Improved artificial hummingbird algorithm for electric vehicle charging station fast and slow charging location determination method

Sixia Fan, Xiangyu Zeng, Lanxin Li and Shuqi Xu

PLOS ONE, 2025, vol. 20, issue 9, 1-23

Abstract: Electric vehicle (EV) charging infrastructure is rapidly improving. To address high site selection costs from unbalanced fast-slow charging ratios and multi-party cost allocation issues, we propose a four-objective optimization model based on a three-party cost game (suppliers, users, power grid). The model minimizes: (1) construction/operation costs, (2) user time loss costs, (3) grid power loss costs, and (4) voltage deviation costs under different charging modes. An improved artificial hummingbird algorithm solves the model. Results show the approach improves economic efficiency, provides valuable reference for EV charging station siting, and demonstrates strong algorithm robustness and generalization.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0332872

DOI: 10.1371/journal.pone.0332872

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