Can synoptic drivers explain rotor‐area wind conditions and predict energy output?

Abstract

AbstractSynoptic‐scale weather patterns are an important driver of wind speed at turbine hub height, but wind energy generation is also affected by the wind profile across the rotor. In this research, we use a 6‐year record of hourly profile measurements at the Eolos Wind Research Station in Minnesota, USA, to investigate whether synoptic weather patterns can provide information about rotor‐area characteristics in addition to hub‐height wind speed. We use sea level pressure data from the MERRA‐2 reanalysis to classify synoptic patterns at the Eolos site into 15 synoptic types and use the Eolos wind profile data to create mean hourly and mean monthly values of wind speed and turbulence intensity at hub height (80 m), and wind speed shear, wind direction shear, and the potential temperature gradient across the rotor (30–129 m), for each synoptic type. Using a simple linear regression model, we find that, at monthly time scales, wind speed, turbulence intensity, and wind speed shear across the rotor are the most important variables for predicting monthly wind energy output from the Eolos turbine. Regression models using the original Eolos data and the derived synoptic types capture about 64% and 55% of the variance in monthly energy output, respectively. When fewer than the full 6 years of observations are used to fit the regression model, however, predictions using the synoptic types slightly outperform predictions using the Eolos observations. These results suggest that seasonal energy projections may be enhanced by incorporating wind profile measurements with synoptic‐scale drivers.