Hourly wind speed prediction based on wavelet decomposition and statistical model
In order to improve the accuracy of hourly wind speed prediction,a hybrid model based on wavelet decomposition combined with AR model (WD-AR) was proposed,in which the wind speed sequence was first decomposed in a multilayered manner by wavelet decomposition technique.Then the auto regressive theory was used to build a prediction model for each layer.Finally,the wind speed prediction values could be yielded by the linearity superposition for each prediction result.Real data on wind speed from Hexi were used to verify the model.The results show that the WD-AR was greatly improved when compared with AR model,the prediction accuracy of the model parameters,i.e.R,RMSE and MAPE were 0.89,0.36 and 27％.The conclusion here is that the WD-AR model is able to improve the accuracy of hourly wind speed prediction and has better predictive ability.
NETL
NSTL
万方数据
维普
