Abstract
Abstract. The importance of wind power forecasting (WPF) is nowadays commonly recognized because it represents a useful tool to reduce problems of grid integration and to facilitate energy trading. If on one side the prediction accuracy is fundamental to these scopes, on the other it has become also clear that a reliable estimation about their uncertainty is paramount. In fact prediction accuracy is unfortunately not constant and can depend on the location of a particular wind farm, on the forecast time and on the atmospheric situation. Previous studies indicated that the spread of power forecasts derived from the Ensemble Prediction System (EPS) in use at the European Centre for Medium-Range Weather Forecast (ECMWF) could be used as indicator of a three-hourly, three days ahead, wind power forecast's accuracy. In this paper a new application of the EPS, whose horizontal resolution was increased on January 2010 from T399/T255 (60 km) to T639/T319 (32 km), shows an improvement in the results implying that the power spread has actually enough correlation with the error calculated on the deterministic forecast in order to be used as an accuracy predictor. The periods for this comparison are from January 2008 until October 2008 (T399/T255) and from January 2011 until October 2011 (T639/T319). Moreover we have focused our attention on the influence of the new EPS configuration on the performance of a deterministic WPF conducted with the ensemble mean: the results show that increasing the EPS resolution yields a single-valued WPF whose performance is comparable with that of the new ECMWF deterministic high-resolution meteorological model, whose spatial resolution increased from T799 (25 km) to T1279 (15 km).
Highlights
Short-term forecasting of wind energy production is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty require a significant commitment to meet the needs of the transmission networks operators and of other agents of the power systems and electricity markets
On the basis of these considerations, our application investigated the performances of the new resolution European Centre for Medium-Range Weather Forecast (ECMWF) deterministic and Ensemble Prediction System (EPS) models applied to the same wind farm as in previous work (Alessandrini et al, 2011), comparing them with the results obtained with the previous lower resolution versions of these two models
The performances have been evaluated with some statistical indices reported in Table 2, in which RMSE, MAE and bias are normalized by Nominal Power (NP)
Summary
Short-term forecasting of wind energy production is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty require a significant commitment to meet the needs of the transmission networks operators and of other agents of the power systems and electricity markets. On the basis of these considerations, our application investigated the performances of the new resolution ECMWF deterministic and EPS models applied to the same wind farm as in previous work (Alessandrini et al, 2011), comparing them with the results obtained with the previous lower resolution versions of these two models. The new versions have been applied to understand if it is possible to increase the performance in both wind power prediction accuracy and uncertainty estimation. Alessandrini et al.: The influence of the new ECMWF Ensemble Prediction System
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