Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals

Abstract. This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with field reconstruction techniques. The first approach consists incorporating flow field, obtained from nacelle lidars, into random, homogeneous Gaussian turbulence fields generated using Mann spectral tensor model. second imposes deficit time series, which are derived fitting a bivariate shape function to observations on fields. approaches numerically evaluated virtual simulator, scans dynamic meandering (DWM) model, i.e., target lidar-reconstructed then input aeroelastic simulations DTU 10 MW carrying out validation analysis. power and predicted fields, exhibit high correlation corresponding simulations, thus reducing statistical uncertainty (realization-to-realization) inherent engineering models such as DWM We quantify reduction in loads' factor between 1.2 5, depending component, when compared model results. Finally, we show that number lidar-scanned points inflow size probe volume critical aspects reconstructed power, predictions.