可再生能源2012，Vol.30Issue(8)：42-45,49,5.
基于小波变换与 Elman 神经网络的短期风速组合预测
Short-term combination forecasting of wind speed based on wavelet transform and Elman neural network
摘要
Abstract
Accurate forecasting of wind speed is important for the economic and secure operation of wind power generation systems. In order to overcome the randomness of wind, improve the accuracy of short-term wind speed forecasting, a combination forecasting model of short-term wind speed based on wavelet transform and Elman neural network is presented in this paper. The model consists of a wavelet pre-processing module and a neural network prediction module. First, using wavelet transform, the wind speed time series is decomposed and reconstructed into the sub-sequences at different frequent band, then these sub-sequences are input into Elman networks for training and prediction, respectively. Results of the actual wind speed forecasting show, in comparison with single Elman network and ARM A method, the prediction accuracy of the combination forecasting model has greatly improved, which can be used as short-term wind speed prediction.关键词
风速预测/小波变换/Elman神经网络/组合预测Key words
wind speed forecasting/ wavelet transform/ Elman neural network/ combination forecasting分类
能源科技引用本文复制引用
姚传安,姬少龙,余泳昌..基于小波变换与 Elman 神经网络的短期风速组合预测[J].可再生能源,2012,30(8):42-45,49,5.基金项目
河南省科技攻关重点项目(112102310478). （112102310478）
