IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v127y2024ics0305048324000720.html
   My bibliography  Save this article

Maximizing the number of satisfied charging demands of electric vehicles on identical chargers

Author

Listed:
  • Zaidi, I.
  • Oulamara, A.
  • Idoumghar, L.
  • Basset, M.

Abstract

This paper addresses the electric vehicle charging scheduling problem in a charging station with a limited overall power capacity and a limited number of chargers. Electric vehicle drivers submit their charging demands. Given the limited resources, these charging demands are either accepted or rejected and accepted demands must be satisfied. The objective of the scheduler is to maximize the number of satisfied demands. The paper provides theoretical results on the scheduling problem and proposes different linear programming models and heuristic methods to provide good-quality solutions in a shorter computational time.

Suggested Citation

  • Zaidi, I. & Oulamara, A. & Idoumghar, L. & Basset, M., 2024. "Maximizing the number of satisfied charging demands of electric vehicles on identical chargers," Omega, Elsevier, vol. 127(C).
    • Handle: RePEc:eee:jomega:v:127:y:2024:i:c:s0305048324000720
    DOI: 10.1016/j.omega.2024.103106
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048324000720
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2024.103106?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiaoli Sun & Zhengguo Li & Xiaolin Wang & Chengjiang Li, 2019. "Technology Development of Electric Vehicles: A Review," Energies, MDPI, vol. 13(1), pages 1-29, December.
    2. Xu, Min & Meng, Qiang, 2019. "Fleet sizing for one-way electric carsharing services considering dynamic vehicle relocation and nonlinear charging profile," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 23-49.
    3. Yu, Guodong & Liu, Aijun & Zhang, Jianghua & Sun, Huiping, 2021. "Optimal operations planning of electric autonomous vehicles via asynchronous learning in ride-hailing systems," Omega, Elsevier, vol. 103(C).
    4. Kim, Jerim & Son, Sung-Yong & Lee, Jung-Min & Ha, Hyung-Tae, 2017. "Scheduling and performance analysis under a stochastic model for electric vehicle charging stations," Omega, Elsevier, vol. 66(PB), pages 278-289.
    5. Sun, Hao & Yang, Jun & Yang, Chao, 2019. "A robust optimization approach to multi-interval location-inventory and recharging planning for electric vehicles," Omega, Elsevier, vol. 86(C), pages 59-75.
    6. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    7. Michael von Bonin & Elias Dörre & Hadi Al-Khzouz & Martin Braun & Xian Zhou, 2022. "Impact of Dynamic Electricity Tariff and Home PV System Incentives on Electric Vehicle Charging Behavior: Study on Potential Grid Implications and Economic Effects for Households," Energies, MDPI, vol. 15(3), pages 1-28, February.
    8. Qin, Hu & Su, E. & Wang, Yilun & Li, Jiliu, 2022. "Branch-and-price-and-cut for the electric vehicle relocation problem in one-way carsharing systems," Omega, Elsevier, vol. 109(C).
    9. Umetani, Shunji & Fukushima, Yuta & Morita, Hiroshi, 2017. "A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system," Omega, Elsevier, vol. 67(C), pages 115-122.
    10. Wu, Ji & Su, Hao & Meng, Jinhao & Lin, Mingqiang, 2023. "Electric vehicle charging scheduling considering infrastructure constraints," Energy, Elsevier, vol. 278(PA).
    Full references (including those not matched with items on IDEAS)

    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. Alp, Osman & Tan, Tarkan & Udenio, Maximiliano, 2022. "Transitioning to sustainable freight transportation by integrating fleet replacement and charging infrastructure decisions," Omega, Elsevier, vol. 109(C).
    2. Jiao, Zihao & Ran, Lun & Zhang, Yanzi & Ren, Yaping, 2021. "Robust vehicle-to-grid power dispatching operations amid sociotechnical complexities," Applied Energy, Elsevier, vol. 281(C).
    3. Gambella, Claudio & Malaguti, Enrico & Masini, Filippo & Vigo, Daniele, 2018. "Optimizing relocation operations in electric car-sharing," Omega, Elsevier, vol. 81(C), pages 234-245.
    4. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    5. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    6. Hu, Xinru & Zhou, Shuiyin & Luo, Xiaomeng & Li, Jianbin & Zhang, Chi, 2024. "Optimal pricing strategy of an on-demand platform with cross-regional passengers," Omega, Elsevier, vol. 122(C).
    7. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.
    8. Junchi Ma & Yuan Zhang & Zongtao Duan & Lei Tang, 2023. "PROLIFIC: Deep Reinforcement Learning for Efficient EV Fleet Scheduling and Charging," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    9. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    10. Krystian Pietrzak & Oliwia Pietrzak, 2022. "Tram System as a Challenge for Smart and Sustainable Urban Public Transport: Effects of Applying Bi-Directional Trams," Energies, MDPI, vol. 15(15), pages 1-29, August.
    11. Ausseil, Rosemonde & Ulmer, Marlin W. & Pazour, Jennifer A., 2024. "Online acceptance probability approximation in peer-to-peer transportation," Omega, Elsevier, vol. 123(C).
    12. Zheng, Hankun & Sun, Huijun & Kang, Liujiang & Dai, Peiling & Wu, Jianjun, 2023. "Multi-route coordination for bus systems in response to road disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    13. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
    14. Sistig, Hubert Maximilian & Sauer, Dirk Uwe, 2023. "Metaheuristic for the integrated electric vehicle and crew scheduling problem," Applied Energy, Elsevier, vol. 339(C).
    15. Qingyu Luo & Zhihao Ye & Hongfei Jia, 2023. "A Charging Planning Method for Shared Electric Vehicles with the Collaboration of Mobile and Fixed Facilities," Sustainability, MDPI, vol. 15(22), pages 1-16, November.
    16. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Dorrell, David G. & Li, Xiaohui & Zhan, Weipeng, 2023. "Operation optimization approaches of electric vehicle battery swapping and charging station: A literature review," Energy, Elsevier, vol. 263(PE).
    17. Zhou, Yu & Wang, Hua & Wang, Yun & Yu, Bin & Tang, Tianpei, 2024. "Charging facility planning and scheduling problems for battery electric bus systems: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    18. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2020. "Stochastic energy management of responsive plug-in electric vehicles characterizing parking lot aggregators," Applied Energy, Elsevier, vol. 279(C).
    19. Wang, Mengtong & Miao, Lixin & Zhang, Canrong, 2021. "A branch-and-price algorithm for a green location routing problem with multi-type charging infrastructure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    20. Zhang, Si & Sun, Huijun & Liu, Yang & Lv, Ying & Wu, Jianjun & Feng, Xiaoyan, 2024. "Carsharing equitable relocation problem: A two-stage stochastic programming approach with learning-embedded endogenous uncertainty in demand," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).

    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:eee:jomega:v:127:y:2024:i:c:s0305048324000720. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.