IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i7p3210-d1627964.html
   My bibliography  Save this article

A Bi-Level Optimization Model for Hydrogen Station Location Considering Hydrogen Cost and Range Anxiety

Author

Listed:
  • Lisha Jiang

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Liang Wang

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

Abstract

In pursuit of sustainable development, worldwide adoption of hydrogen fuel cell vehicles (HFCVs) is growing to cut carbon emissions in the transportation sector. The construction of hydrogen refueling stations (HRSs) is the key to popularizing HFCVs. The popularity of HRSs is hindered by cost, site selection, and user expectations. Selecting mature gas stations with large passenger flow to expand HRSs can improve the accuracy of the hydrogen refueling network. Reducing the range anxiety of HFCV users to improve the path coverage of HFCVs is a favorable way to expand the hydrogen vehicle industry chain. Therefore, this study proposes a bi-level programming model, which considers hydrogen source (HS), hydrogen delivery mode (HDM), initial remaining range, range anxiety, and other factors. The upper-level model is designed to optimize economic costs, including the total chain cost of the HRS. The lower level aims to optimize the range anxiety of HFCV users and more accurately reflect their autonomy by controlling the maximum remaining range of the vehicle. Finally, the expressway in the Liaoning Province of China is taken as an example to verify that the optimization model had the advantages of low hydrogen cost and minimal range anxiety. The cost analysis of several HSs and HDMs was discussed from the perspective of the best site selected, and it was found that the Anshan HS using coal to produce hydrogen and the long tube trailer can provide lower hydrogen cost for the HRS. This method is generalizable to other regions or all types of HFCVs.

Suggested Citation

  • Lisha Jiang & Liang Wang, 2025. "A Bi-Level Optimization Model for Hydrogen Station Location Considering Hydrogen Cost and Range Anxiety," Sustainability, MDPI, vol. 17(7), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3210-:d:1627964
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/7/3210/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/7/3210/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hyunjoon Kim & Byung-In Kim & Daniel Thiel, 2021. "Exact algorithms for incremental deployment of hydrogen refuelling stations," Post-Print hal-03284509, HAL.
    2. Sayarshad, Hamid R., 2025. "Coordinated routing, charging, and power grid for electric and hydrogen vehicles with renewable energy integration," Renewable Energy, Elsevier, vol. 243(C).
    3. Yong Lei & Jun Zhang & Zhihua Ren, 2023. "A Study on Bicycle-Sharing Dispatching Station Site Selection and Planning Based on Multivariate Data," Sustainability, MDPI, vol. 15(17), pages 1-25, August.
    4. Rui Chen & Xinglu Liu & Lixin Miao & Peng Yang, 2020. "Electric Vehicle Tour Planning Considering Range Anxiety," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    5. Guo, Fang & Yang, Jun & Lu, Jianyi, 2018. "The battery charging station location problem: Impact of users’ range anxiety and distance convenience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 1-18.
    6. Yan Zhou & Xunpeng Qin & Chenglong Li & Jun Zhou, 2022. "An Intelligent Site Selection Model for Hydrogen Refueling Stations Based on Fuzzy Comprehensive Evaluation and Artificial Neural Network—A Case Study of Shanghai," Energies, MDPI, vol. 15(3), pages 1-23, February.
    7. Nithin Isaac & Akshay K. Saha, 2023. "A Review of the Optimization Strategies and Methods Used to Locate Hydrogen Fuel Refueling Stations," Energies, MDPI, vol. 16(5), pages 1-16, February.
    8. Kuby, Michael & Lim, Seow, 2005. "The flow-refueling location problem for alternative-fuel vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 39(2), pages 125-145, June.
    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. Tran, Cong Quoc & Keyvan-Ekbatani, Mehdi & Ngoduy, Dong & Watling, David, 2021. "Stochasticity and environmental cost inclusion for electric vehicles fast-charging facility deployment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    2. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    3. Ouyang, Xu & Xu, Min, 2022. "Promoting green transportation under the belt and Road Initiative: Locating charging stations considering electric vehicle users’ travel behavior," Transport Policy, Elsevier, vol. 116(C), pages 58-80.
    4. Long Li & Shuqi Wang & Shengxi Zhang & Ding Liu & Shengbin Ma, 2023. "The Hydrogen Energy Infrastructure Location Selection Model: A Hybrid Fuzzy Decision-Making Approach," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    5. Huasheng Liu & Yu Li & Chongyu Zhang & Jin Li & Xiaowen Li & Yuqi Zhao, 2022. "Electric Vehicle Charging Station Location Model considering Charging Choice Behavior and Range Anxiety," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    6. Mubarak, Mamdouh & Üster, Halit & Abdelghany, Khaled & Khodayar, Mohammad, 2021. "Strategic network design and analysis for in-motion wireless charging of electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Wu, Jiabin & Li, Qihang & Bie, Yiming & Zhou, Wei, 2024. "Location-routing optimization problem for electric vehicle charging stations in an uncertain transportation network: An adaptive co-evolutionary clustering algorithm," Energy, Elsevier, vol. 304(C).
    8. 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.
    9. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    10. Jalili Marand, Ata & Hoseinpour, Pooya, 2024. "A congested facility location problem with strategic customers," European Journal of Operational Research, Elsevier, vol. 318(2), pages 442-456.
    11. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    12. Wei, Ran & Liu, Xiaoyue & Ou, Yi & Kiavash Fayyaz, S., 2018. "Optimizing the spatio-temporal deployment of battery electric bus system," Journal of Transport Geography, Elsevier, vol. 68(C), pages 160-168.
    13. 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.
    14. Roel M. Post & Paul Buijs & Michiel A. J. uit het Broek & Jose A. Lopez Alvarez & Nick B. Szirbik & Iris F. A. Vis, 2018. "A solution approach for deriving alternative fuel station infrastructure requirements," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 592-607, September.
    15. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    16. Schulz, Arne & Boysen, Nils & Briskorn, Dirk, 2024. "Centrally-chosen versus user-selected swaps: How the selection of swapping stations impacts standby battery inventories," European Journal of Operational Research, Elsevier, vol. 319(3), pages 726-738.
    17. 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.
    18. Hong Gao & Kai Liu & Xinchao Peng & Cheng Li, 2020. "Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands," Energies, MDPI, vol. 13(8), pages 1-16, April.
    19. Ke, Jintao & Cen, Xuekai & Yang, Hai & Chen, Xiqun & Ye, Jieping, 2019. "Modelling drivers’ working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 160-180.
    20. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(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:gam:jsusta:v:17:y:2025:i:7:p:3210-:d:1627964. 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.