Articles | Volume 6, issue 6
https://doi.org/10.5194/wes-6-1491-2021
https://doi.org/10.5194/wes-6-1491-2021
Research article
 | 
30 Nov 2021
Research article |  | 30 Nov 2021

On turbulence models and lidar measurements for wind turbine control

Liang Dong, Wai Hou Lio, and Eric Simley

Related authors

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, Nate deVelder, Eric Simley, and Paul Fleming
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-191,https://doi.org/10.5194/wes-2024-191, 2025
Preprint under review for WES
Short summary
Field comparison of load-based wind turbine wake tracking with a scanning lidar reference
David Onnen, Gunner Christian Larsen, Alan Wai Hou Lio, Paul Hulsman, Martin Kühn, and Vlaho Petrović
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-188,https://doi.org/10.5194/wes-2024-188, 2025
Preprint under review for WES
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. Discuss., https://doi.org/10.5194/wes-2024-164,https://doi.org/10.5194/wes-2024-164, 2024
Revised manuscript accepted for WES
Short summary
The value of wake steering wind farm flow control in US energy markets
Eric Simley, Dev Millstein, Seongeun Jeong, and Paul Fleming
Wind Energ. Sci., 9, 219–234, https://doi.org/10.5194/wes-9-219-2024,https://doi.org/10.5194/wes-9-219-2024, 2024
Short summary
Increased power gains from wake steering control using preview wind direction information
Balthazar Arnoldus Maria Sengers, Andreas Rott, Eric Simley, Michael Sinner, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 8, 1693–1710, https://doi.org/10.5194/wes-8-1693-2023,https://doi.org/10.5194/wes-8-1693-2023, 2023
Short summary

Related subject area

Wind and turbulence
Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands
Caleb Phillips, Lindsay M. Sheridan, Patrick Conry, Dimitrios K. Fytanidis, Dmitry Duplyakin, Sagi Zisman, Nicolas Duboc, Matt Nelson, Rao Kotamarthi, Rod Linn, Marc Broersma, Timo Spijkerboer, and Heidi Tinnesand
Wind Energ. Sci., 7, 1153–1169, https://doi.org/10.5194/wes-7-1153-2022,https://doi.org/10.5194/wes-7-1153-2022, 2022
Short summary
Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models
Jana Fischereit, Kurt Schaldemose Hansen, Xiaoli Guo Larsén, Maarten Paul van der Laan, Pierre-Elouan Réthoré, and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022,https://doi.org/10.5194/wes-7-1069-2022, 2022
Short summary
Large-eddy simulation of airborne wind energy farms
Thomas Haas, Jochem De Schutter, Moritz Diehl, and Johan Meyers
Wind Energ. Sci., 7, 1093–1135, https://doi.org/10.5194/wes-7-1093-2022,https://doi.org/10.5194/wes-7-1093-2022, 2022
Short summary
Investigation into boundary layer transition using wall-resolved large-eddy simulations and modeled inflow turbulence
Brandon Arthur Lobo, Alois Peter Schaffarczyk, and Michael Breuer
Wind Energ. Sci., 7, 967–990, https://doi.org/10.5194/wes-7-967-2022,https://doi.org/10.5194/wes-7-967-2022, 2022
Short summary
Evaluation of the global-blockage effect on power performance through simulations and measurements
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 875–886, https://doi.org/10.5194/wes-7-875-2022,https://doi.org/10.5194/wes-7-875-2022, 2022
Short summary

Cited articles

Bak, C., Zahle, F., Bitsche, R., Yde, A., Henriksen, L. C., Natarajan, A., and Hansen, M. H.: Description of the DTU 10 MW Reference Wind Turbine, Tech. rep., DTU Wind Energy Report-I-0092, DTU Wind Energy, Roskilde, Denmark, 2013. a
Bossanyi, E.: Un-freezing the turbulence: application to LiDAR-assisted wind turbine control, IET Renew. Power Generat., 7, 321–329, 2013. a, b
Bossanyi, E., Kumar, A., and Hugues-Salas, O.: Wind turbine control applications of turbine-mounted LIDAR, J. Phys.: Conf. Ser., 555, 012011, https://doi.org/10.1088/1742-6596/555/1/012011, 2014. a
Chougule, A., Mann, J., Kelly, M., Sun, J., Lenschow, D. H., and Patton, E. G.: Vertical cross-spectral phases in neutral atmospheric flow, J. Turbulence, 13, N36, https://doi.org/10.1080/14685248.2012.711524, 2012. a
Eliassen, L. and Obhrai, C.: Coherence of Turbulent Wind under Neutral Wind Conditions at FINO1, in: Energy Procedia, vol. 94, Elsevier Ltd, Trondheim, Norway, 388–398, https://doi.org/10.1016/j.egypro.2016.09.199, 2016. a
Download
Short summary
This paper suggests that the impacts of different turbulence models should be considered as uncertainties while evaluating the benefits of lidar-assisted control (LAC) in wind turbine design. The value creation of LAC, evaluated using the Kaimal turbulence model, will be diminished if the Mann turbulence model is used instead. In particular, the difference in coherence is more significant for larger rotors.
Share
Altmetrics
Final-revised paper
Preprint