Articles | Volume 6, issue 5
https://doi.org/10.5194/wes-6-1247-2021
© 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-6-1247-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Sep 2021
Research article |
| 17 Sep 2021
| 17 Sep 2021
FAST.Farm load validation for single wake situations at alpha ventus
Matthias Kretschmer
CORRESPONDING AUTHOR
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Jason Jonkman
National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
Vasilis Pettas
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Po Wen Cheng
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
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Cited
25 citations as recorded by crossref.
- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al.
- Effects of wake-added turbulence on extreme loads and fatigue damage of floating offshore wind turbines X. Xu et al.
- Development and Verification of an Improved Wake-Added Turbulence Model in FAST.Farm E. Branlard et al.
- A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines A. Guilloré et al.
- On the effects of inter-farm interactions at the offshore wind farm Alpha Ventus V. Pettas et al.
- A FAST.Farm and MATLAB/Simulink interface for wind farm control design C. Smits et al.
- Fatigue degradation of wind turbines considering dynamic wake meandering effects J. Zhang et al.
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al.
- Progress on Offshore Wind Farm Dynamic Wake Management for Energy L. Zhao et al.
- Investigating the interactions between wakes and floating wind turbines using FAST.Farm L. Carmo et al.
- Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons K. Shaler et al.
- Difference in load predictions obtained with effective turbulence vs. a dynamic wake meandering modeling approach P. Doubrawa et al.
- Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights X. Xu et al.
- Processing of offshore measurement data for multi-fidelity wake model performance assessments S. Freitas et al.
- Ranking multi-fidelity model performances in reproducing internal and external wake impacts at neighbouring offshore wind farms S. Freitas et al.
- Effects of atmospheric stability on the structural response of a 12 MW semisubmersible floating wind turbine I. Rivera‐Arreba et al.
- A novel spatiotemporal Fourier neural operator for dynamic wake prediction X. Zhang et al.
- Wind Tunnel Evaluation of Aerodynamic Loads in FAST.Farm Under Controlled Wake Conditions A. Fontanella et al.
- Wake Interactions of Two Tandem Semisubmersible Floating Offshore Wind Turbines Based on FAST.Farm L. Xue et al.
- Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al.
- Wind farm dynamic wake modeling analysis using engineering scale wake modeling simulations against flow field monitoring data Z. Mehmood et al.
- Optimization study of control strategy for combined multi-wind turbines energy production and loads during wake effects L. Zhao et al.
- Dynamic coupling of wake added turbulence and array effects: nonlinear impacts on power performance and fatigue damage of 22 MW floating offshore wind turbines Z. Xu et al.
- Deep Learning Approaches for Offshore Wind Turbine Load Prediction: A Comparative Study Using Simulation, Measurement, and Transfer Learning D. Liu et al.
- An improved dynamic model for wind-turbine wake flow D. Feng et al.
25 citations as recorded by crossref.
- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al.
- Effects of wake-added turbulence on extreme loads and fatigue damage of floating offshore wind turbines X. Xu et al.
- Development and Verification of an Improved Wake-Added Turbulence Model in FAST.Farm E. Branlard et al.
- A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines A. Guilloré et al.
- On the effects of inter-farm interactions at the offshore wind farm Alpha Ventus V. Pettas et al.
- A FAST.Farm and MATLAB/Simulink interface for wind farm control design C. Smits et al.
- Fatigue degradation of wind turbines considering dynamic wake meandering effects J. Zhang et al.
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al.
- Progress on Offshore Wind Farm Dynamic Wake Management for Energy L. Zhao et al.
- Investigating the interactions between wakes and floating wind turbines using FAST.Farm L. Carmo et al.
- Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons K. Shaler et al.
- Difference in load predictions obtained with effective turbulence vs. a dynamic wake meandering modeling approach P. Doubrawa et al.
- Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights X. Xu et al.
- Processing of offshore measurement data for multi-fidelity wake model performance assessments S. Freitas et al.
- Ranking multi-fidelity model performances in reproducing internal and external wake impacts at neighbouring offshore wind farms S. Freitas et al.
- Effects of atmospheric stability on the structural response of a 12 MW semisubmersible floating wind turbine I. Rivera‐Arreba et al.
- A novel spatiotemporal Fourier neural operator for dynamic wake prediction X. Zhang et al.
- Wind Tunnel Evaluation of Aerodynamic Loads in FAST.Farm Under Controlled Wake Conditions A. Fontanella et al.
- Wake Interactions of Two Tandem Semisubmersible Floating Offshore Wind Turbines Based on FAST.Farm L. Xue et al.
- Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al.
- Wind farm dynamic wake modeling analysis using engineering scale wake modeling simulations against flow field monitoring data Z. Mehmood et al.
- Optimization study of control strategy for combined multi-wind turbines energy production and loads during wake effects L. Zhao et al.
- Dynamic coupling of wake added turbulence and array effects: nonlinear impacts on power performance and fatigue damage of 22 MW floating offshore wind turbines Z. Xu et al.
- Deep Learning Approaches for Offshore Wind Turbine Load Prediction: A Comparative Study Using Simulation, Measurement, and Transfer Learning D. Liu et al.
- An improved dynamic model for wind-turbine wake flow D. Feng et al.
Saved (final revised paper)
Latest update: 28 Apr 2026
Short summary
We perform a validation of the new simulation tool FAST.Farm for the prediction of power output and structural loads in single wake conditions with respect to measurement data from the offshore wind farm alpha ventus. With a new wake-added turbulence functionality added to FAST.Farm, good agreement between simulations and measurements is achieved for the considered quantities. We hereby give insights into load characteristics of an offshore wind turbine subjected to single wake conditions.
We perform a validation of the new simulation tool FAST.Farm for the prediction of power output...
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