Integrating Radial Basis Function Neural Network with Fuzzy Control for Load Forecasting in Power System

Short-term load forecasting of power system is not only the basis of scheduling of generating sets, but also the basis of working out the transaction schedule in electricity market. This paper proposes a short-term load forecasting method based on combination of Radial Basis Function (RBF) neural network and fuzzy control, uses on-line self-modify factor fuzzy control to eliminate forecast error on the basis of RBF neural network forecasting. The practical examples show that the accuracy of short-term load forecasting and training speed can be improved and gains the very satisfactory results by the proposed method.