Power economic dispatch using a hybrid genetic algorithm
暂无分享,去创建一个
This letter outlines a hybrid genetic algorithm (HGA) for solving the economic dispatch problem. The algorithm incorporates the solution produced by an improved Hopfield neural network (NN) as a part of its initial population. Elitism, arithmetic crossover and mutation are used in the GAs to generate successive sets of possible operating policies. The technique improves the quality of the solution and reduces the computation time, and is compared with the classical optimization technique, an improved Hopfield NN approach (IHN), a fuzzy logic controlled GA and an improved GA.
[1] Y. H. Song,et al. Advanced engineered-conditioning genetic approach to power economic dispatch , 1997 .
[2] A. T. Johns,et al. Environmental/economic dispatch using fuzzy logic controlled genetic algorithms , 1997 .
[3] M. J. Short,et al. Neural networks approach for solving economic dispatch problem with transmission capacity constraints , 1998 .
[4] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.