Articles | Volume 5, issue 2
https://doi.org/10.5194/wes-5-451-2020
© 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-5-451-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Apr 2020
Research article |
| 08 Apr 2020
| 08 Apr 2020
Design and analysis of a wake steering controller with wind direction variability
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
Jennifer King
National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
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- A novel hybrid model for the estimation of energy conversion in a wind farm combining wake effects and stochastic dependability F. Famoso et al. 10.1016/j.apenergy.2020.115967
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
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- 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
- The Jensen wind farm parameterization Y. Ma et al. 10.5194/wes-7-2407-2022
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- 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
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. 10.5194/wes-8-1693-2023
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
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- Data-driven yaw misalignment correction for utility-scale wind turbines L. Gao & J. Hong 10.1063/5.0056671
- Wind farm yaw control set-point optimization under model parameter uncertainty M. Howland 10.1063/5.0051071
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- Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
- 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
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- Modeling dynamic wind direction changes in large eddy simulations of wind farms A. Stieren et al. 10.1016/j.renene.2021.02.018
- 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
- Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models P. Brugger et al. 10.5194/wes-5-1253-2020
- Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
- 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
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Wake steering optimization under uncertainty J. Quick et al. 10.5194/wes-5-413-2020
- 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
45 citations as recorded by crossref.
- 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
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
- A novel hybrid model for the estimation of energy conversion in a wind farm combining wake effects and stochastic dependability F. Famoso et al. 10.1016/j.apenergy.2020.115967
- Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
- A Probabilistic Learning Approach Applied to the Optimization of Wake Steering in Wind Farms J. Almeida & F. Rochinha 10.1115/1.4054501
- Control-oriented modelling of wind direction variability S. Dallas et al. 10.5194/wes-9-841-2024
- Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms G. Kütükçü & O. Uzol 10.1063/5.0107244
- 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
- The Jensen wind farm parameterization Y. Ma et al. 10.5194/wes-7-2407-2022
- Study on the yaw-based wake steering control considering dynamic flow characteristics for wind farm power improvement X. Yu et al. 10.1088/1742-6596/2505/1/012010
- 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
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. 10.5194/wes-8-1693-2023
- Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
- Dynamic wake tracking based on wind turbine rotor loads and Kalman filtering D. Onnen et al. 10.1088/1742-6596/2265/2/022024
- Data-driven yaw misalignment correction for utility-scale wind turbines L. Gao & J. Hong 10.1063/5.0056671
- Wind farm yaw control set-point optimization under model parameter uncertainty M. Howland 10.1063/5.0051071
- 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
- Numerical investigation of rotor asymmetry to promote wake recovery A. Abraham et al. 10.1088/1742-6596/2505/1/012032
- Wind tunnel testing of wake steering with dynamic wind direction changes F. Campagnolo et al. 10.5194/wes-5-1273-2020
- Turbulence and Control of Wind Farms C. Shapiro et al. 10.1146/annurev-control-070221-114032
- FarmConners market showcase results: wind farm flow control considering electricity prices K. Kölle et al. 10.5194/wes-7-2181-2022
- 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
- Reinforcement learning for wind-farm flow control: Current state and future actions M. Abkar et al. 10.1016/j.taml.2023.100475
- 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
- FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
- Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
- Predicting the benefit of wake steering on the annual energy production of a wind farm using large eddy simulations and Gaussian process regression D. Hoek et al. 10.1088/1742-6596/1618/2/022024
- Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
- 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
- Fast yaw optimization for wind plant wake steering using Boolean yaw angles A. Stanley et al. 10.5194/wes-7-741-2022
- Data-driven wake model parameter estimation to analyze effects of wake superposition M. LoCascio et al. 10.1063/5.0163896
- 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
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- Wind energy-harvesting technologies and recent research progresses in wind farm control models B. Desalegn et al. 10.3389/fenrg.2023.1124203
- Sensitivity analysis of wake steering optimisation for wind farm power maximisation F. Gori et al. 10.5194/wes-8-1425-2023
- Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
- A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
- Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
- The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-7-345-2022
- Modeling dynamic wind direction changes in large eddy simulations of wind farms A. Stieren et al. 10.1016/j.renene.2021.02.018
- 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
- Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models P. Brugger et al. 10.5194/wes-5-1253-2020
- Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
4 citations as recorded by crossref.
- 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
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Wake steering optimization under uncertainty J. Quick et al. 10.5194/wes-5-413-2020
- 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
Latest update: 25 Apr 2024
Short summary
Wind farm wake losses occur when turbines operate in the wakes of upstream turbines. However, wake steering control can be used to deflect wakes away from downstream turbines. A method for including wind direction variability in wake steering simulations is presented here. Controller performance is shown to improve when wind direction variability is accounted for. Furthermore, the importance of wind direction variability is shown for different turbine spacings and atmospheric conditions.
Wind farm wake losses occur when turbines operate in the wakes of upstream turbines. However,...
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