Genetic Algorithm Optimizing Neural Network for Short-Term Load Forecasting

Short-term load forecasting in power system is necessary for management and control of power system. A new method for short-term load forecasting was presented based on neural networks optimized by genetic algorithm (GA) is proposed in this paper, short-term load forecasting model for power system was setup as sample sets for Elman neural network (Elman NN), with GA´s optimizing and Elman NN´s dynamic feature, the higher forecasting pricision was realized and the simulation indicates the method is feasible and effective.