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Performance Evaluation of a Hydrogen-Based Clean Energy Hub with Electrolyzers as a Self-Regulating Demand Response Management Mechanism

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  • Weiliang Wang

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Dan Wang

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Hongjie Jia

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Guixiong He

    (China Electric Power Research Institute, Haidian District, Beijing 100192, China)

  • Qing’e Hu

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Pang-Chieh Sui

    (School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Menghua Fan

    (State Grid Energy Research Institute, Changping District, Beijing 102249, China)

Abstract

Energy management of hybrid resources has become a critical issue in integrated energy system analysis. In this study, as a self-regulating demand response (DR) management mechanism, deferrable electrolyzers are used as a main controlled resource in a hydrogen-based clean energy hub (CEH), which includes a traditional generation plant (TGP), a low-carbon generation plant (LGP), and wind energy. Based on the hysteresis control model for aggregated electrolyzers, a comfort-constrained optimal energy state regulation (OESR) control strategy is implemented to model the deregulation feature of aggregated electrolyzers. The electrolyzers’ population can be integrated as a controlled efficient power plant (EPP) to provide the virtual spinning reserve for CEH. As a flexible and self-regulating participant, the electrolyzer-based EPP is integrated into the hybrid resource constrained optimization model; this reduces the total cost of CEH and carbon emissions and improves the integration of wind energy. Combined with TGP, LGP, and wind energy, the simulation results show that the deployment of aggregated electrolyzers on both the supply and demand sides of the CEH contributes to significant amounts of low-carbon hydrogen. The simulation also illustrates that the DR control strategy has a positive effect on active power and reserve re-dispatch.

Suggested Citation

  • Weiliang Wang & Dan Wang & Hongjie Jia & Guixiong He & Qing’e Hu & Pang-Chieh Sui & Menghua Fan, 2017. "Performance Evaluation of a Hydrogen-Based Clean Energy Hub with Electrolyzers as a Self-Regulating Demand Response Management Mechanism," Energies, MDPI, vol. 10(8), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1211-:d:108297
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    Cited by:

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    2. Tiejiang Yuan & Qingxi Duan & Xiangping Chen & Xufeng Yuan & Wenping Cao & Juan Hu & Quanmin Zhu, 2017. "Coordinated Control of a Wind-Methanol-Fuel Cell System with Hydrogen Storage," Energies, MDPI, vol. 10(12), pages 1-21, December.
    3. Weiliang Wang & Dan Wang & Liu Liu & Hongjie Jia & Yunqiang Zhi & Zhengji Meng & Wei Du, 2019. "Research on Modeling and Hierarchical Scheduling of a Generalized Multi-Source Energy Storage System in an Integrated Energy Distribution System," Energies, MDPI, vol. 12(2), pages 1-28, January.
    4. He, Gui-Xiong & Yan, Hua-guang & Chen, Lei & Tao, Wen-Quan, 2020. "Economic dispatch analysis of regional Electricity–Gas system integrated with distributed gas injection," Energy, Elsevier, vol. 201(C).
    5. Yongjie Zhong & Dongliang Xie & Suwei Zhai & Yonghui Sun, 2018. "Day-Ahead Hierarchical Steady State Optimal Operation for Integrated Energy System Based on Energy Hub," Energies, MDPI, vol. 11(10), pages 1-18, October.
    6. Yao Yao & Peichao Zhang & Sijie Chen, 2019. "Aggregating Large-Scale Generalized Energy Storages to Participate in the Energy and Regulation Market," Energies, MDPI, vol. 12(6), pages 1-22, March.

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