基于小波变换和时间序列法考虑随机分量的短期风速预测

Short-term Wind Speed Prediction Based on Wavelet Transform and Time Series Method and Random Components

为提高短期风速预测的准确性,本文结合小波变换和时间序列法,考虑随机分量进行短期风速预测.利用小波变换对风速时间序列分层,将高频变化的风速时间序列利用自回归滑动平均模型(ARMA)进行预测,低频变化的风速时间序列利用持续法进行预测,最后将预测结果叠加并通过随机阵列对结果进行修正.通过实例验证以及与时间序列方法进行对比,结果证明该方法的预测精度和预测稳定性都有所提高.

In order to improve the accuracy of short-term wind speed prediction,this paper combines the wavelet transformation and time series method and takes random components into consideration for short-term wind speed prediction.The wavelet transformation was used to stratify the wind speed time series.After that,the high-frequency-varied wind speed time series were predicted by time series Autoregressive Moving Average Model (ARMA),and the low-frequency-varied wind speed time series were predicted by time series continuous method.The final prediction results were the combination of the above two components,and they were further refined by a method of random array.The example verification and the comparison with the prediction by time series method show that the prediction accuracy and prediction stability of the method are significantly improved.