Short-term Prediction Of Wind Speed Based On Wavelet-Autoregressive Integrated Moving Average Model

Short-term prediction of wind speed is important for utility of wind power. Based on accurate prediction of wind speed, the wind generating plan can be efficiently accommodated to mitigate the impaction from instable wind power on wind grids. The wind speed data from a wind farm measured by 10 minutes is forecasted for short-term based on traditional rolling ARIMA model. On account of non-stationary of the original sequence and outliers, the original data are decomposed and reconstructed by wavelet, then the reconstructed part and the detail part are cumulated to predict the future wind speed, by a comparative anglicizing, the predicting with wavelet-ARIMA model is superior to the traditional rolling one.