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An Optimization Model for the Temporary Locations of Mobile Charging Stations

Author

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  • Maria-Simona Răboacă

    (Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, 13 Universităţii Street, 720229 Suceava, Romania
    Faculty of Electrical Engineering, Technical University of Cluj-Napoca, 26-28 G. Bariţiu Street, 400027 Cluj-Napoca, Romania
    Current Address: National Research and Development Institute for Cryogenic and Isotopic Technologies-ICSI, 4 Uzinei Street, 240050 Râmnicu Vâlcea, Romania.)

  • Irina Băncescu

    (Costin C. Kiriţescu, National Institute of Economic Research, 13 Calea 13 Septembrie Street, 050711 Bucharest, Romania)

  • Vasile Preda

    (Costin C. Kiriţescu, National Institute of Economic Research, 13 Calea 13 Septembrie Street, 050711 Bucharest, Romania
    Gheorghe Mihoc-Caius Iacob, Institute of Mathematical Statistics and Applied Mathematics, 13 Calea 13 Septembrie Street, 050711 Bucharest, Romania)

  • Nicu Bizon

    (Faculty of Electronics, Communications and Computers University of Piteşti, 1 Târgu din Vale Street, 110040 Piteşti, Romania)

Abstract

A possible solution with which to alleviate the range anxiety of electric vehicle (EV) drivers could be a mobile charging station which moves in different places to charge EVs, having a charging time of even half an hour. A problem that arises is the impossibility of charging in any location due to heavy traffic or limited space constraints. This paper proposes a new operational mode for the mobile charging station through temporarily stationing it at different places for certain amounts of time. A mathematical model, in the form of an optimization problem, is built by modeling the mobile charging station as a queuing process, the goal of the problem being to place a minimum number of temporary service centers (which may have one or more mobile charging stations) to minimize operating costs and the charger capacity of the mobile charging station so that the service offered is efficient. The temporary locations obtained are in areas with no or few fixed charging stations, making the mobile station infrastructure complementary to the fixed charging station infrastructure. The temporary location operational mode, compared to current moving operational mode, is more efficient, having a small miss ratio, short mean response time and short mean queuing time.

Suggested Citation

  • Maria-Simona Răboacă & Irina Băncescu & Vasile Preda & Nicu Bizon, 2020. "An Optimization Model for the Temporary Locations of Mobile Charging Stations," Mathematics, MDPI, vol. 8(3), pages 1-20, March.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:3:p:453-:d:335208
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    References listed on IDEAS

    as
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    Cited by:

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    2. Nazari-Heris, Morteza & Loni, Abdolah & Asadi, Somayeh & Mohammadi-ivatloo, Behnam, 2022. "Toward social equity access and mobile charging stations for electric vehicles: A case study in Los Angeles," Applied Energy, Elsevier, vol. 311(C).
    3. Loni, Abdolah & Asadi, Somayeh, 2023. "Data-driven equitable placement for electric vehicle charging stations: Case study San Francisco," Energy, Elsevier, vol. 282(C).
    4. Zixuan Wang & Qingyuan Yang & Chuwen Wang & Lanxi Wang, 2023. "Spatial Layout Analysis and Evaluation of Electric Vehicle Charging Infrastructure in Chongqing," Land, MDPI, vol. 12(4), pages 1-18, April.
    5. Hung, Ying-Chao & PakHai Lok, Horace & Michailidis, George, 2022. "Optimal routing for electric vehicle charging systems with stochastic demand: A heavy traffic approximation approach," European Journal of Operational Research, Elsevier, vol. 299(2), pages 526-541.
    6. 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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