4.3 Article

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model

Journal

Publisher

AMER INST PHYSICS
DOI: 10.1063/1.4885111

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Funding

  1. National Science Foundation [CNS-0821794]
  2. University of Colorado Boulder
  3. University of Colorado Denver
  4. National Center for Atmospheric Research
  5. National Renewable Energy Laboratory [UGA-0-41026-22, UGA-0-41026-65]
  6. U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]

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Recently, an actuator disk parameterization was implemented in the Weather Research and Forecasting (WRF) Model for large eddy simulation (LES) of wind turbine wakes. To thoroughly verify this model, simulations of various types of turbines and atmospheric conditions must be evaluated against corresponding experimental data. In this work, numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristics-such as the velocity deficit, centerline location, and wake width-as metrics for model verification, the simulations show good agreement with the observations. Notable results include a high average velocity deficit, decreasing from 73% at a downwind distance x of 1.2 rotor diameters (D) to 25% at x=6.6D, resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover, the wake width expands from 1.4D at x=1.2D to 2.3D at x=6.6D. Finally, new features-namely rotor tilt and drag from the nacelle and tower-are added to the existing actuator disk model in WRF-LES. Compared to the rotor, the effect of the tower and nacelle on the flow is relatively small but nevertheless important for an accurate representation of the entire turbine. Adding rotor tilt to the model causes the vertical location of the wake center to shift upward. Continued advancement of the actuator disk model in WRF-LES will help lead to optimized turbine siting and controls at wind farms. (C) 2014 AIP Publishing LLC.

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