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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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    1. Abbas Afshar & Fariborz Massoumi & Amin Afshar & Miquel Mariño, 2015. "State of the Art Review of Ant Colony Optimization Applications in Water Resource Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 3891-3904, September.
    2. Hamid Bashiri-Atrabi & Kourosh Qaderi & David Rheinheimer & Erfaneh Sharifi, 2015. "Application of Harmony Search Algorithm to Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5729-5748, December.
    3. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.
    4. Dias, Bruno Henriques & Tomim, Marcelo Aroca & Marcato, André Luís Marques & Ramos, Tales Pulinho & Brandi, Rafael Bruno S. & Junior, Ivo Chaves da Silva & Filho, João Alberto Passos, 2013. "Parallel computing applied to the stochastic dynamic programming for long term operation planning of hydrothermal power systems," European Journal of Operational Research, Elsevier, vol. 229(1), pages 212-222.
    5. Takriti, Samer & Krasenbrink, Benedikt, 1999. "A decomposition approach for the fuel-constrained economic power-dispatch problem," European Journal of Operational Research, Elsevier, vol. 112(2), pages 460-466, January.
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    Cited by:

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    2. 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.
    3. Zhe Yang & Kan Yang & Lyuwen Su & Hu Hu, 2020. "The Short-Term Economical Operation Problem for Hydropower Station Using Chaotic Normal Cloud Model Based Discrete Shuffled Frog Leaping Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 905-927, February.
    4. Zhe Yang & Kan Yang & Hu Hu & Lyuwen Su, 2019. "The Cascade Reservoirs Multi-Objective Ecological Operation Optimization Considering Different Ecological Flow Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 207-228, January.
    5. Yufei Ma & Ping-an Zhong & Bin Xu & Feilin Zhu & Yao Xiao & Qingwen Lu, 2020. "Multidimensional Parallel Dynamic Programming Algorithm Based on Spark for Large-Scale Hydropower Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(11), pages 3427-3444, September.
    6. 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.
    7. 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.
    8. 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.
    9. Zhiqiang Jiang & Zhengyang Tang & Yi Liu & Yuyun Chen & Zhongkai Feng & Yang Xu & Hairong Zhang, 2019. "Area Moment and Error Based Forecasting Difficulty and its Application in Inflow Forecasting Level Evaluation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4553-4568, October.
    10. Yang, Zhe & Wang, Yufeng & Yang, Kan, 2022. "The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts," Energy, Elsevier, vol. 241(C).

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