Articles | Volume 8, issue 1
Adv. Sci. Res., 8, 143–147, 2012
https://doi.org/10.5194/asr-8-143-2012
Adv. Sci. Res., 8, 143–147, 2012
https://doi.org/10.5194/asr-8-143-2012

  27 Jul 2012

27 Jul 2012

The influence of the new ECMWF Ensemble Prediction System resolution on wind power forecast accuracy and uncertainty estimation

S. Alessandrini et al.

Cited articles

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Alessandrini, S., Pinson, P., Hagedorn, R., Decimi, G., and Sperati, S.: An application of ensemble/multi model approach for wind power production forecasting, Adv. Sci. Res., 6, 35–37, https://doi.org/10.5194/asr-6-35-2011, 2011.
Cali, Ue., Lange, B., Dobschinski, J., Kurt, M., Moehrlen, C., and Ernst, B.: Artificial neural network based wind power forecasting using a multi-model approach, 7th International Workshop on Large Scale Integration of Wind Power and on Transmission Networks for Offshore Wind Farms, Madrid, 2008.
ECMWF internal report: Horizontal resolution increase (www.ecmwf.int), 2010.
Giebel, G., Brownsword, R., Kariniotakis, G., Denhard, M., and Draxl, C.: The State of the Art in Short-Term Prediction of Wind Power, Anemos.plus deliverable report, 2011.