Articles | Volume 15, issue 24
https://doi.org/10.5194/amt-15-7211-2022
https://doi.org/10.5194/amt-15-7211-2022
Research article
 | 
16 Dec 2022
Research article |  | 16 Dec 2022

High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning

Kenneth A. Brown and Thomas G. Herges

Related authors

Spectral proper orthogonal decomposition of active wake mixing dynamics in a stable atmospheric boundary layer
Gopal R. Yalla, Kenneth Brown, Lawrence Cheung, Dan Houck, Nathaniel deVelder, and Nicholas Hamilton
Wind Energ. Sci., 10, 2449–2474, https://doi.org/10.5194/wes-10-2449-2025,https://doi.org/10.5194/wes-10-2449-2025, 2025
Short summary
Detailed experimental investigation of the aerodynamics and blade/tower interaction of a 1.5 MW wind turbine in a downwind configuration
Helge Aagaard Madsen, Pietro Bortolotti, Athanasios Barlas, Pourya Nikoueeyan, Christopher Kelley, Claus Brian Munk Pedersen, Per Hansen, Andreas Fischer, Chris Ivanov, Jason Roadman, Jonathan W. Naughton, Kenneth Brown, Mark Iverson, and Simon Thao
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-204,https://doi.org/10.5194/wes-2025-204, 2025
Preprint under review for WES
Short summary
Comparison of wind-farm control strategies under realistic offshore wind conditions: wake quantities of interest
Kenneth Brown, Gopal Yalla, Lawrence Cheung, Joeri Frederik, Dan Houck, Nathaniel deVelder, Eric Simley, and Paul Fleming
Wind Energ. Sci., 10, 1737–1762, https://doi.org/10.5194/wes-10-1737-2025,https://doi.org/10.5194/wes-10-1737-2025, 2025
Short summary
Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures
Lawrence Cheung, Gopal Yalla, Prakash Mohan, Alan Hsieh, Kenneth Brown, Nathaniel deVelder, Daniel Houck, Marc T. Henry de Frahan, Marc Day, and Michael Sprague
Wind Energ. Sci., 10, 1403–1420, https://doi.org/10.5194/wes-10-1403-2025,https://doi.org/10.5194/wes-10-1403-2025, 2025
Short summary
Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest
Joeri A. Frederik, Eric Simley, Kenneth A. Brown, Gopal R. Yalla, Lawrence C. Cheung, and Paul A. Fleming
Wind Energ. Sci., 10, 755–777, https://doi.org/10.5194/wes-10-755-2025,https://doi.org/10.5194/wes-10-755-2025, 2025
Short summary

Cited articles

Albers, A., Janssen, A., and Mander, J.: German Test Station for Remote Wind Sensing Devices, EWEC, Marseille, https://www.researchgate.net/profile/Axel_Albers/publication/237616810_German_Test_Station_for_Remote_Wind_Sensing_Devices/links/568e2aee08ae78cc0514b121.pdf (last access: 19 September 2020), 2009. 
Angelou, N., Abari, F. F., Mann, J., Mikkelsen, T., and Sjöholm, M.: Challenges in noise removal from Doppler spectra acquired by a continuous-wave lidar, Proc. 26th Int. Laser Radar Conf., Porto Heli, Greece, 10 pp., 2012. 
Beck, H. and Kühn, M.: Dynamic data filtering of long-range Doppler LiDAR wind speed measurements, Remote Sens., 9, 561, https://doi.org/10.3390/rs9060561, 2017.  
Benedict, L. and Gould, R.: Towards better uncertainty estimates for turbulence statistics, Exp. Fluids, 22, 129–136, https://doi.org/10.1007/s003480050030, 1996. 
Download
Short summary
The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.
Share