Optimal combination of wind power forecasts

Abstract

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. Copyright © 2007 John Wiley & Sons, Ltd.

Wind power forecasting : state-of-the-art 2009.

“…Another method that was studied to improve performance involved combining several meteorological forecasts [181]. The authors showed that a simple optimal and self-calibrating procedure for the combination of a few forecasts can easily improve the forecast error.…”

“…CENER also developed a technique for combining different forecasts that is able to improve the performance of the individual forecasts for a single wind farm [181].…”

“…The authors of [181] showed that combining several NWP forecasts can easily improve the forecast error.…”

“…One example is the procedure presented by Nielsen et al [181], already mentioned in Section 4.1.2.2. This multi-model ensemble approach is the one used by the WEPROG WPF system, as described in Section 4.2.1.9.…”

A quick guide to wind power forecating : state-of-the-art 2009.

“…The authors of [62] showed that combining a few number of NWP forecasts can easily improve the forecast error.…”