Paper
24 October 2022 Research on wake characteristics and power output of Spar wind turbine at medium and low wind speeds
Jiaping Cui, Yingming Liu, Xiaodong Wang, Pengbo Zhang
Author Affiliations +
Proceedings Volume 12289, International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022); 122890V (2022) https://doi.org/10.1117/12.2640704
Event: International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022), 2022, Kunming, China
Abstract
With the development of wind energy industry, the application of floating wind turbine has been largely solved at the technical level. Since the floating wind turbine has six additional degrees of freedom, the dynamic response of its rotor and the wake characteristics also change accordingly. Compared with offshore bottom-fixed wind turbines, the wake of floating wind turbines has a different impact on the power output of downstream units. A Spar-type floating wind farm model is established, and simulation calculations are carried out under medium and low ambient wind speeds. By using scatter plots, box plots, etc., the time series data of the displacement of the rotor and the position of the center of the wake are compared and studied. The conclusions are as follows: Spar-type wind turbine has a wider range of motion of the rotor, and the wake is more dispersed. Meanwhile, the wake effect of Spar-type wind turbine has a wider range but a weaker degree of influence to the downstream units. Floating wind farms composed of Spar-type wind turbines have higher power output under the same external environment.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiaping Cui, Yingming Liu, Xiaodong Wang, and Pengbo Zhang "Research on wake characteristics and power output of Spar wind turbine at medium and low wind speeds", Proc. SPIE 12289, International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022), 122890V (24 October 2022); https://doi.org/10.1117/12.2640704
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KEYWORDS
Wind turbine technology

Turbulence

Wind energy

Analytical research

Data modeling

Motion analysis

Performance modeling

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