Articles | Volume 8, issue 2
https://doi.org/10.5194/wes-8-149-2023
https://doi.org/10.5194/wes-8-149-2023
Research article
 | 
09 Feb 2023
Research article |  | 09 Feb 2023

Evaluation of lidar-assisted wind turbine control under various turbulence characteristics

Feng Guo, David Schlipf, and Po Wen Cheng

Related authors

Analysis of Turbine Yaw Misalignment Estimated by LIDAR Assuming Homogeneous Flow
Zhaoyu Zhang, Feng Guo, David Schlipf, Paolo Schito, and Alberto Zasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-162,https://doi.org/10.5194/wes-2023-162, 2024
Preprint withdrawn
Short summary
Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar
Wei Fu, Feng Guo, David Schlipf, and Alfredo Peña
Wind Energ. Sci., 8, 1893–1907, https://doi.org/10.5194/wes-8-1893-2023,https://doi.org/10.5194/wes-8-1893-2023, 2023
Short summary
Assessing lidar-assisted feedforward and multivariable feedback controls for large floating wind turbines
Feng Guo and David Schlipf
Wind Energ. Sci., 8, 1299–1317, https://doi.org/10.5194/wes-8-1299-2023,https://doi.org/10.5194/wes-8-1299-2023, 2023
Short summary
Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars
Yiyin Chen, Feng Guo, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 7, 539–558, https://doi.org/10.5194/wes-7-539-2022,https://doi.org/10.5194/wes-7-539-2022, 2022
Short summary

Related subject area

Thematic area: Dynamics and control | Topic: Wind turbine control
Multi-objective calibration of vertical-axis wind turbine controllers: balancing aero-servo-elastic performance and noise
Livia Brandetti, Sebastiaan Paul Mulders, Roberto Merino-Martinez, Simon Watson, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 471–493, https://doi.org/10.5194/wes-9-471-2024,https://doi.org/10.5194/wes-9-471-2024, 2024
Short summary
Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar
Wei Fu, Feng Guo, David Schlipf, and Alfredo Peña
Wind Energ. Sci., 8, 1893–1907, https://doi.org/10.5194/wes-8-1893-2023,https://doi.org/10.5194/wes-8-1893-2023, 2023
Short summary
Wind vane correction during yaw misalignment for horizontal-axis wind turbines
Andreas Rott, Leo Höning, Paul Hulsman, Laura J. Lukassen, Christof Moldenhauer, and Martin Kühn
Wind Energ. Sci., 8, 1755–1770, https://doi.org/10.5194/wes-8-1755-2023,https://doi.org/10.5194/wes-8-1755-2023, 2023
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
Combining wake redirection and derating strategies in a wind farm load-constrained power maximization
Alessandro Croce, Stefano Cacciola, and Federico Isella
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-145,https://doi.org/10.5194/wes-2023-145, 2023
Revised manuscript accepted for WES
Short summary

Cited articles

Abbas, N. J., Zalkind, D. S., Pao, L., and Wright, A.: A reference open-source controller for fixed and floating offshore wind turbines, Wind Energ. Sci., 7, 53–73, https://doi.org/10.5194/wes-7-53-2022, 2022. a, b, c, d
Bossanyi, E. A., 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
Chen, Y., Schlipf, D., and Cheng, P. W.: Parameterization of wind evolution using lidar, Wind Energ. Sci., 6, 61–91, https://doi.org/10.5194/wes-6-61-2021, 2021. a, b, c
Chen, Y., Guo, F., Schlipf, D., and Cheng, P. W.: Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars, Wind Energ. Sci., 7, 539–558, https://doi.org/10.5194/wes-7-539-2022, 2022. a, b, c, d, e, f, g
Chen, Z. and Stol, K.: An assessment of the effectiveness of individual pitch control on upscaled wind turbines, J. Phys.-Conf. Ser., 524, 012045, https://doi.org/10.1088/1742-6596/524/1/012045, 2014. a
Download
Short summary
The benefits of lidar-assisted control are evaluated using both the Mann model and Kaimal model-based 4D turbulence, considering the variation of turbulence parameters. Simulations are performed for the above-rated mean wind speed, using the NREL 5.0 MW reference wind turbine and a four-beam lidar system. Using lidar-assisted control reduces the variations in rotor speed, pitch rate, tower base fore–aft bending moment, and electrical power significantly.
Altmetrics
Final-revised paper
Preprint