Assessment of wind resource considering local turbulence based on data acquisition with SODAR

Abstract

This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.