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Multicore Parallel Dynamic Programming Algorithm for Short-Term Hydro-Unit Load Dispatching of Huge Hydropower Stations Serving Multiple Power Grids

Author

Listed:
  • Shengli Liao

    (Dalian University of Technology)

  • Jie Liu

    (North China Municipal Engineering Design & Research Institute co., LTD)

  • Benxi Liu

    (Dalian University of Technology)

  • Chuntian Cheng

    (Dalian University of Technology)

  • Lingan Zhou

    (Dalian University of Technology)

  • Huijun Wu

    (Electric Power Dispatching and Control Center, China Southern Power Grid)

Abstract

Short-term hydro-unit load dispatching (SHULD) refers to the determination of the power output of each unit within a hydropower station over a planning horizon to minimize the operational cost or maximize the power-generation profit while satisfying hydraulic and electrical constraints. In China, huge hydropower stations, such as the Three Gorges (TG) and Xiluodu (XLD) stations, are composed of a large number of hydro units, which feature a high installed capacity and a high water head. SHULD models of these stations are more complex and difficult to solve compared with those of traditional stations, especially when the stations serve multiple power grids. This study develops a practical method for optimizing SHULD models by considering the XLD hydropower station as a case study. First, a SHULD model for huge hydropower stations with multiple vibration zones and multiple receiving power grids is presented. Second, classical and sophisticated dynamic programming (DP) is applied to the SHULD model, and a practical strategy is proposed to balance the available water in a reservoir’s left and right banks to satisfy their load demands. Finally, the Fork/Join framework is used to parallelize DP to reduce the computation time and fully utilize the computer resources. The wet and dry season results demonstrate that the approach is efficient and suitable for huge hydropower stations with a high water head and multiple receiving power grids, thereby demonstrating its potential practicability and validity for solving the SHULD problem.

Suggested Citation

  • Shengli Liao & Jie Liu & Benxi Liu & Chuntian Cheng & Lingan Zhou & Huijun Wu, 2020. "Multicore Parallel Dynamic Programming Algorithm for Short-Term Hydro-Unit Load Dispatching of Huge Hydropower Stations Serving Multiple Power Grids," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 359-376, January.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:1:d:10.1007_s11269-019-02455-w
    DOI: 10.1007/s11269-019-02455-w
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    References listed on IDEAS

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    Cited by:

    1. Liao, Shengli & Liu, Huan & Liu, Benxi & Liu, Tian & Li, Chonghao & Su, Huaying, 2023. "Solution framework for short-term cascade hydropower system optimization operations based on the load decomposition strategy," Energy, Elsevier, vol. 277(C).
    2. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Wang, Haidong & Jin, Xiaoyu, 2023. "Short-term operation of cascade hydropower system sharing flexibility via high voltage direct current lines for multiple grids peak shaving," Renewable Energy, Elsevier, vol. 213(C), pages 11-29.
    3. Liao, Shengli & Liu, Huan & Liu, Zhanwei & Liu, Benxi & Li, Gang & Li, Shushan, 2021. "Medium-term peak shaving operation of cascade hydropower plants considering water delay time," Renewable Energy, Elsevier, vol. 179(C), pages 406-417.
    4. Fang, Zhou & Liao, Shengli & Cheng, Chuntian & Zhao, Hongye & Liu, Benxi & Su, Huaying, 2023. "Parallel improved DPSA algorithm for medium-term optimal scheduling of large-scale cascade hydropower plants," Renewable Energy, Elsevier, vol. 210(C), pages 134-147.

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