LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics

Abstract

Wake meandering disturbs the stability of the far wake field and thus increases the fatigue loads of downstream wind turbines. A deep understanding of this phenomenon under atmospheric boundary layers and its relation to the structural loads helps to better model the dynamic wake and alleviate adverse effects. A large eddy simulation and an actuator line model are introduced in the present work to simulate the wake field and aerodynamic loads of wind turbines with different longitudinal spacings. By temporal filtering and the gaussian fitting method, the wake center and edge are precisely defined, and the dynamic wake characteristics, including the wake width, oscillation amplitude, and frequency, are described based on the statistical data of the simulated flow field. Results reveal that the wake meandering is caused by both large-scale atmospheric structure and the unstable vortex shed from the rotor because two distinct meandering frequency ranges are detected. As the atmosphere instability increases, the former becomes the dominant inducing factor of the meandering movements. Further, the analysis of the correlation between the inflow characteristics and the wake deflection shows that the Taylor hypothesis remains valid within a distance of over a thousand meters under both neutral and convective boundary layers, proving the feasibility of using this hypothesis for wake evolution prediction. In addition, our study shows that the fluctuation of blade root moment and yaw moment is significantly intensified by the meandering wake, with their standard deviation is augmenting by over two times under both atmospheric conditions. The power spectrum illustrates that the component with rotor rotation frequency of the former is sensible to the wake effect, but for the latter, the power spectrum density of all frequencies is increased under the meandering wake. These indicate that the fatigue loads will be underestimated without considering the wake meandering effect. Moreover, the high correlation between the wake deflection and yaw moment implies that we can predict yaw moment based on the incoming flow information with high accuracy.