Economic load dispatch using intelligent optimization with fuzzy control

In this paper, Differential Evolution (DE) that incorporates fuzzy control and k-nearest neighbors algorithm is proposed to tackle the economic load dispatch problem. To provide the self-terminating ability, a technique called Iteration Windows (IW) is introduced to govern the number of iteration in each searching stage during the optimization. The size of IW is controlled by a fuzzy controller, which uses the information provided by the k-nearest neighbors system to analyze the population during the searching process. The controller keeps controlling the IW till the end of the searching process. A wavelet based mutation process is embedded in the DE searching process to enhance the searching performance. The weight F of DE is also controlled by the fuzzy controller to further speed up the searching process. The proposed method is employed to solve the Economic Load Dispatch with Valve-Point Loading (ELD-VPL) Problem. It is shown empirically that the proposed method can terminate the searching process with a reasonable number of iteration and performs significantly better than the conventional methods in terms of convergence speed and solution quality.