Short-term prediction of wind power using EMD and chaotic theory

Due to the strong non-linear, complexity and non-stationary characteristics of wind farm power, a hybrid prediction model with empirical mode decomposition (EMD), chaotic theory, and grey theory is constructed. The EMD is used to decompose the wind farm power into several intrinsic mode function (IMF) components and one residual component. The grey forecasting model is used to predict the residual component. For the IMF components, identify their characteristics, if it is chaotic time series use largest Lyapunov exponent prediction method to predict. If not, use grey forecasting model to predict. Prediction results of residual component and all IMF components are aggregated to produce the ultimate predicted result for wind farm power. The ultimate predicted result shows that the proposed method has good prediction accuracy, can be used for short-term prediction of wind farm power.

► A hybrid model for wind power forecasting is suggested. The model is based on EMD, chaotic theory, and grey theory. ► EMD is used to decompose wind farm power into several intrinsic mode function (IMF) components and one residual component. ► The grey forecasting model is used to predict the residual component. ► Grey forecasting or chaotic prediction method is used to predict the IMF components for their different characteristics. ► Prediction results of residual component and all IMF components are aggregated to produce the ultimate prediction.