Short-Term Wind Speed and Output Power Forecasting Based on WT and LSSVM

Wind speed and output power forecasting is very important to the utilization of wind energy. In order to improve the forecast precision, a forecasting method based on wavelet transform (WT) and least square support vector machine (LSSVM) is proposed in this paper. The wind speed time series was decomposed into different frequency components. The different LSSVM models to forecast the high frequency and low frequency are built up. These forecasting results of the different frequency bands are combined to obtain the final forecasting results. According to the power characteristics, unit efficiency and the operate condition of the generators, the short-term output power forecasting on the wind farm can be obtained.