Articles | Volume 8, issue 2
https://doi.org/10.5194/wes-8-149-2023
© Author(s) 2023. 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-8-149-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Feb 2023
Research article |
| 09 Feb 2023
| 09 Feb 2023
Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, Germany
David Schlipf
Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, Germany
Po Wen Cheng
Stuttgart Wind Energy (SWE), Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
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Cited
22 citations as recorded by crossref.
- Lidar-assisted nonlinear output regulation of wind turbines for fatigue load reduction R. Moldenhauer & R. Schmid https://doi.org/10.5194/wes-10-1907-2025
- Experimental investigation of wind turbine controllers for the Hybrid-Lambda Rotor D. Ribnitzky et al. https://doi.org/10.5194/wes-11-469-2026
- Wind speed estimation using second-order sliding-mode observers: simulation and experimental validation on a floating offshore wind turbine M. Sarbandi et al. https://doi.org/10.5194/wes-11-2405-2026
- The performance of two control strategies for floating wind turbines: lidar-assisted feedforward and multi-variable feedback F. Guo et al. https://doi.org/10.1088/1742-6596/2626/1/012005
- Enhancing Wind Turbine Sustainability Through LiDAR Configuration Analysis and Evaluation of Two Reference LiDAR-Assisted Control Strategies C. Steinmann Perez et al. https://doi.org/10.3390/su17136083
- LIDAR‐assisted feedforward individual pitch control of a 15 MW floating offshore wind turbine A. Russell et al. https://doi.org/10.1002/we.2891
- A LiDAR-Based Active Yaw Control Strategy for Optimal Wake Steering in Paired Wind Turbines E. Mahmoodi et al. https://doi.org/10.3390/en17225635
- Assessing lidar-assisted feedforward and multivariable feedback controls for large floating wind turbines F. Guo & D. Schlipf https://doi.org/10.5194/wes-8-1299-2023
- 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
- Wind Turbine Generator Speed Regulation Enabled by Ground‐Level Air Pressure Measurements M. Lingad et al. https://doi.org/10.1049/rpg2.70292
- Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar W. Fu et al. https://doi.org/10.5194/wes-8-1893-2023
- Analysis and evaluation of two reference LiDAR-assisted control designs for wind turbines C. Steinmann Perez et al. https://doi.org/10.1088/1742-6596/2767/3/032048
- Design and experimental validation of a continuous-wave lidar for wind-field measurements in a wave-basin model test of a floating wind turbine F. Guo et al. https://doi.org/10.1016/j.joes.2026.10.005
- Effects of turbulence inhomogeneity and atmosphere stability on the aeroelastic response of the IEA 22 MW wind turbine F. Guo et al. https://doi.org/10.1016/j.renene.2025.124384
- 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
- LiDAR-informed transformer framework for spatiotemporal estimation of rotor-effective wind speed beyond Taylor’s frozen turbulence hypothesis M. Zhang et al. https://doi.org/10.1016/j.energy.2026.142669
- On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods F. Guo et al. https://doi.org/10.1002/we.70098
- Performance and robustness evaluation of retrofit and standard LiDAR-assisted control in wind turbines A. Lio et al. https://doi.org/10.1016/j.renene.2026.126338
- Rotor equivalent wind speed prediction based on mechanism analysis and residual correction using Lidar measurements D. Song et al. https://doi.org/10.1016/j.enconman.2023.117385
- Adaptive PI Optimal Pitch Control for Wind Turbines with Tower Active Damping R. Wang et al. https://doi.org/10.1177/18758967251357634
- Turbulence structure in a boundary layer wind tunnel X. Wang et al. https://doi.org/10.1063/5.0246592
- A key conditional quotient filter for nonlinear, non-Gaussian, and non-Markovian systems Y. Zeng et al. https://doi.org/10.3934/math.2026366
22 citations as recorded by crossref.
- Lidar-assisted nonlinear output regulation of wind turbines for fatigue load reduction R. Moldenhauer & R. Schmid https://doi.org/10.5194/wes-10-1907-2025
- Experimental investigation of wind turbine controllers for the Hybrid-Lambda Rotor D. Ribnitzky et al. https://doi.org/10.5194/wes-11-469-2026
- Wind speed estimation using second-order sliding-mode observers: simulation and experimental validation on a floating offshore wind turbine M. Sarbandi et al. https://doi.org/10.5194/wes-11-2405-2026
- The performance of two control strategies for floating wind turbines: lidar-assisted feedforward and multi-variable feedback F. Guo et al. https://doi.org/10.1088/1742-6596/2626/1/012005
- Enhancing Wind Turbine Sustainability Through LiDAR Configuration Analysis and Evaluation of Two Reference LiDAR-Assisted Control Strategies C. Steinmann Perez et al. https://doi.org/10.3390/su17136083
- LIDAR‐assisted feedforward individual pitch control of a 15 MW floating offshore wind turbine A. Russell et al. https://doi.org/10.1002/we.2891
- A LiDAR-Based Active Yaw Control Strategy for Optimal Wake Steering in Paired Wind Turbines E. Mahmoodi et al. https://doi.org/10.3390/en17225635
- Assessing lidar-assisted feedforward and multivariable feedback controls for large floating wind turbines F. Guo & D. Schlipf https://doi.org/10.5194/wes-8-1299-2023
- 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
- Wind Turbine Generator Speed Regulation Enabled by Ground‐Level Air Pressure Measurements M. Lingad et al. https://doi.org/10.1049/rpg2.70292
- Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar W. Fu et al. https://doi.org/10.5194/wes-8-1893-2023
- Analysis and evaluation of two reference LiDAR-assisted control designs for wind turbines C. Steinmann Perez et al. https://doi.org/10.1088/1742-6596/2767/3/032048
- Design and experimental validation of a continuous-wave lidar for wind-field measurements in a wave-basin model test of a floating wind turbine F. Guo et al. https://doi.org/10.1016/j.joes.2026.10.005
- Effects of turbulence inhomogeneity and atmosphere stability on the aeroelastic response of the IEA 22 MW wind turbine F. Guo et al. https://doi.org/10.1016/j.renene.2025.124384
- 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
- LiDAR-informed transformer framework for spatiotemporal estimation of rotor-effective wind speed beyond Taylor’s frozen turbulence hypothesis M. Zhang et al. https://doi.org/10.1016/j.energy.2026.142669
- On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods F. Guo et al. https://doi.org/10.1002/we.70098
- Performance and robustness evaluation of retrofit and standard LiDAR-assisted control in wind turbines A. Lio et al. https://doi.org/10.1016/j.renene.2026.126338
- Rotor equivalent wind speed prediction based on mechanism analysis and residual correction using Lidar measurements D. Song et al. https://doi.org/10.1016/j.enconman.2023.117385
- Adaptive PI Optimal Pitch Control for Wind Turbines with Tower Active Damping R. Wang et al. https://doi.org/10.1177/18758967251357634
- Turbulence structure in a boundary layer wind tunnel X. Wang et al. https://doi.org/10.1063/5.0246592
- A key conditional quotient filter for nonlinear, non-Gaussian, and non-Markovian systems Y. Zeng et al. https://doi.org/10.3934/math.2026366
Saved (final revised paper)
Latest update: 02 Nov 2026
Short summary
The benefits of lidar-assisted control are evaluated using both the Mann model and Kaimal model-based 4D turbulence, considering the variation of turbulence parameters. Simulations are performed for the above-rated mean wind speed, using the NREL 5.0 MW reference wind turbine and a four-beam lidar system. Using lidar-assisted control reduces the variations in rotor speed, pitch rate, tower base fore–aft bending moment, and electrical power significantly.
The benefits of lidar-assisted control are evaluated using both the Mann model and Kaimal...
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