Title :
Short-term Load Forecasting in Power System Based on Wavelet Coefficients and BP Neural Network
Author :
Song, Renjie ; Bian, Yixin
Author_Institution :
Sch. of Inf. Eng., Northeast Dianli Univ., Jilin
Abstract :
A novel method of short-term load forecasting based on wavelet coefficients and BP neural network is proposed in this paper. The method of forecasting of load sequences has been replaced by the method of forecasting of wavelet coefficients. The wavelet coefficients on different scales are forecasted by BP neural networks respectively after wavelet detail coefficients have been dealt with by layer soft threshold. The new method combining wavelet coefficients with BP neural network is introduced in detail in this paper and the example about the method is given as well.
Keywords :
backpropagation; load forecasting; neural nets; power engineering computing; wavelet transforms; BP neural network; power system; short-term load forecasting; wavelet coefficients; Continuous wavelet transforms; Discrete wavelet transforms; Load forecasting; Neural networks; Power systems; Predictive models; Prototypes; Wavelet analysis; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
DOI :
10.1109/APPEEC.2009.4918868