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The variability of wind power will be an increasing challenge for the power system as wind penetration grows and thus needs to be studied. In this paper a model for generation of hourly aggregated wind power time series is described and evaluated. The model is based on MERRA reanalysis data and information on wind energy converters in Sweden. Installed capacity during the studied period (2007–2012) increased from around 600 to over 3500 MW. When comparing with data from the Swedish TSO, the mean absolute error in hourly energy was 2.9% and RMS error was 3.8%. The model was able to adequately capture step changes and also yielded a nicely corresponding distribution of hourly energy. Two key factors explaining the good results were the use of a globally optimised power curve smoothing parameter and the correction of seasonal and diurnal bias. Because of bottlenecks in the Swedish transmission system it is relevant to model certain areas separately. For the two southern areas the MAE were 3.7 and 4.2%. The northern area was harder to model and had a MAE of 6.5%. This might be explained by a low installed capacity, more complex terrain and icing losses not captured in the model.
Olauson et al. (Fri,) studied this question.