Articles | Volume 5, issue 4
https://doi.org/10.5194/wes-5-1273-2020
© 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-5-1273-2020
© 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 Oct 2020
Research article |
| 08 Oct 2020
| 08 Oct 2020
Wind tunnel testing of wake steering with dynamic wind direction changes
Filippo Campagnolo
Wind Energy Institute, Technische Universität München,
85748 Garching bei München, Germany
Robin Weber
Wind Energy Institute, Technische Universität München,
85748 Garching bei München, Germany
Johannes Schreiber
Wind Energy Institute, Technische Universität München,
85748 Garching bei München, Germany
Wind Energy Institute, Technische Universität München,
85748 Garching bei München, Germany
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Cited
39 citations as recorded by crossref.
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- A Machine Learning Method for Modeling Wind Farm Fatigue Load Y. Miao et al. 10.3390/app12157392
- Wind farm yaw control set-point optimization under model parameter uncertainty M. Howland 10.1063/5.0051071
- Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
- Field validation of a yaw misalignment observer for wind farm control M. Bertelè et al. 10.1088/1742-6596/2767/9/092013
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- A fast-running physics-based wake model for a semi-infinite wind farm M. Bastankhah et al. 10.1017/jfm.2024.282
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- 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
- Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
- Control-oriented modelling of wind direction variability S. Dallas et al. 10.5194/wes-9-841-2024
- Model Predictive Control for Wind Farm Power Tracking With Deep Learning-Based Reduced Order Modeling K. Chen et al. 10.1109/TII.2022.3157302
- 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
- Assessing Closed-Loop Data-Driven Wind Farm Control Strategies within a Wind Tunnel P. Hulsman et al. 10.1088/1742-6596/2767/3/032049
- Prediction and Validation of the Annual Energy Production of a Wind Turbine Using WindSim and a Dynamic Wind Turbine Model Y. Song & I. Paek 10.3390/en13246604
- Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
- Dynamic interaction of inflow and rotor time scales and impact on single turbine wake recovery S. Andersen et al. 10.1088/1742-6596/2767/9/092002
- Closely spaced corotating helical vortices: General solutions A. Castillo-Castellanos et al. 10.1103/PhysRevFluids.6.114701
- A General Method For The Diagnosis Of Wind Turbine Systematic Yaw Error Based Solely On SCADA Data D. Astolfi et al. 10.1088/1742-6596/2767/4/042007
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-7-345-2022
- Wind Tunnel Testing of Combined Derating and Wake Steering F. Campagnolo et al. 10.1016/j.ifacol.2023.10.1034
- Identification of airfoil polars from uncertain experimental measurements C. Wang et al. 10.5194/wes-5-1537-2020
- A wind tunnel investigation of yawed wind turbine wake impacts on downwind wind turbine performances and wind loads T. Uchida et al. 10.1177/0309524X221150219
- First experimental results on lifetime-aware wind farm control R. Braunbehrens et al. 10.1088/1742-6596/2767/3/032042
- Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- Design, steady performance and wake characterization of a scaled wind turbine with pitch, torque and yaw actuation E. Nanos et al. 10.5194/wes-7-1263-2022
- 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
- Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines J. Sun et al. 10.1016/j.renene.2022.08.137
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- 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
- How realistic are the wakes of scaled wind turbine models? C. Wang et al. 10.5194/wes-6-961-2021
- Joint optimization of wind farm layout considering optimal control K. Chen et al. 10.1016/j.renene.2021.10.032
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
- Investigating the impact of various operating parameters on blade aeroelasticity and wake characteristics of large-scale wind turbines Y. Tian et al. 10.1016/j.oceaneng.2023.115768
39 citations as recorded by crossref.
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- A Machine Learning Method for Modeling Wind Farm Fatigue Load Y. Miao et al. 10.3390/app12157392
- Wind farm yaw control set-point optimization under model parameter uncertainty M. Howland 10.1063/5.0051071
- Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
- Field validation of a yaw misalignment observer for wind farm control M. Bertelè et al. 10.1088/1742-6596/2767/9/092013
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- A fast-running physics-based wake model for a semi-infinite wind farm M. Bastankhah et al. 10.1017/jfm.2024.282
- Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
- 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
- Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
- Control-oriented modelling of wind direction variability S. Dallas et al. 10.5194/wes-9-841-2024
- Model Predictive Control for Wind Farm Power Tracking With Deep Learning-Based Reduced Order Modeling K. Chen et al. 10.1109/TII.2022.3157302
- 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
- Assessing Closed-Loop Data-Driven Wind Farm Control Strategies within a Wind Tunnel P. Hulsman et al. 10.1088/1742-6596/2767/3/032049
- Prediction and Validation of the Annual Energy Production of a Wind Turbine Using WindSim and a Dynamic Wind Turbine Model Y. Song & I. Paek 10.3390/en13246604
- Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
- Dynamic interaction of inflow and rotor time scales and impact on single turbine wake recovery S. Andersen et al. 10.1088/1742-6596/2767/9/092002
- Closely spaced corotating helical vortices: General solutions A. Castillo-Castellanos et al. 10.1103/PhysRevFluids.6.114701
- A General Method For The Diagnosis Of Wind Turbine Systematic Yaw Error Based Solely On SCADA Data D. Astolfi et al. 10.1088/1742-6596/2767/4/042007
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-7-345-2022
- Wind Tunnel Testing of Combined Derating and Wake Steering F. Campagnolo et al. 10.1016/j.ifacol.2023.10.1034
- Identification of airfoil polars from uncertain experimental measurements C. Wang et al. 10.5194/wes-5-1537-2020
- A wind tunnel investigation of yawed wind turbine wake impacts on downwind wind turbine performances and wind loads T. Uchida et al. 10.1177/0309524X221150219
- First experimental results on lifetime-aware wind farm control R. Braunbehrens et al. 10.1088/1742-6596/2767/3/032042
- Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
- Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- Design, steady performance and wake characterization of a scaled wind turbine with pitch, torque and yaw actuation E. Nanos et al. 10.5194/wes-7-1263-2022
- 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
- Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines J. Sun et al. 10.1016/j.renene.2022.08.137
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- 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
- How realistic are the wakes of scaled wind turbine models? C. Wang et al. 10.5194/wes-6-961-2021
- Joint optimization of wind farm layout considering optimal control K. Chen et al. 10.1016/j.renene.2021.10.032
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
- Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
- Investigating the impact of various operating parameters on blade aeroelasticity and wake characteristics of large-scale wind turbines Y. Tian et al. 10.1016/j.oceaneng.2023.115768
Latest update: 29 Jun 2024
Short summary
The performance of an open-loop wake-steering controller is investigated with a new wind tunnel experiment. Three scaled wind turbines are placed on a large turntable and exposed to a turbulent inflow, resulting in dynamically varying wake interactions. The study highlights the importance of using a robust formulation and plant flow models of appropriate fidelity and the existence of possible margins for improvement by the use of dynamic controllers.
The performance of an open-loop wake-steering controller is investigated with a new wind tunnel...
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