Combined economic emission dispatch problem using chaotic self adaptive PSO

This research work presents a Chaotic Self Adaptive Particle Swarm Optimization (CSAPSO) algorithm in order to solve the Combined Economic Emission Dispatch (CEED) problem. The main purpose of the work is to derive a simple and effective method for optimum generation dispatch to minimize the fuel cost and emission of power networks by considering several non-linear characteristics of the generator such as valve point effect, prohibited operating zones and ramp rate limits. A chaotic local search operator is introduced in the proposed algorithm to avoid premature convergence. Simulation studies are carried out, using MATLAB software, to show the effectiveness of the proposed optimization method. The applicability and high feasibility of the proposed method is validated on IEEE 30 bus, six generator systems. The CSAPSO based approach has been extended to evaluate the trade-off curve between the fuel cost and emission according to the bi-criterion objective function. In order to see the effectiveness of the proposed algorithm, it has been compared with other algorithms in the literature. Results show that the CSAPSO is more powerful than other algorithms.