Open Access

ARTICLE

An Optimisation Strategy for Electric Vehicle Charging Station Layout Incorporating Mini Batch K-Means and Simulated Annealing Algorithms

by Haojie Yang, Xiang Wen, Peng Geng^*

School of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

* Corresponding Author: Peng Geng. Email:

Journal on Artificial Intelligence 2024, 6, 283-300. https://doi.org/10.32604/jai.2024.056303

Received 19 July 2024; Accepted 30 September 2024; Issue published 18 October 2024

Abstract

To enhance the rationality of the layout of electric vehicle charging stations, meet the actual needs of users, and optimise the service range and coverage efficiency of charging stations, this paper proposes an optimisation strategy for the layout of electric vehicle charging stations that integrates Mini Batch K-Means and simulated annealing algorithms. By constructing a circle-like service area model with the charging station as the centre and a certain distance as the radius, the maximum coverage of electric vehicle charging stations in the region and the influence of different regional environments on charging demand are considered. Based on the real data of electric vehicle charging stations in Nanjing, Jiangsu Province, this paper uses the model proposed in this paper to optimise the layout of charging stations in the study area. The results show that the optimisation strategy incorporating Mini Batch K-Means and simulated annealing algorithms outperforms the existing charging station layouts in terms of coverage and the number of stations served, and compared to the original charging station layouts, the optimised charging station layouts have flatter Lorentzian curves and are closer to the average distribution. The proposed optimisation strategy not only improves the service efficiency and user satisfaction of EV (Electric Vehicle) charging stations but also provides a reference for the layout optimisation of EV charging stations in other cities, which has important practical value and promotion potential.

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Keywords

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