POWER SYSTEM SHORT-TERM LOAD FORECASTING BASED ON FUZZY CLUSTERING ANALYSIS AND BP NEURAL NETWORK
Wan Shi-xin · Power System Technology · 2005
A short-term load forecasting method based on fuzzy clustering analysis and BP neural network is presented. Some factors influencing load such as temperature, relative humidity and day type are considered. By means of dividing the historical load data into several categories by fuzzy clustering analysis and finding out the category coincident with that of the daily load to be forecasted, corresponding BP neural network model is built, then the additional momentum and diverse learning speed algorithm are employed to forecast hourly load. The actual load forecasting results for Xi抋n district show that the proposed method possesses better forecasting accuracy and the forecasting is satisfactory.