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

S Sixia Fan X Xiangyu Zeng L Lanxin Li (Department of Biology, School of Life Sciences, Southern University of Science and Technology) S Shuqi Xu

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.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 9
Published September 30, 2025
Pages e0332872
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (4)

S

Sixia Fan

X

Xiangyu Zeng

L

Lanxin Li

Department of Biology, School of Life Sciences, Southern University of Science and Technology

S

Shuqi Xu