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Research on Joint Impoundment Dispatching Model for Cascade Reservoir

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  • Xuemin Wang
  • Jianzhong Zhou
  • Shuo Ouyang
  • Chunlong Li

Abstract

As more and more large reservoirs been built, competitive impoundment problem of cascade reservoirs becomes a serious matter in the flood recession. Combining the impounding principle with K value discriminant method, a novel impounding strategy of cascade reservoirs is proposed for determining the impoundment sequence and opportunity of each reservoir in premise of the flood control safety. At the same time, the impounding water level control lines of different frequency runoff are drawn according to the flood routing simulation, and then the Impounding Operation Chart (IOC) is manufactured. On this basis, a model of impoundment dispatching in advance based on the IOC is developed. Then the proposed method can be obviously accelerated by using Self-adaptive Electromagnetism-like Mechanism algorithm (SEM). Compared with the original design of impounding scheme, the result indicates that the optimal scheme can improve the fill storage ratio of cascade reservoirs and ease the contradiction between supply and demand of water resources as well with guaranteeing the safety of flood control in the watershed. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Xuemin Wang & Jianzhong Zhou & Shuo Ouyang & Chunlong Li, 2014. "Research on Joint Impoundment Dispatching Model for Cascade Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5527-5542, December.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:15:p:5527-5542
    DOI: 10.1007/s11269-014-0820-y
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    References listed on IDEAS

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    Cited by:

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    2. Jiang, Zhiqiang & Ji, Changming & Qin, Hui & Feng, Zhongkai, 2018. "Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs," Energy, Elsevier, vol. 148(C), pages 309-323.
    3. Yutao Qi & Liang Bao & Yingying Sun & Jungang Luo & Qiguang Miao, 2016. "A Memetic Multi-objective Immune Algorithm 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. 30(9), pages 2957-2977, July.
    4. Ming Zhang & Fei Yang & Jing-Xiu Wu & Zi-Wu Fan & Ying-Ying Wang, 2016. "Application of Minimum Reward Risk Model in Reservoir Generation Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1345-1355, March.
    5. He, Shaokun & Guo, Shenglian & Yin, Jiabo & Liao, Zhen & Li, He & Liu, Zhangjun, 2022. "A novel impoundment framework for a mega reservoir system in the upper Yangtze River basin," Applied Energy, Elsevier, vol. 305(C).
    6. Ming Zhang & Fei Yang & Jing-Xiu Wu & Zi-Wu Fan & Ying-Ying Wang, 2016. "Application of Minimum Reward Risk Model in Reservoir Generation Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1345-1355, March.

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