Short-term wind speed forecasting for wind farm based on empirical mode decomposition

As an important renewable energy form, wind power obtains rapid development recently. More advanced accurate and reliable techniques for wind speed forecasting are required. It can reduce the disadvantageous impact to the power system. According to the outstanding feature of EMD algorithm, this paper presents a new technique for wind speed forecasting based on Empirical Mode Decomposition (EMD) and ARMA. EMD is a new method for analyzing nonlinear and non-stationary signal. It is an adaptive wavelet decomposition strategy. We make full use of the characteristic of the EMD and the ARMA in the EMD-ARMA model. Actual wind speed data are used to test the approach. It concludes that the EMD-ARMA model is an effective method in wind speed forecasting.