Short-term load forecasting based on wavelet transform and BP neural network

In order to improve the accuracy of short-term electric power load forecasting, we use DB wavelet and the BP neural network method for short-term power load forecasting. Firstly, the load sequence was decomposed into different sub-sequences by using the wavelet transform, high-frequency son sequence and low frequency son sequence Then, these sub-sequences were forecasted by neural networks .Finally, the load forecasting sequence was obtained by the reconstruction of the forecasted results from the sub-sequences. In the example we use hebei baoding area 's historical load data, and we compare the algorithm with BP neural network method. The simulation results show that the proposed method possesses high forecasting accuracy.