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Wind speed modelling and prediction has been gaining importance because ofits significant roles in various stages of wind energy management. In thispaper, we propose a hybrid model, based on wavelet transform to improve theaccuracy of the short-term forecast. The wind speed time series are split intovarious frequency components using wavelet decomposition technique, and eachfrequency components are modelled separately. Since the components associatedwith the high- frequency range shows stochastic nature, we modelled them withautoregressive (AR) method and rest of low-frequency components modelled withsupport vector machine (SVM). The results of the hybrid method show a promisingimprovement in accuracy of wind speed prediction compared to that ofstand-alone AR or SVM model.

A Wavelet, AR and SVM based hybrid method for short-term wind speed prediction