Adaptive filtering based short-term wind power prediction with multiple observation points

This paper presents a method to improve the short-term wind power prediction at a given turbine using information from numerical weather prediction (NWP) and from multiple observation points which correspond to locations of nearby turbines at a particular wind farm site. The prediction of wind power is achieved in two stages; in the first stage wind speed is predicted using our proposed method. In the second stage, wind speed to output power conversion is accomplished using our proposed power curve (PC) model based on the historical wind speed and power observations at the given wind farm. The proposed wind power prediction method is tested using real measurements and NWP data from one of the wind farm sites in Australia. The performance is compared with the persistence and Grey predictor model in terms of the mean absolute percentage error. The analysis and simulation results demonstrate that the proposed approach gives better performance.