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A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height
Weather and Forecasting
  • Adam Joshua Deppe, Iowa State University
  • William A. Gallus, Jr., Iowa State University
  • Eugene S. Takle, Iowa State University
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Publication Version
Published Version
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The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with different planetary boundary layer (PBL) schemes showed little spread among the individual ensemble members for forecasting wind speed. A second configuration using three random perturbations of the Global Forecast System model produced more spread in the wind speed forecasts, but the ensemble mean possessed a higher mean absolute error (MAE). A third ensemble of different initialization times showed larger model spread, but model MAE was not compromised. In addition, postprocessing techniques such as training of the model for the day 2 forecast based on day 1 results and bias correction based on observed wind direction are examined. Ramp event forecasting was also explored. An event was considered to be a ramp event if the change in wind power was 50% or more of total capacity in either 4 or 2 h or less. This was approximated using a typical wind turbine power curve such that any wind speed increase or decrease of more than 3 m s21 within the 6–12 m s21 window (where power production varies greatly) in 4 h or less would be considered a ramp. Model MAE, climatology of ramp events, and causes were examined. All PBL schemes examined predicted fewer ramp events compared to the observations, and model forecasts for ramps in general were poor.

This article is from Weather and Forecasting 28 (2013): 212, doi: 10.1175/WAF-D-11-00112.1. Posted with permission.

Copyright Owner
American Meteorological Society
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Citation Information
Adam Joshua Deppe, William A. Gallus and Eugene S. Takle. "A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height" Weather and Forecasting Vol. 28 Iss. 1 (2013) p. 212 - 228
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