A Research on Power Load Forecasting Model Based on Data Mining

Utilizing the advantage of data mining technology in processing large data and eliminating redundant information, the system mines the historical daily loading which has the same meteorological category as the forecasting day in order to compose data sequence with highly similar meteorological features. With this method it can decrease SVM training data and overcome the disadvantage of very large data and slow processing speed when constructing SVM model. Comparing with single SVM and BP neural network in short-term load forecasting, this new method can achieve greater forecasting accuracy. It is denoted that the SVM learning system has advantage when the information preprocessing is based on data mining technology.