Calibration of Mean Wind Profiles Using Wind Lidar Measurements

This paper explores the applicability of Lidar wind measurements for the calibration of mean wind profiles depending on the extension in time and space of the available measurements. Starting from logarithmic wind speed profiles corresponding to different site conditions, pseudo-experimental wind speed profiles are generated artificially by adding a zero-mean Gaussian-distributed noise, representative of realistic measurement errors. Then, a least-square fitting procedure is applied to identify the roughness length and the zero-plane displacement. The results obtained show an increase in the scatter of the estimated parameters of the logarithmic law with increasing elevation of the lowest measurement point. Then, a parametric study is developed to analyse the influence of the number of available experimental profiles on the uncertainty associated with the estimated logarithmic law parameters. Based on the results obtained, it can be pointed out that the availability of measurements at low elevations is essential to identify the logarithmic mean wind profile using a reasonable number of observations.