Investigation of a new analytical wake prediction method for offshore floating wind turbines considering an accurate incoming wind flow

Yangwei Wang, Jiahuan Lin and Jun Zhang

Renewable Energy, 2022, vol. 185, issue C, 827-849

Abstract: High prediction accuracy of the wake is crucial for the aerodynamic design and layout optimization of the offshore floating wind turbine (OFWT) in a wind farm. In order to achieve this, an innovative three-dimensional (3D) analytical wake prediction method is developed for the first time. Compared with previous methods, the present one considers an accurate incoming wind flow including the environmental and structural disturbances, which is more closer to the reality. Besides, it adopts a more physically intuitive wake expansion model and a novel 3D Gaussian wake model to predict the wake. To verify this method, comparisons with the experimental data from four worldwide wind tunnels are conducted. The results are excellent from the near to far wake regions, which can prove its high prediction accuracy. Finally, based on this method, the effects of the included wind disturbances on the wake are analyzed comprehensively to reveal the internal mechanism affecting the prediction. The results show that these wind disturbances can affect the wake significantly. The present study could make a theoretical contribution to the wake modeling and the aerodynamic study of the OFWT.

Keywords: Offshore floating wind turbine; Incoming wind flow; Wind tunnel measured data; Wake prediction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:185:y:2022:i:c:p:827-849

DOI: 10.1016/j.renene.2021.12.060

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