Articles | Volume 7, issue 5
https://doi.org/10.5194/wes-7-2117-2022
© Author(s) 2022. 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-7-2117-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Oct 2022
Research article |
| 26 Oct 2022
| 26 Oct 2022
Predictive and stochastic reduced-order modeling of wind turbine wake dynamics
Department of Wind and Energy Systems, Technical University of Denmark, Anker Engelunds Vej 1, 2800 Kgs Lyngby, Denmark
Juan Pablo Murcia Leon
Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Viewed
Total article views: 5,592 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jun 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 4,191 | 1,300 | 101 | 5,592 | 200 | 149 | 168 |
- HTML: 4,191
- PDF: 1,300
- XML: 101
- Total: 5,592
- Supplement: 200
- BibTeX: 149
- EndNote: 168
Total article views: 4,116 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Oct 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,174 | 861 | 81 | 4,116 | 117 | 137 | 160 |
- HTML: 3,174
- PDF: 861
- XML: 81
- Total: 4,116
- Supplement: 117
- BibTeX: 137
- EndNote: 160
Total article views: 1,476 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jun 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,017 | 439 | 20 | 1,476 | 83 | 12 | 8 |
- HTML: 1,017
- PDF: 439
- XML: 20
- Total: 1,476
- Supplement: 83
- BibTeX: 12
- EndNote: 8
Viewed (geographical distribution)
Total article views: 5,592 (including HTML, PDF, and XML)
Thereof 5,312 with geography defined
and 280 with unknown origin.
Total article views: 4,116 (including HTML, PDF, and XML)
Thereof 3,895 with geography defined
and 221 with unknown origin.
Total article views: 1,476 (including HTML, PDF, and XML)
Thereof 1,417 with geography defined
and 59 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
19 citations as recorded by crossref.
- Stochastic wind farm flow generation using a reduced order model of LES S. Andersen & J. Murcia Leon https://doi.org/10.1088/1742-6596/2505/1/012050
- A Data-Driven Model Predictive Control for Wind Farm Power Maximization M. Kim et al. https://doi.org/10.1109/ACCESS.2024.3420872
- Reduced-Order Modeling Approach to Blunt-Body Aerodynamic Modeling H. Dean et al. https://doi.org/10.2514/1.A36095
- Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. https://doi.org/10.1016/j.rser.2025.115605
- Convergence and efficiency of global bases using proper orthogonal decomposition for capturing wind turbine wake aerodynamics J. Céspedes Moreno et al. https://doi.org/10.5194/wes-10-597-2025
- SuperOB: Super-resolution flow reconstruction from sparse measurements via re-Orthogonalization of a global Basis S. Andersen & J. Leon https://doi.org/10.1088/1742-6596/3224/3/032140
- Wind field estimation for lidar-assisted control: a comparison of proper orthogonal decomposition and interpolation techniques E. Soto Sagredo et al. https://doi.org/10.5194/wes-11-1705-2026
- Dissipation-optimized proper orthogonal decomposition P. Olesen et al. https://doi.org/10.1063/5.0131923
- Wind-field characterization using synthetic lidar measurements and proper orthogonal decomposition E. Soto Sagredo et al. https://doi.org/10.1088/1742-6596/2767/5/052061
- Parameter optimisation for real-time RAWS estimation using a hub-mounted lidar E. Soto Sagredo & J. Rinker https://doi.org/10.1088/1742-6596/3224/6/062072
- Mechanisms and modelling of turbulent total-pressure fluctuations in wakes L. Chen et al. https://doi.org/10.1063/5.0333119
- Observation and modelling of asymmetric loading on large offshore wind turbines in wake conditions V. Bernard et al. https://doi.org/10.1088/1742-6596/2767/9/092092
- Consistent reduced order modeling for wind turbine wakes using variational multiscale method and actuator line model S. Dave & A. Korobenko https://doi.org/10.1016/j.cma.2025.118194
- On the interaction of a wind turbine wake with a conventionally neutral atmospheric boundary layer A. Hodgkin et al. https://doi.org/10.1016/j.ijheatfluidflow.2023.109165
- Predictive digital twin for wind energy systems: a literature review E. Kandemir et al. https://doi.org/10.1186/s42162-024-00373-9
- Dynamic mode decomposition and mechanism analysis of unsteady wind turbine wake evolution in complex terrain S. Gan et al. https://doi.org/10.1063/5.0325738
- A call for enhanced data-driven insights into wind energy flow physics C. Moss et al. https://doi.org/10.1016/j.taml.2023.100488
- Effects of turbulent inflow time scales on wind turbine wake behavior and recovery E. Hodgson et al. https://doi.org/10.1063/5.0162311
- Synthesis of realistic non-homogeneous non-Gaussian turbulent wind fields C. Gallego-Castillo et al. https://doi.org/10.1088/1742-6596/2767/5/052019
19 citations as recorded by crossref.
- Stochastic wind farm flow generation using a reduced order model of LES S. Andersen & J. Murcia Leon https://doi.org/10.1088/1742-6596/2505/1/012050
- A Data-Driven Model Predictive Control for Wind Farm Power Maximization M. Kim et al. https://doi.org/10.1109/ACCESS.2024.3420872
- Reduced-Order Modeling Approach to Blunt-Body Aerodynamic Modeling H. Dean et al. https://doi.org/10.2514/1.A36095
- Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. https://doi.org/10.1016/j.rser.2025.115605
- Convergence and efficiency of global bases using proper orthogonal decomposition for capturing wind turbine wake aerodynamics J. Céspedes Moreno et al. https://doi.org/10.5194/wes-10-597-2025
- SuperOB: Super-resolution flow reconstruction from sparse measurements via re-Orthogonalization of a global Basis S. Andersen & J. Leon https://doi.org/10.1088/1742-6596/3224/3/032140
- Wind field estimation for lidar-assisted control: a comparison of proper orthogonal decomposition and interpolation techniques E. Soto Sagredo et al. https://doi.org/10.5194/wes-11-1705-2026
- Dissipation-optimized proper orthogonal decomposition P. Olesen et al. https://doi.org/10.1063/5.0131923
- Wind-field characterization using synthetic lidar measurements and proper orthogonal decomposition E. Soto Sagredo et al. https://doi.org/10.1088/1742-6596/2767/5/052061
- Parameter optimisation for real-time RAWS estimation using a hub-mounted lidar E. Soto Sagredo & J. Rinker https://doi.org/10.1088/1742-6596/3224/6/062072
- Mechanisms and modelling of turbulent total-pressure fluctuations in wakes L. Chen et al. https://doi.org/10.1063/5.0333119
- Observation and modelling of asymmetric loading on large offshore wind turbines in wake conditions V. Bernard et al. https://doi.org/10.1088/1742-6596/2767/9/092092
- Consistent reduced order modeling for wind turbine wakes using variational multiscale method and actuator line model S. Dave & A. Korobenko https://doi.org/10.1016/j.cma.2025.118194
- On the interaction of a wind turbine wake with a conventionally neutral atmospheric boundary layer A. Hodgkin et al. https://doi.org/10.1016/j.ijheatfluidflow.2023.109165
- Predictive digital twin for wind energy systems: a literature review E. Kandemir et al. https://doi.org/10.1186/s42162-024-00373-9
- Dynamic mode decomposition and mechanism analysis of unsteady wind turbine wake evolution in complex terrain S. Gan et al. https://doi.org/10.1063/5.0325738
- A call for enhanced data-driven insights into wind energy flow physics C. Moss et al. https://doi.org/10.1016/j.taml.2023.100488
- Effects of turbulent inflow time scales on wind turbine wake behavior and recovery E. Hodgson et al. https://doi.org/10.1063/5.0162311
- Synthesis of realistic non-homogeneous non-Gaussian turbulent wind fields C. Gallego-Castillo et al. https://doi.org/10.1088/1742-6596/2767/5/052019
Saved (final revised paper)
Latest update: 11 Jun 2026
Short summary
Simulating the turbulent flow inside large wind farms is inherently complex and computationally expensive. A new and fast model is developed based on data from high-fidelity simulations. The model captures the flow dynamics with correct statistics for a wide range of flow conditions. The model framework provides physical insights and presents a generalization of high-fidelity simulation results beyond the case-specific scenarios, which has significant potential for future turbulence modeling.
Simulating the turbulent flow inside large wind farms is inherently complex and computationally...
Altmetrics
Final-revised paper
Preprint