Articles | Volume 6, issue 3
https://doi.org/10.5194/wes-6-701-2021
© 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-6-701-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 May 2021
Research article |
| 21 May 2021
| 21 May 2021
Control-oriented model for secondary effects of wake steering
Jennifer King
CORRESPONDING AUTHOR
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Paul Fleming
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Ryan King
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Luis A. Martínez-Tossas
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
Christopher J. 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
Eric Simley
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA
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Cited
76 citations as recorded by crossref.
- Integrated floating wind farm layout design and mooring system optimization to increase annual energy production M. Mahfouz et al. 10.1088/1742-6596/2767/6/062020
- Exploring the Power & Loads Paradigm: Tocha Farm Case Study T. Lucas Frutuoso et al. 10.1088/1742-6596/2767/9/092102
- Wind turbine wakes modeling and applications: Past, present, and future L. Wang et al. 10.1016/j.oceaneng.2024.118508
- Multi-fidelity Bayesian Optimisation of Wind Farm Wake Steering using Wake Models and Large Eddy Simulations A. Mole & S. Laizet 10.1007/s10494-024-00629-0
- A multi-fidelity framework for power prediction of wind farm under yaw misalignment Y. Tu et al. 10.1016/j.apenergy.2024.124600
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Toward ultra-efficient high-fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models with machine learning C. Santoni et al. 10.1063/5.0213321
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
- A Probabilistic Learning Approach Applied to the Optimization of Wake Steering in Wind Farms J. Almeida & F. Rochinha 10.1115/1.4054501
- Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models R. Scott et al. 10.1063/5.0207013
- 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
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Bi-level multi-objective optimization framework for wake escape in floating offshore wind farm C. Huang et al. 10.1016/j.apenergy.2024.124712
- A nonlinear wake model of a wind turbine considering the yaw wake steering Y. Li et al. 10.1007/s00343-023-3040-6
- Optimizing yaw angles for improved power generation in offshore wind farms: A statistical approach I. Formoso 10.1016/j.oceaneng.2024.119830
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi 10.1115/1.4052775
- 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
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- Overview of recent observations and simulations from the American WAKE experimeNt (AWAKEN) field campaign P. Moriarty et al. 10.1088/1742-6596/2505/1/012049
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- Numerical modelling of offshore wind-farm cluster wakes P. Ouro et al. 10.1016/j.rser.2025.115526
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- A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity Z. Sadek et al. 10.1016/j.renene.2023.03.129
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
- Time-domain fatigue damage assessment for wind turbine tower bolts under yaw optimization control at offshore wind farm T. Tao et al. 10.1016/j.oceaneng.2024.117706
- Dynamic performance of a passively self-adjusting floating wind farm layout to increase the annual energy production M. Mahfouz et al. 10.5194/wes-9-1595-2024
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- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
- 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
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- On the importance of wind predictions in wake steering optimization E. Kadoche et al. 10.5194/wes-9-1577-2024
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- An analytical modeling study on yaw-based wake redirection control for large-scale offshore wind farm annual energy power improvement J. Tan et al. 10.1063/5.0207111
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- Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
- Flow in a large wind field with multiple actuators in the presence of constant vorticity S. Basu et al. 10.1063/5.0104902
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- Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
- 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
- Comparative Analysis of Wind Farm Simulators for Wind Farm Control M. Kim et al. 10.3390/en16093676
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- Assessment of yaw-control effects on wind turbine-wake interaction: A coupled unsteady vortex lattice method and curled wake model analysis W. Han et al. 10.1016/j.jweia.2023.105559
- Stochastic black-box optimization using multi-fidelity score function estimator A. Agrawal et al. 10.1088/2632-2153/ad8e2b
- The fluid mechanics of active flow control at very large scales C. Meneveau 10.1017/jfm.2024.846
- Study of three wake control strategies for power maximization of offshore wind farms with different layouts B. Li et al. 10.1016/j.enconman.2022.116059
- FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
- Effectively using multifidelity optimization for wind turbine design J. Jasa et al. 10.5194/wes-7-991-2022
- Robust wind farm layout optimization M. Sinner & P. Fleming 10.1088/1742-6596/2767/3/032036
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
- Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
- An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
- Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2 P. Fleming et al. 10.5194/wes-5-945-2020
- Influence of Wake Model Superposition and Secondary Steering on Model-Based Wake Steering Control with SCADA Data Assimilation M. Howland & J. Dabiri 10.3390/en14010052
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-5-1315-2020
- Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
- The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows L. Martínez-Tossas et al. 10.5194/wes-6-555-2021
- Design and analysis of a wake steering controller with wind direction variability E. Simley et al. 10.5194/wes-5-451-2020
66 citations as recorded by crossref.
- Integrated floating wind farm layout design and mooring system optimization to increase annual energy production M. Mahfouz et al. 10.1088/1742-6596/2767/6/062020
- Exploring the Power & Loads Paradigm: Tocha Farm Case Study T. Lucas Frutuoso et al. 10.1088/1742-6596/2767/9/092102
- Wind turbine wakes modeling and applications: Past, present, and future L. Wang et al. 10.1016/j.oceaneng.2024.118508
- Multi-fidelity Bayesian Optimisation of Wind Farm Wake Steering using Wake Models and Large Eddy Simulations A. Mole & S. Laizet 10.1007/s10494-024-00629-0
- A multi-fidelity framework for power prediction of wind farm under yaw misalignment Y. Tu et al. 10.1016/j.apenergy.2024.124600
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Toward ultra-efficient high-fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models with machine learning C. Santoni et al. 10.1063/5.0213321
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
- A Probabilistic Learning Approach Applied to the Optimization of Wake Steering in Wind Farms J. Almeida & F. Rochinha 10.1115/1.4054501
- Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models R. Scott et al. 10.1063/5.0207013
- 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
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Bi-level multi-objective optimization framework for wake escape in floating offshore wind farm C. Huang et al. 10.1016/j.apenergy.2024.124712
- A nonlinear wake model of a wind turbine considering the yaw wake steering Y. Li et al. 10.1007/s00343-023-3040-6
- Optimizing yaw angles for improved power generation in offshore wind farms: A statistical approach I. Formoso 10.1016/j.oceaneng.2024.119830
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi 10.1115/1.4052775
- 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
- Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms G. Kütükçü & O. Uzol 10.1063/5.0107244
- Overview of recent observations and simulations from the American WAKE experimeNt (AWAKEN) field campaign P. Moriarty et al. 10.1088/1742-6596/2505/1/012049
- Machine learning enables national assessment of wind plant controls with implications for land use D. Harrison‐Atlas et al. 10.1002/we.2689
- Large-eddy simulation of a wind-turbine array subjected to active yaw control M. Lin & F. Porté-Agel 10.5194/wes-7-2215-2022
- Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
- Data–Driven Wake Steering Control for a Simulated Wind Farm Model S. Simani et al. 10.31875/2409-9694.2023.10.02
- Ada2MF: Dual-adaptive multi-fidelity neural network approach and its application in wind turbine wake prediction L. Zhan et al. 10.1016/j.engappai.2024.109061
- Numerical modelling of offshore wind-farm cluster wakes P. Ouro et al. 10.1016/j.rser.2025.115526
- Fast yaw optimization for wind plant wake steering using Boolean yaw angles A. Stanley et al. 10.5194/wes-7-741-2022
- A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions C. Santoni et al. 10.3390/en17030753
- A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity Z. Sadek et al. 10.1016/j.renene.2023.03.129
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
- Time-domain fatigue damage assessment for wind turbine tower bolts under yaw optimization control at offshore wind farm T. Tao et al. 10.1016/j.oceaneng.2024.117706
- Dynamic performance of a passively self-adjusting floating wind farm layout to increase the annual energy production M. Mahfouz et al. 10.5194/wes-9-1595-2024
- On the power and control of a misaligned rotor – beyond the cosine law S. Tamaro et al. 10.5194/wes-9-1547-2024
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
- 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
- Multicluster Distributed Optimization Strategy for Turbine Wake Environment Z. Yu et al. 10.1002/aisy.202400884
- 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
- On the importance of wind predictions in wake steering optimization E. Kadoche et al. 10.5194/wes-9-1577-2024
- 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
- Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model Y. Tu et al. 10.1016/j.oceaneng.2023.114992
- Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
- LES-based validation of a dynamic wind farm flow model under unsteady inflow and yaw misalignment J. Bohrer et al. 10.1088/1742-6596/2767/3/032041
- An analytical modeling study on yaw-based wake redirection control for large-scale offshore wind farm annual energy power improvement J. Tan et al. 10.1063/5.0207111
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. 10.1017/jfm.2021.1010
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Scalable SCADA-Based Calibration for Analytical Wake Models Across an Offshore Cluster D. Binsbergen et al. 10.1088/1742-6596/2745/1/012014
- Distributed Fixed-Time Fatigue Minimization Control For Waked Wind Farms M. Firouzbahrami et al. 10.1109/TCST.2024.3362518
- Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes S. Tamaro et al. 10.1088/1742-6596/2767/9/092067
- Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
- Flow in a large wind field with multiple actuators in the presence of constant vorticity S. Basu et al. 10.1063/5.0104902
- 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
- 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
- A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
- Sensitivity analysis of wake steering optimisation for wind farm power maximisation F. Gori et al. 10.5194/wes-8-1425-2023
- Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
- 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
- Comparative Analysis of Wind Farm Simulators for Wind Farm Control M. Kim et al. 10.3390/en16093676
- Data-driven wake model parameter estimation to analyze effects of wake superposition M. LoCascio et al. 10.1063/5.0163896
- Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations N. Bempedelis et al. 10.5194/wes-9-869-2024
- Assessment of yaw-control effects on wind turbine-wake interaction: A coupled unsteady vortex lattice method and curled wake model analysis W. Han et al. 10.1016/j.jweia.2023.105559
- Stochastic black-box optimization using multi-fidelity score function estimator A. Agrawal et al. 10.1088/2632-2153/ad8e2b
- The fluid mechanics of active flow control at very large scales C. Meneveau 10.1017/jfm.2024.846
- Study of three wake control strategies for power maximization of offshore wind farms with different layouts B. Li et al. 10.1016/j.enconman.2022.116059
- FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
- Effectively using multifidelity optimization for wind turbine design J. Jasa et al. 10.5194/wes-7-991-2022
- Robust wind farm layout optimization M. Sinner & P. Fleming 10.1088/1742-6596/2767/3/032036
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
10 citations as recorded by crossref.
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
- Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
- An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
- Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2 P. Fleming et al. 10.5194/wes-5-945-2020
- Influence of Wake Model Superposition and Secondary Steering on Model-Based Wake Steering Control with SCADA Data Assimilation M. Howland & J. Dabiri 10.3390/en14010052
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-5-1315-2020
- Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
- The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows L. Martínez-Tossas et al. 10.5194/wes-6-555-2021
- Design and analysis of a wake steering controller with wind direction variability E. Simley et al. 10.5194/wes-5-451-2020
Latest update: 02 Apr 2025
Short summary
This paper highlights the secondary effects of wake steering, including yaw-added wake recovery and secondary steering. These effects enhance the value of wake steering especially when applied to a large wind farm. This paper models these secondary effects using an analytical model proposed in the paper. The results of this model are compared with large-eddy simulations for several cases including 2-turbine, 3-turbine, 5-turbine, and 38-turbine cases.
This paper highlights the secondary effects of wake steering, including yaw-added wake recovery...
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