Articles | Volume 5, issue 3
https://doi.org/10.5194/wes-5-945-2020
© Author(s) 2020. 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-5-945-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jul 2020
Research article |
| 24 Jul 2020
| 24 Jul 2020
Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
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
Jason Roadman
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Andrew Scholbrock
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Patrick Murphy
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Dept. Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80303, USA
Julie K. Lundquist
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Dept. Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80303, USA
Patrick Moriarty
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Katherine Fleming
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Jeroen van Dam
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Christopher Bay
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Rafael Mudafort
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
David Jager
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Jason Skopek
NextEra Energy Resources, 700 Universe Blvd, Juno Beach, FL 33408, USA
Michael Scott
NextEra Energy Resources, 700 Universe Blvd, Juno Beach, FL 33408, USA
Brady Ryan
NextEra Energy Resources, 700 Universe Blvd, Juno Beach, FL 33408, USA
Charles Guernsey
NextEra Energy Resources, 700 Universe Blvd, Juno Beach, FL 33408, USA
Dan Brake
NextEra Energy Resources, 700 Universe Blvd, Juno Beach, FL 33408, USA
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Cited
78 citations as recorded by crossref.
- Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
- Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
- Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control Y. Wang & Z. Liu 10.1016/j.energy.2025.136266
- Wind energy-harvesting technologies and recent research progresses in wind farm control models B. Desalegn et al. 10.3389/fenrg.2023.1124203
- Effectiveness of cooperative yaw control based on reinforcement learning for in-line multiple wind turbines L. Wang et al. 10.1016/j.conengprac.2024.106124
- Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
- Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
- Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al. 10.1002/we.2756
- Artificial intelligence-aided wind plant optimization for nationwide evaluation of land use and economic benefits of wake steering D. Harrison-Atlas et al. 10.1038/s41560-024-01516-8
- Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
- Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model Z. Deng et al. 10.3390/en16093932
- An open-source framework for the development, deployment and testing of wind farm control strategies C. Sucameli et al. 10.1088/1742-6596/2767/9/092043
- Data–Driven Wake Steering Control for a Simulated Wind Farm Model S. Simani et al. 10.31875/2409-9694.2023.10.02
- 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
- Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
- Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment D. Kumar et al. 10.1002/we.2799
- Maximization of the Power Production of an Offshore Wind Farm R. Balakrishnan & S. Hur 10.3390/app12084013
- Design of the American Wake Experiment (AWAKEN) field campaign M. Debnath et al. 10.1088/1742-6596/2265/2/022058
- Region-based convolutional neural network for wind turbine wake characterization from scanning lidars J. Aird et al. 10.1088/1742-6596/2265/3/032077
- A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control R. He et al. 10.1016/j.apenergy.2022.120013
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- Investigating the impact of atmospheric conditions on wake-steering performance at a commercial wind plant E. Simley et al. 10.1088/1742-6596/2265/3/032097
- Impact of the wake deficit model on wind farm yield: A study of yaw-based control optimization B. Rak & R. Santos Pereira 10.1016/j.jweia.2021.104827
- Wake Recovery Enhancement with Helix Active Wake Control: Vortex Structures in a Porous Disk Wake Observed in PIV Experiments J. Gutknecht et al. 10.1088/1742-6596/3016/1/012030
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
- Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
- Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines S. Dana et al. 10.1088/1742-6596/2265/2/022106
- Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control A. Dittmer et al. 10.1016/j.ifacol.2023.10.1037
- Serial-Refine Method for Fast Wake-Steering Yaw Optimization P. Fleming et al. 10.1088/1742-6596/2265/3/032109
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
- 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
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
- Three-dimensional yaw wake model development with validations from wind tunnel experiments R. He et al. 10.1016/j.energy.2023.128402
- On the Load Impact of Dynamic Wind Farm Wake Mixing Strategies J. Frederik & J. van Wingerden 10.2139/ssrn.3910237
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Are steady-state wake models and lookup tables sufficient to design profitable wake steering strategies? A Large Eddy Simulation investigation M. Lejeune et al. 10.1088/1742-6596/2767/9/092075
- Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
- Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings M. Sinner et al. 10.1063/5.0039899
- Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy B. Doekemeijer et al. 10.5194/wes-6-159-2021
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
- Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en16124550
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- Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers S. Macrí et al. 10.5194/wes-6-585-2021
- Wind Farm Loads under Wake Redirection Control S. Kanev et al. 10.3390/en13164088
- Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
- How generalizable is a machine-learning approach for modeling hub-height turbulence intensity? N. Bodini et al. 10.1088/1742-6596/2265/2/022028
- Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
- Positive effect of wind farm control on energy production and revenue in European markets F. Wasilczuk et al. 10.1016/j.energy.2025.136159
- Uncertainty of toggling in wake steering experiments under diurnal cycle atmospheric conditions: an LES study E. Hodgson et al. 10.1088/1742-6596/3016/1/012026
- Synergizing Helix Active Wake Mixing with Dynamic Yawing: An Exploration Study using Porous Discs in a Wind Tunnel J. Gutknecht et al. 10.1088/1742-6596/3016/1/012014
- Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions P. Hulsman et al. 10.1088/1742-6596/2265/3/032074
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
- Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering R. Thedin et al. 10.5194/wes-10-1033-2025
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies M. Becker et al. 10.5194/wes-10-1055-2025
- Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
- Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
- 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
- On the load impact of dynamic wind farm wake mixing strategies J. Frederik & J. van Wingerden 10.1016/j.renene.2022.05.110
- Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons K. Shaler et al. 10.5194/wes-9-1451-2024
- Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning Z. Deng et al. 10.1016/j.enconman.2023.117031
- Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
- A low-computational physics-guided deep learning model for wind farm flow control under time-varying wind conditions S. He et al. 10.1016/j.energy.2025.137048
- Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant P. Bachant et al. 10.5194/wes-9-2235-2024
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Analytical solutions for yawed wind-turbine wakes with application to wind-farm power optimization by active yaw control Z. Zhang et al. 10.1016/j.oceaneng.2024.117691
- Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest J. Frederik et al. 10.5194/wes-10-755-2025
- 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
77 citations as recorded by crossref.
- Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
- Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
- Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control Y. Wang & Z. Liu 10.1016/j.energy.2025.136266
- Wind energy-harvesting technologies and recent research progresses in wind farm control models B. Desalegn et al. 10.3389/fenrg.2023.1124203
- Effectiveness of cooperative yaw control based on reinforcement learning for in-line multiple wind turbines L. Wang et al. 10.1016/j.conengprac.2024.106124
- Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
- Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
- Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al. 10.1002/we.2756
- Artificial intelligence-aided wind plant optimization for nationwide evaluation of land use and economic benefits of wake steering D. Harrison-Atlas et al. 10.1038/s41560-024-01516-8
- Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
- Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model Z. Deng et al. 10.3390/en16093932
- An open-source framework for the development, deployment and testing of wind farm control strategies C. Sucameli et al. 10.1088/1742-6596/2767/9/092043
- Data–Driven Wake Steering Control for a Simulated Wind Farm Model S. Simani et al. 10.31875/2409-9694.2023.10.02
- 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
- Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
- Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment D. Kumar et al. 10.1002/we.2799
- Maximization of the Power Production of an Offshore Wind Farm R. Balakrishnan & S. Hur 10.3390/app12084013
- Design of the American Wake Experiment (AWAKEN) field campaign M. Debnath et al. 10.1088/1742-6596/2265/2/022058
- Region-based convolutional neural network for wind turbine wake characterization from scanning lidars J. Aird et al. 10.1088/1742-6596/2265/3/032077
- A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control R. He et al. 10.1016/j.apenergy.2022.120013
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- Investigating the impact of atmospheric conditions on wake-steering performance at a commercial wind plant E. Simley et al. 10.1088/1742-6596/2265/3/032097
- Impact of the wake deficit model on wind farm yield: A study of yaw-based control optimization B. Rak & R. Santos Pereira 10.1016/j.jweia.2021.104827
- Wake Recovery Enhancement with Helix Active Wake Control: Vortex Structures in a Porous Disk Wake Observed in PIV Experiments J. Gutknecht et al. 10.1088/1742-6596/3016/1/012030
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
- Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
- Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines S. Dana et al. 10.1088/1742-6596/2265/2/022106
- Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control A. Dittmer et al. 10.1016/j.ifacol.2023.10.1037
- Serial-Refine Method for Fast Wake-Steering Yaw Optimization P. Fleming et al. 10.1088/1742-6596/2265/3/032109
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
- 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
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
- Three-dimensional yaw wake model development with validations from wind tunnel experiments R. He et al. 10.1016/j.energy.2023.128402
- On the Load Impact of Dynamic Wind Farm Wake Mixing Strategies J. Frederik & J. van Wingerden 10.2139/ssrn.3910237
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Are steady-state wake models and lookup tables sufficient to design profitable wake steering strategies? A Large Eddy Simulation investigation M. Lejeune et al. 10.1088/1742-6596/2767/9/092075
- Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
- Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings M. Sinner et al. 10.1063/5.0039899
- Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy B. Doekemeijer et al. 10.5194/wes-6-159-2021
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
- Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en16124550
- Effect of Atmospheric Stability on Meandering and Wake Characteristics in Wind Turbine Fluid Dynamics B. Løvøy Alvestad et al. 10.3390/app14178025
- Quantification of wake shape modulation and deflection for tilt and yaw misaligned wind turbines J. Bossuyt et al. 10.1017/jfm.2021.237
- 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
- Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance E. Simley et al. 10.5194/wes-6-1427-2021
- Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers S. Macrí et al. 10.5194/wes-6-585-2021
- Wind Farm Loads under Wake Redirection Control S. Kanev et al. 10.3390/en13164088
- Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
- How generalizable is a machine-learning approach for modeling hub-height turbulence intensity? N. Bodini et al. 10.1088/1742-6596/2265/2/022028
- Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
- Positive effect of wind farm control on energy production and revenue in European markets F. Wasilczuk et al. 10.1016/j.energy.2025.136159
- Uncertainty of toggling in wake steering experiments under diurnal cycle atmospheric conditions: an LES study E. Hodgson et al. 10.1088/1742-6596/3016/1/012026
- Synergizing Helix Active Wake Mixing with Dynamic Yawing: An Exploration Study using Porous Discs in a Wind Tunnel J. Gutknecht et al. 10.1088/1742-6596/3016/1/012014
- Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions P. Hulsman et al. 10.1088/1742-6596/2265/3/032074
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
- Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering R. Thedin et al. 10.5194/wes-10-1033-2025
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies M. Becker et al. 10.5194/wes-10-1055-2025
- Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
- Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
- 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
- On the load impact of dynamic wind farm wake mixing strategies J. Frederik & J. van Wingerden 10.1016/j.renene.2022.05.110
- Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons K. Shaler et al. 10.5194/wes-9-1451-2024
- Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning Z. Deng et al. 10.1016/j.enconman.2023.117031
- Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
- A low-computational physics-guided deep learning model for wind farm flow control under time-varying wind conditions S. He et al. 10.1016/j.energy.2025.137048
- Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant P. Bachant et al. 10.5194/wes-9-2235-2024
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Analytical solutions for yawed wind-turbine wakes with application to wind-farm power optimization by active yaw control Z. Zhang et al. 10.1016/j.oceaneng.2024.117691
- Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest J. Frederik et al. 10.5194/wes-10-755-2025
Latest update: 30 Jun 2025
Short summary
This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.
This paper presents the results of a field campaign investigating the performance of wake...
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