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Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market

Author

Listed:
  • Yang Li

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Ni Fang

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Shengming He

    (Yalong River Hydropower Development Company Ltd., Chengdu 610051, China)

  • Feng Wu

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Outing Li

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Linjun Shi

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Renshan Ding

    (Yalong River Hydropower Development Company Ltd., Chengdu 610051, China)

Abstract

With the advancement of China’s electricity markets and the continuous development of renewable energy sources (RESs), it is of great importance to investigate the strategic behavior of RESs in electricity markets. In this paper, a two-stage stochastic optimization model is proposed for a hybrid energy system composed of cascade hydropower plants, wind farms, and photovoltaic stations. Firstly, typical scenarios are generated based on Latin hypercube sampling (LHS) and the K-means clustering algorithm to represent uncertainties of wind–photovoltaic power outputs. Then, with an analysis of China’s electricity market structure, a two-stage coordinated scheduling model of hydropower–wind–photovoltaic hybrid systems in electricity markets is established with the objective of maximizing total revenues considering bilateral contract decomposition, the day-ahead energy market, and the real-time balance market. In addition, the proposed model is transformed into a mixed-integer linear programming (MILP) problem for computational convenience. As shown in an analysis of case studies, cascade hydropower plants can compensate for the fluctuation in wind and photovoltaic power outputs to reduce financial risks caused by uncertainties of wind and photovoltaic power generation. Simulation results show that compared with uncoordinated operation, the coordinated operation of hydropower–wind–photovoltaic hybrid systems increases total revenue by 1.08% and reduces the imbalance penalty by 29.85%.

Suggested Citation

  • Yang Li & Ni Fang & Shengming He & Feng Wu & Outing Li & Linjun Shi & Renshan Ding, 2024. "Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market," Sustainability, MDPI, vol. 16(3), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1093-:d:1327680
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    References listed on IDEAS

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    1. Liao, Shengli & Liu, Zhanwei & Liu, Benxi & Cheng, Chuntian & Wu, Xinyu & Zhao, Zhipeng, 2021. "Daily peak shaving operation of cascade hydropower stations with sensitive hydraulic connections considering water delay time," Renewable Energy, Elsevier, vol. 169(C), pages 970-981.
    2. Zhang, Hongxuan & Lu, Zongxiang & Hu, Wei & Wang, Yiting & Dong, Ling & Zhang, Jietan, 2019. "Coordinated optimal operation of hydro–wind–solar integrated systems," Applied Energy, Elsevier, vol. 242(C), pages 883-896.
    3. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    4. Wang, Zizhao & Wu, Feng & Li, Yang & Li, Jingyan & Liu, Ying & Liu, Wenge, 2023. "Day-ahead dispatch approach for cascaded hydropower-photovoltaic complementary system based on two-stage robust optimization," Energy, Elsevier, vol. 265(C).
    5. Xu, Shitian & Liu, Pan & Li, Xiao & Cheng, Qian & Liu, Zheyuan, 2023. "Deriving long-term operating rules of the hydro-wind-PV hybrid energy system considering electricity price," Renewable Energy, Elsevier, vol. 219(P1).
    6. Su, Chengguo & Cheng, Chuntian & Wang, Peilin & Shen, Jianjian & Wu, Xinyu, 2019. "Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants," Applied Energy, Elsevier, vol. 242(C), pages 285-293.
    7. Hans Ole Riddervold & Ellen Krohn Aasg{aa}rd & Lisa Haukaas & Magnus Korp{aa}s, 2021. "Internal hydro- and wind portfolio optimisation in real-time market operations," Papers 2102.10098, arXiv.org.
    8. Javed, Muhammad Shahzad & Ma, Tao & Jurasz, Jakub & Amin, Muhammad Yasir, 2020. "Solar and wind power generation systems with pumped hydro storage: Review and future perspectives," Renewable Energy, Elsevier, vol. 148(C), pages 176-192.
    9. Zhang, Yuquan & Zang, Wei & Zheng, Jinhai & Cappietti, Lorenzo & Zhang, Jisheng & Zheng, Yuan & Fernandez-Rodriguez, E., 2021. "The influence of waves propagating with the current on the wake of a tidal stream turbine," Applied Energy, Elsevier, vol. 290(C).
    10. Yuan, Wenlin & Zhang, Shijie & Su, Chengguo & Wu, Yang & Yan, Denghua & Wu, Zening, 2022. "Optimal scheduling of cascade hydropower plants in a portfolio electricity market considering the dynamic water delay," Energy, Elsevier, vol. 252(C).
    11. Wang, Xuebin & Chang, Jianxia & Meng, Xuejiao & Wang, Yimin, 2018. "Short-term hydro-thermal-wind-photovoltaic complementary operation of interconnected power systems," Applied Energy, Elsevier, vol. 229(C), pages 945-962.
    12. Lei, Kaixuan & Chang, Jianxia & Wang, Xuebin & Guo, Aijun & Wang, Yimin & Ren, Chengqing, 2023. "Peak shaving and short-term economic operation of hydro-wind-PV hybrid system considering the uncertainty of wind and PV power," Renewable Energy, Elsevier, vol. 215(C).
    13. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
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