Research on the Optimal Location of Urban Electric Vehicle Charging Stations Based on the Whale Optimization Algorithm in the Context of Green Energy

With the gradual increase in the number of new energy vehicles in cities, the current location and number of urban charging piles have seriously affected the residents’ demand for charging due to the limitations of urban population and urban roads. Based on the perspective of economic operation and user experience, a charging pile location model based on charging pile maintenance cost and user satisfaction is proposed, and the whale optimisation algorithm is used to seek the optimal location. Since the whale optimization algorithm has the disadvantage of fast convergence and easy to fall into local optimum, we propose a new algorithm based on Tent population initialization and adaptive factor optimization-Tent Adapt Whale Optimization Alogrithm (TAWOA)-to improve the performance of the algorithm as a whole, and in the simulation experiments, the performance of TAWOA is improved compared with that of ACO, PSO, and WOA in the three benchmark functions, and in the charging pile siting, TAWOA algorithm is able to obtain better results than WOA, which can effectively reduce the number of charging piles and reduce energy consumption.

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Publication Details

Journal
Distributed Generation & Alternative Energy Journal
Published
2025-04-23
DOI
https://doi.org/10.13052/dgaej2156-3306.4018
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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Research on the Optimal Location of Urban Electric Vehicle Charging Stations Based on the Whale Optimization Algorithm in the Context of Green Energy

Wen Zhang, Fangheng Xu
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Distributed Generation & Alternative Energy Journal
Electric Vehicles and Infrastructure
article

Research on the Optimal Location of Urban Electric Vehicle Charging Stations Based on the Whale Optimization Algorithm in the Context of Green Energy

Wen Zhang, Fangheng Xu
article en

Abstract

With the gradual increase in the number of new energy vehicles in cities, the current location and number of urban charging piles have seriously affected the residents’ demand for charging due to the limitations of urban population and urban roads. Based on the perspective of economic operation and user experience, a charging pile location model based on charging pile maintenance cost and user satisfaction is proposed, and the whale optimisation algorithm is used to seek the optimal location. Since the whale optimization algorithm has the disadvantage of fast convergence and easy to fall into local optimum, we propose a new algorithm based on Tent population initialization and adaptive factor optimization-Tent Adapt Whale Optimization Alogrithm (TAWOA)-to improve the performance of the algorithm as a whole, and in the simulation experiments, the performance of TAWOA is improved compared with that of ACO, PSO, and WOA in the three benchmark functions, and in the charging pile siting, TAWOA algorithm is able to obtain better results than WOA, which can effectively reduce the number of charging piles and reduce energy consumption.

Distributed Generation & Alternative Energy Journal
State Grid Corporation of China (China) (CN), Zhejiang Industry Polytechnic College (CN)
Openalex Percentile: Top 93%
Electric Vehicles and Infrastructure
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