopic planning of charging station (CS) siting and sizing with microscopic optimization of charging pile (CP) configurations is proposed in this paper, effectively addressing the complexities in balancing investment costs and user satisfaction. Targeting urban charging infrastructure, the framework systematically translates heterogeneous electric vehicle (EV) charging demands into optimal infrastructure deployments. At the upper stage, the model determines optimal CS locations and capacities, incorporating spatial-temporal charging demand patterns and inter-grid transfer willingness. The lower stage optimizes the detailed configuration of CPs within each station, enhancing user experiences by precisely modeling service interactions and queue dynamics. An efficient hybrid solution method integrating heuristic initialization with iterative refinements is developed, significantly improving computational tractability and solution quality. Case studies confirm the framework's effectiveness in achieving high user satisfaction levels while maintaining cost efficiency.

Suggested Citation

  • Meng, Yunfan & Sun, Yonghui & Xie, Dongliang & Xiao, Min & Yin, Chenxu & Zhao, Liang, 2025. "A two-stage optimization framework for EV charging station planning considering investment cost and service satisfaction," Applied Energy, Elsevier, vol. 402(PA).
    • Handle: RePEc:eee:appene:v:402:y:2025:i:pa:s0306261925016411
    DOI: 10.1016/j.apenergy.2025.126911
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