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Location of electric vehicle charging stations: A perspective using the grey decision-making model

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  • Ren, Xianqiang
  • Zhang, Huiming
  • Hu, Ruohan
  • Qiu, Yueming

Abstract

the reasonable location of a charging station will promote the rapid development of the new energy automobile industry. This paper initially establishes the location model of minimizing the total social cost with the purpose of a genetic algorithm solution. Next, an evaluation index system is constructed based on five location influencing factors; land cost, construction costs, road traffic flow, power grid conditions and the surrounding environment. Numerical studies show that both grey incidence decision and grey target theory have the advantages of ease of operation, low requirement of data collection and processing when they are employed while selecting the optimal location.

Suggested Citation

  • Ren, Xianqiang & Zhang, Huiming & Hu, Ruohan & Qiu, Yueming, 2019. "Location of electric vehicle charging stations: A perspective using the grey decision-making model," Energy, Elsevier, vol. 173(C), pages 548-553.
    • Handle: RePEc:eee:energy:v:173:y:2019:i:c:p:548-553
    DOI: 10.1016/j.energy.2019.02.015
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    References listed on IDEAS

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    1. Wang, Ying-Wei & Lin, Chuah-Chih, 2013. "Locating multiple types of recharging stations for battery-powered electric vehicle transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 76-87.
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    Cited by:

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    2. Mansur Arief & Yan Akhra & Iwan Vanany, 2023. "A Robust and Efficient Optimization Model for Electric Vehicle Charging Stations in Developing Countries under Electricity Uncertainty," Papers 2307.05470, arXiv.org.
    3. Jun-liang Du & Si-feng Liu & Yong Liu, 2021. "Grey Target Negotiation Consensus Model Based on Super Conflict Equilibrium," Group Decision and Negotiation, Springer, vol. 30(4), pages 915-944, August.
    4. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    5. Muhammad Huzaifa & Arif Hussain & Waseem Haider & Syed Ali Abbas Kazmi & Usman Ahmad & Habib Ur Rehman, 2023. "Optimal Planning Approaches under Various Seasonal Variations across an Active Distribution Grid Encapsulating Large-Scale Electrical Vehicle Fleets and Renewable Generation," Sustainability, MDPI, vol. 15(9), pages 1-32, May.
    6. Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    7. Di Xu & Wenhui Pei & Qi Zhang, 2022. "Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience," Energies, MDPI, vol. 15(14), pages 1-16, July.
    8. Andrea Stabile & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "An Algorithm for Optimization of Recharging Stops: A Case Study of Electric Vehicle Charging Stations on Canadian’s Ontario Highway 401," Energies, MDPI, vol. 13(8), pages 1-19, April.
    9. Yongzhong Wu & Yikuan Lu & Zhijie Zhu & José Holguín-Veras, 2023. "Optimizing Electric Vehicle Charging Infrastructure on Highways: A Multi-Agent-Based Planning Approach," Sustainability, MDPI, vol. 15(18), pages 1-14, September.
    10. Alcázar-García, Désirée & Romeral Martínez, José Luis, 2022. "Model-based design validation and optimization of drive systems in electric, hybrid, plug-in hybrid and fuel cell vehicles," Energy, Elsevier, vol. 254(PA).
    11. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    12. Qingyou Yan & Hua Dong & Meijuan Zhang, 2021. "Service Evaluation of Electric Vehicle Charging Station: An Application of Improved Matter-Element Extension Method," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    13. Li, Chengzhe & Zhang, Libo & Ou, Zihan & Wang, Qunwei & Zhou, Dequn & Ma, Jiayu, 2022. "Robust model of electric vehicle charging station location considering renewable energy and storage equipment," Energy, Elsevier, vol. 238(PA).
    14. Lin, Haiyang & Bian, Caiyun & Wang, Yu & Li, Hailong & Sun, Qie & Wallin, Fredrik, 2022. "Optimal planning of intra-city public charging stations," Energy, Elsevier, vol. 238(PC).
    15. Gururaghav Raman & Gurupraanesh Raman & Jimmy Chih-Hsien Peng, 2022. "Resilience of urban public electric vehicle charging infrastructure to flooding," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    16. Milan Straka & Pasquale De Falco & Gabriella Ferruzzi & Daniela Proto & Gijs van der Poel & Shahab Khormali & v{L}ubov{s} Buzna, 2019. "Predicting popularity of EV charging infrastructure from GIS data," Papers 1910.02498, arXiv.org.
    17. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    18. Susheng Wang & Gang Chen & Dawei Huang, 2021. "Can the New Energy Vehicle Pilot Policy Achieve Green Innovation and Emission Reduction?—A Difference-in-Differences Analysis on the Evaluation of China’s New Energy Fiscal Subsidy Policy," Sustainability, MDPI, vol. 13(15), pages 1-21, August.

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