Comparing scanning lidar configurations for wake measurements based on the reduction of associated measurement uncertainties

Abstract

Abstract Scanning lidars are increasingly being used for new measurement applications, such as wake measurements. This type of measurement requires an uncertainty quantification, and the setup of such instruments should ideally be planned to minimize the overall measurement uncertainty. Based on a previous experimental study, we quantify the overall uncertainty for a scanning lidar wake measurement campaign by analyzing the pointing accuracy for distinct configuration scenarios. The selected scenarios are based on a single ground-based scanning lidar measuring the downstream flow, a scanning lidar mounted on the turbine’s nacelle and, finally, two scanning lidars measuring dual-Doppler points within the wake. The results for each configuration are presented in terms of the overall uncertainty and measurement outputs provided from these setups. In a case study using the experimental dataset to compare ground- and nacelle-based configurations, we find that – under slightly stable conditions at 5D downstream – the overall radial wind speed uncertainty, normalized by reference wind speed without counting the sample size uncertainty, decreases on average from 2.78% for the ground-based lidar to 1.33% for the nacelle-based setup. Another advantage of the nacelle-based setup is the potentially larger sample size, as it can measure multiple downstream distances at once. The dual-lidar configuration has advantages in providing horizontal wind speed and direction instead of radial wind speed components only, hence reducing uncertainties associated with wind direction. However, this comes with the cost of fewer measured points to be compared with an engineering wake model and less flexibility to position the lidars, since their relative spatial position impacts the uncertainty. In summary, the presented methodology can benefit the best selection of scanning lidar configuration for a particular application, here demonstrated for wake measurements, proving the user with an estimation of the overall measurement uncertainty and, most importantly, the sensitivity of each parameter.