Spatial variability of turbulence in a finite sized wind farm: a study using wavelet analysis

In this talk, we investigate a spatial variability of length scales in a 3 × 3 wind turbine array driven by a neutral atmospheric boundary layer precursor. The study is performed with a spectral element LES code with a near-wall modeling framework and an actuator line model to represent the effect of rotating wind turbine blades. We have utilized wavelet transforms on the spatio-temporal turbulent signals and studied the intermittency of the energy spectra, as well as their correlations along the wall normal direction. The goal of the study is to provide a fundamental understanding of the spatial variability of the turbulent structures in the flow and its modulation by wind turbines. Large scale well correlated organizations with an order of magnitude larger than turbine rotor diameter are shown to be present above the wind turbine rotors, contributing towards the downdrafts which are also responsible for wind turbine power. The understanding of spatial variability of the turbulent structures and their correlations will be useful in increasing the capability of wind farms by adding turbines optimally to extract power from the modulated energetic structures.