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Day-ahead optimal dispatching of multi-source power system

Author

Listed:
  • Lu, Mengke
  • Guan, Jun
  • Wu, Huahua
  • Chen, Huizhe
  • Gu, Wei
  • Wu, Ye
  • Ling, ChengXiang
  • Zhang, Linqiang

Abstract

In this paper, the day-ahead optimal dispatching model of power system that is combined by wind-photovoltaic-hydropower-thermal-pumped storage is established. Firstly, according to the characteristics of the short-term hydropower system dispatching problem, a new mathematical model of the cascade hydropower group system with pumped storage power stations is proposed. The coordinated optimized dispatching model of the hydropower group system formed by the cascading of pumped storage power plants and conventional hydropower in the power system is studied. Secondly, the opportunity constraint programming model of forecast error reserve is used to deal with the output uncertainty of wind power and photovoltaic. The randomness and intermittency of renewable energy on the stability of the power system are overcame by the combination of wind-photovoltaic-pumped storage. Thirdly, the model for the joint optimal dispatch of short-term wind, photovoltaic, hydropower and thermal power systems with pumped storage is developed with system economics as the goal. Fourthly, the operation volatility coefficient of thermal power units is proposed to study the impact of renewable energy on the operation of thermal power. Finally, an example system is used to verify the correctness of the proposed dispatching optimal scheduling model, and the results prove that the daily dispatch optimization model proposed in this paper can increase the economic efficiency of the power system by 5%, reduce the start-stop times of thermal power units by 36.55%, and reduce the fluctuation coefficient of the unit by 2.8.

Suggested Citation

  • Lu, Mengke & Guan, Jun & Wu, Huahua & Chen, Huizhe & Gu, Wei & Wu, Ye & Ling, ChengXiang & Zhang, Linqiang, 2022. "Day-ahead optimal dispatching of multi-source power system," Renewable Energy, Elsevier, vol. 183(C), pages 435-446.
    • Handle: RePEc:eee:renene:v:183:y:2022:i:c:p:435-446
    DOI: 10.1016/j.renene.2021.10.093
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    5. Chao Chen & Shan Huang & Yue Yin & Zifan Tang & Qiang Shuai, 2025. "Enhancing Pumped Hydro Storage Regulation Through Adaptive Initial Reservoir Capacity in Multistage Stochastic Coordinated Planning," Energies, MDPI, vol. 18(11), pages 1-21, May.
    6. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    7. Ji, Fan & Zhu, Ziyu & Fan, Hongtao & Ma, Lei & Li, Xinran & Ji, Renyun & Yu, Zhuying & Fu, Shiyi & Sun, Yaojie, 2026. "Adaptive optimization algorithms for scheduling multiple battery energy storage systems in complex grid scenarios," Applied Energy, Elsevier, vol. 405(C).
    8. Yang, Tianrun & Liu, Wen & Kramer, Gert Jan, 2024. "Seasonal thermal energy storage employing solar heat: A case study of Heilongjiang, China, exploring the transition to clean heating and renewable power integration," Energy, Elsevier, vol. 305(C).
    9. Kangkang Huang & Yanlai Zhou & Yadong Mei & Fi-John Chang & Chong-Yu Xu, 2025. "Boosting Efficiency: Optimizing Pumped-Storage Power Station Operation by a Mixed Integer Linear Programming Approach," Energies, MDPI, vol. 18(18), pages 1-25, September.
    10. Gang Zhang & Yaning Zhu & Tuo Xie & Kaoshe Zhang & Xin He, 2022. "Wind Power Consumption Model Based on the Connection between Mid- and Long-Term Monthly Bidding Power Decomposition and Short-Term Wind-Thermal Power Joint Dispatch," Energies, MDPI, vol. 15(19), pages 1-25, September.
    11. Dong, Yuqun & Zhuang, Yaming & Pan, Zhilei, 2024. "Storage capacity plan and transition of heterogeneous energy at regional strategic level: A financial derivative perspective," Energy, Elsevier, vol. 308(C).
    12. Zhu, Yanmei & Zhou, Yerong & Tao, Xiangming & Chen, Shijun & Huang, Weibin & Ma, Guangwen, 2024. "A new clearing method for cascade hydropower spot market," Energy, Elsevier, vol. 289(C).
    13. Hu, Jinhui & Xie, Yulei & Wang, Bingyi & Wu, Zhentong & Sun, Yongxi & Wu, Kun & Yan, Weijian, 2026. "Short-term multi-objective scheduling optimization model for a pumping-integrated hybrid renewable energy system considering ecological flow constrain," Renewable Energy, Elsevier, vol. 264(C).
    14. Wang, Sen & Li, Fengting & Zhang, Gaohang & Yin, Chunya, 2023. "Analysis of energy storage demand for peak shaving and frequency regulation of power systems with high penetration of renewable energy," Energy, Elsevier, vol. 267(C).
    15. Zheng, J.H. & Guo, J.C. & Deng, Weisi & Li, Zhigang & Wu, Q.H. & Zhou, X.X., 2024. "Flexible allocation and optimal configuration of multi-level energy exploitation units for heterogeneous energy systems considering resource distribution," Renewable Energy, Elsevier, vol. 230(C).
    16. Wang, Kaiyan & Zhu, Hengtao & Dang, Jian & Ming, Bo & Wu, Xiong, 2024. "Short-term optimal scheduling of wind-photovoltaic-hydropower-thermal-pumped hydro storage coupled system based on a novel multi-objective priority stratification method," Energy, Elsevier, vol. 309(C).

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