Investigation on the recovery mechanisms of wind turbine wakes through statistical analysis of LiDAR measurements and RANS simulations

The recovery of wind turbine wakes is the result of the interaction between the incoming atmospheric turbulence, the wake-generated turbulence, and the vorticity structures shed by the blades. A deeper understanding of such intertwined mechanisms is needed to improve the accuracy of wake models. In this study, LiDAR measurements of wind turbine wakes collected under a vast breadth of inflow conditions are analyzed through the LiDAR Statistical Barnes Objective Analysis (LiSBOA) tool to retrieve single-point statistics of the streamwise velocity. The results show that the blade rotation has a significant effect on the statistical properties of turbulence. The mean velocity field is used as a reference for tuning the turbulent eddy viscosity of an in-house-developed Pseudo-2D RANS model. The turbulent eddy viscosity increases in convective conditions compared to stable conditions. A secondary increasing trend of the turbulent eddy viscosity as a function of the turbine thrust coefficient is also captured for moderately turbulent inflows. Interestingly, this trend is reversed for incoming wind conditions with higher turbulence intensity. We speculate that this unexpected flow feature is linked to the action of the turbine blades on the incoming turbulent coherent structures.