Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-133-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-133-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Mar 2017
Research article |
| 13 Mar 2017
Turbulence characterization from a forward-looking nacelle lidar
DTU Wind Energy, Technical University of Denmark, Roskilde, Denmark
Jakob Mann
DTU Wind Energy, Technical University of Denmark, Roskilde, Denmark
Nikolay Dimitrov
DTU Wind Energy, Technical University of Denmark, Roskilde, Denmark
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Cited
28 citations as recorded by crossref.
- Wind turbine load validation using lidar‐based wind retrievals N. Dimitrov et al. 10.1002/we.2385
- Influence of nacelle-lidar scanning patterns on inflow turbulence characterization W. Fu et al. 10.1088/1742-6596/2265/2/022016
- Unsteady responses and correlation characteristics of propeller blades under turbulence excitation H. Yao et al. 10.1016/j.oceaneng.2022.112631
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. 10.5194/wes-5-1129-2020
- Evaluation of lidar-assisted wind turbine control under various turbulence characteristics F. Guo et al. 10.5194/wes-8-149-2023
- Field Study of Turbulence Intensity measurement by Nacelle Mounted Lidar (NML) Z. Liang et al. 10.1088/1742-6596/2265/2/022104
- Characterization of turbulence under different stability conditions using lidar scanning data R. Rai et al. 10.1088/1742-6596/1452/1/012085
- Detection of wakes in the inflow of turbines using nacelle lidars D. Held & J. Mann 10.5194/wes-4-407-2019
- Comparison of methods to derive radial wind speed from a continuous-wave coherent lidar Doppler spectrum D. Held & J. Mann 10.5194/amt-11-6339-2018
- Turbulence velocity spectra and intensities in the inflow of a turbine rotor I. Milne & J. Graham 10.1017/jfm.2019.339
- The space-time structure of turbulence for lidar-assisted wind turbine control F. Guo et al. 10.1016/j.renene.2022.05.133
- Investigating Suppression of Cloud Return with a Novel Optical Configuration of a Doppler Lidar L. Jin et al. 10.3390/rs14153576
- Turbulence statistics from three different nacelle lidars W. Fu et al. 10.5194/wes-7-831-2022
- How does turbulence change approaching a rotor? J. Mann et al. 10.5194/wes-3-293-2018
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
- Probabilistic estimation of the Dynamic Wake Meandering model parameters using SpinnerLidar-derived wake characteristics D. Conti et al. 10.5194/wes-6-1117-2021
- Very short-term forecast of near-coastal flow using scanning lidars L. Valldecabres et al. 10.5194/wes-3-313-2018
- Dependence of turbulence estimations on nacelle lidar scanning strategies W. Fu et al. 10.5194/wes-8-677-2023
- High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning K. Brown & T. Herges 10.5194/amt-15-7211-2022
- Østerild: A natural laboratory for atmospheric turbulence A. Peña 10.1063/1.5121486
- Inflow characterization using measurements from the SpinnerLidar: the ScanFlow experiment A. Peña et al. 10.1088/1742-6596/1037/5/052027
- Lower Order Description and Reconstruction of Sparse Scanning Lidar Measurements of Wind Turbine Inflow Using Proper Orthogonal Decomposition A. Kidambi Sekar et al. 10.3390/rs14112681
- Analysis and design of an adaptive turbulence-based controller for wind turbines L. Dong et al. 10.1016/j.renene.2021.06.080
- Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars Y. Chen et al. 10.5194/wes-7-539-2022
- Lidar-based Estimation of Turbulence Intensity for Controller Scheduling D. Schlipf et al. 10.1088/1742-6596/1618/3/032053
- Turbulence Measurements with Dual-Doppler Scanning Lidars A. Peña & J. Mann 10.3390/rs11202444
- Wind turbine wake characterization using the SpinnerLidar measurements D. Conti et al. 10.1088/1742-6596/1618/6/062040
- Dynamic Data Filtering of Long-Range Doppler LiDAR Wind Speed Measurements H. Beck & M. Kühn 10.3390/rs9060561
27 citations as recorded by crossref.
- Wind turbine load validation using lidar‐based wind retrievals N. Dimitrov et al. 10.1002/we.2385
- Influence of nacelle-lidar scanning patterns on inflow turbulence characterization W. Fu et al. 10.1088/1742-6596/2265/2/022016
- Unsteady responses and correlation characteristics of propeller blades under turbulence excitation H. Yao et al. 10.1016/j.oceaneng.2022.112631
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. 10.5194/wes-5-1129-2020
- Evaluation of lidar-assisted wind turbine control under various turbulence characteristics F. Guo et al. 10.5194/wes-8-149-2023
- Field Study of Turbulence Intensity measurement by Nacelle Mounted Lidar (NML) Z. Liang et al. 10.1088/1742-6596/2265/2/022104
- Characterization of turbulence under different stability conditions using lidar scanning data R. Rai et al. 10.1088/1742-6596/1452/1/012085
- Detection of wakes in the inflow of turbines using nacelle lidars D. Held & J. Mann 10.5194/wes-4-407-2019
- Comparison of methods to derive radial wind speed from a continuous-wave coherent lidar Doppler spectrum D. Held & J. Mann 10.5194/amt-11-6339-2018
- Turbulence velocity spectra and intensities in the inflow of a turbine rotor I. Milne & J. Graham 10.1017/jfm.2019.339
- The space-time structure of turbulence for lidar-assisted wind turbine control F. Guo et al. 10.1016/j.renene.2022.05.133
- Investigating Suppression of Cloud Return with a Novel Optical Configuration of a Doppler Lidar L. Jin et al. 10.3390/rs14153576
- Turbulence statistics from three different nacelle lidars W. Fu et al. 10.5194/wes-7-831-2022
- How does turbulence change approaching a rotor? J. Mann et al. 10.5194/wes-3-293-2018
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
- Probabilistic estimation of the Dynamic Wake Meandering model parameters using SpinnerLidar-derived wake characteristics D. Conti et al. 10.5194/wes-6-1117-2021
- Very short-term forecast of near-coastal flow using scanning lidars L. Valldecabres et al. 10.5194/wes-3-313-2018
- Dependence of turbulence estimations on nacelle lidar scanning strategies W. Fu et al. 10.5194/wes-8-677-2023
- High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning K. Brown & T. Herges 10.5194/amt-15-7211-2022
- Østerild: A natural laboratory for atmospheric turbulence A. Peña 10.1063/1.5121486
- Inflow characterization using measurements from the SpinnerLidar: the ScanFlow experiment A. Peña et al. 10.1088/1742-6596/1037/5/052027
- Lower Order Description and Reconstruction of Sparse Scanning Lidar Measurements of Wind Turbine Inflow Using Proper Orthogonal Decomposition A. Kidambi Sekar et al. 10.3390/rs14112681
- Analysis and design of an adaptive turbulence-based controller for wind turbines L. Dong et al. 10.1016/j.renene.2021.06.080
- Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars Y. Chen et al. 10.5194/wes-7-539-2022
- Lidar-based Estimation of Turbulence Intensity for Controller Scheduling D. Schlipf et al. 10.1088/1742-6596/1618/3/032053
- Turbulence Measurements with Dual-Doppler Scanning Lidars A. Peña & J. Mann 10.3390/rs11202444
- Wind turbine wake characterization using the SpinnerLidar measurements D. Conti et al. 10.1088/1742-6596/1618/6/062040
1 citations as recorded by crossref.
Latest update: 26 Sep 2023
Short summary
Nacelle lidars are nowadays extensively used to scan the turbine inflow. Thus, it is important to characterize turbulence from their measurements. We present two methods to perform turbulence estimation and demonstrate them using two types of lidars. With one method we can estimate the along-wind unfiltered variance accurately. With the other we can estimate the filtered radial velocity variance accurately and velocity-tensor parameters under neutral and high wind-speed conditions.
Nacelle lidars are nowadays extensively used to scan the turbine inflow. Thus, it is important...
