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Locating charging stations for electric vehicles

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  • Sun, Zhuo
  • Gao, Wei
  • Li, Bin
  • Wang, Longlong

Abstract

The insufficient charging infrastructure greatly obstructs the development of the electric vehicle(EV) industry. How to efficiently deploy charging stations in a city becomes an urgent problem for the local government. Previous refueling location models are not suitable for fulfilling the EVs' charging demand. This paper proposes a location model for charging stations based on the characteristics of travel behaviors of urban residents. The model consists of two parts: one for short distance commuters which utilize slow charging (SC) facilities, and the other for long distance travelers which utilize fast recharging (FR) facilities. It aims to harness limited resource to meet as much as possible charging demand for both parking vehicles and vehicles on long journeys. A typical city of China is used as an example to demonstrate the implementation and results of the model. We employed sensitive analyses to search for specific factors having strong impact on the number and location of charging stations. It is suggested that travel distance and locating capacity will greatly affect the final result.

Suggested Citation

  • Sun, Zhuo & Gao, Wei & Li, Bin & Wang, Longlong, 2020. "Locating charging stations for electric vehicles," Transport Policy, Elsevier, vol. 98(C), pages 48-54.
    • Handle: RePEc:eee:trapol:v:98:y:2020:i:c:p:48-54
    DOI: 10.1016/j.tranpol.2018.07.009
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    References listed on IDEAS

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    Citations

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    Cited by:

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    3. Pichamon Keawthong & Veera Muangsin & Chupun Gowanit, 2022. "Location Selection of Charging Stations for Electric Taxis: A Bangkok Case," Sustainability, MDPI, vol. 14(17), pages 1-23, September.
    4. Ramesh Bollapragada & Uday S. Rao & Junying Wu, 2023. "Hub location–allocation for combined fixed-wireless and wireline broadband access networks," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 50(1), pages 115-128, March.
    5. El Mehdi Er Raqabi & Wenkai Li, 2022. "An Electric Vehicle Migration Framework," Working Papers EMS_2022_03, Research Institute, International University of Japan.
    6. Jenn, Alan PhD & Brown, Austin PhD, 2021. "Green Charging of Electric Vehicles Under a Net-Zero Emissions Policy Transition in California," Institute of Transportation Studies, Working Paper Series qt2rv3h345, Institute of Transportation Studies, UC Davis.
    7. Tiande Mo & Yu Li & Kin-tak Lau & Chi Kin Poon & Yinghong Wu & Yang Luo, 2022. "Trends and Emerging Technologies for the Development of Electric Vehicles," Energies, MDPI, vol. 15(17), pages 1-34, August.
    8. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    9. Sophia Alim, 2021. "Web Accessibility of the Top Research-Intensive Universities in the UK," SAGE Open, , vol. 11(4), pages 21582440211, November.
    10. Hamza El Hafdaoui & Hamza El Alaoui & Salma Mahidat & Zakaria El Harmouzi & Ahmed Khallaayoun, 2023. "Impact of Hot Arid Climate on Optimal Placement of Electric Vehicle Charging Stations," Energies, MDPI, vol. 16(2), pages 1-19, January.
    11. Wilfredo F. Yushimito & Sebastian Moreno & Daniela Miranda, 2023. "The Potential of Battery Electric Taxis in Santiago de Chile," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    12. Kłos, Marcin Jacek & Sierpiński, Grzegorz, 2023. "Siting of electric vehicle charging stations method addressing area potential and increasing their accessibility," Journal of Transport Geography, Elsevier, vol. 109(C).

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