A bi-level programming model for inter-city charging station location with heterogeneous range anxiety

Dingding Hu, Kaile Zhou and Xinhui Lu

Energy, 2025, vol. 316, issue C

Abstract: With the rapid expansion of electric vehicles, the distribution of charging stations is inadequate to meet travel demands, especially for long-distance trips. In this situation, determining the optimal distribution of charging stations within the road network can boost the adoption of electric vehicles and alleviate drivers' range anxiety. Therefore, this study focuses on the location problem of electric vehicle charging stations, the aim of which is to identify an optimal set of charging station locations while minimizing electric vehicle drivers' range anxiety. The problem is formulated as a bi-level programming model. To solve the model, an efficient algorithm integrating the partial enumeration algorithm into the genetic algorithm is proposed to reduce the solution space. Experimental results based on the Nguyen-Dupuis network and the Anhui expressway network validate the effectiveness and superiority of the proposed algorithm. The results indicate that deploying more charging stations can effectively reduce drivers' range anxiety. Electric vehicles with insufficient driving range will increase their reliance on charging stations and drivers will choose more expensive routes.

Keywords: Electric vehicle charging; Charging station location; Bi-level programming; Range anxiety; Partial enumeration algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:316:y:2025:i:c:s0360544225002610

DOI: 10.1016/j.energy.2025.134619

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