Study of Optimal Operation of Cascade Hydropower Stations Based on an Improved Particle Swarm Algorithm

An improved swarm-intelligence-based algorithm of particle swarm optimization calling IPSP is introduced and applied to the global optimization of complex hydroelectric energy nonlinear dynamic system. Considering the shortcomings of falling into local optimization easily and the post slow convergence speed of the PSO algorithm, the mutation operator of the genetic algorithm is introduced and the an adaptive weighting factor in adopted to improve the global optimization capability and the searching efficiency. A particulate matrix is introduced and achieving the optimal calculation step by step through searching the optimal position in the multi-dimensional of the particles. The algorithm is applied to the complex hydropower system for long-term optimal operation of energy calculation. The calculation results show that the IPSO method has a superior optimization performance on the global optimization problems of complex systems comparing with the conventional mathematical optimization algorithm. Therefore, a new and effective method is provided to solve the global optimization problems of the complex nonlinear dynamic systems of hydroelectric system.