IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2022i1p347-d1014992.html
   My bibliography  Save this article

Optimized Operation Plan for Hydrogen Refueling Station with On-Site Electrolytic Production

Author

Listed:
  • Di Lu

    (Powerchina Huadong Engineering Corporation, Hangzhou 311122, China)

  • Jing Sun

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yonggang Peng

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Xiaofeng Chen

    (Powerchina Huadong Engineering Corporation, Hangzhou 311122, China)

Abstract

The cost reduction of hydrogen refueling stations (HRSs) is very important for the popularization of hydrogen vehicles. This paper proposes an optimized operation algorithm based on hydrogen energy demand estimation for on-site hydrogen refueling stations. Firstly, the user’s hydrogen demand was estimated based on the simulation of their hydrogenation behavior. Secondly, mixed integer linear programming method was used to optimize the operation of the hydrogen refueling station to minimize the unit hydrogen energy cost by using the peak–valley difference of the electricity price. We then used three typical scenario cases to evaluate the optimized operation method. The results show that the optimized operation method proposed in this paper can effectively reduce the rated configuration of electrolyzer and storage tank for HRS and can significantly reduce the unit hydrogen energy cost considering the construction cost compared with the traditional method. Therefore, the optimization operation method of a local hydrogen production and hydrogen refueling station proposed in this paper can reduce the cost of a hydrogen refueling station and accelerate the popularization of hydrogen energy vehicles. Finally, the scope of application of the proposed optimization method and the influence of the variation of the electricity price curve and the unit cost of the electrolyzer are discussed.

Suggested Citation

  • Di Lu & Jing Sun & Yonggang Peng & Xiaofeng Chen, 2022. "Optimized Operation Plan for Hydrogen Refueling Station with On-Site Electrolytic Production," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:347-:d:1014992
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/347/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/1/347/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jing Sun & Yonggang Peng & Di Lu & Xiaofeng Chen & Weifeng Xu & Liguo Weng & Jun Wu, 2022. "Optimized Configuration and Operating Plan for Hydrogen Refueling Station with On-Site Electrolytic Production," Energies, MDPI, vol. 15(7), pages 1-20, 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. Mengxuan Yan & Shen-En Peng & Chun Sing Lai & Si-Zhe Chen & Jing Liu & Junhua Xu & Fangyuan Xu & Loi Lei Lai & Gang Chen, 2023. "Two-Layer Optimization Planning Model for Integrated Energy Systems in Hydrogen Refueling Original Station," Sustainability, MDPI, vol. 15(10), pages 1-16, May.

    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. Sofia Polymeni & Vasileios Pitsiavas & Georgios Spanos & Quentin Matthewson & Antonios Lalas & Konstantinos Votis & Dimitrios Tzovaras, 2024. "Toward Sustainable Mobility: AI-Enabled Automated Refueling for Fuel Cell Electric Vehicles," Energies, MDPI, vol. 17(17), pages 1-17, August.
    2. Mengxuan Yan & Shen-En Peng & Chun Sing Lai & Si-Zhe Chen & Jing Liu & Junhua Xu & Fangyuan Xu & Loi Lei Lai & Gang Chen, 2023. "Two-Layer Optimization Planning Model for Integrated Energy Systems in Hydrogen Refueling Original Station," Sustainability, MDPI, vol. 15(10), pages 1-16, May.

    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:2022:i:1:p:347-:d:1014992. 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.