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Electric Vehicle Charging Station Layout for Tourist Attractions Based on Improved Two-Population Genetic PSO

Author

Listed:
  • Shuang Che

    (School of Shipping Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Yan Chen

    (School of Shipping Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Longda Wang

    (School of Automation and Electrical Engineering, Dalian Jiaotong University, Dalian 116028, China)

Abstract

In this paper, the optimization issue of electric vehicle charging station layout (EVCSL) for tourist attractions is addressed, and an improved PSO is used to solve the optimization issue. Specifically, the improved particle swarm optimization (PSO) is proposed to obtain an appreciative planning solution of EVCSL, and dynamic weight adjustment strategy and integration into the two-population genetic mode are proposed to improve the optimization quality for PSO. Simulation results show that the proposed improvement strategies can increase the optimization quality for PSO effectively so that a more appreciative planning solution of EVCSL can be obtained.

Suggested Citation

  • Shuang Che & Yan Chen & Longda Wang, 2023. "Electric Vehicle Charging Station Layout for Tourist Attractions Based on Improved Two-Population Genetic PSO," Energies, MDPI, vol. 16(2), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:983-:d:1036928
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    References listed on IDEAS

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    1. LaMonaca, Sarah & Ryan, Lisa, 2022. "The state of play in electric vehicle charging services – A review of infrastructure provision, players, and policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    2. Liu, Zongwei & Hao, Han & Cheng, Xiang & Zhao, Fuquan, 2018. "Critical issues of energy efficient and new energy vehicles development in China," Energy Policy, Elsevier, vol. 115(C), pages 92-97.
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    Cited by:

    1. Bahman Ahmadi & Elham Shirazi, 2023. "A Heuristic-Driven Charging Strategy of Electric Vehicle for Grids with High EV Penetration," Energies, MDPI, vol. 16(19), pages 1-26, October.

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