Impact of atmospheric turbulence on wind farms sited over complex terrain

This article investigates the impact of atmospheric turbulence on wind farms in mountainous regions using Scale-Adaptive Large-Eddy Simulation (SALES) combined with the immersed boundary method. An array of 25 Gaussian hills was considered to mimic the mountainous terrain, and three cases were simulated: atmospheric boundary layer flow over complex terrain, 25 full-scale turbines positioned on hilltops, and 125 full-scale turbines positioned across the mountainous landscape. These simulations captured the intrinsic spatial inhomogeneity caused by the complex topographic features of mountainous terrain, challenging the assumption of horizontally homogeneous atmospheric turbulence. This study emphasizes the significance of velocity gradient dynamics and stresses on surface mounted obstacles to evaluate data quality and uncertainty. However, it also considered more detailed comparisons with other methods, validation of topographic impact using experimental work with windbreak and isolated hill, and a comprehensive analysis of the results. The findings include significantly enhanced power production at hilltop turbine locations as compared to homogeneous terrain. Although wind turbines in windward and leeward directions experienced a reduced power output in the near-wake region, these local losses recovered globally by the enhanced vertical energy entrainment from higher altitudes. Additionally, the presence of mountains indicated an increase in the power density by up to five times compared to flat terrain. A wavelet-based autoencoder demonstrated superior performance in separating the harmonic component of time-varying mean and subgrid-scale fluctuations compared to constant and Gaussian weighting kernels. The study suggests wavelet filtering as a promising technique for subgrid-scale modeling, offering improvements not only in wind energy applications but also in other turbulence flow scenarios.