Cloud Adaptive Chaos Particle Swarm Optimization Algorithm for Economic Load Dispatch of Power System

A cloud adaptive chaos particle swarm optimization algorithm is proposed for economic load dispatch problems of power system, which has the characteristics of nonlinear, non-convex and discontinuous. Normal cloud generator was used to adaptively adjust the inertia weight of each particles, so as to optimize their optimization direction and improve the convergence speed of the algorithm; and the chaotic variation operation was introduced to adjust the particle's positions, so as to improve the diversity of the solution and avoid falling into local optimum. Simulation of 6 unit system demonstrates that the proposed algorithm has high accuracy and quick speed used in economic load dispatch of power system.