Articles | Volume 6, issue 7
https://doi.org/10.5194/amt-6-1673-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-6-1673-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Jul 2013
Research article |
| 15 Jul 2013
Retrieving wind statistics from average spectrum of continuous-wave lidar
E. Branlard
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
A. T. Pedersen
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
N. Angelou
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
A. Fischer
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
T. Mikkelsen
DTU Wind Energy, Risø Campus, Technical University of Denmark, Roskilde, Denmark
M. Harris
ZephIR Ltd., The Old Barns, Fairoaks Farm, Hollybush, Ledbury, HR8 1EU, UK
C. Slinger
ZephIR Ltd., The Old Barns, Fairoaks Farm, Hollybush, Ledbury, HR8 1EU, UK
B. F. Montes
LM Wind Power, Lunderskov, Denmark
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- Robust Lidar Data Processing and Quality Control Methods Developed for the SWiFT Wake Steering Experiment T. Herges & P. Keyantuo 10.1088/1742-6596/1256/1/012005
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29 citations as recorded by crossref.
- Measured wind and morphological characteristics of a peri-urban environment and their impact on the performance of an operational large-scale wind turbine R. Byrne et al. 10.1016/j.jweia.2021.104592
- Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar F. Kelberlau et al. 10.3390/rs12050898
- A review of turbulence measurements using ground-based wind lidars A. Sathe & J. Mann 10.5194/amt-6-3147-2013
- Robust Lidar Data Processing and Quality Control Methods Developed for the SWiFT Wake Steering Experiment T. Herges & P. Keyantuo 10.1088/1742-6596/1256/1/012005
- Turbulence characterization from a forward-looking nacelle lidar A. Peña et al. 10.5194/wes-2-133-2017
- Detection of wakes in the inflow of turbines using nacelle lidars D. Held & J. Mann 10.5194/wes-4-407-2019
- Dependence of turbulence estimations on nacelle lidar scanning strategies W. Fu et al. 10.5194/wes-8-677-2023
- The lidar probe volume averaging effect: A wind tunnel investigation in streamwise turbulence with continuous-wave lidar S. Uluocak et al. 10.1088/1742-6596/2767/4/042027
- An error reduction algorithm to improve lidar turbulence estimates for wind energy J. Newman & A. Clifton 10.5194/wes-2-77-2017
- A comparison of four microscale wind flow models in predicting the real-world performance of a large-scale peri-urban wind turbine, using onsite LiDAR wind measurements R. Byrne et al. 10.1016/j.seta.2021.101323
- Better turbulence spectra from velocity–azimuth display scanning wind lidar F. Kelberlau & J. Mann 10.5194/amt-12-1871-2019
- A six-beam method to measure turbulence statistics using ground-based wind lidars A. Sathe et al. 10.5194/amt-8-729-2015
- Suppression of precipitation bias in wind velocities from continuous-wave Doppler lidars L. Jin et al. 10.5194/amt-16-6007-2023
- Directly measuring the power-law exponent and kinetic energy of atmospheric turbulence using coherent Doppler wind lidar J. Xian et al. 10.5194/amt-17-1837-2024
- Investigation of single-particle detection of continuous-wave coherent Doppler lidar: theoretical feasibility and performance comparison with multiple-particle detection state S. Kameyama 10.35848/1347-4065/ad2f19
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. 10.5194/wes-5-1129-2020
- Wake detection in the turbine inflow using nacelle lidars D. Held et al. 10.1088/1742-6596/1102/1/012005
- Wind turbine load validation using lidar‐based wind retrievals N. Dimitrov et al. 10.1002/we.2385
- Detailed analysis of a waked turbine using a high-resolution scanning lidar T. Herges et al. 10.1088/1742-6596/1037/7/072009
- Detecting wind turbine wakes with nacelle lidars D. Held et al. 10.1088/1742-6596/854/1/012020
- An assessment of the mesoscale to microscale influences on wind turbine energy performance at a peri-urban coastal location from the Irish wind atlas and onsite LiDAR measurements R. Byrne et al. 10.1016/j.seta.2019.100537
- Exploring the Feasibility of Using Commercially Available Vertically Pointing Wind Profiling Lidars to Acquire Thunderstorm Wind Profiles W. Gunter 10.3389/fbuil.2019.00119
- Assessing the Severity of Wind Gusts with Lidar R. Bos et al. 10.3390/rs8090758
- Errors in radial velocity variance from Doppler wind lidar H. Wang et al. 10.5194/amt-9-4123-2016
- 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
- Characteristics of the atmospheric boundary layer height: A perspective on turbulent motion J. Xian et al. 10.1016/j.scitotenv.2024.170895
- 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
- Alternative Braking Method for Small Scaled-Wind Turbines Connected DC Green House with Analogical Experiment on Blade Destruction A. Koswatta et al. 10.25046/aj050264
- Assessment of wind fields over forested sites with LES and a nacelle lidar H. Olivares-Espinosa et al. 10.1088/1742-6596/1256/1/012002
1 citations as recorded by crossref.
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