Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 3
Articles | Volume 14, issue 3
https://doi.org/10.5194/amt-14-2095-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-2095-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 3
Research article
 | 
16 Mar 2021
Research article |  | 16 Mar 2021

LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 2: Applications to lidar measurements of wind turbine wakes

Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo

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Cited articles

Aitken, M. L. and Lundquist, J. K.: Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar, J. Atmos. Ocean. Tech., 31, 1529–1539, https://doi.org/10.1175/JTECH-D-13-00218.1, 2014. a
Argyle, P., Watson, S., Montavon, C., Jones, I., and Smith, M.: Modelling turbulence intensity within a large offshore wind farm, Wind Energy, 21, 1329–1343, https://doi.org/10.1002/we.2257, 2018. a
Ashton, R., Iungo, G. V., Viola, F., Gallaire, F., and Camarri, S.: Hub vortex instability within wind turbine wakes: Effects of wind turbulence, loading conditions and blade aerodynamics, Phys. Rev. Fluids, 1, 073603, https://doi.org/10.1103/PhysRevFluids.1.073603, 2016. a
Aubrun, S., Torres Garcia, E., Boquet, M., Coupiac, O., and Girard, N.: Wind turbine wake tracking and its correlations with wind turbine monitoring sensors. Preliminary results, J. Phys. Conf. Ser., 753, 032003, https://doi.org/10.1088/1742-6596/753/3/032003, 2016. a, b
Barnes, S. L.: A Technique for Maximizing Details in Numerical Weather Map Analysis, J. Appl. Meteorol., 3, 396–409, https://doi.org/10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2, 1964. a
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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. Various lidar scans performed during a field campaign for a wind farm in complex terrain are analyzed. The results endorse the application of the LiSBOA for lidar-based wind resource assessment and farm diagnosis.
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