Dynamic economic dispatch based on improved differential evolution algorithm

Dynamic economic dispatch optimum scheduling of power plant generation is of great importance to electric utility systems, it is difficult to solve because of its complex structure, variable parameter, nonlinear characteristics et al. Based on analysis of DE searching mechanism, an improved differential evolution (IDE) algorithm based DE/target-to-best is presented,which adopts an improved mutation strategy that a random vector and the previous best vector is used instead of the current vector in case the DE algorithm may be in early maturity or decline in convergence speed.The algorithm is applied to solve the generators dynamic load economic dispatch problems taking into account the incremental fuel cost function and the valve-point effects. Computer simulation test shows that IDE algorithm provides better solution of less cost In the case of less generations and outperforms GA, PSO and DE.