Short-term wind power forecasting with combined prediction based on chaotic analysis

With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind power forecasts. In this paper, models for short-term wind power prediction in large wind farms are discussed. The analysis of modeling with low dimensions nonlinear dynamics indicates that wind power time series have chaotic characteristics and wind power can be predicted in the short-term. The wind power prediction models are built with phase space reconstruction method and the combination model with different embedding dimensions is tested.