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

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.