Combined time‐varying forecast based on the proper scoring approach for wind power generation

Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind‐power combined forecasts are relatively limited. Here, based on forecasting error distribution, a proper scoring approach is applied to combine plausible models to form an overall time‐varying model for the next day forecasts, rather than weights‐based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction.