Successful integration of wind power into power systems can be facilitated through better understanding of future uncertainty in wind power generation. This paper explores a new approach to characterizing this uncertainty using measures of the variability in the wind speeds predicted at multiple grid points in a Numerical Weather Prediction (NWP) system. This approach is compared to the traditional approach of using the spread from an NWP ensemble by using two measures of uncertainty; forecast errors in single time-series forecasts and observed temporal variability. Results show that the multiple grid point approach has a comparable skill level to NWP ensembles for predicting these uncertainty measures and in particular, demonstrates very good skill in predicting large forecast errors. These results also provide a positive evaluation of a terrain standardization method described in a companion paper. A possible extension of this work is to combine the multiple grid point approach with NWP ensembles to improve uncertainty characterization.
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