Аннотация
AbstractEnergy traders and decision makers need accurate wind power forecasts. For this purpose numerical weather predictions (NWP) are often statistically post-processed to correct systematic errors. This requires a data set of past forecasts and observations which is often limited by frequent NWP model enhancements that change the statistical model properties. Reforecasts that recompute past forecast with a recent model provide considerably longer data sets but usually use weaker setups than operational models. This study tests the reforecasts from the National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) for wind power predictions. The NOAA reforecast performs clearly worse than the ECMWF reforecast, the operational ECMWF deterministic and ensemble forecasts, and a limited area model of the Austrian weather service (ZAMG). On the contrary, the ECMWF reforecast has, of all tested models, the smallest squared errors and one of the highest financial values in an energy market.
