Articles | Volume 6, issue 6
https://doi.org/10.5194/wes-6-1521-2021
© Author(s) 2021. 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-6-1521-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Dec 2021
Research article |
| 07 Dec 2021
| 07 Dec 2021
Experimental results of wake steering using fixed angles
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Michael Sinner
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Tom Young
RES Group, Beaufort Court, Egg Farm Lane, Kings Langley, Hertfordshire, WD4 8LR, UK
Marine Lannic
RES Group, Beaufort Court, Egg Farm Lane, Kings Langley, Hertfordshire, WD4 8LR, UK
Jennifer King
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Eric Simley
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Bart Doekemeijer
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
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Cited
13 citations as recorded by crossref.
- Method to Predict Outputs of Two-Dimensional VAWT Rotors by Using Wake Model Mimicking the CFD-Created Flow Field J. Buranarote et al. 10.3390/en15145200
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment B. Sengers et al. 10.5194/wes-8-747-2023
- Maximizing wind farm power output with the helix approach: Experimental validation and wake analysis using tomographic particle image velocimetry D. van der Hoek et al. 10.1002/we.2896
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- Combined wake control of aligned wind turbines for power optimization based on a 3D wake model considering secondary wake steering Y. Liu et al. 10.1016/j.energy.2024.132900
- Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
- Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model C. Bay et al. 10.5194/wes-8-401-2023
- Free-vortex models for wind turbine wakes under yaw misalignment – a validation study on far-wake effects M. van den Broek et al. 10.5194/wes-8-1909-2023
- Adjoint optimisation for wind farm flow control with a free-vortex wake model M. van den Broek et al. 10.1016/j.renene.2022.10.120
- Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
12 citations as recorded by crossref.
- Method to Predict Outputs of Two-Dimensional VAWT Rotors by Using Wake Model Mimicking the CFD-Created Flow Field J. Buranarote et al. 10.3390/en15145200
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment B. Sengers et al. 10.5194/wes-8-747-2023
- Maximizing wind farm power output with the helix approach: Experimental validation and wake analysis using tomographic particle image velocimetry D. van der Hoek et al. 10.1002/we.2896
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- Combined wake control of aligned wind turbines for power optimization based on a 3D wake model considering secondary wake steering Y. Liu et al. 10.1016/j.energy.2024.132900
- Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
- Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model C. Bay et al. 10.5194/wes-8-401-2023
- Free-vortex models for wind turbine wakes under yaw misalignment – a validation study on far-wake effects M. van den Broek et al. 10.5194/wes-8-1909-2023
- Adjoint optimisation for wind farm flow control with a free-vortex wake model M. van den Broek et al. 10.1016/j.renene.2022.10.120
1 citations as recorded by crossref.
Latest update: 13 Dec 2024
Short summary
The paper presents a new validation campaign of wake steering at a commercial wind farm. The campaign uses fixed yaw offset positions, rather than a table of optimal yaw offsets dependent on wind direction, to enable comparison with engineering models of wake steering. Additionally, by applying the same offset in beneficial and detrimental conditions, we are able to collect important data for assessing second-order wake model predictions.
The paper presents a new validation campaign of wake steering at a commercial wind farm. The...
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