skip to main content


Title: Investigating wind turbine impacts on near-wake flow using profiling Lidar data and large-eddy simulations with an actuator disk model

In this study, 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 (VD) 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, σ u, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σ u , 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 atmore » 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 VD characteristics, albeit with smaller magnitudes than observed, while σu 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.« less
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [6]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Iowa State Univ., Ames, IA (United States)
  3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of California, Berkeley, CA (United States)
  4. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  5. National Center for Atmospheric Research, Boulder, CO (United States)
  6. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 1941-7012; JRSEBH
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Journal of Renewable and Sustainable Energy
Additional Journal Information:
Journal Volume: 7; Journal Issue: 4; Related Information: Journal of Renewable and Sustainable Energy; Journal ID: ISSN 1941-7012
American Institute of Physics (AIP)
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
17 WIND ENERGY; 42 ENGINEERING; LIDAR; wind turbines; automatic speech recognition systems; large eddy simulations; computer modeling
OSTI Identifier: