An Improved Particle Swarm Optimization for economic dispatch with carbon tax considerations

This paper presents an Improved Particles Swarm Optimization(IPSO) to the economic dispatch problems with carbon tax consideration. This economic dispatch problem has a nonconvex cost function and nonlinear emission cost function with linear and nonlinear constraints that it is difficult to find the compromised solution using mathematical approaches. Integration of Random Particles and Fine-Tuning Mechanism in the PSO procedure, an IPSO is proposed to solve this problem. The proposed developed in such a way that a simple PSO is applied as a based level search, which can give a good direction to the optimal global region, and random particles and fine-tuning mechanism is used as a fine tuning to determine the optimal solutions at the final. Effectiveness of the proposed method is demonstrated on example systems and compared to that of PSO, SA, GA, EP, and previous publications. Results show that the proposed method is more effective in solving economic dispatch problems.