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Robust energy management in isolated microgrids with hydrogen storage and demand response

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  • Tostado-Véliz, Marcos
  • Rezaee Jordehi, Ahmad
  • Fernández-Lobato, Lázuli
  • Jurado, Francisco

Abstract

Hydrogen is called to be one of the main energy vectors in future energy systems, especially for energy storage, where this carrier presents some interesting features. Its application in microgrids might help to improve economic, environmental and reliability indicators, providing greater storage capacity than other technologies, like batteries. Following this idea, this paper develops a robust energy management methodology for isolated microgrids considering hydrogen storage and demand response initiatives. The new proposal is raised as a nested max-min optimization framework. To reduce the original problem to a tractable single-level one, a master-slave scheme is developed by which binary variables can be fixed and thus the inner problem can be reduced to its equivalent Karush-Kuhn-Tucker conditions. Then, the overall optimization paradigm is solved in an iterative fashion used the Constraint-and-Column Generation Algorithm. The resulting tool is applied to a benchmark isolated microgrid, thus validating it for industry applications. Moreover, different relevant results are analysed in-depth. Thus, the role of hydrogen storage and demand response initiatives is discussed, concluding that flexible demand has a more notable impact on monetary savings than hydrogen storage, reducing the total cost by 6 % with respect to the base case. Some intrinsic issues are also identified. For example, it is observed that flexible consumers are more frequently called when the hydrogen chain is enabled, which may provoke undesirable effects like response fatigue.

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  • Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Fernández-Lobato, Lázuli & Jurado, Francisco, 2023. "Robust energy management in isolated microgrids with hydrogen storage and demand response," Applied Energy, Elsevier, vol. 345(C).
    • Handle: RePEc:eee:appene:v:345:y:2023:i:c:s0306261923006839
    DOI: 10.1016/j.apenergy.2023.121319
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    References listed on IDEAS

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    Cited by:

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    2. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Mansouri, Seyed Amir & Zhou, Yuekuan & Jurado, Francisco, 2024. "A local electricity-hydrogen market model for industrial parks," Applied Energy, Elsevier, vol. 360(C).
    3. Yun Chen & Yunhao Zhao & Xinghao Zhang & Ying Wang & Rongyao Mi & Junxiao Song & Zhiguo Hao & Chuanbo Xu, 2025. "A Two-Stage Robust Optimization Strategy for Long-Term Energy Storage and Cascaded Utilization of Cold and Heat Energy in Peer-to-Peer Electricity Energy Trading," Energies, MDPI, vol. 18(2), pages 1-26, January.
    4. Turdybek, Balgynbek & Tostado-Véliz, Marcos & Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2024. "A local electricity market mechanism for flexibility provision in industrial parks involving Heterogenous flexible loads," Applied Energy, Elsevier, vol. 359(C).
    5. Huo, Shasha & Li, Qi & Pu, Yuchen & Xie, Shuqi & Chen, Weirong, 2024. "Low carbon dispatch method for hydrogen-containing integrated energy system considering seasonal carbon trading and energy sharing mechanism," Energy, Elsevier, vol. 308(C).
    6. Yin, Xin & Chen, Haoyong & Liang, Zipeng & Zhu, Yanjin, 2023. "A Flexibility-oriented robust transmission expansion planning approach under high renewable energy resource penetration," Applied Energy, Elsevier, vol. 351(C).
    7. Zhang, Rongquan & Bu, Siqi & Li, Gangqiang, 2024. "Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach," Applied Energy, Elsevier, vol. 367(C).
    8. Huy, Truong Hoang Bao & Duy, Nguyen Thanh Minh & Phu, Pham Van & Le, Tien-Dat & Park, Seongkeun & Kim, Daehee, 2024. "Robust real-time energy management for a hydrogen refueling station using generative adversarial imitation learning," Applied Energy, Elsevier, vol. 373(C).
    9. Xu, Xuesong & Xu, Kai & Zeng, Ziyang & Tang, Jiale & He, Yuanxing & Shi, Guangze & Zhang, Tao, 2024. "Collaborative optimization of multi-energy multi-microgrid system: A hierarchical trust-region multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 375(C).
    10. Tostado-Véliz, Marcos & Horrillo-Quintero, Pablo & García-Triviño, Pablo & Fernández-Ramírez, Luis M. & Jurado, Francisco, 2024. "Optimal sitting and sizing of hydrogen refilling stations in distribution networks under locational marginal prices," Applied Energy, Elsevier, vol. 374(C).

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