Particle Swarm Optimization And Its Application In Cascade Hydropower Stations Scheduling

Two critical problems confronted in reservoir optimal scheduling procedures are to convert a real optimal scheduling problem to an appropriate mathematical model and to construct a best optimal technique for solving this model. Particle swarm optimization in swarm intelligence is proper to solve nonlinear programming problems with restrictions, which most of the reservoir optimal scheduling models belong to.A method of particle swarm optimization in solving reservoir optimal scheduling model is introduced and developed by the description of particle swarm optimization. A new particle swarm optimization are introduced which created by combining the particle swarm optimization method with the genetic algorithm and the immune algorithm. the progressive optimality algorithm of particle swarm optimization are introduced by applying the particle swarm optimization into the rogressive optimality algorithm. In the case of Wuxi river reservoir programming, these new methods are adapted. It is indicated that particle swarm optimization approach is efficient in solving reservoir optimal scheduling problems. Expansion of this approach to other types of reservoir optimal scheduling areas is also available.