IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i3p453-d335208.html
   My bibliography  Save this article

An Optimization Model for the Temporary Locations of Mobile Charging Stations

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/3/453/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/8/3/453/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bizon, N., 2011. "Nonlinear control of fuel cell hybrid power sources: Part I - Voltage control," Applied Energy, Elsevier, vol. 88(7), pages 2559-2573, July.
    2. Rahman, Imran & Vasant, Pandian M. & Singh, Balbir Singh Mahinder & Abdullah-Al-Wadud, M. & Adnan, Nadia, 2016. "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1039-1047.
    3. Sayarshad, Hamid R. & Chow, Joseph Y.J., 2017. "Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 60-77.
    4. Bizon, Nicu, 2013. "Energy efficiency for the multiport power converters architectures of series and parallel hybrid power source type used in plug-in/V2G fuel cell vehicles," Applied Energy, Elsevier, vol. 102(C), pages 726-734.
    5. 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.
    6. He, Fang & Wu, Di & Yin, Yafeng & Guan, Yongpei, 2013. "Optimal deployment of public charging stations for plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 87-101.
    7. Bizon, N., 2011. "Nonlinear control of fuel cell hybrid power sources: Part II - Current control," Applied Energy, Elsevier, vol. 88(7), pages 2574-2591, July.
    8. Hidrue, Michael K. & Parsons, George R. & Kempton, Willett & Gardner, Meryl P., 2011. "Willingness to pay for electric vehicles and their attributes," Resource and Energy Economics, Elsevier, vol. 33(3), pages 686-705, September.
    9. Asamer, Johannes & Reinthaler, Martin & Ruthmair, Mario & Straub, Markus & Puchinger, Jakob, 2016. "Optimizing charging station locations for urban taxi providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 233-246.
    10. Csiszár, Csaba & Csonka, Bálint & Földes, Dávid & Wirth, Ervin & Lovas, Tamás, 2019. "Urban public charging station locating method for electric vehicles based on land use approach," Journal of Transport Geography, Elsevier, vol. 74(C), pages 173-180.
    11. Bizon, Nicu, 2012. "Energy efficiency of multiport power converters used in plug-in/V2G fuel cell vehicles," Applied Energy, Elsevier, vol. 96(C), pages 431-443.
    12. Zhu, Zhi-Hong & Gao, Zi-You & Zheng, Jian-Feng & Du, Hao-Ming, 2016. "Charging station location problem of plug-in electric vehicles," Journal of Transport Geography, Elsevier, vol. 52(C), pages 11-22.
    13. Awasthi, Abhishek & Venkitusamy, Karthikeyan & Padmanaban, Sanjeevikumar & Selvamuthukumaran, Rajasekar & Blaabjerg, Frede & Singh, Asheesh K., 2017. "Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm," Energy, Elsevier, vol. 133(C), pages 70-78.
    14. Davidov, Sreten & Pantoš, Miloš, 2017. "Planning of electric vehicle infrastructure based on charging reliability and quality of service," Energy, Elsevier, vol. 118(C), pages 1156-1167.
    15. Vladimir Marianov & Daniel Serra, 2002. "Location–Allocation of Multiple-Server Service Centers with Constrained Queues or Waiting Times," Annals of Operations Research, Springer, vol. 111(1), pages 35-50, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Afshar, Shahab & Pecenak, Zachary K. & Barati, Masoud & Disfani, Vahid, 2022. "Mobile charging stations for EV charging management in urban areas: A case study in Chattanooga," Applied Energy, Elsevier, vol. 325(C).
    2. 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.
    3. 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.
    4. 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).
    5. Loni, Abdolah & Asadi, Somayeh, 2023. "Data-driven equitable placement for electric vehicle charging stations: Case study San Francisco," Energy, Elsevier, vol. 282(C).
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Calviño, Aida, 2019. "Fast charging stations placement methodology for electric taxis in urban zones," Energy, Elsevier, vol. 188(C).
    3. Bizon, Nicu, 2019. "Hybrid power sources (HPSs) for space applications: Analysis of PEMFC/Battery/SMES HPS under unknown load containing pulses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 14-37.
    4. 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.
    5. Davidov, Sreten & Pantoš, Miloš, 2017. "Impact of stochastic driving range on the optimal charging infrastructure expansion planning," Energy, Elsevier, vol. 141(C), pages 603-612.
    6. Metais, M.O. & Jouini, O. & Perez, Y. & Berrada, J. & Suomalainen, E., 2022. "Too much or not enough? Planning electric vehicle charging infrastructure: A review of modeling options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    7. He, Sylvia Y. & Kuo, Yong-Hong & Sun, Ka Kit, 2022. "The spatial planning of public electric vehicle charging infrastructure in a high-density city using a contextualised location-allocation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 21-44.
    8. Eleftherios Anastasiadis & Panagiotis Angeloudis & Daniel Ainalis & Qiming Ye & Pei-Yuan Hsu & Renos Karamanis & Jose Escribano Macias & Marc Stettler, 2020. "On the Selection of Charging Facility Locations for EV-Based Ride-Hailing Services: A Computational Case Study," Sustainability, MDPI, vol. 13(1), pages 1-16, December.
    9. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    10. Tao, Ye & Huang, Miaohua & Yang, Lan, 2018. "Data-driven optimized layout of battery electric vehicle charging infrastructure," Energy, Elsevier, vol. 150(C), pages 735-744.
    11. Davidov, Sreten & Pantoš, Miloš, 2019. "Optimization model for charging infrastructure planning with electric power system reliability check," Energy, Elsevier, vol. 166(C), pages 886-894.
    12. Park, Junseok & Moon, Ilkyeong, 2023. "A facility location problem in a mixed duopoly on networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    13. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    14. Vasallo, Manuel Jesús & Bravo, José Manuel & Andújar, José Manuel, 2013. "Optimal sizing for UPS systems based on batteries and/or fuel cell," Applied Energy, Elsevier, vol. 105(C), pages 170-181.
    15. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Nicu Bizon & Alin Gheorghita Mazare & Laurentiu Mihai Ionescu & Phatiphat Thounthong & Erol Kurt & Mihai Oproescu & Gheorghe Serban & Ioan Lita, 2019. "Better Fuel Economy by Optimizing Airflow of the Fuel Cell Hybrid Power Systems Using Fuel Flow-Based Load-Following Control," Energies, MDPI, vol. 12(14), pages 1-17, July.
    17. Sayarshad, Hamid R. & Gao, H. Oliver, 2020. "Optimizing dynamic switching between fixed and flexible transit services with an idle-vehicle relocation strategy and reductions in emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 198-214.
    18. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    19. 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).
    20. Khaleghikarahrodi, Mehrsa & Macht, Gretchen A., 2023. "Patterns, no patterns, that is the question: Quantifying users’ electric vehicle charging," Transport Policy, Elsevier, vol. 141(C), pages 291-304.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:8:y:2020:i:3:p:453-:d:335208. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.