Minimum-cost numerical prediction system for wind power in Uruguay, with an assessment of the diurnal and seasonal cycles of its quality


  • Gabriel Cazes Boezio Universidad de la República, Uruguay
  • Sofia Ortelli Usinas y Trasmisiones Eléctricas, Montevidéu



NWP, Diurnal cycle, Seasonal cycle


This work presents the results of a numerical forecast system of minimum cost for the electric power generated by wind farms in Uruguay. By keeping at minimum levels both the computational costs and the complexity of the empirical corrections of the numerical results, we obtain a benchmark for the forecast skill of more complex forecast systems, that is easily available during their calibration stages and operative functioning. The work also aims to explore the diurnal and seasonal cycle of the forecasts quality. It is found that this simple forecast system produces very good results, albeit the dependencies of the forecast skill and errors respect to the season of the year and the time of the day are distinguishable. It is also found that it is necessary to take into account the diurnal and the seasonal cycles during the calibration of the empirical corrections. The good results of this simple technique might had been possible due to the relative smooth topography of Uruguay.


Download data is not yet available.

Author Biography

Gabriel Cazes Boezio, Universidad de la República, Uruguay

IMFIA, Profesor Adjunto


BHARGAVA; KALNAY, E.; CARTON, J. A. Estimation and correction of the gfs systematic errors. In: AMERICAN METEOROLOGICAL SOCIETY MEETING, 97., 2017, Keystone. Anais eletrôni cos... Boston: American Meteorological Society, 2017. Availavable at: .

FREDIANI, M.; HACKER, J. P.; ANANGNOSTOU, E. N.; HOPSON, T. Evaluation of pbl parameterizations for modeling surface wind speed during storms in the northeast united states. weather and forecasting. Weather and Forecasting, v. 31, p. 1511-1528, 2016.

GARCíADIEZ, M.; FERNáNDEZ, J.; FITA, L.; YAGüE, C. Seasonal dependence of wrf model biases and sensitivity to pbl schemes over europe. Quarterly Journal of the Royal Meteorological Society, v. 139, p. 501-514, 2013.

DE MELLO, S.; BOEZIO, G. C.; GUTIERREZ, A. Operational wind energy forecast with power assimilation. In: INTERNATIONAL CONFERENCE ON WIND ENERGY, 14., 2015. Porto Alegre, RS, 2015.

ORTELLI, S.; BOEZIO, G. C. Construction of empirical speed-power curves in wind farms installed in uruguay. application to real-time data quality control and estimation of possible generation in case of restriction. In: X WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA, 10., 2017. Santa Maria, RS, 2017. Available at: .

SEIDEL, D. J.; CHI, O. A.; LI, K. Estimating climatological planetary boundary layer heights from radiosonde observations: Comparison of methods and uncertainty analysis. J. of Geophysical Research, v. 115, p. D16113, 2010.



How to Cite

Boezio, G. C., & Ortelli, S. (2018). Minimum-cost numerical prediction system for wind power in Uruguay, with an assessment of the diurnal and seasonal cycles of its quality. Ciência E Natura, 40, 205–210.

Most read articles by the same author(s)