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Multi-stage stochastic programming based offering strategy for hydrogen fueling station in joint energy, reserve markets

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  • Wu, Xiong
  • Zhao, Wencheng
  • Li, Haoyu
  • Liu, Bingwen
  • Zhang, Ziyu
  • Wang, Xiuli

Abstract

Hydrogen fueling stations (HFSs) with onsite hydrogen production systems, which are usually composed of electrolyzers, hydrogen storage tanks and fuel cells, not only supply hydrogen for hydrogen-powered vehicles but also serve as a dispatchable technology that can bid in electricity markets. Except participating in energy market, joining in reserve market can compensate the cost in energy market and increase the total revenue of HFS. This paper proposes a multi-stage stochastic programming model to find the optimal offering strategy of the HFS in energy, reserve markets taking into account a series of uncertainties: day-ahead price, secondary reserve price, system imbalance price and hydrogen demand. Nonanticipativity constraints are employed to guarantee the decisions are made according to the realized uncertainty information up to the present stage. Compared with traditional stochastic programming model, the proposed model adequately considers the sequential bidding decisions with the gradual revealing of the uncertainty over time. Numerical experiments based on one case study indicate that the participation of reserve market greatly increase the revenue of HFS. In addition, the proposed multi-stage stochastic programming model is effective in characterizing the sequential decision.

Suggested Citation

  • Wu, Xiong & Zhao, Wencheng & Li, Haoyu & Liu, Bingwen & Zhang, Ziyu & Wang, Xiuli, 2021. "Multi-stage stochastic programming based offering strategy for hydrogen fueling station in joint energy, reserve markets," Renewable Energy, Elsevier, vol. 180(C), pages 605-615.
    • Handle: RePEc:eee:renene:v:180:y:2021:i:c:p:605-615
    DOI: 10.1016/j.renene.2021.08.076
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    References listed on IDEAS

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    Cited by:

    1. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Tsaousoglou, Georgios & Leonowicz, Zbigniew, 2023. "Integrating hydrogen technology into active distribution networks: The case of private hydrogen refueling stations," Energy, Elsevier, vol. 278(PB).
    2. Fragiacomo, Petronilla & Martorelli, Michele & Genovese, Matteo & Piraino, Francesco & Corigliano, Orlando, 2024. "Thermodynamic modelling, testing and sensitive analysis of a directly pressurized hydrogen refuelling process with a compressor," Renewable Energy, Elsevier, vol. 226(C).
    3. Belessiotis, George V. & Kontos, Athanassios G., 2022. "Plasmonic silver (Ag)-based photocatalysts for H2 production and CO2 conversion: Review, analysis and perspectives," Renewable Energy, Elsevier, vol. 195(C), pages 497-515.
    4. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Pourakbari-Kasmaei, Mahdi & Lehtonen, Matti & Leonowicz, Zbigniew, 2023. "Participation of hydrogen-rich energy hubs in day-ahead and regulation markets: A hybrid stochastic-robust model," Applied Energy, Elsevier, vol. 339(C).
    5. Jixian Cui & Chenghao Liao & Ling Ji & Yulei Xie & Yangping Yu & Jianguang Yin, 2021. "A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    6. Qi, Yunying & Xu, Xiao & Liu, Youbo & Pan, Li & Liu, Junyong & Hu, Weihao, 2024. "Intelligent energy management for an on-grid hydrogen refueling station based on dueling double deep Q network algorithm with NoisyNet," Renewable Energy, Elsevier, vol. 222(C).
    7. Zhu, Junpeng & Meng, Dexin & Dong, Xiaofeng & Fu, Zhixin & Yuan, Yue, 2023. "An integrated electricity - hydrogen market design for renewable-rich energy system considering mobile hydrogen storage," Renewable Energy, Elsevier, vol. 202(C), pages 961-972.

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