Improved Stochastic Fractal Search Algorithm for Joint Optimal Operation of Cascade Hydropower Stations

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Sustainable Development of Water and Environment

Part of the book series: Environmental Science and Engineering ((ESE))

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Abstract

The joint optimal operation of cascade reservoirs can not only improve the overall capacity of flood control and disaster reduction, but also increase the power generation benefit of hydropower stations, which is conducive to the efficient utilization of water resources in the basin. Long-term joint operation of hydropower stations is a typical multi-stage constrained optimization problem, which has the characteristics of high dimension, nonlinear and strong coupling. To solve this problem effectively, this paper proposes an improved stochastic classification algorithm (ISFS) based on the stochastic fractal search (SFS) algorithm and the disruption operator. The simulation results of 13 benchmark functions show that the algorithm can effectively improve the optimization performance of SFS. The calculation results of the joint operation of four cascade hydropower stations in the upper reaches of the Yangtze River show that the proposed algorithm is superior to the comparison method in terms of convergence speed and solution quality, and the overall power generation of cascade hydropower stations is significantly increased, which proves the advantages of the proposed algorithm in solving the joint operation problem of reservoir groups.

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References

  • Feng ZK, Niu WJ, Liu S, Luo B, Miao SM, Liu K (2020) Multiple hydropower reservoirs operation optimization by adaptive mutation sine cosine algorithm based on neighborhood search and simplex search strategies. J Hydrol 590

    Google Scholar 

  • He Z, Zhou J, Qin H, Jia B, Lu C (2019) Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution. Eng Appl Artif Intell 81

    Google Scholar 

  • Salimi H (2015) Stochastic fractal search: a powerful metaheuristic algorithm. Knowl-Based Syst 75

    Google Scholar 

  • Sun L, Niu D, Wang K, Xu X (2021) Sustainable development pathways of hydropower in China: interdisciplinary qualitative analysis and scenario-based system dynamics quantitative modeling. J Clean Prod 287

    Google Scholar 

  • Yang T, Gao X, Sorooshian S, Li X (2016) Simulating California reservoir operation using the classification and regression‐tree algorithm combined with a shuffled cross‐validation scheme. Water Resour Res 52(3)

    Google Scholar 

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Acknowledgements

This study is supported by the National Natural Science Foundation Key Project of China (No. 52039004) and National Natural Science Foundation of China (No. U1865202).

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Correspondence to Zhanxing Xu or Jianzhong Zhou .

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Xu, Z., Zhou, J., Yang, Y., Qin, Z. (2022). Improved Stochastic Fractal Search Algorithm for Joint Optimal Operation of Cascade Hydropower Stations. In: Jeon, HY. (eds) Sustainable Development of Water and Environment. Environmental Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-07500-1_2

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