Quantifying Wind Turbine Wake Effects on the Downwind Environment in Different Boundary Layer Conditions by Analyzing LIDAR and Surface Flux Spectra

Wind energy is an increasingly popular method to meet rising energy demands, so much so that turbines are now a common sight in many locations across the US. Wind turbine deployment is especially prolific in agricultural regions as the climatologies of the regions are productive and farmers receive consistent income from land leases. However, the interactions between turbines, their local environment, and nearby crops are not well understood. Downwind of the turbines, turbine wake regions experience wind shear, increased turbulence, and momentum deficits. A distinctive peak in the power spectrum occurs in wind tunnel measurements of turbine wakes. But this peak has not been clearly observed in the field simultaneously in both surface station and wind measurements at the turbine rotor level.

Prior studies applied wind-profiling lidars to study wind turbine wakes in different stability regimes or have analyzed surface flux station data in and out of waked conditions. We use both the lidar and surface flux data from the 2011 Crop Wind Energy Experiment (CWEX-11) to provide new insights into the vertical extent of the wake impacts. We first quantify the significance of turbine wake signatures in lidar data in different atmospheric stability conditions. Next, we apply spectral analysis to the surface flux data for these case studies in a range of stability conditions. By combining surface flux and lidar data, we can understand the net effect of turbine wakes and their propagation. Further, this method helps link surface fluxes to wake structures that occur in a range of conditions defined by atmospheric stability, wind speed, and wind direction.

Our results show that wakes are most clearly defined in stable conditions, that a distinct wake signature occurs in power spectra, and that wake signatures propagate vertically outside of the elevations of the turbine rotor disk.