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Optimization Scheduling of Integrated Park Energy Systems with Hydrogen Energy Storage Based on Hybrid Copula

Author

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  • Wu Zhongqun

    (School of Economics and Management, North China Electric Power University, Changping, Beijing 102206, China)

  • Liang Jian

    (School of Economics and Management, North China Electric Power University, Changping, Beijing 102206, China)

Abstract

In order to improve the energy utilization efficiency of the comprehensive energy park and the proportion of renewable energy grid connection, this paper first proposes to use the hybrid copula theory to construct a wind power and photovoltaics joint output model, reducing the uncertainty of wind power output and photovoltaic output. Secondly, this paper proposes the participation of hydrogen energy storage equipment in the power system scheduling of integrated energy parks. Hydrogen energy storage, as a clean, efficient, and sustainable carbon-free energy storage technology, can be used to mitigate the impact of wind power and photovoltaics output on the power grid. Finally, this paper proposes to construct an optimized scheduling model that considers economic optimization and proves the economic feasibility of the model through case analysis. The calculation results show that the comprehensive energy operating cost has been reduced by 14.15%, the proportion of thermal power output has been reduced by 32.54%, and the proportion of wind solar combined output has increased by 30.9%.

Suggested Citation

  • Wu Zhongqun & Liang Jian, 2025. "Optimization Scheduling of Integrated Park Energy Systems with Hydrogen Energy Storage Based on Hybrid Copula," Decision Analysis, INFORMS, vol. 22(3), pages 206-226, September.
    • Handle: RePEc:inm:ordeca:v:22:y:2025:i:3:p:206-226
    DOI: 10.1287/deca.2024.0261
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    References listed on IDEAS

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    1. Xie, Jiehua & Fang, Jun & Yang, Jingping & Bu, Lan, 2022. "Multivariate Composite Copulas – Corrigendum," ASTIN Bulletin, Cambridge University Press, vol. 52(1), pages 361-361, January.
    2. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    3. Xie, Jiehua & Fang, Jun & Yang, Jingping & Bu, Lan, 2022. "Multivariate Composite Copulas," ASTIN Bulletin, Cambridge University Press, vol. 52(1), pages 145-184, January.
    4. Song, Siming & Li, Tianxiao & Liu, Pei & Li, Zheng, 2022. "The transition pathway of energy supply systems towards carbon neutrality based on a multi-regional energy infrastructure planning approach: A case study of China," Energy, Elsevier, vol. 238(PC).
    5. Zhang, Shicong & Wang, Ke & Xu, Wei & Iyer-Raniga, Usha & Athienitis, Andreas & Ge, Hua & Cho, Dong woo & Feng, Wei & Okumiya, Masaya & Yoon, Gyuyoung & Mazria, Edward & Lyu, Yanjie, 2021. "Policy recommendations for the zero energy building promotion towards carbon neutral in Asia-Pacific Region," Energy Policy, Elsevier, vol. 159(C).
    6. Valizadeh Haghi, H. & Tavakoli Bina, M. & Golkar, M.A. & Moghaddas-Tafreshi, S.M., 2010. "Using Copulas for analysis of large datasets in renewable distributed generation: PV and wind power integration in Iran," Renewable Energy, Elsevier, vol. 35(9), pages 1991-2000.
    7. Kumar, R. Seshu & Raghav, L. Phani & Raju, D. Koteswara & Singh, Arvind R., 2021. "Intelligent demand side management for optimal energy scheduling of grid connected microgrids," Applied Energy, Elsevier, vol. 285(C).
    8. Wu, Haitao & Xue, Yan & Hao, Yu & Ren, Siyu, 2021. "How does internet development affect energy-saving and emission reduction? Evidence from China," Energy Economics, Elsevier, vol. 103(C).
    9. Han, Shuang & Qiao, Yan-hui & Yan, Jie & Liu, Yong-qian & Li, Li & Wang, Zheng, 2019. "Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network," Applied Energy, Elsevier, vol. 239(C), pages 181-191.
    10. Zhou, Suyang & Sun, Kaiyu & Wu, Zhi & Gu, Wei & Wu, Gaoxiang & Li, Zhe & Li, Junjie, 2020. "Optimized operation method of small and medium-sized integrated energy system for P2G equipment under strong uncertainty," Energy, Elsevier, vol. 199(C).
    11. Qureshy, Ali M.M.I. & Dincer, Ibrahim, 2020. "Energy and exergy analyses of an integrated renewable energy system for hydrogen production," Energy, Elsevier, vol. 204(C).
    12. Koirala, Binod Prasad & Koliou, Elta & Friege, Jonas & Hakvoort, Rudi A. & Herder, Paulien M., 2016. "Energetic communities for community energy: A review of key issues and trends shaping integrated community energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 722-744.
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