Articles | Volume 4, issue 3
https://doi.org/10.5194/wes-4-407-2019
© Author(s) 2019. 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-4-407-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jul 2019
Research article |
| 11 Jul 2019
| 11 Jul 2019
Detection of wakes in the inflow of turbines using nacelle lidars
Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 399, 4000 Roskilde, Denmark
Windar Photonics A/S, Helgeshøj Alle 16–18, 2630 Taastrup, Denmark
Jakob Mann
Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 399, 4000 Roskilde, Denmark
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Cited
18 citations as recorded by crossref.
- Wind farm fluid mechanics for high-penetration wind energy X. Yang et al. https://doi.org/10.1016/j.rser.2025.116260
- LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics X. Ning & D. Wan https://doi.org/10.3390/su11246939
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. https://doi.org/10.5194/wes-5-1129-2020
- Data Reliability Enhancement for Wind-Turbine-Mounted Lidars N. Angelou & M. Sjöholm https://doi.org/10.3390/rs14133225
- Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines J. Sun et al. https://doi.org/10.1016/j.renene.2022.08.137
- Improved wind speed estimation and rain quantification with continuous-wave wind lidar L. Jin et al. https://doi.org/10.1088/1742-6596/2265/2/022093
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. https://doi.org/10.5194/wes-8-1511-2023
- Dynamic wake tracking using a cost-effective LiDAR and Kalman filtering: Design, simulation and full-scale validation W. Lio et al. https://doi.org/10.1016/j.renene.2021.03.081
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. https://doi.org/10.5194/wes-6-841-2021
- On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods F. Guo et al. https://doi.org/10.1002/we.70098
- Wind vane correction during yaw misalignment for horizontal-axis wind turbines A. Rott et al. https://doi.org/10.5194/wes-8-1755-2023
- Field testing of a local wind inflow estimator and wake detector J. Schreiber et al. https://doi.org/10.5194/wes-5-867-2020
- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. https://doi.org/10.3389/fmech.2023.1261017
- From Blade Loads to Rotor Health: An Inverse Modelling Approach for Wind Turbine Monitoring A. Bibi et al. https://doi.org/10.3390/en19030619
- How accurate is nacelle-based anemometry during intentional yaw misalignment? An experimental assessment from a near-ideal site T. Vanelli et al. https://doi.org/10.1088/1742-6596/3224/2/022026
- Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges B. Kosović et al. https://doi.org/10.5194/wes-11-509-2026
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. https://doi.org/10.1016/j.apenergy.2024.122985
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. https://doi.org/10.5194/wes-8-1693-2023
18 citations as recorded by crossref.
- Wind farm fluid mechanics for high-penetration wind energy X. Yang et al. https://doi.org/10.1016/j.rser.2025.116260
- LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics X. Ning & D. Wan https://doi.org/10.3390/su11246939
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. https://doi.org/10.5194/wes-5-1129-2020
- Data Reliability Enhancement for Wind-Turbine-Mounted Lidars N. Angelou & M. Sjöholm https://doi.org/10.3390/rs14133225
- Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines J. Sun et al. https://doi.org/10.1016/j.renene.2022.08.137
- Improved wind speed estimation and rain quantification with continuous-wave wind lidar L. Jin et al. https://doi.org/10.1088/1742-6596/2265/2/022093
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. https://doi.org/10.5194/wes-8-1511-2023
- Dynamic wake tracking using a cost-effective LiDAR and Kalman filtering: Design, simulation and full-scale validation W. Lio et al. https://doi.org/10.1016/j.renene.2021.03.081
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. https://doi.org/10.5194/wes-6-841-2021
- On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods F. Guo et al. https://doi.org/10.1002/we.70098
- Wind vane correction during yaw misalignment for horizontal-axis wind turbines A. Rott et al. https://doi.org/10.5194/wes-8-1755-2023
- Field testing of a local wind inflow estimator and wake detector J. Schreiber et al. https://doi.org/10.5194/wes-5-867-2020
- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. https://doi.org/10.3389/fmech.2023.1261017
- From Blade Loads to Rotor Health: An Inverse Modelling Approach for Wind Turbine Monitoring A. Bibi et al. https://doi.org/10.3390/en19030619
- How accurate is nacelle-based anemometry during intentional yaw misalignment? An experimental assessment from a near-ideal site T. Vanelli et al. https://doi.org/10.1088/1742-6596/3224/2/022026
- Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges B. Kosović et al. https://doi.org/10.5194/wes-11-509-2026
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. https://doi.org/10.1016/j.apenergy.2024.122985
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. https://doi.org/10.5194/wes-8-1693-2023
Saved (final revised paper)
Latest update: 11 Jun 2026
Short summary
In this study the capabilities of detecting wakes in the inflow of turbines by nacelle-mounted lidars are investigated. It is shown that higher turbulence levels can be measured within a wake by estimating the Doppler spectrum width. In an experimental setup all half- and full-wake situations have been identified. A correction method for the influence of the wake on the lidar system has also been proposed..
In this study the capabilities of detecting wakes in the inflow of turbines by nacelle-mounted...
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