Optimal combination of wind power forecasts

We consider wind power forecasts based on a number of different meteorological forecasts originating from three different global meteorological models. Wind power forecasts based on these meteorological forecasts have fairly similar performance. However, in the paper, we show that the wind power forecast errors are relatively uncorrelated. For this reason, we can combine the forecasts and obtain a final forecast which performs better than any of the individual forecasts. Optimal weights are found based on the bias of the individual forecasts and the variance–covariance matrix of the individual forecast errors. In the paper, we show that quite significant improvements can be obtained using only a few different meteorological forecasts.