Abstract
Wind turbines are among the fastest-growing technologies for producing sustainable energy. Although numerous studies have been carried out to investigate the dynamic behavior of wind turbines exposed to synoptic winds, the dynamic behavior of such structures under downbursts is not comprehensively studied and not yet well-understood. As such, the main objective of the current study is to develop a numerical model that can be used to investigate the dynamic response of wind turbines subjected to downbursts taking into account the fluid-structure interaction (FSI) effect. To achieve this task, two modules are developed in this study and are integrated with the open-source code, fatigue, aerodynamics, structures, and turbulence (FAST). These modules introduce a three-dimensional (3D) time history of the downburst wind field into FAST inflow-wind module and simulate the interaction between the downburst wind field and the wind turbine structure. The downburst wind field consists of a moving mean component with a superimposed turbulence. The mean component is generated using a previously conducted computational fluid dynamics (CFD) simulation. The turbulence is simulated using the consistent discrete random flow generation (CDRFG) method as a stochastic process based on the turbulence power spectral density and the coherence functions pertaining to downbursts. The developed numerical model is validated using the results of a previously performed experiment on a wind turbine model sited in microburst-liked winds. A parametric study is then conducted on a wind turbine model to investigate the dynamic responses of the tower and blades with and without FSI effect under various downburst configurations. A comparison between the wind turbine quasistatic and dynamic responses is conducted, and the dynamic amplification factor (DAF) is then calculated. The aerodynamic damping of the blades is also estimated and compared with a previously developed closed form solution.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors acknowledge the support from the Natural Sciences and Engineering Research Council of Canada (NSERC), National Natural Science Foundation of China (51878426), and Research Funds from Chengdu (2019-GH02-00081-HZ) and Deyang (2021JBJZ002).
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Journal of Structural Engineering
Volume 149 • Issue 11 • November 2023
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© 2023 American Society of Civil Engineers.
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Received: Aug 5, 2022
Accepted: Jun 23, 2023
Published online: Aug 18, 2023
Published in print: Nov 1, 2023
Discussion open until: Jan 18, 2024
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