A modified Particle Swarm Optimization for solving the non-convex economic dispatch

This paper presents a novel particle swarm optimizer combined with roulette selection operator to solve the economic load dispatch (ELD) problem of thermal generators of a power system. Several factors such as quadratic cost functions with valve point loading, transmission loss, generator ramp rate limits and prohibited operating zone are considered in the computation models. This new approach provides a new mechanism to restrain the predominating of super (global best) particles in early stage and can effectively avoid the premature convergence problem and speed up the convergence property. The proposed method has been applied to a 3 & 10 generator power system whose cost functions are non-convex in nature. Results obtained by this method have been compared with those obtained from particle swarm optimization (PSO) method. The experimental results show that the proposed modified PSO method is indeed capable of obtaining solution in less time and in fewer numbers of iterations.