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Abstract Optimization of a wind farm’s layout is a strategic task to reduce wake effects on downstream turbines, thus maximizing wind power harvesting. However, downstream evolution and recovery of each wind turbine wake are strongly affected by the characteristics of the incoming atmospheric boundary layer (ABL) flow, such as the vertical profiles of the mean wind velocity and the turbulence intensity, which are in turn affected by the ABL thermal stability. Therefore, the characterization of the variability of wind turbine wakes under different ABL stability regimes becomes fundamental to better predict wind power harvesting and to improve wind farm efficiency. To this aim, wind velocity measurements of the wake produced by a 2-MW Enercon E-70 wind turbine were performed with three scanning Doppler wind lidars. One lidar was devoted to the characterization of the incoming wind—in particular, wind velocity, shear, and turbulence intensity at the height of the rotor disc. The other two lidars performed volumetric scans of the wind turbine wake under different atmospheric conditions. Through the evaluation of the minimum wake velocity deficit as a function of the downstream distance, it is shown that the ABL stability regime has a significant effect on the wake evolution; in particular, the wake recovers faster under convective conditions. This result suggests that atmospheric inflow conditions, and particularly thermal stability, should be considered for improved wake models and predictions of wind power harvesting.
Iungo et al. (Fri,) studied this question.