A Method of Short-term Load Forecasting Based on Artificial Neural Network and Fuzzy Logic
In order to consider the factors such as temperature、date type、weather status and etc which influence the short-term electric load forecasting, this paper provides a method based on radial basis function neural network combined with fuzzy logic. Short-term system load can be subdivided into periodic basic load and variable load influenced by number of factors. ANN is used to forecast the periodic load, here we adopt the RBF model which is relative precise in load forecasting; we use fuzzy logical to give different fuzzy deals to the weather factor temperature and date-types, then update the elementary result of load forecasting with the fuzzy reasoning rules. By Comparing between typical example and usual forecasting result by BP model, the result indicates that this method has high accuracy and some factual values.