Study of power system load forecast based on wavelet neural networks
Jiang Shi-fang · Dianli zidonghua shebei · 2003
The characters of WNN(Wavelet Neural Network)are analyzed and the advantages and disadvantages of its applications in power system load forecast are studied.By theoretic analyzing the network structures and algorithms of WNN and BP Net and comparing the forecast results of power load,it is pointed out that WNN is suitable for forecasting the variable signals.When they have same number of network node,WNN is better than BP NET in forecast accuracy.Therefore,WNN may be applied to reduce the number of hidden node.It is also indicated that current WNN has a poor convergence performance because of adopting the random initialization method and gradient training algorithm of traditional BP NET.