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Improved Dynamic Programming for Reservoir Flood Control Operation

Author

Listed:
  • Tongtiegang Zhao

    (Wuhan University
    Tsinghua University)

  • Jianshi Zhao

    (Tsinghua University)

  • Xiaohui Lei

    (Institute of Water Resources and Hydropower Research)

  • Xu Wang

    (Institute of Water Resources and Hydropower Research)

  • Bisheng Wu

    (Energy Division, Commonwealth Scientific and Industrial Research Organization)

Abstract

In flood control operation, the maximum release from a reservoir is minimized to lessen flood risks. Two properties of the minimax problem are derived by formulating the multi-period decision process as a recursive two-stage model. First, the cost-to-go function, which represents the maximum release in the remaining periods, is a non-decreasing function of the carryover storage. Second, monotonic relationships exist between the initial storage of the two-stage model and the optimal decisions of release and carryover storage. The two properties hold not only in the deterministic case with a given streamflow scenario, but also in the stochastic case with an ensemble of streamflow scenarios. The monotonic relationships are incorporated into the dynamic programming (DP) and sampling stochastic DP (SSDP). Two novel algorithms—improved DP (IDP) and improved SSDP (ISSDP)—are developed. The algorithms are applied to a case study of the Danjiangkou Reservoir in Central China. IDP and ISSDP respectively obtain the same decisions as DP and SSDP, and they are more computationally efficient. The execution times of IDP and ISSDP increase linearly with the number of storage discretizations, while those of DP and SSDP increase quadratically. With 1000 discretizations of reservoir storage, IDP and ISSDP derive optimal decisions at 0.939 and 97.453 s, respectively, whereas DP and SSDP finish at 115.931 and 6372.915 s, respectively. These results suggest that IDP and ISSDP can be useful tools for flood control operation – testing different flood scenarios and determining the optimal decisions.

Suggested Citation

  • Tongtiegang Zhao & Jianshi Zhao & Xiaohui Lei & Xu Wang & Bisheng Wu, 2017. "Improved Dynamic Programming for Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(7), pages 2047-2063, May.
  • Handle: RePEc:spr:waterr:v:31:y:2017:i:7:d:10.1007_s11269-017-1599-4
    DOI: 10.1007/s11269-017-1599-4
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    2. Deepti Rani & Sandra Mourato & Madalena Moreira, 2020. "A Generalized Dynamic Programming Modelling Approach for Integrated Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1335-1351, March.
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    4. Aili Xie & Pan Liu & Shenglian Guo & Xiaoqi Zhang & Hao Jiang & Guang Yang, 2018. "Optimal Design of Seasonal Flood Limited Water Levels by Jointing Operation of the Reservoir and Floodplains," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 179-193, January.
    5. 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.
    6. Yong-Gun Kim & Myong-Bong Jo & Pyol Kim & Song-Nam Oh & Chung-Hyok Paek & Sung-Ryol So, 2021. "Effective Optimization-Simulation Model for Flood Control of Cascade Barrage Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 135-157, January.
    7. Xinyu Wu & Shuai Yin & Chuntian Cheng & Zhiyong Chen & Huaying Su, 2023. "SSDP Model with Inflow Clustering for Hydropower System Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1109-1123, February.
    8. Hai-tao Chen & Wen-chuan Wang & Kwok-wing Chau & Lei Xu & Ji He, 2021. "Flood Control Operation of Reservoir Group Using Yin-Yang Firefly Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5325-5345, December.
    9. Ji He & Xiaoqi Guo & Haitao Chen & Fuxin Chai & Shengming Liu & Hongping Zhang & Wenbin Zang & Songlin Wang, 2023. "Application of HSMAAOA Algorithm in Flood Control Optimal Operation of Reservoir Groups," Sustainability, MDPI, vol. 15(2), pages 1-16, January.

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