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The charging station and swapping station site selection with many-objective evolutionary algorithm

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Abstract

The battery swap mode is a novel way of energy supplement for electric vehicles. Inevitably, there are some business transactions between battery swapping station (BSS) and battery centralized charging station (BCCS) in the mode. Therefore, it is essential to plan the construction of BSS and BCCS uniformly. Moreover, the needs of enterprises and users are not taken into account simultaneously in the existing site selection model. To resolve this problem, a many-objective joint site selection (MOJSS) model of BSS and BCCS is proposed in this paper. It mainly includes four objective functions: construction cost, coverage rate, investment income and satisfaction, which consider distance constraint between user demand points and the BSS, distance constraint between BBS and BSS, and the service ability constraint of BSS and the BCCS. To better solve the proposed model, a Grid-based evolutionary algorithm based on hybrid environment selection strategy is proposed. Furthermore, the segmented integer coding strategy and the specific genetic operation are designed based on the characteristic of model. It is compared with the existing many-objective evolutionary algorithms on standard test problems. Then the algorithm is applied to solve the established model. The experimental result demonstrated the reasonableness and effectiveness of proposed model. Finally, the site selection results are illustrated by a set of solutions.

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Acknowledgements

This work is supported by National Natural Science Foundation of China under Grant No.61806138; Science and Technology Development Foundation of the Central Guiding Local under Grant No. YDZJSX2021A038; Key R&D program of Shanxi Province (International Cooperation) under Grant No. 201903D421048; Postgraduate Innovation Project of Shanxi Province under Grant No. 2021Y696; China University Industry-University-Research Collaborative Innovation Fund Grant No. 2021FNA04014.

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Authors and Affiliations

  1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, China

    Yongqiang He, Yanjun Zhang, Tian Fan, Xingjuan Cai & Yubin Xu

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  1. Yongqiang He
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  2. Yanjun Zhang
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  3. Tian Fan
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  4. Xingjuan Cai
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Contributions

Yongqiang He performs the experimental research and paper writing. Yanjun Zhang reviews grammar of the paper. Tian Fan revised and reviewed the whole paper. Xingjuan Cai and Yubin Xu provide guidance on topic selection of paper.

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Correspondence to Xingjuan Cai or Yubin Xu.

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He, Y., Zhang, Y., Fan, T. et al. The charging station and swapping station site selection with many-objective evolutionary algorithm. Appl Intell 53, 18041–18060 (2023). https://doi.org/10.1007/s10489-022-04292-8

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