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

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.

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Publication Details

Journal
PLoS ONE
Published
2025-09-30
DOI
https://doi.org/10.1371/journal.pone.0332872
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Sixia Fan, X. Zeng, Lanxin Li, S. Y. Xu
PLoS ONE
Electric Vehicles and Infrastructure
article

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

Sixia Fan, X. Zeng, Lanxin Li, S. Y. Xu
article en

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.

PLoS ONEVol. 20(9)
Shanghai Dianji University (CN)
Openalex Percentile: Top 74%
Electric Vehicles and Infrastructure
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Improved artificial hummingbird algorithm for electric vehicle charging station fast and slow charging location determination method — Sixia Fan, X. Zeng, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS