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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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Preprints
https://doi.org/10.5194/wes-2020-73
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2020-73
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 Apr 2020

29 Apr 2020

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

Lidar measurements of yawed wind turbine wakes: characterisation and validation of analytical models

Peter Brugger1, Mithu Debnath2, Andrew Scholbrock2, Paul Fleming2, Patrick Moriarty2, Eric Simley2, David Jager2, Mark Murphy2, Haohua Zong1, and Fernando Porté-Agel1 Peter Brugger et al.
  • 1Wind Engineering and Renewable Energy Laboratory (WiRE), École Polytechnique Fedérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
  • 2National Renewable Energy Laboratory (NREL), 15013 Denver West Parkway, Golden, Colorado, 80401, USA

Abstract. Wake measurements of a scanning Doppler lidar mounted on the nacelle of a yawed full-scale wind turbine are used for the characterization of the wake flow and the validation of analytical wake models. Inflow scanning Doppler lidars, a meteorological mast and the data of the wind turbine control system complemented the set-up. Results showed an increase of the wake deflection with the yaw angle that agreed with two of the three compared models. For yawed cases, the predicted power of a waked downwind turbine estimated by the two previously successful models had an error of 17 % and 24 % compared to the SCADA data and 12 % and 13 % compared to the power estimated from the Doppler lidar measurements. Shortcomings of the method to compute the power coefficient in an inhomogeneous wind field are likely the reason for disagreement between estimates using the Doppler lidar data versus SCADA data. Further, it was found that some wake steering cases were detrimental to the power output due to errors of the inflow wind direction perceived by the yawed wind turbine and the wake steering design implemented. Lastly, it was observed that the spanwise cross-section of the wake is strongly affected by wind veer, masking the kidney-shaped wake cross-sections observed from wind-tunnel experiments and numerical simulations.

Peter Brugger et al.

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Peter Brugger et al.

Peter Brugger et al.

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Latest update: 23 Sep 2020
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Short summary
A test implementation of a method to mitigate adverse interactions between wind turbines in a wind farm is investigated in terms of behavior and success. Measurements of the atmospheric flow around a pair of wind turbines and power readings of the wind turbines itself are analyzed for this purpose. The behavior of the wake agrees with the predictions of newer analytical models and a bias of the wind direction perceived by the wind turbine under certain conditions is reducing the power gains.
A test implementation of a method to mitigate adverse interactions between wind turbines in a...
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