Articles | Volume 11, issue 1
https://doi.org/10.5194/wes-11-265-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-265-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Jan 2026
Research article |
| 23 Jan 2026
| 23 Jan 2026
Bidirectional wakes over complex terrain using SCADA data and wake models
Nanako Sasanuma
CORRESPONDING AUTHOR
Graduate School of Science and Technology, Hirosaki University, Bunkyo–cho 3, Hirosaki, 036–8561, Japan
Akihiro Honda
Aomori Public University, Department of Management and Economics, Aomori, 030-0196, Japan
Christian Bak
DTU Wind and Energy Systems, Technical University of Denmark, Roskilde, 4000, Denmark
Niels Troldborg
DTU Wind and Energy Systems, Technical University of Denmark, Roskilde, 4000, Denmark
Mac Gaunaa
DTU Wind and Energy Systems, Technical University of Denmark, Roskilde, 4000, Denmark
Morten Nielsen
DTU Wind and Energy Systems, Technical University of Denmark, Roskilde, 4000, Denmark
Teruhisa Shimada
Graduate School of Science and Technology, Hirosaki University, Bunkyo–cho 3, Hirosaki, 036–8561, Japan
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Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Michael McWilliam
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Kenneth Loenbaek, Christian Bak, and Michael McWilliam
Wind Energ. Sci., 6, 917–933, https://doi.org/10.5194/wes-6-917-2021, https://doi.org/10.5194/wes-6-917-2021, 2021
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This study investigates aero-elasticity of wind turbines present in the turbulent and chaotic wind flow of the lower atmosphere, using fluid–structure interaction simulations. This method combines structural response computations with high-fidelity modeling of the turbulent wind flow, using a novel turbulence model which combines the capabilities of large-eddy simulations for atmospheric flows with improved delayed detached eddy simulations for the separated flow near the rotor.
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Short summary
We verify wake effects between two wind turbines in complex terrain using supervisory control and data acquisition data. By identifying “wake conditions” and “no-wake conditions” detected by the blade pitch angle of upstream wind turbines, we evaluate wake effects on wind speed ratio, turbulent intensity, and power output. Results show that flow downhill has a significant impact on wake effects compared to flow uphill. The method shows the potential of SCADA data during the downtime of wind turbines.
We verify wake effects between two wind turbines in complex terrain using supervisory control...
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