Hunan Electric Power ›› 2026, Vol. 46 ›› Issue (4): 121-128.doi: 10.3969/j.issn.1008-0198.2026.04.016

• Artifical Intelligence and Digitization • Previous Articles     Next Articles

Charging Station Layout Optimization Based on Voronoi Diagram and Improved Immune Clonal Selection Algorithm

PENG Shibo1, XIAO Hui2, LEI Jiale3, ZENG Linjun4   

  1. 1. Hua Neng Hunan Clean Energy Branch, Changsha 410000, China;
    2. State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410114, China;
    3. University of California, Davis, California 95616, America;
    4. College of Energy and Power Engineering, Changsha University of Science & Technology, Changsha 410114, China
  • Received:2026-03-08 Online:2026-08-25 Published:2026-09-11

Abstract: Aiming at the problems of imprecise service scope division and insufficient algorithmic optimization ability in the layout optimization of electric vehicle charging stations, a charging station site selection and capacity determination method based on Voronoi diagram and improved immune clone selection algorithm is proposed. Firstly, a charging station planning model is constructed with the goal of minimizing annual total costs by considering the economics of charging station construction and operation and maintenance, the power constraints of the regional power grid, and the convenience of charging for users. Secondly, a Voronoi diagram is introduced to classify the service scope of the planning area, and the service area is dynamically generated based on the location of charging stations to ensure that the coverage of each station is reasonable and the degree of overlap is controllable. On this basis, the immune clonal selection algorithm is improved by introducing affinity calculation between antibodies and polynomial variation strategy to improve its global search capability and convergence speed, so as to solve the joint optimization problem of charging station siting and capacity determination efficiently. Finally, the effectiveness of the proposed model and algorithm is verified by MATLAB simulation examples, and the results show that the method can reduce the comprehensive cost of charging stations under the premise of satisfying the coverage and grid constraints.

Key words: electric vehicles, charging station layout, voronoi diagram, immune clonal selection algorithm, service scope

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