Turbulence coherence in wind farms

Wind power has inherent variability across a wide range of scales due to atmospheric turbulence, and for power systems it is crucial to understand the power fluctuations of extended wind farms. Models for wind farm power fluctuations assume that turbines are passive probes of the atmospheric boundary layer, and they primarily focus on the impact of atmospheric turbulence. We employ Large Eddy Simulation (LES) to demonstrate that dynamic changes in thrust (C_T) and power (C_P) coefficients affect the coherence of velocity and power fluctuations in consecutive turbine rows. We simulated a wind farm with 28 DTU 10MW wind turbines, arranged in 7 rows and 4 columns. We consider various inflow wind speeds to examine the velocity and power coherence between turbine pairs under three scenarios: (I) a fully developed region where all turbines operate below rated power with fixed C_T and C_P, (II) the front row operates above-rated power while the downstream row operates below rated power, and (III) both rows operate above rated power.

In scenario I, the random sweeping hypothesis turbulence model by Tobin and Chamorro, JFM855, 1116-1129(2018) can effectively predict the coherence between the turbines. However, in scenario II and III, the model fails to capture the simulation results. This discrepancy arises due to the operation of above-rated turbines, with dynamically varying C_T and C_P, which have a distinctly different effect on the flow than turbines operating with fixed C_T and C_P.