Articles | Volume 11, issue 6
https://doi.org/10.5194/amt-11-3801-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-3801-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2018
Research article |
| 28 Jun 2018
| 28 Jun 2018
Wind turbine wake measurements with automatically adjusting scanning trajectories in a multi-Doppler lidar setup
Deutsches Zentrum für Luft- und Raumfahrt e.V., Münchner Str. 20, Oberpfaffenhofen, Germany
Nikola Vasiljevic
DTU Wind Energy, Technical University of Denmark, Frederiksborgvej 399, Building 118-VEA, 4000 Roskilde, Denmark
Thomas Gerz
Deutsches Zentrum für Luft- und Raumfahrt e.V., Münchner Str. 20, Oberpfaffenhofen, Germany
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29 citations as recorded by crossref.
- Adaptive measuring trajectory for scanning lidars: proof of concept Y. Chen et al. 10.1088/1742-6596/2265/2/022099
- Distributed wind measurements with multiple quadrotor unmanned aerial vehicles in the atmospheric boundary layer T. Wetz et al. 10.5194/amt-14-3795-2021
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- Multi-point in situ measurements of turbulent flow in a wind turbine wake and inflow with a fleet of uncrewed aerial systems T. Wetz & N. Wildmann 10.5194/wes-8-515-2023
- Turbulence Measurements with Dual-Doppler Scanning Lidars A. Peña & J. Mann 10.3390/rs11202444
- Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network A. Luther et al. 10.5194/acp-22-5859-2022
- Influences of lidar scanning parameters on wind turbine wake retrievals in complex terrain R. Robey & J. Lundquist 10.5194/wes-9-1905-2024
- Fast Dual-LiDAR Reconstruction for Dynamic Wind Field Retrieval Y. Bao et al. 10.3390/atmos13060905
- Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans N. Wildmann et al. 10.5194/amt-13-4141-2020
- Actuator Disc Approach of Wind Turbine Wake Simulation Considering Balance of Turbulence Kinetic Energy H. Ren et al. 10.3390/en12010016
- First identification and quantification of detached-tip vortices behind a wind energy converter using fixed-wing unmanned aircraft system M. Mauz et al. 10.5194/wes-4-451-2019
- Inter-comparison study of wind measurement between the three-lidar-based virtual tower and four lidars using VAD techniques X. Liu et al. 10.1080/10095020.2024.2307930
- The Second Wind Forecast Improvement Project (WFIP2): General Overview W. Shaw et al. 10.1175/BAMS-D-18-0036.1
- The Role of Computational Science in Wind and Solar Energy: A Critical Review D. Drikakis & T. Dbouk 10.3390/en15249609
- Grand challenges in the science of wind energy P. Veers et al. 10.1126/science.aau2027
- A Review of Progress and Applications of Pulsed Doppler Wind LiDARs Z. Liu et al. 10.3390/rs11212522
- A novel two-dimensional entrainment wake model for wind turbine wakes N. Li et al. 10.1080/15435075.2021.1987916
- Long-range Doppler lidar measurements of wind turbine wakes and their interaction with turbulent atmospheric boundary-layer flow at Perdigao 2017 N. Wildmann et al. 10.1088/1742-6596/1618/3/032034
- The COTUR project: remote sensing of offshore turbulence for wind energy application E. Cheynet et al. 10.5194/amt-14-6137-2021
- Investigation of wind turbine performance coupling wake and topography effects based on LiDAR measurements and SCADA data X. Gao et al. 10.1016/j.apenergy.2019.113816
- Long-term simulation of the boundary layer flow over the double-ridge site during the Perdigão 2017 field campaign J. Wagner et al. 10.5194/acp-19-1129-2019
- Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign N. Wildmann et al. 10.5194/amt-12-6401-2019
- Analysis of flow in complex terrain using multi-Doppler lidar retrievals T. Bell et al. 10.5194/amt-13-1357-2020
- An evaluation of different measurement strategies to measure wind turbine near wake flow with small multicopter UAS N. Wildmann & J. Kistner 10.1088/1742-6596/2767/4/042004
- Comparison studies of the Scheimpflug lidar technique and the pulsed lidar technique for atmospheric aerosol sensing L. Mei et al. 10.1364/AO.58.008981
- Spatially distributed and simultaneous wind measurements with a fleet of small quadrotor UAS T. Wetz & N. Wildmann 10.1088/1742-6596/2265/2/022086
- Automated wind turbine wake characterization in complex terrain R. Barthelmie & S. Pryor 10.5194/amt-12-3463-2019
- On the self-similarity of wind turbine wakes in a complex terrain using large eddy simulation A. Dar et al. 10.5194/wes-4-633-2019
- Exploring dual-lidar mean and turbulence measurements over Perdigão's complex terrain I. Coimbra et al. 10.5194/amt-18-287-2025
Latest update: 23 Apr 2025
Short summary
Wind turbines extract energy from the flow which manifests in a region of lower wind speeds and increased turbulence downstream of the rotor, the so-called wake. Understanding the characteristics of the wake is a key challenge for wind-energy research. A new strategy for measuring the wind in the wake with three synchronized lidar instruments is presented. The measurement points are automatically adapted to the prevailing wind direction to achieve continuous monitoring of wake properties.
Wind turbines extract energy from the flow which manifests in a region of lower wind speeds and...
