Application analysis of particle swarm optimization algorithm in reservoir scheduling

particle swarm algorithm;  Optimal scheduling of reservoirs;  Penalty function

Seeking the optimal reservoir scheduling trajectory process line is a classic and difficult problem in reservoir optimal scheduling. Based on the analysis of the advantages and disadvantages of previous reservoir optimization scheduling models, this paper proposes a reservoir optimization scheduling model based on Particle Swarm Optimization (PSO), and solves the problem of strong constraint by introducing a penalty function. The optimal scheduling of a comprehensive utilization reservoir is studied as an example, and the calculation results of dynamic programming model are compared and analyzed. The results show that the particle swarm optimization algorithm is simple in principle, easy to program, occupies small computer memory, and has fast calculation speed, which is suitable for determining the optimal scheduling rules of reservoirs within the year.