IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i24p16716-d1297518.html
   My bibliography  Save this article

Optimizing Electric Vehicle Charging Station Location on Highways: A Decision Model for Meeting Intercity Travel Demand

Author

Listed:
  • Ibrahim Tumay Gulbahar

    (Industrial Engineering Department, Abdullah Gul University, Sumer Campus, Barbaros Boulevard, Kocasinan, 38080 Kayseri, Türkiye)

  • Muhammed Sutcu

    (Engineering Management Department, College of Engineering & Architecture, Gulf University for Science & Technology, Mishref 32093, Kuwait)

  • Abedalmuhdi Almomany

    (Electrical & Computer Engineering Department, College of Engineering & Architecture, Gulf University for Science & Technology, Mishref 32093, Kuwait
    Department of Computer Engineering, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan)

  • Babul Salam KSM Kader Ibrahim

    (Electrical & Computer Engineering Department, College of Engineering & Architecture, Gulf University for Science & Technology, Mishref 32093, Kuwait)

Abstract

Electric vehicles have emerged as one of the top environmentally friendly alternatives to traditional internal combustion engine vehicles. The development of a comprehensive charging infrastructure, particularly determining the optimal locations for charging stations, is essential for the widespread adoption of electric vehicles. Most research on this subject focuses on popular areas such as city centers, shopping centers, and airports. With numerous charging stations available, these locations typically satisfy daily charging needs in routine life. However, the availability of charging stations for intercity travel, particularly on highways, remains insufficient. In this study, a decision model has been proposed to determine the optimal placement of electric vehicle charging stations along highways. To ensure a practical approach to the location of charging stations, the projected number of electric vehicles in Türkiye over the next few years is estimated by using a novel approach and the outcomes are used as crucial input in the facility location model. An optimization technique is employed to identify the ideal locations for charging stations on national highways to meet customer demand. The proposed model selects the most appropriate locations for charging stations and the required number of chargers to be installed, ensuring that electric vehicle drivers on highways do not encounter charging problems.

Suggested Citation

  • Ibrahim Tumay Gulbahar & Muhammed Sutcu & Abedalmuhdi Almomany & Babul Salam KSM Kader Ibrahim, 2023. "Optimizing Electric Vehicle Charging Station Location on Highways: A Decision Model for Meeting Intercity Travel Demand," Sustainability, MDPI, vol. 15(24), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16716-:d:1297518
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/24/16716/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/24/16716/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lim, Seow & Kuby, Michael, 2010. "Heuristic algorithms for siting alternative-fuel stations using the Flow-Refueling Location Model," European Journal of Operational Research, Elsevier, vol. 204(1), pages 51-61, July.
    2. Chung, Sung Hoon & Kwon, Changhyun, 2015. "Multi-period planning for electric car charging station locations: A case of Korean Expressways," European Journal of Operational Research, Elsevier, vol. 242(2), pages 677-687.
    3. Tehseen Mazhar & Rizwana Naz Asif & Muhammad Amir Malik & Muhammad Asgher Nadeem & Inayatul Haq & Muhammad Iqbal & Muhammad Kamran & Shahzad Ashraf, 2023. "Electric Vehicle Charging System in the Smart Grid Using Different Machine Learning Methods," Sustainability, MDPI, vol. 15(3), pages 1-26, February.
    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. Alexander Mutiso Mutua & Ruairí de Fréin, 2024. "Sustainable Mobility: Machine Learning-Driven Deployment of EV Charging Points in Dublin," Sustainability, MDPI, vol. 16(22), pages 1-37, November.

    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. Yang, Jun & Guo, Fang & Zhang, Min, 2017. "Optimal planning of swapping/charging station network with customer satisfaction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 174-197.
    2. Anjos, Miguel F. & Gendron, Bernard & Joyce-Moniz, Martim, 2020. "Increasing electric vehicle adoption through the optimal deployment of fast-charging stations for local and long-distance travel," European Journal of Operational Research, Elsevier, vol. 285(1), pages 263-278.
    3. Hosseini, Meysam & MirHassani, S.A., 2015. "Refueling-station location problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 101-116.
    4. Kuby, Michael & Capar, Ismail & Kim, Jong-Geun, 2017. "Efficient and equitable transnational infrastructure planning for natural gas trucking in the European Union," European Journal of Operational Research, Elsevier, vol. 257(3), pages 979-991.
    5. Yıldız, Barış & Arslan, Okan & Karaşan, Oya Ekin, 2016. "A branch and price approach for routing and refueling station location model," European Journal of Operational Research, Elsevier, vol. 248(3), pages 815-826.
    6. Zhi Wu & Yuxuan Zhuang & Suyang Zhou & Shuning Xu & Peng Yu & Jinqiao Du & Xiner Luo & Ghulam Abbas, 2020. "Bi-Level Planning of Multi-Functional Vehicle Charging Stations Considering Land Use Types," Energies, MDPI, vol. 13(5), pages 1-17, March.
    7. Böhle, Alexander, 2021. "Multi-Period Optimization of the Refuelling Infrastructure for Alternative Fuel Vehicles," Junior Management Science (JUMS), Junior Management Science e. V., vol. 6(4), pages 790-825.
    8. Tran, Trung Hieu & Nagy, Gábor & Nguyen, Thu Ba T. & Wassan, Niaz A., 2018. "An efficient heuristic algorithm for the alternative-fuel station location problem," European Journal of Operational Research, Elsevier, vol. 269(1), pages 159-170.
    9. Xu, Min & Meng, Qiang, 2020. "Optimal deployment of charging stations considering path deviation and nonlinear elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 120-142.
    10. Rabl, Regina & Reuter-Oppermann, Melanie & Jochem, Patrick E.P., 2024. "Charging infrastructure for electric vehicles in New Zealand," Transport Policy, Elsevier, vol. 148(C), pages 124-144.
    11. Faping Wang & Rui Chen & Lixin Miao & Peng Yang & Bin Ye, 2019. "Location Optimization of Electric Vehicle Mobile Charging Stations Considering Multi-Period Stochastic User Equilibrium," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    12. Zhao, Jiangjiang & Ma, Tieju, 2016. "Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations," European Journal of Operational Research, Elsevier, vol. 249(2), pages 706-716.
    13. Joonho Ko & Tae-Hyoung Tommy Gim & Randall Guensler, 2017. "Locating refuelling stations for alternative fuel vehicles: a review on models and applications," Transport Reviews, Taylor & Francis Journals, vol. 37(5), pages 551-570, September.
    14. Göpfert, Paul & Bock, Stefan, 2019. "A Branch&Cut approach to recharging and refueling infrastructure planning," European Journal of Operational Research, Elsevier, vol. 279(3), pages 808-823.
    15. Van Can Nguyen & Chi-Tai Wang & Ying-Jiun Hsieh, 2021. "Electrification of Highway Transportation with Solar and Wind Energy," Sustainability, MDPI, vol. 13(10), pages 1-28, May.
    16. Trung Hieu Tran & Thu Ba T. Nguyen, 2019. "Alternative-fuel station network design under impact of station failures," Annals of Operations Research, Springer, vol. 279(1), pages 151-186, August.
    17. Zhang, Anpeng & Kang, Jee Eun & Kwon, Changhyun, 2017. "Incorporating demand dynamics in multi-period capacitated fast-charging location planning for electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 5-29.
    18. Arslan, Okan & Karaşan, Oya Ekin, 2016. "A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 670-695.
    19. Marković, Nikola & Ryzhov, Ilya O. & Schonfeld, Paul, 2017. "Evasive flow capture: A multi-period stochastic facility location problem with independent demand," European Journal of Operational Research, Elsevier, vol. 257(2), pages 687-703.
    20. Chung, Byung Do & Park, Sungjae & Kwon, Changhyun, 2018. "Equitable distribution of recharging stations for electric vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 1-11.

    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:jsusta:v:15:y:2023:i:24:p:16716-:d:1297518. 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.