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Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode of hydrogen energy via FV-IGDT approach

Author

Listed:
  • Tan, Hong
  • Wang, Yuwei
  • Wang, Qiujie
  • Lin, Zhenjia
  • Mohamed, Mohamed A.

Abstract

Hydrogen energy has the advantages of being clean and carbon-free, convenient storage, and easy conversion to electrical energy. The use of renewable energy electrolysis for hydrogen production is an important solution to promote clean energy utilization and decarburization in the power and transportation industries. However, hydrogen has a low hydrogen storage density and is prone to explosion. The high cost and risk of hydrogen transportation pose challenges to the promotion and utilization of hydrogen. To address these difficulties, this paper proposes a day-ahead dispatch of electricity-hydrogen systems (EHS) under the solid-state transportation mode of hydrogen energy. Firstly, based on the Van't Hoff equation, the relationship between gas pressure and the reaction temperature is established during the gas-solid conversion process, and a hydrogen energy solid-state transport model based on a magnesium-based hydrogen transport vehicle (MHTV) is proposed. Secondly, a renewable energy uncertainty set is established based on the information-gap decision theory (IGDT) envelope constraint for addressing the uncertainty of renewable energy and a day-ahead bi-level dispatch model of the EHS is constructed based on the solid-state transportation mode of hydrogen energy. Finally, the IGDT approach considering fuzzy variables (FV-IGDT) is presented by using a fuzzy variable membership function, and the proposed bi-level model is transformed into a single-level model for a solution based on this approach. The effectiveness of the proposed model and solution method is verified through simulation on an EHS consisting of a modified IEEE-118 power system, 2 hydrogen production stations (HPS), and 10 hydrogen refueling stations (HRS).

Suggested Citation

  • Tan, Hong & Wang, Yuwei & Wang, Qiujie & Lin, Zhenjia & Mohamed, Mohamed A., 2024. "Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode of hydrogen energy via FV-IGDT approach," Energy, Elsevier, vol. 300(C).
    • Handle: RePEc:eee:energy:v:300:y:2024:i:c:s0360544224008855
    DOI: 10.1016/j.energy.2024.131113
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    References listed on IDEAS

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    1. Boroumandfar, Gholamreza & Khajehzadeh, Alimorad & Eslami, Mahdiyeh & Syah, Rahmad B.Y., 2023. "Information gap decision theory with risk aversion strategy for robust planning of hybrid photovoltaic/wind/battery storage system in distribution networks considering uncertainty," Energy, Elsevier, vol. 278(PA).
    2. Liu, Zhouding & Nazari-Heris, Morteza, 2023. "Optimal bidding strategy of multi-carrier systems in electricity markets using information gap decision theory," Energy, Elsevier, vol. 280(C).
    3. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    4. Ding, Jianyong & Gao, Ciwei & Song, Meng & Yan, Xingyu & Chen, Tao, 2022. "Bi-level optimal scheduling of virtual energy station based on equal exergy replacement mechanism," Applied Energy, Elsevier, vol. 327(C).
    5. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).
    6. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response," Energy, Elsevier, vol. 239(PA).
    7. Li, Qi & Xiao, Xukang & Pu, Yuchen & Luo, Shuyu & Liu, Hong & Chen, Weirong, 2023. "Hierarchical optimal scheduling method for regional integrated energy systems considering electricity-hydrogen shared energy," Applied Energy, Elsevier, vol. 349(C).
    8. Izadi, Mehdi & Hossein Hosseinian, Seyed & Dehghan, Shahab & Fakharian, Ahmad & Amjady, Nima, 2023. "Resiliency-Oriented operation of distribution networks under unexpected wildfires using Multi-Horizon Information-Gap decision theory," Applied Energy, Elsevier, vol. 334(C).
    Full references (including those not matched with items on IDEAS)

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