Work

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

Year: 2025

Type: article

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.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0332872

Authors: Sixia Fan, Xiangyu Zeng, Lanxin Li, Shuqi Xu

Institution: Shanghai Dianji University

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,382