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Wind-photovoltaic co-generation prediction and energy scheduling of low-carbon complex regional integrated energy system with hydrogen industry chain based on copula-MILP

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  • Gao, Chong
  • Lin, Junjie
  • Zeng, Jianfeng
  • Han, Fengwu

Abstract

The application of hydrogen is promising for achieving carbon neutrality. To promote hydrogen utilization and carbon emission reduction, this paper attempts to integrate the hydrogen industry chain, carbon capture and storage (CCS) into a regional integrated energy system (forming a complex regional integrated energy system (CRIES)) and proposes an energy scheduling model for optimizing CRIES operation considering wind and photovoltaic co-generation (WT-PV) uncertainties. Firstly, to measure the uncertainties of WT-PV, the Wasserstein distance with better geometric properties is introduced to select the best Copula to model the correlation between wind and photovoltaic generation and to generate a typical scenario of WT-PV for each season. Secondly, based on MILP, the system is modularly modeled considering the pressure difference of various gases, the time interval of carbon capture and natural gas synthesis, and the energy coupling relationship. Finally, based on the above WT-PV prediction and modeling, the energy dispatch status in each season is investigated, and the economics of the proposed system is verified in the minimum hydrogen demand variation of hydrogen metallurgy plant, hydrogen blending ratio, and uncertainties of electric vehicles and hydrogen vehicles loads. Results show that 1) hydrogen-rich natural gas improves system’s energy use efficiency, CCS weakens system’s dependence on the upstream natural gas network, and the multi-energy coupling improves system’s arbitrage ability under different prices; 2) hydrogen is richest in the summer, causing system’s revenue to be 8.54%–32.17% and 29.29%–244.21% higher than in the transition season and winter. 3) zero-carbon energy interaction with the outside world and fully accommodating WT-PV are achieved by integrating the hydrogen industry chain; 4) the proposed CRIES operates reliably and economically under multiple uncertainties.

Suggested Citation

  • Gao, Chong & Lin, Junjie & Zeng, Jianfeng & Han, Fengwu, 2022. "Wind-photovoltaic co-generation prediction and energy scheduling of low-carbon complex regional integrated energy system with hydrogen industry chain based on copula-MILP," Applied Energy, Elsevier, vol. 328(C).
    • Handle: RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014623
    DOI: 10.1016/j.apenergy.2022.120205
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    3. Jorge Sousa & Inês Azevedo & Cristina Camus & Luís Mendes & Carla Viveiros & Filipe Barata, 2024. "Decarbonizing Hard-to-Abate Sectors with Renewable Hydrogen: A Real Case Application to the Ceramics Industry," Energies, MDPI, vol. 17(15), pages 1-15, July.
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    5. Li, Yuxuan & Zhang, Junli & Wu, Xiao & Shen, Jiong & Maréchal, François, 2023. "Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system," Energy, Elsevier, vol. 283(C).
    6. Kong, Feng & Zhang, Dongyue & Song, Minghao & Zhou, Xuecong & Wang, Yuwei, 2024. "Collaborative scheduling and benefit allocation for waste-to-energy, hydrogen storage, and power-to-gas under uncertainties with temporal relevance," Energy, Elsevier, vol. 307(C).
    7. Gao, Jianwei & Meng, Qichen & Liu, Jiangtao & Wang, Ziying, 2024. "Thermoelectric optimization of integrated energy system considering wind-photovoltaic uncertainty, two-stage power-to-gas and ladder-type carbon trading," Renewable Energy, Elsevier, vol. 221(C).
    8. Li, Fei & Wang, Dong & Guo, Hengdao & Zhang, Jianhua, 2024. "Distributionally Robust Optimization for integrated energy system accounting for refinement utilization of hydrogen and ladder-type carbon trading mechanism," Applied Energy, Elsevier, vol. 367(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. Wang, L.L. & Xian, R.C. & Jiao, P.H. & Chen, J.J. & Chen, Y. & Liu, H.G., 2024. "Multi-timescale optimization of integrated energy system with diversified utilization of hydrogen energy under the coupling of green certificate and carbon trading," Renewable Energy, Elsevier, vol. 228(C).
    11. Zhang, Jinliang & Liu, Ziyi, 2024. "Low carbon economic scheduling model for a park integrated energy system considering integrated demand response, ladder-type carbon trading and fine utilization of hydrogen," Energy, Elsevier, vol. 290(C).
    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).
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