Preprints
https://doi.org/10.5194/amt-2020-228
https://doi.org/10.5194/amt-2020-228

  31 Aug 2020

31 Aug 2020

Review status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part II: Applications to synthetic and real LiDAR data of wind turbine wakes

Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo Stefano Letizia et al.
  • Wind Fluids and Experiments (WindFluX) Laboratory, Mechanical Engineering Department, The University of Texas at Dallas, 800 W Campbell Rd, 75080 Richardson, TX, USA

Abstract. The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in Letizia et al., is a procedure for the optimal design of LiDAR scans and calculation over a Cartesian grid of the statistical moments of the velocity field. The LiSBOA is applied to LiDAR data collected in the wake of wind turbines to reconstruct mean and turbulence intensity of the wind velocity field. The proposed procedure is firstly tested for a numerical dataset obtained by means of the virtual LiDAR technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind LiDAR are retrieved from the LiSBOA, then the estimated statistics are calculated showing a maximum error of about 4 % for both the normalized mean velocity and the turbulence intensity. Subsequently, LiDAR data collected during a field campaign conducted at a wind farm in complex terrain are analyzed through the LiSBOA for two different configurations. In the first case, the wake velocity fields of four utility-scale turbines are reconstructed on a 3D grid, showing the capability of the LiSBOA to capture complex flow features, such as high-speed jet around the nacelle and the wake turbulent shear layers. For the second case, the statistics of the wakes generated by four interacting turbines are calculated over a 2D Cartesian grid and compared to the measurements provided by the nacelle-mounted anemometers. Maximum discrepancies as low as 3 % for the normalized mean velocity and turbulence intensity endorse the application of the LiSBOA for LiDAR-based wind resource assessment and diagnostic surveys for wind farms.

Stefano Letizia et al.

 
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Status: closed
Status: closed
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Stefano Letizia et al.

Stefano Letizia et al.

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Short summary
The LiDAR Statistical Barnes Objective Analysis (LiSBOA) is applied to LiDAR data collected in the wake of wind turbines to reconstruct mean wind speed and turbulence intensity. This procedure is firstly tested for a numerical dataset obtained by means of the virtual LiDAR technique applied to LES data, then to data collected during a field campaign for a wind farm in complex terrain. The results endorse the application of the LiSBOA for LiDAR-based wind resource assessment and farm diagnostics.