Forecast of electric power load by genetic algorithm for adaptation,symmetry and congruity-ANN

In order to solve the conflict between accuracy and convergence rate in genetic algorithm,a novel genetic algorithm for adaptation,symmetry and congruity is proposed.In that algorithm,crossover rate and mutation rate change dynamically with the fitness value of chromosome;child group comes not only from one single parent group but from three parts: optimal individuals of parent group,new individuals derived from crossover selection,new individuals generated randomly.A coupling model for power load prediction is established;by using combination of the new algorithm and ANNS and applied to Sichuan Grid.The result demonstrates that the new coupling model avoids blindness of network seeking optimization,so that to achieve the best fitting result,improve effectively forecasting accuracy and speed,and to provide new analytical method for forecast research of regional power load.