IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v300y2024ics0360544224008855.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224008855
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.131113?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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).
    3. 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).
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    8. 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).
    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. Wang, Yongli & Guo, Lu & Wang, Yanan & Zhang, Yunfei & Zhang, Siwen & Liu, Zeqiang & Xing, Juntai & Liu, Ximei, 2024. "Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment," Energy, Elsevier, vol. 298(C).
    2. Han, Fengwu & Zhao, Yunlong & Zeng, Jianfeng & Zhang, Shengnan & Wu, Tianyu, 2024. "Uncertain parameters adjustable two-stage robust optimization of a rural housing integrated energy system considering biomass on-site utilization," Energy, Elsevier, vol. 296(C).
    3. Gao, Hongjun & Wang, Wenqin & He, Shuaijia & Tang, Zhiyuan & Liu, Junyong, 2024. "Low-carbon economic scheduling for AIES considering flexible load coordination and multiple uncertainties," Renewable Energy, Elsevier, vol. 228(C).
    4. 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).
    5. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    6. Qinqin Xia & Yao Zou & Qianggang Wang, 2024. "Optimal Capacity Planning of Green Electricity-Based Industrial Electricity-Hydrogen Multi-Energy System Considering Variable Unit Cost Sequence," Sustainability, MDPI, vol. 16(9), pages 1-20, April.
    7. Jia, Jiandong & Li, Haiqiao & Wu, Di & Guo, Jiacheng & Jiang, Leilei & Fan, Zeming, 2024. "Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing," Renewable Energy, Elsevier, vol. 225(C).
    8. Chen, Lei & Jiang, Yuqi & Zheng, Shencong & Deng, Xinyi & Chen, Hongkun & Islam, Md. Rabiul, 2023. "A two-layer optimal configuration approach of energy storage systems for resilience enhancement of active distribution networks," Applied Energy, Elsevier, vol. 350(C).
    9. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    10. Xiaozhi Gao & Han Xiao & Shiwei Xu & Hsiung-Cheng Lin & Pengyu Chang, 2024. "What Is the Optimal Solution for Scheduling Multiple Energy Systems? Overview and Analysis of Integrated Energy Co-Dispatch Models," Energies, MDPI, vol. 17(18), pages 1-25, September.
    11. 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).
    12. Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Xiang, Zhi-Bo & Zhang, Sen, 2024. "Economic and low-carbon planning for interconnected integrated energy systems considering emerging technologies and future development trends," Energy, Elsevier, vol. 302(C).
    13. Yang, Dongfeng & Xu, Yang & Liu, Xiaojun & Jiang, Chao & Nie, Fanjie & Ran, Zixu, 2022. "Economic-emission dispatch problem in integrated electricity and heat system considering multi-energy demand response and carbon capture Technologies," Energy, Elsevier, vol. 253(C).
    14. Ting Chen & Lei Gan & Sheeraz Iqbal & Marek Jasiński & Mohammed A. El-Meligy & Mohamed Sharaf & Samia G. Ali, 2023. "A Novel Evolving Framework for Energy Management in Combined Heat and Electricity Systems with Demand Response Programs," Sustainability, MDPI, vol. 15(13), pages 1-23, July.
    15. Cui, Shiting & Gao, Yao & Zhu, Ruijin, 2024. "A new integrated energy system cluster energy sharing framework adapted to high altitude areas," Applied Energy, Elsevier, vol. 366(C).
    16. Zhang, Y.Q. & Chen, J.J. & Wang, Y.X. & Feng, L., 2024. "Enhancing resilience of agricultural microgrid through electricity–heat–water based multi-energy hub considering irradiation intensity uncertainty," Renewable Energy, Elsevier, vol. 220(C).
    17. Kuoyi Lin & Bin Li, 2024. "A Cloud- and Game Model-Based Approach to Project Evaluations of Sustainable Power Supply Investments," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
    18. Ahmed A. Alguhi & Majed A. Alotaibi & Essam A. Al-Ammar, 2023. "Probabilistic Planning for an Energy Storage System Considering the Uncertainties in Smart Distribution Networks," Sustainability, MDPI, vol. 16(1), pages 1-23, December.
    19. Jian Chen & Tao Jin & Mohamed A. Mohamed & Andres Annuk & Udaya Dampage, 2022. "Investigating the Impact of Wind Power Integration on Damping Characteristics of Low Frequency Oscillations in Power Systems," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
    20. Yuan, Yi & Ding, Tao & Chang, Xinyue & Jia, Wenhao & Xue, Yixun, 2024. "A distributed multi-objective optimization method for scheduling of integrated electricity and hydrogen systems," Applied Energy, Elsevier, vol. 355(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:eee:energy:v:300:y:2024:i:c:s0360544224008855. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.