Improved differential evolution for economic dispatch

This paper presents an improved differential evolution to solve economic dispatch problem of thermal generating units with non-smooth/non-convex cost functions due to valve-point loading taking into account transmission losses and nonlinear generator constraints such as prohibited operating zones. Differential evolution exploits the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently the variation between vectors will outfit the objective function toward the optimization process and therefore provides efficient global optimization capability. However, although DE is shown to be precise, fast as well as robust, its search efficiency will be impaired during solution process with fast descending diversity of population. This paper proposes Gaussian random variable instead of scaling factor which improves search efficiency. The proposed method has been applied to four different non-convex economic dispatch problems with valve-point effects, prohibited operating zones with transmission losses, multiple fuels with valve point effects and the large-scale Korean power system with valve-point effects and prohibited operating zones. The results of the proposed approach are compared with those obtained by other evolutionary methods. It is found that the proposed improved differential evolution based approach is able to provide better solution.