Abstract. Atmospheric gravity waves (AGWs) are large-scale wave-like flow structures commonly generated when atmospheric flows are vertically perturbed by topographical features or meteorological phenomena. These transient phenomena can significantly affect wind turbine outputs and loads; however, their influence on wake dynamics remains poorly understood, posing challenges for accurate wind farm modeling. In this study, we perform large-eddy simulation of wind turbines operating under an atmospheric condition reconstructed by assimilating lidar measurements of AGWs. Our results show that (i) low-frequency wake meandering becomes more pronounced owing to large-scale AGW flow structures and intensified smaller-scale turbulent structures. This enhanced meandering, combined with stronger turbulent mixing, accelerates mean wake recovery. (ii) The turbulence kinetic energy (TKE) spectrum in the wake region exhibits a peak Strouhal number of approximately 0.3, although the inflow spectrum peaks at significantly lower frequencies. This observation indicates that, under AGW conditions, wake turbulence generation follows a convective instability mechanism. Notably, faster wake recovery reduces wake shear, leading to lower amplification of TKE. Power analysis for two turbines arranged in a streamwise column further highlights the dominant role of convective instabilities. Large-amplitude, low-frequency power fluctuations observed at the most upstream turbine are significantly attenuated for downstream turbines as low-frequency velocity fluctuations are suppressed in the far-wake region. These findings add further insights into wake meandering and turbulence generation, offering guidance for modeling wind turbine and farm flows under non-stationary atmospheric conditions.
Building similarity graph...
Analyzing shared references across papers
Loading...
Dachuan Feng
Tongji University
Nirav Dangi
Netherlands Organisation for Applied Scientific Research
Simon Watson
University of Manchester
Wind energy science
Delft University of Technology
Tongji University
Building similarity graph...
Analyzing shared references across papers
Loading...
Feng et al. (Mon,) studied this question.
synapsesocial.com/papers/698c1d1d267fb587c655fae3 — DOI: https://doi.org/10.5194/wes-11-395-2026
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: