Articles | Volume 10, issue 6
https://doi.org/10.5194/wes-10-1033-2025
© Author(s) 2025. 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-10-1033-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering
National Renewable Energy Laboratory, Golden, CO, USA
Garrett Barter
National Renewable Energy Laboratory, Golden, CO, USA
Jason Jonkman
National Renewable Energy Laboratory, Golden, CO, USA
Rafael Mudafort
National Renewable Energy Laboratory, Golden, CO, USA
Christopher J. Bay
National Renewable Energy Laboratory, Golden, CO, USA
Kelsey Shaler
Shell International Exploration and Production, Houston, TX, USA
Jasper Kreeft
Shell Global Solutions International B.V., the Hague, the Netherlands
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Cited
13 citations as recorded by crossref.
- Multi-objective wake steering optimization for monopile offshore wind turbines considering pile-soil interaction B. Li et al. https://doi.org/10.1016/j.apor.2026.105218
- A Review of Natural Hazards’ Impacts on Wind Turbine Performance, Part 2: Earthquakes, Waves, Tropical Cyclones, and Thunderstorm Downbursts X. Wang et al. https://doi.org/10.3390/en19020385
- Balancing energy yield and turbine fatigue: a load-aware approach to wind farm layout optimization S. Kainz et al. https://doi.org/10.1088/1742-6596/3224/3/032041
- Trailing-Edge Noise and Amplitude Modulation Under Yaw-Induced Partial Wake: A Curl–UVLM Analysis with Atmospheric Stability Effects H. Kim et al. https://doi.org/10.3390/en18195205
- Calibration and validation of FAST.Farm against LES for floating offshore wind farms B. Iacono et al. https://doi.org/10.1088/1742-6596/3224/3/032130
- Wind Turbine Yaw Misalignment Detection Based on Simulated Data H. Rocha et al. https://doi.org/10.1088/1742-6596/3224/6/062071
- Wake steering in offshore wind farms: Field experiment and SCADA-driven simulations for quantifying power and blade root loads H. Wang et al. https://doi.org/10.1016/j.oceaneng.2025.124001
- Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies J. Frederik https://doi.org/10.1109/TCST.2026.3715229
- Aeroelastic Response of Offshore Wind Turbines to Low-Level Jets Using OpenFAST L. Schena et al. https://doi.org/10.1088/1742-6596/3224/4/042038
- Power and Fatigue–Load Assessment of Static Wake Steering in a Floating Wind Farm with 15 MW Turbines M. Ebrahimi et al. https://doi.org/10.3390/en19163938
- An experimental investigation on wake mixing and steering techniques D. Bortolin et al. https://doi.org/10.1088/1742-6596/3224/3/032050
- Power system load vulnerability assessment based on X13-transformer model under extreme weather events K. Yang et al. https://doi.org/10.1088/1742-6596/3231/1/012033
- Numerical Study on Wake Characteristics and Fatigue Loads of Turbine Arrays with Different Layouts in Multiple Hills Terrain Y. Huang et al. https://doi.org/10.3390/modelling7040131
13 citations as recorded by crossref.
- Multi-objective wake steering optimization for monopile offshore wind turbines considering pile-soil interaction B. Li et al. https://doi.org/10.1016/j.apor.2026.105218
- A Review of Natural Hazards’ Impacts on Wind Turbine Performance, Part 2: Earthquakes, Waves, Tropical Cyclones, and Thunderstorm Downbursts X. Wang et al. https://doi.org/10.3390/en19020385
- Balancing energy yield and turbine fatigue: a load-aware approach to wind farm layout optimization S. Kainz et al. https://doi.org/10.1088/1742-6596/3224/3/032041
- Trailing-Edge Noise and Amplitude Modulation Under Yaw-Induced Partial Wake: A Curl–UVLM Analysis with Atmospheric Stability Effects H. Kim et al. https://doi.org/10.3390/en18195205
- Calibration and validation of FAST.Farm against LES for floating offshore wind farms B. Iacono et al. https://doi.org/10.1088/1742-6596/3224/3/032130
- Wind Turbine Yaw Misalignment Detection Based on Simulated Data H. Rocha et al. https://doi.org/10.1088/1742-6596/3224/6/062071
- Wake steering in offshore wind farms: Field experiment and SCADA-driven simulations for quantifying power and blade root loads H. Wang et al. https://doi.org/10.1016/j.oceaneng.2025.124001
- Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies J. Frederik https://doi.org/10.1109/TCST.2026.3715229
- Aeroelastic Response of Offshore Wind Turbines to Low-Level Jets Using OpenFAST L. Schena et al. https://doi.org/10.1088/1742-6596/3224/4/042038
- Power and Fatigue–Load Assessment of Static Wake Steering in a Floating Wind Farm with 15 MW Turbines M. Ebrahimi et al. https://doi.org/10.3390/en19163938
- An experimental investigation on wake mixing and steering techniques D. Bortolin et al. https://doi.org/10.1088/1742-6596/3224/3/032050
- Power system load vulnerability assessment based on X13-transformer model under extreme weather events K. Yang et al. https://doi.org/10.1088/1742-6596/3231/1/012033
- Numerical Study on Wake Characteristics and Fatigue Loads of Turbine Arrays with Different Layouts in Multiple Hills Terrain Y. Huang et al. https://doi.org/10.3390/modelling7040131
Saved (final revised paper)
Latest update: 05 Sep 2026
Short summary
We investigate asymmetries in terms of power performance and fatigue loading on a five-turbine wind farm subject to wake steering strategies. Both the yaw misalignment angle and the wind direction were varied from negative to positive. We highlight conditions in which fatigue loading is lower while still maintaining good power gains and show that a partial wake is the source of the asymmetries observed. We provide recommendations in terms of yaw misalignment angles for a given wind direction.
We investigate asymmetries in terms of power performance and fatigue loading on a five-turbine...
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