Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem

This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.