Articles | Volume 7, issue 2
Research article
11 Mar 2022
Research article |  | 11 Mar 2022

Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars

Yiyin Chen, Feng Guo, David Schlipf, and Po Wen Cheng

Related authors

Parameterization of wind evolution using lidar
Yiyin Chen, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 6, 61–91,,, 2021
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,,, 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,,, 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,,, 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,,, 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,,, 2022
Short summary

Cited articles

Banakh, V. and Smalikho, I.: Estimation of the turbulence energy dissipation rate from the pulsed Doppler lidar data, J. Atmos. Ocean. Tech., 10, 957–965, 1994. a
Bartlett, M. S.: Smoothing periodograms from time-series with continuous spectra, Nature, 161, 686–687,, 1948. a
Bos, R.: Extreme gusts and their role in wind turbine design, Dissertation, Delft University of Technology,, 2017. a, b
Bossanyi, E.: Un-freezing the turbulence: Application to LiDAR-assisted wind turbine control, IET Renew. Power Gen., 7, 321–329,, 2013. a, b
Bossanyi, E. A., Kumar, A., and Hugues-Salas, O.: Wind turbine control applications of turbine-mounted LIDAR, J. Phys.-Conf. Ser., 555, 012011,, 2014. a, b
Short summary
Lidar-assisted control of wind turbines requires a wind field generator capable of simulating wind evolution. Out of this need, we extend the Veers method for 3D wind field generation to 4D and propose a two-step Cholesky decomposition approach. Based on this, we develop a 4D wind field generator – evoTurb – coupled with TurbSim and Mann turbulence generator. We further investigate the impacts of the spatial discretization in 4D wind fields on lidar simulations to provide practical suggestions.
Final-revised paper