Advancements in Wind Turbine Wake Modelling using 3D scanning LiDAR measurements

Abstract This study investigates the capability of numerical models to estimate wind turbine wake characteristics under varying atmospheric stability conditions using three-dimensional wind data obtained from a scanning LiDAR. The LiDAR was set to measure the wake of a 3.8 MW test turbine up to 5 rotor diameters downstream from the hub, for a period of four months, capturing both vertical and horizontal wake profiles. These measurements were compared against results from the parabolized Navier-Stokes (PNS) solver FarmFlow (FF) and Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations. The results showed a good correlation between the measured wake profiles and the simulation results for both models. The URANS model effectively captured horizontal wake profiles, including detailed features such as double-Gaussian profiles and turbine misalignment effects, performing best under stable atmospheric conditions. However, URANS had limitations in accurately matching vertical profiles, especially under neutral atmospheric conditions. The FarmFlow model provided reliable estimates without tuning, demonstrating good agreement with measurements for all conditions, though it underestimated the wake strength in neutral atmospheric conditions. This study provides insights into atmospheric and wind turbine wake measurements as well as into wake models capabilities, bringing forward directions for wind turbine wake simulations improvements.