A nonlinear wake model of a wind turbine considering the yaw wake steering

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外文摘要：Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a"prediction-correction"method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8％compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.

外文关键词：

far wakewake modelwake steeringwind shearwind farm

作者：

Yunzhou LI、Zhiteng GAO、Shoutu LI、Suiping QI、Xiaoyu TANG

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作者单位：

College of Meteorology and Oceanography,National University of Defense Technology,Changsha 410073,China

School of Energy and Power Engineering,Lanzhou University of Technology,Lanzhou 730050,China

Laoshan Laboratory,Qingdao 266237,China

Multi-function Towing Tank,School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

Institute of Oceanographic Instrumentation,Qilu University of Technology(Shandong Academy of Sciences),Qingdao 266061,China

State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,Zhejiang University,Hangzhou 310027,China

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基金：

山东省重点研发计划国家重点研发计划国家自然科学基金中国博士后科学基金Zhejiang Provincial Natural Science Foundation(ZJNSF)

项目编号：

2023ZLYS012022YFC3104200123023012023M742229LQ22F030002

出版年：

2024

DOI：

10.1007/s00343-023-3040-6

海洋湖沼学报(英文版)

中国海洋湖沼学会

海洋湖沼学报(英文版)

CSTPCD

影响因子：0.386

ISSN：2096-5508

年,卷(期)：2024.42(3)