Forecasting wind power production from a wind farm using the RAMS model
- 1Institute of Atmospheric Sciences and Climate of the Italian National Council of Research, ISAC-CNR, UOS of Lamezia Terme, zona Industriale Comparto 15, 88046 Lamezia Terme, Italy
- 2Wind Energy Department, Danish Technical University, Frederiksborgvej 399, 4000-Roskilde, Denmark
- 3ISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, Italy
Abstract. The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading.
This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography around the site is complex and the horizontal resolution of the wind forecast has an important role.
To explore this point we compared the performance of two 48 h wind power forecasts using the winds predicted by the Regional Atmospheric Modeling System (RAMS) for the year 2011. The two forecasts differ only for the horizontal resolution of the RAMS model, which is 3 km (R3) and 12 km (R12), respectively. Both forecasts use the 12 UTC analysis/forecast cycle issued by the European Centre for Medium range Weather Forecast (ECMWF) as initial and boundary conditions.
As an additional comparison, the results of R3 and R12 are compared with those of the ECMWF Integrated Forecasting System (IFS), whose horizontal resolution over Central Italy is about 25 km at the time considered in this paper. v Because wind observations were not available for the site, the power curve for the whole wind farm was derived from the ECMWF wind operational analyses available at 00:00, 06:00, 12:00 and 18:00 UTC for the years 2010 and 2011. Also, for R3 and R12, the RAMS model was used to refine the horizontal resolution of the ECMWF analyses by a two-years hindcast at 3 and 12 km horizontal resolution, respectively.
The R3 reduces the RMSE of the predicted wind power of the whole 2011 by 5% compared to R12, showing an impact of the meteorological model horizontal resolution in forecasting the wind power for the specific site.