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/content/aip/journal/jrse/7/4/10.1063/1.4928873
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/content/aip/journal/jrse/7/4/10.1063/1.4928873
2015-08-27
2016-09-27

Abstract

Wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits ( ) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, , likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake characteristics, albeit with smaller magnitudes than observed, while values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.

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