Genetic Algorithm Optimizing Neural Network for Short-Term Load Forecasting

Abstract

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.