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Unlock the flexibility for cooperative operation of hydrogen providers under transportation delay

Author

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  • Yang, Xu
  • Yang, Bo
  • Wang, Zhaojian
  • Liu, Sicheng
  • Guan, Xinping

Abstract

Hydrogen provides a pathway to the clean transition of the future energy mix, rendering hydrogen energy service providers (HESPs) an important role in hydrogen supply. Additionally, collaborative operation through vehicle-based hydrogen transportation exhibits great potential for mitigating source–load fluctuations of HESPs. However, current collaborations on hydrogen transportation primarily focus on route selection while neglecting delay risks, which may precipitate abrupt energy deficits during the scheduling of energy receivers. This work proposes a multi-HESP cooperative game that considers a deadline assignment mechanism to ensure the robustness of hydrogen delivery while fully unlocking the scheduling flexibility supported by the road network. Considering the transportation-time uncertainty, the distributionally robust joint chance constraint (DRJCC) is introduced to model delay uncertainties effectively and improve hydrogen delivery reliability. A customized approximation method is proposed to reformulate the DRJCC model into a tractable approximation with low conservatism while enhancing flexibility in decision-making under transportation delay uncertainty. Case studies verify that the proposed framework can improve the flexibility and enthusiasm of multi-HESP cooperation under the electricity–hydrogen transmission network.

Suggested Citation

  • Yang, Xu & Yang, Bo & Wang, Zhaojian & Liu, Sicheng & Guan, Xinping, 2025. "Unlock the flexibility for cooperative operation of hydrogen providers under transportation delay," Applied Energy, Elsevier, vol. 394(C).
  • Handle: RePEc:eee:appene:v:394:y:2025:i:c:s0306261925008827
    DOI: 10.1016/j.apenergy.2025.126152
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    References listed on IDEAS

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    1. Alizadeh, Ali & Esfahani, Moein & Dinar, Farid & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud & Busvelle, Eric, 2024. "A cooperative transactive multi-carrier energy control mechanism with P2P energy + reserve trading using Nash bargaining game theory under renewables uncertainty," Applied Energy, Elsevier, vol. 353(PB).
    2. Souto, Laiz & Parisio, Alessandra & Taylor, Philip C., 2024. "MPC-based framework incorporating pre-disaster and post-disaster actions and transportation network constraints for weather-resilient power distribution networks," Applied Energy, Elsevier, vol. 362(C).
    3. Siqin, Zhuoya & Niu, DongXiao & Li, MingYu & Gao, Tian & Lu, Yifan & Xu, Xiaomin, 2022. "Distributionally robust dispatching of multi-community integrated energy system considering energy sharing and profit allocation," Applied Energy, Elsevier, vol. 321(C).
    4. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    5. Maaike Hoogeboom & Yossiri Adulyasak & Wout Dullaert & Patrick Jaillet, 2021. "The Robust Vehicle Routing Problem with Time Window Assignments," Transportation Science, INFORMS, vol. 55(2), pages 395-413, March.
    6. Wang, Jiawei & Wang, Yi & Qiu, Dawei & Su, Hanguang & Strbac, Goran & Gao, Zhiwei, 2025. "Resilient energy management of a multi-energy building under low-temperature district heating: A deep reinforcement learning approach," Applied Energy, Elsevier, vol. 378(PA).
    7. Diaz-Cachinero, Pablo & Muñoz-Hernandez, Jose Ignacio & Contreras, Javier, 2021. "Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management," Applied Energy, Elsevier, vol. 304(C).
    Full references (including those not matched with items on IDEAS)

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