A New Chaotic PSO with Dynamic Inertia Weight for Economic Dispatch Problem

The rational economic load dispatch can not only save the energy, but also improve efficiency of power systems, so it is important to research economic load dispatch problem. However, duo to its complex and nonlinear characteristics, it is difficult to solve the problem using traditional optimization method. PSO has been successfully applied to a wide range of applications, in solving continuous nonlinear optimization problems. Owing to good characteristics of ergodicity, chaotic particle swarm optimization (CPSO) was presented to avoid the premature phenomenon of PSO, and furthermore, tent map has the outstanding advantages and higher iterative speed than logistic map in chaotic optimization. Therefore, this paper presents a modified tent-map-based chaotic PSO (TCPSO) to solve the economic load dispatch problem. More specifically, a novel dynamic inertial weight factor was incorporated with the modified hybrid TCPSO, which balances the global and local search better. Numerical simulation results of three test systems successfully validate that TCPSO outperformed CPSO and other heuristic optimization techniques on the same problem.