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Data-Driven Chance-Constrained Schedule Optimization of Cascaded Hydropower and Photovoltaic Complementary Generation Systems for Shaving Peak Loads

Author

Listed:
  • Yang Li

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

  • Feng Wu

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

  • Xudong Song

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

  • Linjun Shi

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

  • Keman Lin

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

  • Feilong Hong

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

Abstract

The coordinated scheduling of cascade hydropower with photovoltaic (PV) power stations can significantly improve the utilization rate of delivery transmission lines. However, the inherent uncertainty associated with photovoltaic (PV) forecasts challenges the reliable and economic operation of the complementary energy system. Against this background, in this paper, a day-ahead, chance-constrained scheduling for cascaded hydro–photovoltaic complementary generation systems (CHPSs) considering the transmission capacity is proposed. Firstly, the uncertainty of PV forecast errors is simulated by a probability density function fitted using kernel density estimation with historical sampling data. Then, a chance-constrained optimization model considering peak-shaving demands of the receiving-end power grid is developed to determine the day-ahead optimal schedules of CHPSs. Also, complex hydraulic coupling and unit operation constraints of cascade hydropower are considered in the proposed model. To deal with the nonlinear and stochastic constraints, an efficient linearization method is adopted to transform the proposed model into a mixed-integer linear programming (MILP) problem. Finally, the effectiveness and feasibility are verified by case studies. The results show that the day-ahead schedule optimized by the proposed method can fully balance peak-shaving and photovoltaic accommodation while considering photovoltaic output uncertainty.

Suggested Citation

  • Yang Li & Feng Wu & Xudong Song & Linjun Shi & Keman Lin & Feilong Hong, 2023. "Data-Driven Chance-Constrained Schedule Optimization of Cascaded Hydropower and Photovoltaic Complementary Generation Systems for Shaving Peak Loads," Sustainability, MDPI, vol. 15(24), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16916-:d:1301749
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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. Yuan, Wenlin & Xin, Wenpeng & Su, Chengguo & Cheng, Chuntian & Yan, Denghua & Wu, Zening, 2022. "Cross-regional integrated transmission of wind power and pumped-storage hydropower considering the peak shaving demands of multiple power grids," Renewable Energy, Elsevier, vol. 190(C), pages 1112-1126.
    6. Connolly, D. & Lund, H. & Finn, P. & Mathiesen, B.V. & Leahy, M., 2011. "Practical operation strategies for pumped hydroelectric energy storage (PHES) utilising electricity price arbitrage," Energy Policy, Elsevier, vol. 39(7), pages 4189-4196, July.
    7. 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.
    8. 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).
    9. Irshad, Ahmad Shah & Samadi, Wais Khan & Fazli, Agha Mohammad & Noori, Abdul Ghani & Amin, Ahmad Shah & Zakir, Mohammad Naseer & Bakhtyal, Irfan Ahmad & Karimi, Bashir Ahmad & Ludin, Gul Ahmad & Senjy, 2023. "Resilience and reliable integration of PV-wind and hydropower based 100% hybrid renewable energy system without any energy storage system for inaccessible area electrification," Energy, Elsevier, vol. 282(C).
    10. Wei, Hu & Hongxuan, Zhang & Yu, Dong & Yiting, Wang & Ling, Dong & Ming, Xiao, 2019. "Short-term optimal operation of hydro-wind-solar hybrid system with improved generative adversarial networks," Applied Energy, Elsevier, vol. 250(C), pages 389-403.
    11. 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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    1. Hu, Jinhui & Wu, Kun & Yan, Weijian & Wu, Zhentong & Xie, Yulei, 2025. "Economic dispatch model for a hydropower-wind-photovoltaic system with pumping installations to respond to uncertainties," Energy, Elsevier, vol. 334(C).

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