Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine

被引:101
作者
Hong, Jiarong [1 ,2 ]
Toloui, Mostafa [1 ,2 ]
Chamorro, Leonardo P. [1 ,3 ]
Guala, Michele [1 ,4 ]
Howard, Kevin [1 ,4 ]
Riley, Sean [2 ]
Tucker, James [1 ]
Sotiropoulos, Fotis [1 ,4 ]
机构
[1] St Anthony Falls Lab, Minneapolis, MN 55414 USA
[2] Univ Minnesota, Dept Mech Engn, Minneapolis, MN 55455 USA
[3] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL 61801 USA
[4] Univ Minnesota, Dept Civil Engn, Minneapolis, MN 55455 USA
关键词
PARTICLE IMAGE VELOCIMETRY; HORIZONTAL-AXIS; MODEL;
D O I
10.1038/ncomms5216
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
To improve power production and structural reliability of wind turbines, there is a pressing need to understand how turbines interact with the atmospheric boundary layer. However, experimental techniques capable of quantifying or even qualitatively visualizing the large-scale turbulent flow structures around full-scale turbines do not exist today. Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine in a sampling area of similar to 36 x 36m(2). The spatial and temporal resolutions of the measurements are sufficiently high to quantify the evolution of blade-generated coherent motions, such as the tip and trailing sheet vortices, identify their instability mechanisms and correlate them with turbine operation, control and performance. Our experiment provides an unprecedented in situ characterization of flow structures around utility-scale turbines, and yields significant insights into the Reynolds number similarity issues presented in wind energy applications.
引用
收藏
页数:9
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