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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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Volume 1, issue 1
Wind Energ. Sci., 1, 41–53, 2016
https://doi.org/10.5194/wes-1-41-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Wind Energ. Sci., 1, 41–53, 2016
https://doi.org/10.5194/wes-1-41-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 Apr 2016

Research article | 11 Apr 2016

Full-field assessment of wind turbine near-wake deviation in relation to yaw misalignment

Juan José Trujillo et al.
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Cited articles  
Aitken, M. L., Banta, R. M., Pichugina, Y. L., and Lundquist, J. K.: Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data, J. Atmos. Ocean. Tech., 31, 765–787, https://doi.org/10.1175/JTECH-D-13-00104.1, 2014.
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Dörenkämper, M.: An investigation of the atmospheric influence on spatial and temporal power fluctuations in offshore wind farms, PhD thesis, University of Oldenburg, Dr. Hut-Verlag, Munich, Germany, 168 pp., 2015.
España, G., Aubrun, S., Loyer, S., and Devinant, P.: Spatial study of the wake meandering using modelled wind turbines in a wind tunnel, Wind Energy, 14, 923–937, https://doi.org/10.1002/we.515, , 2011.
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We present the analysis of the trajectories followed by the wind, in the immediate vicinity, behind an offshore wind turbine and their dependence on its yaw misalignment. We apply wake tracking on wind fields measured with a lidar (light detection and ranging) system located at the nacelle of the wind turbine and pointing downstream. The analysis reveals discrepancies of the estimated mean wake paths against theoretical and wind tunnel experiments using different wake-tracking techniques.
We present the analysis of the trajectories followed by the wind, in the immediate vicinity,...
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