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Monthly Operation Optimization of Cascade Hydropower Reservoirs with Dynamic Programming and Latin Hypercube Sampling for Dimensionality Reduction

Author

Listed:
  • Zhong-kai Feng

    (Huazhong University of Science and Technology)

  • Wen-jing Niu

    (ChangJiang Water Resources Commission)

  • Zhi-qiang Jiang

    (Huazhong University of Science and Technology)

  • Hui Qin

    (Huazhong University of Science and Technology)

  • Zhen-guo Song

    (China Ship Development and Design Center)

Abstract

The dimensionality problem is posing an enormous challenge for cascade hydropower reservoirs operation because the memory usage and execution time grow exponentially with the expansion of system scale. To effectively address this problem, this paper develops a novel Latin dynamic programming algorithm for dimensionality reduction in hydropower reservoir operation problem, where the Latin hypercube sampling method is firstly adopted to produce a subset of discrete state variables at each stage, and then the standard dynamic programming recursive equation is used to search for a modified trajectory around the newly-generated solutions, while the iterative search strategy is used to gradually enhance the solution quality. The results in a real-world hydropower system of China demonstrate that compared with the standard dynamic programming method, the execution efficiency of the presented method is significantly improved while the power generation is well maintained in different scenarios. Hence, the novelty of the paper is to provide an effective dimensionality reduction tool for solving the complex hydropower operation problem.

Suggested Citation

  • Zhong-kai Feng & Wen-jing Niu & Zhi-qiang Jiang & Hui Qin & Zhen-guo Song, 2020. "Monthly Operation Optimization of Cascade Hydropower Reservoirs with Dynamic Programming and Latin Hypercube Sampling for Dimensionality Reduction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2029-2041, April.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:6:d:10.1007_s11269-020-02545-0
    DOI: 10.1007/s11269-020-02545-0
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    References listed on IDEAS

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    Cited by:

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    2. 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).
    3. Wu, Zhiyuan & Fang, Guohua & Ye, Jian & Huang, Xianfeng & Yan, Min, 2024. "Optimizing ecological benefits in weekly-regulated hydropower plants: A framework integrating power market information," Renewable Energy, Elsevier, vol. 231(C).
    4. Wang, Jin & Zhao, Zhipeng & Zhou, Jinglin & Cheng, Chuntian & Su, Huaying, 2024. "Developing operating rules for a hydro–wind–solar hybrid system considering peak-shaving demands," Applied Energy, Elsevier, vol. 360(C).
    5. Gi Joo Kim & Young-Oh Kim, 2021. "How Does the Coupling of Real-World Policies with Optimization Models Expand the Practicality of Solutions in Reservoir Operation Problems?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3121-3137, August.
    6. Luckny Zephyr & Bernard F. Lamond & Pascal Lang, 2024. "Hybrid simplicial-randomized approximate stochastic dynamic programming for multireservoir optimization," Computational Management Science, Springer, vol. 21(1), pages 1-44, June.

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