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Research and Application of Parallel Normal Cloud Mutation Shuffled Frog Leaping Algorithm in Cascade Reservoirs Optimal Operation

Author

Listed:
  • Ping Sun

    (POWERCHINA Beijing Engineering Corporation Limited)

  • Zhi-qiang Jiang

    (Huazhong University of Science and Technology)

  • Ting-ting Wang

    (POWERCHINA Beijing Engineering Corporation Limited)

  • Yan-ke Zhang

    (North China Electric Power University)

Abstract

In order to improve the premature convergence problem of traditional shuffled frog leaping algorithm (SFLA), this paper proposed a normal cloud mutation shuffled frog leaping algorithm (NCM-SFLA) by mixing the cloud model algorithm (NCM) with SFLA algorithm, NCM is used to overcome the shortage of SFLA which is easy to fall into local optimal solution. The proposed NCM-SFLA has a good parallel characteristic, and the parallel computing can be implemented easily in multi core environment. In case study, this paper takes the Li Xianjiang cascade reservoirs in China as an instance to solve the cascade reservoirs operation optimization problem by the proposed NCM-SFLA. The results show that, compared with the Multi- dimensional Dynamic Programming (MDP), NCM-SFLA has the better global search ability and faster convergence speed, and the corresponding parallel computing can effectively shorten the run-time of NCM-SFLA. Therefore, the feasibility and rationality of the proposed NCM-SFLA and its parallel computing are effectively proved by the case study results.

Suggested Citation

  • Ping Sun & Zhi-qiang Jiang & Ting-ting Wang & Yan-ke Zhang, 2016. "Research and Application of Parallel Normal Cloud Mutation Shuffled Frog Leaping Algorithm in Cascade Reservoirs Optimal Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1019-1035, February.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:3:d:10.1007_s11269-015-1208-3
    DOI: 10.1007/s11269-015-1208-3
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    References listed on IDEAS

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    Cited by:

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    2. Qiang Zou & Li Liao & Hui Qin, 2020. "Fast Comprehensive Flood Risk Assessment Based on Game Theory and Cloud Model Under Parallel Computation (P-GT-CM)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1625-1648, March.
    3. Guohua Fang & Yuxue Guo & Xin Wen & Xiaomin Fu & Xiaohui Lei & Yu Tian & Ting Wang, 2018. "Multi-Objective Differential Evolution-Chaos Shuffled Frog Leaping Algorithm for Water Resources System Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 3835-3852, September.
    4. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm," Energy, Elsevier, vol. 153(C), pages 706-718.
    5. Jiang, Zhiqiang & Li, Anqiang & Ji, Changming & Qin, Hui & Yu, Shan & Li, Yuanzheng, 2016. "Research and application of key technologies in drawing energy storage operation chart by discriminant coefficient method," Energy, Elsevier, vol. 114(C), pages 774-786.
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    7. Majid Mohammadi & Saeed Farzin & Sayed-Farhad Mousavi & Hojat Karami, 2019. "Investigation of a New Hybrid Optimization Algorithm Performance in the Optimal Operation of Multi-Reservoir Benchmark Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4767-4782, November.
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