Deterministically guided PSO for dynamic dispatch considering valve-point effect

This paper presents a deterministically guided particle swarm optimization (DGPSO) algorithm to solve the dynamic economic dispatch problem (DEDP) of generating units considering the valve-point effects. The cost function of the generating units exhibits the non-convex characteristics, as the valve-point effects are modeled and imposed as rectified sinusoid components in the cost function. The DGPSO method is a two-phase optimizer: in the first phase the PSO technique will explore the solution space freely. In the second phase, SQP (sequential quadratic programming) will be called only when there is an improvement of solution (a feasible solution) in the PSO run. Thus, SQP (deterministically) guides the PSO algorithm for better performance in the complex solution space. To validate the feasibility of the DGPSO method a 10-unit system is considered and studied under three different cases. The effectiveness of the presented method over EP (evolutionary programming) and EP-SQP methods is shown in general.