Hybrid PSO–SQP for economic dispatch with valve-point effect

Abstract This paper presents a novel and efficient method for solving the economic dispatch problem (EDP), by integrating the particle swarm optimization (PSO) technique with the sequential quadratic programming (SQP) technique. PSO is the main optimizer and the SQP is used to fine tune for every improvement in the solution of the PSO run. PSO is a derivative free optimization technique which produces results quickly and proves itself fit for solving large-scale complex EDP without considering the nature of the incremental fuel cost function it minimizes. SQP is a nonlinear programming method which starts from a single searching point and finds a solution using the gradient information. The effectiveness of the proposed method is validated by carrying out extensive tests on three different EDP with incremental fuel cost function takes into account the valve-point loadings effects. The proposed method out-performs and provides quality solutions compared to other existing techniques for EDP considering valve-point effects are shown in general.