Particle Swarm Optimization Based on Cultural Algorithm for Short-Term Optimal Operation of Cascade Hydropower Stations

Difficulties likely exist in optimal reservoir operation along with discreteness and nonlinear constraints. Therefore, particle swarm optimization based on cultural Algorithm (PSO-CA) is presented in this paper for overcoming these defects. In this article the evolutionary mechanism of particle swarm optimization algorithm (PSO) is guided by cultural algorithm (CA). PSO-CA uses PSO in population space and guides the evolution by shape knowledge and standardization knowledge in belief space. An example is also used to show that the PSO-CA algorithm has a better applied prospect for its high reliability and fast operation speed in global optimization.