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Locating Multiple Size and Multiple Type of Charging Station for Battery Electricity Vehicles

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  • Shaohua Cui

    (MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Hui Zhao

    (MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Huijie Wen

    (MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Cuiping Zhang

    (Computing Center, Beijing Information Science & Technology University, Beijing 100192, China)

Abstract

As environmental and energy issues have attracted more and more attention from the public, research on electric vehicles has become extensive and in-depth. As driving range limit is one of the key factors restricting the development of electric vehicles, the energy supply of electric vehicles mainly relies on the building of charging stations, battery swapping stations, and wireless charging lanes. Actually, the latter two kinds of infrastructure are seldom employed due to their immature technology, relatively large construction costs, and difficulty in standardization. Currently, charging stations are widely used since, in the real world, there are different types of charging station with various levels which could be suitable for the needs of network users. In the past, the study of the location charging stations for battery electric vehicles did not take the different sizes and different types into consideration. In fact, it is of great significance to set charging stations with multiple sizes and multiple types to meet the needs of network users. In the paper, we define the model as a location problem in a capacitated network with an agent technique using multiple sizes and multiple types and formulate the model as a 0–1 mixed integer linear program (MILP) to minimize the total trip travel time of all agents. Finally, we demonstrate the model through numerical examples on two networks and make sensitivity analyses on total budget, initial quantity, and the anxious range of agents accordingly. The results show that as the initial charge increases or the budget increases, travel time for all agents can be reduced; a reduction in range anxiety can increase travel time for all agents.

Suggested Citation

  • Shaohua Cui & Hui Zhao & Huijie Wen & Cuiping Zhang, 2018. "Locating Multiple Size and Multiple Type of Charging Station for Battery Electricity Vehicles," Sustainability, MDPI, vol. 10(9), pages 1-20, September.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3267-:d:169470
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    References listed on IDEAS

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    1. Liu, Haoxiang & Wang, David Z.W., 2017. "Locating multiple types of charging facilities for battery electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 30-55.
    2. Yongxi Huang & Shengyin Li & Zhen Qian, 2015. "Optimal Deployment of Alternative Fueling Stations on Transportation Networks Considering Deviation Paths," Networks and Spatial Economics, Springer, vol. 15(1), pages 183-204, March.
    3. Lee, Chungmok & Han, Jinil, 2017. "Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 130-152.
    4. Yang, Woosuk, 2018. "A user-choice model for locating congested fast charging stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 189-213.
    5. Cavadas, Joana & Homem de Almeida Correia, Gonçalo & Gouveia, João, 2015. "A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 188-201.
    6. Xu, Min & Meng, Qiang & Liu, Kai, 2017. "Network user equilibrium problems for the mixed battery electric vehicles and gasoline vehicles subject to battery swapping stations and road grade constraints," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 138-166.
    7. Shaohua Cui & Hui Zhao & Cuiping Zhang, 2018. "Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles," Sustainability, MDPI, vol. 10(8), pages 1-26, August.
    8. Nie, Yu (Marco) & Ghamami, Mehrnaz & Zockaie, Ali & Xiao, Feng, 2016. "Optimization of incentive polices for plug-in electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 103-123.
    9. 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.
    10. Chen, Zhibin & He, Fang & Yin, Yafeng, 2016. "Optimal deployment of charging lanes for electric vehicles in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 344-365.
    11. He, Fang & Yin, Yafeng & Lawphongpanich, Siriphong, 2014. "Network equilibrium models with battery electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 306-319.
    12. Nie, Yu (Marco) & Ghamami, Mehrnaz, 2013. "A corridor-centric approach to planning electric vehicle charging infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 172-190.
    13. Adler, Jonathan D. & Mirchandani, Pitu B., 2014. "Online routing and battery reservations for electric vehicles with swappable batteries," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 285-302.
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    Cited by:

    1. Simona Bigerna & Silvia Micheli, 2018. "Attitudes Toward Electric Vehicles: The Case of Perugia Using a Fuzzy Set Analysis," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    2. Anastasia Gorbunova & Ilya Anisimov & Elena Magaril, 2020. "Studying the Formation of the Charging Session Number at Public Charging Stations for Electric Vehicles," Sustainability, MDPI, vol. 12(14), pages 1-18, July.
    3. Shaohua Cui & Hui Zhao & Cuiping Zhang, 2018. "Locating Charging Stations of Various Sizes with Different Numbers of Chargers for Battery Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-22, November.
    4. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    5. Li Zhang & Ke Gong & Maozeng Xu, 2019. "Congestion Control in Charging Stations Allocation with Q-Learning," Sustainability, MDPI, vol. 11(14), pages 1-11, July.
    6. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    7. Zeinab Teimoori & Abdulsalam Yassine, 2022. "A Review on Intelligent Energy Management Systems for Future Electric Vehicle Transportation," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    8. Afshar, Shahab & Macedo, Pablo & Mohamed, Farog & Disfani, Vahid, 2021. "Mobile charging stations for electric vehicles — A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).

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