Dynamic harmonic regression approach to wind power generation forecasting

Time series models provide a very flexible approach to nonstationary time series analysis. In this paper, a statistical framework based upon dynamic harmonic regression for examining modal behavior, trend extraction and forecasting is provided. Both, synthetic and observational data are used to assess the performance of the model. The practical application of this technique is tested on wind power generation measurements under various conditions of data acquisition.