Application of Improved Particle Swarm Optimization Algorithm in Optimal Operation of Reservoir
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Abstract:
The optimal operation model for flood control of reservoir is a high-dimensional multimodal extremum problem in general, and intelligent optimization algorithm is usually used to solve such problems. Particle swarm optimization (PSO) algorithm is widely used in the optimal operation of reservoir due to its simplicity; however, there are shortcomings in the PSO algorithm such as premature convergence, low efficiency in global convergence, and deficiency in local search capability. Logistic equation and mutation operator are introduced to increase the diversity of population and convergence factor is introduced to improve the convergence rate during the iterative process. The improved PSO algorithm was applied in the optimal operation for flood control of the Dongzhen Reservoir and Mulanxi Watershed. The resulted showed that the maximum water level is 6.35 m and the maximum flow rate is 959.2m3/s at the pivotal watercourse. The solutions were much better than that obtained from the present reservoir control regulations (maximum water level of 6.93 m and maximum flow rate of 1139.5 m3/s) and that determined by the standard PSO algorithm (maximum water level of 6.51 m and maximum flow rate of 1066.3 m3/s).
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