Prediction of multi-wake problems using an improved Jensen wake model

被引：46

作者：

Tian, Linlin ^{[1
]}

Zhu, Weijun ^{[2
]}

Shen, Wenzhong ^{[2
]}

Song, Yilei ^{[1
]}

Zhao, Ning ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Jiangsu Key Lab Hitech Res Wind Turbine Design, Nanjing 210016, Jiangsu, Peoples R China

[2] Tech Univ Denmark, Dept Wind Energy, Fluid Mech Sect, Bldg 403, DK-2800 Lyngby, Denmark

来源：

RENEWABLE ENERGY | 2017年 / 102卷

关键词：

Wake model; Wind turbine wakes; Multiple wakes interaction; Power losses; Horns Rev wind farm; WIND-TURBINE WAKES; OFFSHORE; FARMS; LES;

D O I：

10.1016/j.renene.2016.10.065

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The improved analytical wake model named as 2D_k Jensen model (which was proposed to overcome some shortcomes in the classical Jensen wake model) is applied and validated in this work for wind turbine multi-wake predictions. Different from the original Jensen model, this newly developed 2D_k Jensen model uses a cosine shape instead of the top-hat shape for the velocity deficit in the wake, and the wake decay rate as a variable that is related to the ambient turbulence as well as the rotor generated turbulence. Coupled with four different multi-wake combination models, the 2D_k Jensen model is assessed through (1) simulating two wakes interaction under full wake and partial wake conditions and (2) predicting the power production in the Horns Rev wind farm for different wake sectors around two different wind directions. Through comparisons with field measurements, results from Large Eddy Simulations (LES) as well as results from other commercial codes, it is found that the predictions obtained with the 2D_k Jensen model exhibit good to excellent agreements with experimental and LES data. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：457 / 469

页数：13

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