AIAA 2011-3815
29th AIAA Applied Aerodynamics Conference
27 - 30 June 2011, Honolulu, Hawaii
An Experimental Investigation on the Wake Characteristics of a
Wind Turbine in an Atmospheric Boundary Layer Wind
Zifeng Yang1, Partha Sarkar2 and Hui Hu3 ()
Department of Aerospace Engineering, Iowa State University, Ames, IA, 50010
An experimental study is conducted to characterize the dynamic wind loads and
evolution of the turbulent vortex and flow structures in the wake of a horizontal axis wind
turbine (HAWT). In addition to measuring dynamic wind loads (both aerodynamic forces
and moments) acting on a wind turbine model, a high-resolution Particle Image Velocimetry
(PIV) system was used to make “free-run” and phase-locked flow field measurements to
quantify the time evolution of the turbulence vortex and flow structures in the wake of the
wind turbine model. The detailed flow field measurements were correlated with the dynamic
wind load measurements to elucidate the underlying physics associated with power
generation and fatigue loads acting on wind turbines operating in an atmospheric boundary
wind.
Nomenclature
D
H
R
c
U (z )
U0
U
x
y
z
z0


Diameter of the rotor
Hub height
Radius of the rotor
Blade chord
Wind speed at height z
Wind speed at hub height
Free stream wind speed
Axial coordinate
Vertical coordinate
Transverse coordinate
Roughness height

Rotational speed of the rotor
Tip speed ratio,   (R ) / V
Air density
CD
Drag coefficient, C D  T / 1 V02R 2
CM z
Bend moment coefficient along z direction, CM  M z / 1 V02R 2 H
2
z
2
1
Postdoc Research Associate, Department of Aerospace Engineering, AIAA Member.
Professor, Department of Aerospace Engineering.
3
Associate Professor, Department of Aerospace Engineering, AIAA Associate Fellow, Email: huhui@iastate.edu
1
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2
Copyright © 2011 by Zifeng Yang. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.
I. Introduction
W
ith the oil and gas supply security and climate change emerging as high concerns, the need for renewable
energy sources to alleviate dependence on hydrocarbons and reduce carbon dioxide (CO2) emissions is
becoming increasingly urgent. Wind energy is one of the cleanest renewable power sources in the world today.
While wind energy provides only approximately 1.0% of total U.S. electricity generation in 2008, a target of 20% of
US total electricity generation from wind energy by 2030 has been set up recently by the U.S. Department of Energy
(DoE). To achieve the goal of 20% of electricity generation by 2030, the total wind power capacity in U.S.A. will
need to exceed 300 gigawatts (Schreck et al., 2008). Suppose if each wind turbine could generate about 2.0MW,
which corresponds to large wind turbines with the hub-height about 60 – 100 m and rotor blade diameters about 70
m, it would require at least 150,000 additional large wind turbines installed in onshore or/and offshore wind farms in
order to meet the 20% electricity generation goal. Wind turbine dynamics, micrositing and array effects have been
identified amongst the most significant research topics needed for wind resource characterization and wind power
generation (Schreck et al., 2008). More specifically, detailed measurements and modeling to characterize the surface
wind energy resources and turbulent wake flows of wind turbines are highly desirable in order to provide more
accurate estimations of the power generation and fatigue wind loads acting on wind turbines required for the optimal
wind turbine designs.
The wake of a wind turbine is typically divided into a near and a far wake. The near wake is referred to the
region from the turbine to approximately one rotor diameter downstream. In the near wake, the presence of the rotor
is apparent by the number of blades, blade aerodynamics such as attached or stalled flows, 3-D effects and tip
vortices. A significant feature in the near wake of a wind turbine is the helical tip vortices induced by the rotating
blades. The evolution of the helical tip vortices has been found to affect the behavior of the turbulent wake flow
structures behind a wind turbine significantly. The tip vortices were also recognized as an important source of noise
generation and blade vibration (Massouh & Dobrev, 2007). The far wake is the region beyond the near wake, where
the actual rotor shape is less important. The main attentions for far wake flows are usually drawn in wake models,
wake interference, turbulence models, and topographical effects (Vermeer, 2003).
A good physical understanding about the characteristics of the turbulent vortex flows in the wakes of wind
turbines and the resultant dynamic wind loads acting on the wind turbines is essential for the optimal design of wind
turbines. This requires a detailed knowledge about transient behavior of the turbulent flow structures in the wakes
of wind turbines and the evolution of the helical tip vortices induced by the rotating turbine blades. Although a
number of experimental studies have been conducted to investigate wind turbine wake aerodynamics, most of the
previous studies were carried out based on qualitative flow visualization and/or pointwise flow measurement
techniques, such as hot-wire anemometry, hot-film anemometry and laser Doppler velocimetry, to conduct flow
velocity measurements at limited points of interest (Alfredsson et al.,1979; Tsustui & Matsumya, 1987; Ebert &
Wood, 1997; Vermeer, 2001; Medici & Alfredsson, 2006; and Chamorro and Porte’-Agel, 2009). A common
shortcoming of such pointwise flow measurements is the incapability of providing spatial correlation of the turbulent
wake flow structures to effectively reveal the transient behavior of the helical tip vortices. Temporally-synchronized
and spatially-resolved flow field measurements are highly desirable in order to elucidate the underlying physics to
improve our understanding about the turbulent wake flow characteristics and the transient behavior of the helical tip
vortices in wakes of wind turbines. Advanced flow diagnostic techniques, such as particle image velocimetry (PIV)
to be used in the present study, are capable of providing such information.
Surprisingly, only very few experimental studies can be found in literature to provide whole-field measurements
to quantify the transient behavior of the helical tip vortices in the wakes of wind turbines. Whale et al. (2000)
studied the tip vortices generated by an untwisted two-bladed rotor in a water tank by using a PIV system. Based on
the comparison of the PIV measurements with the numerical simulation results using a rotor vortex lattice method,
they suggested that the fundamental behavior of the helical tip vortices would be almost insensitive to the blade
chord Reynolds number as long as the similarity of the tip-speed-ratio (TSR) of the wind turbine is observed. Grant
and Parkin (2000) used a digital PIV system to measure the flow velocity fields at the downstream of a two-bladed
wind turbine model in a low-speed wind tunnel. The PIV measurement results reveal clear pictures of the turbine
wake flows, including the size and persistence of the velocity deficit and tip vortices in the wake as well as the wake
deflection in yaw, both aligned into the incoming wind direction and at a range of yaw angles, up to approximately 5
rotor diameters downstream. More recently, Massouh & Dobrev (2007) conducted a wind tunnel study to
characterize the wake flow downstream of a small wind turbine model based on the phased-locked PIV and hotwire
measurements. The evolution of the helical tip vortices downstream of the wind turbine was revealed clearly from
the measurement results. While useful information has been uncovered by those previous studies, it should be noted
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that most of those experimental studies were conducted with the wind turbine models installed in air or water flows
with homogenous, uniform incoming flow velocity and relatively low turbulence intensity. However, in reality,
most of the wind turbines operate in atmospheric boundary layer winds with significant variations in both incoming
wind speed and turbulence intensity. The effects of the significant variations in mean and turbulence characteristics
of the atmospheric boundary layer winds on the power productivity, dynamic wind loads and the evolution of the
unsteady tip vortices in the wakes of wind turbines have not been fully explored.
In the present study, an experimental study was conducted to characterize the turbulent flow structures and the
evolution of the helical tip vortices in the near wake of a horizontal axis wind turbine (HAWT) model placed in an
atmospheric boundary layer wind.
The experimental study was performed in a large-scale
Aerodynamic/Atmospheric Boundary Layer (AABL) Wind Tunnel available at Iowa State University. In addition to
measuring dynamic wind loads (both aerodynamic forces and moments) acting on the wind turbine model using a
high-sensitive six-component load cell, a high-resolution digital Particle Image Velocimetry (PIV) system was used
to achieve detailed flow field measurements to quantify the characteristics of the turbulent wake flow and evolution
of the helical tip vortex structures in the wake of the wind turbine model. Besides conducting “free-run” PIV
measurements to determine the ensemble-averaged statistics of the flow quantities such as mean velocity, turbulence
intensity, Reynolds Stress, and turbulence kinetic energy distributions in the wake flow, phased-locked PIV
measurements were also conducted to elucidate details about the time evolution of the helical tip vortices in relation
to the position of the rotating turbine blades. The detailed flow field measurements were correlated with the dynamic
wind load measurements to elucidate the underlying physics in order to gain further insight into the characteristics of
the turbulent wake flows and evolution of the helical tip vortex structures in the wakes of wind turbines for the
optimal design of the wind turbines operating in more realistic environments.
II. Experimental Setup and Wind Turbine Model
2.1 Atmospheric boundary layer wind tunnel
Wind tunnel facilities have been widely used for wind turbine studies due to their capabilities to produce wellcontrolled flow environments. In the present study, a large-scale Aerodynamic/Atmospheric Boundary Layer
(AABL) Wind Tunnel located at the Aerospace Engineering Department of Iowa State University was used to
perform the experimental investigations. The AABL wind tunnel is a closed circuit wind tunnel with a test section
of 20m long, 2.4m wide and 2.3m high, optically transparent side walls and a capacity of generating a maximum
wind speed of 55m/s in the test section.
Fig. 1: A picture of the test section of the AABL wind tunnel
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Fig. 1 shows a picture of the test section of the AABL wind tunnel with a three-blade, horizontal axis wind
turbine (HAWT) model (at a scale ratio of 1:350) mounted in the center of a turntable. Arrays of wood blocks were
mounted at the upstream of the wind turbine model as the roughness elements to generate a turbulent boundary layer
flow to simulate the atmospheric boundary layer wind usually seen in a wind farm. The wood blocks are 0.076m tall
with a square cross section of 0.038 × 0.038m. The blocks were arranged in a staggered pattern with 30 rows along
the flow direction, starting at 12.89m and ending at 1.46m upstream of the tested wind turbine model. The space
between the blocks was 0.38m in both streamwise and spanwise directions. The odd rows of the blocks started
0.076m from the side walls of the tunnel, while the even rows of the blocks started 0.28m from the side walls of the
tunnel.
Fig. 2 shows the measured mean velocity and the turbulence intensity profiles at the center of the measurement
region, i.e., the location where the wind turbine model would be installed, by using a hotwire anemometer probe. It
is well known that the wind speed at 10m elevation height above the ground is widely used to characterize an
atmospheric boundary layer wind. The horizontal axis in Fig. 2(a) represents non-dimensional mean velocity
U/U(z10), where U(z10) is the reference velocity at a height of z10= 28.6mm about the wind tunnel ground floor,
which is equivalent 10m elevation height in nature based on the scale ratio of 1:350. It has been suggested that the
mean velocity profile of an atmospheric boundary layer flow over an open terrain can usually be fitted well by using
a logarithmic function or a power function (ASCE, 2005). The logarithmic and power curves fitting to the
measurement data were also shown in Fig. 2(a) for comparison. It can be seen clearly that the measurement data can
by represented reasonably well by either the logarithmic function or the power function. It should also be noted that,
while the power law exponent for an open terrain atmospheric boundary layer wind found in nature usually ranges
from 0.1 to 0.2 according to ASCE standard (ASCE, 2005), the power law exponent of the curve fitting to the
present measurement data was found to be 0.165, which is well within the range of those of an atmospheric
boundary layer wind over an open terrain. Fig. 2(b) shows the measured the turbulence intensity of the turbulent
boundary layer flow generated inside the wind tunnel as a function of the evaluation height above the wind tunnel
floor. The standard turbulence intensity profile of an atmospheric boundary layer wind over an open terrain as
suggested by Architectural Institute of Japan (AIJ, 1996) was also plotted in the figure for comparison. It can be
seen clearly that the turbulent boundary layer flow generated inside the wind tunnel for the present study can be used
to simulate an atmospheric boundary layer wind found in nature reasonably well.
Measurement dara
25
25
AIJ standard
Power Law fit
20
H/z10
20
H/z10
Measurement data
Logarithmic Law fit
15
15
10
10
5
5
0
0
0
0.5
1.0
U/U(z10)
1.5
0
5
10 15 20 25 30
Turbulence Intensity, Iu %
(a). Mean velocity profile
(b). Turbulence intensity profile
Fig. 2: The measured profiles of the atmospheric boundary layer wind
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2.2 Wind turbine model
The wind turbine model used for the present study represents the most widely used three-blade horizontal axial
wind turbines (HAWT) found in on-shore and/or off-shore wind farms. As shown in Fig. 3, the rotor radius of the
wind turbine model is 127 mm and the height of the turbine nacelle is 225mm above the wind tunnel floor. With the
scale ratio of 1:350, the test model would represent a wind turbine in a wind farm with the rotor diameter about 90m
and tower height about 80m. It should be noted that the blockage ratio of the wind turbine model (i.e., the ratio of
the blade swept area to the tunnel cross section area) was found to be about 1:90. Thus, the block effects of the wind
turbine model would be very small, which is almost negligible, for the present study.
The rotor blades of the wind turbine model used for the present study are MA0530TE (5  3 three-blade)
propeller blades of Windsor Propeller Inc. The blades are twisted with the pitch angle of 14 deg at 75% radius,
which is ranging from 20 deg at root to 10 deg at tip. The blades have a 12mm chord length at tip, 19mm in the
middle, and 16mm at root. The airfoil cross section of blades has a concave pressure surface and is well adapted for
low Reynolds number applications. Since they were originally designed for propeller applications, the blades were
mounted reversely with the pressure side of the blades facing the incoming wind streams during the experiments in
order to improve their aerodynamic performance when used as wind turbine blades. A small electricity generator
was installed inside the nacelle of the wind turbine model, which would produce electricity as driven by the rotating
turbine blades. The primary design parameters of the wind turbine model are listed in Table 1.
Table 1: The primary design parameters of the wind turbine model
Parameter
R
H
d rod
d naccele
Dimension (mm)
127
225
18
28

a
a1
a2
6o
100
15
70
Fig. 3: A schematic of the wind turbine model used in the present study
During the experiments, while the wind turbine model was installed in the simulated atmospheric boundary
layer wind, the wind speed at the hub height was found to be 4.0 m/s (i.e., VO = 4.0 m/s). The corresponding chord
Reynolds number (i.e., based on the averaged chord length of the rotor blades and the wind speed at hub height) was
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found to be about 6,000, which is significant lower than those of the wind turbines installed in a wind farm.
According to Alfredsson et al., (1982), the chord Reynolds number would have significant effects on the
characteristics of the wind turbine performance. For example, the maximum power coefficient would be much lower
for the wind turbine models operating at much low Reynolds numbers. However, as suggested by Medici &
Alfredsson (2006), the fundamental behavior of the helical tip vortices and turbulent wake flow structures at the
downstream of wind turbines would be almost independent to the chord Reynolds number. The wind turbines with
similar tip-speed-ratio (TSR) would produce similar near wake characteristics such as helical shape, rotation and tip
vortices. In the present study, while the incoming atmospheric boundary layer wind was kept in constant during the
experiments, the rotation speed of the wind turbine model was adjusted by applying different electric loads to the
small electricity generator inside the turbine nacelle. With the rotation speed of the wind turbine blades changed
from 0 to 1700rpm, the corresponding tip-speed- ratio of the wind turbine model (i.e.,  = blade tip rotation
speed/wind speed) was found to be changed from 0.0 to about 4.5.
2.3 Experimental setup for dynamic wind load and flow field measurements
In the present study, an aluminum rod was used as the tower to support the nacelle and rotor blades of the wind
turbine model. Through a hole on the wind tunnel ground, the aluminum rod was connected to a high-sensitivity
force-moment sensor (JR3, model 30E12A-I40) in order to measure the dynamic wind loads (both force and
moment) acting on the wind turbine model. The JR3 load cell is composed of foil strain gage bridges, which are
capable of measuring the forces on three orthogonal axes, and the moment (torque) about each axis. The precision of
the force-moment sensor cell for force measurements is ±0.25% of the full range (40N). In the present study, the
thrust coefficient (i.e., aerodynamic force coefficients along X –direction) and bending moment coefficient (i.e., the
moment coefficient along Z-direction) of the wind turbine model were calculated by using the expressions of
CT  2T / U 02R 2 , and C M  2 M z / U 02 R 2 H , where  is the air density, U 0 is the mean flow velocity at the hub
z
height, H. During the experiments, the wind loads data were acquired for 60 seconds at the sample rate of 1,000 Hz
for each tested case.
Fig. 4: Experimental Setup for the dynamic wind load and flow field measurements
In addition to the wind load measurements, a high-resolution digital Particle Image Velocimetry (PIV) system
was used to achieve detailed flow field measurements to quantify the characteristics of turbulent wake flow the
transient behavior of the unsteady tip vortices at the downstream of the wind turbine model. Fig. 4 shows the
schematic of the PIV system used in the present study. For the PIV measurements, the flow was seeded with ~ 1 μm
oil droplets by using a droplet generator. Illumination was provided by a double-pulsed Nd:YAG laser (NewWave
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Gemini 200) adjusted on the second harmonic and emitting two pulses of 200 mJ at the wavelength of 532 nm. The
laser beam was shaped to a sheet by a set of mirrors with spherical and cylindrical lenses. The thickness of the laser
sheet in the measurement region was about 1.5mm. A high resolution 12-bit CCD camera (PCO2000, CookeCorp)
was used for PIV image acquisition with the axis of the camera perpendicular to the laser sheet. The CCD camera
and the double-pulsed Nd:YAG lasers were connected to a workstation (host computer) via a Digital Delay
Generator (Berkeley Nucleonics, Model 565), which controlled the timing of the laser illumination and the image
acquisition. During the experiments, “free-run” PIV measurements were conducted at first in order to determine the
ensemble-averaged wake flow statistics (e.g., mean velocity, turbulence intensity, Reynolds Stress, and turbulence
kinetic energy) at the downstream of the wind turbine model. It should be noted that the data acquisition rate for the
“free-run” PIV measurements was pre-selected at a frequency that is not a harmonic frequency of the rotation
frequency of the rotor blades in order to ensure a meaningful determination of the ensemble-averaged flow
quantities.
Phased-locked PIV measurements were also conducted to elucidate more details about the time evolution of the
helical tip vortices in relation to the position of the rotating rotor blades. In order to achieving the phase-locked PIV
measurements, as shown in Fig. 4, a digital tachometer was used to detect the position of a pre-marked rotor blade
(i.e., named blade #1). The tachometer would generate a pulsed signal as the pre-marked rotor blade passed through
the vertical PIV measurement plane. The pulsed signal was used as the input signal to a Digital Delay Generator
(DDG) to trigger the digital PIV system for the phased-locked PIV measurements. By adding different time delays
between the input signal from the tachometer and the TTL signal output from the DDG to trigger the digital PIV
system, the phased-locked PIV measurements at different rotation phase angles of the pre-marked rotor blade (i.e.,
corresponding to different rotating positions of the pre-marked rotor blade) can be accomplished. At each preselected phase angle, 160 frames of the instantaneous PIV measurements were used to calculate the phase-averaged
flow velocity distribution in the wake of the wind turbine model.
In the present study, instantaneous PIV velocity vectors were obtained by a frame to frame cross-correlation
technique involving successive frames of patterns of particle images in an interrogation window of 3232 pixels. An
effective overlap of 50% of the interrogation windows was employed in PIV image processing. After the
instantaneous velocity vectors ( ui , vi ) were determined, the vorticity (  z ) can be derived. The distributions of the
ensemble-averaged flow quantities such as the mean velocity, turbulence intensity, Reynolds Stress, and turbulence
kinetic energy were obtained from a cinema sequence of about 1000 frames of the instantaneous PIV measurements.
The measurement uncertainty level for the velocity vectors is estimated to be within 2% and 5% for the turbulent
velocity fluctuations, Reynolds stress, and turbulent kinetic energy calculations.
III. Results and Discussion
3.1 Dynamic wind load measurement results
Figure 5 shows the typical measurement results of the wind loads acting on the wind turbine model with the tipspeed-ratio of the wind turbine being 3.2. While Fig. 5(a) and Fig. 5(b) give the measured instantaneous thrust force
and bending moment acting on the wind turbine model, Fig. 5 (c) and Fig. 5(d) show the histograms of the measured
instantaneous thrust force and bending moment. It can be seen clearly, while the instantaneous wind loads acting on
the wind turbine model were found to be highly unsteady, the histograms of both the dynamic thrust force and
bending moment acting on the wind turbine model were found to be fitted reasonably well by using Gaussian
functions. While the standard deviation of dynamic thrust force coefficient was found to be 0.103 with the mean
value at CT = 0.337, and the standard deviation of instantaneous bending moment coefficient was 0.152 with the
mean value of CM = 0.351. Fig. 5(e) and Fig. 5(f) show the Fast Fourier Transform (FFT) power spectrum analysis
of the measured dynamic thrust force and bending moment. A dominant peak at f0 = 17.0 hz can be identified clearly
in the spectrum plots, which corresponds to the rotation speed of the rotor blades of the wind turbine model at the
tip-speed-ratio of  = 3.2. The rotation frequency of f0 = 17.0 hz based on the FFT analysis of the wind load
measurements were found to agree very well with the independently measured rotation speed of the rotor blades by
using the digital tachometer. Other peaks, which correspond to the harmonic frequencies of the rotation frequency of
the rotor blades, f0, can also be clearly identified from the power spectrum plots.
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1.0
1.0
Measurement data
Time-averaged thrust coefficient
0.8
Thrust coefficient, CT
Bending moment coefficient , CMz
Measurement data
0.6
0.4
0.2
0
20
40
Time-averaged bending moment coefficient
0.8
0.6
0.4
0.2
0
60
20
40
Time, (s)
Time, (s)
(a). Time sequence of the measured CT .
3500
(b). Time sequence of the measured CMz.
4000
Gaussian distribution function
Gaussian distribution function
3000
Measurement data
Measurement data
Number of the samples
Number of the samples
60
2500
2000
1500
1000
3000
2000
1000
500
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0
-0.2
0.7
0
0.2
0.4
CT
0.6
0.8
1.0
CMz
(c). Histogram of the measured CT .
(d). Histogram of the measured CMz.
600
1000
fo=17Hz
fo=17Hz
800
400
600
A. U.
A.U.
2fo
2fo
400
200
3fo
3fo
200
0
0
20
40
60
80
100
0
0
20
Frequency (Hz)
(e). Power spectrum of measured CT.
40
60
80
Frequency (Hz)
(f). Power spectrum of measured CMz.
Fig. 5: Measured wind loads acting on the wind turbine model with the tip-speed-ratio, =3.2
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100
Time-averaged bending moment coefficient, CMz
Time-averaged thrust coefficient, CT
0.35
0.30
0.25
0.20
0.15
Curve fit
Experimental data
0.10
0.05
0
0
1
2
3
4
5
0.40
0.35
0.30
0.25
0.20
Curve fit
0.15
Experimental data
0.10
0.05
0
0
1
Tip-Speed-Ratio, 
(a). Time-averaged thrust coefficient
2
3
4
5
Tip-Speed-Ratio, 
(b). Time-averaged moment coefficient
Fig. 6: Time-averaged wind loads acting on the wind turbine model vs. the tip-speed-ratio
It is well known that the tip-speed-ratio (often known as the TSR) of a wind turbine is of vital importance in the
design of the wind turbine generators. In the present study, the effects of tip-speed ratio of the wind turbine on the
aerodynamic force and wake flow structures of the wind turbine were investigated systematically. As described
above, during the experiments, while the incoming atmospheric boundary layer wind was kept in constant, the
rotation speed of the rotor blades of the wind turbine model was adjusted by applying different electric loads to the
small electricity generator mounted inside the turbine nacelle. With the rotation speed of the wind turbine blades
changed from 0 to 1700rpm, the corresponding tip-speed-ratio of the wind turbine model was changed from 0.0 to
about 4.5 (i.e., = 0 ~ 0. 45). It should be noted that, while the variations of the power coefficients of a wind turbine
model as a function of the tip-speed-ratio have been reported in several previous studies (Boeing, 1982), very little
can be found in the literature about the variations of the wind loads (i.e., thrust and bending moment) acting on the
wind turbine as a function of the tip-speed-ratio of the wind turbine even though the wind load data are very
important and critical for the mechanic design of wind turbines for better wind energy harvesting performance and
long fatigue lifetime of the wind turbines operating in turbulent atmospheric boundary layer winds. Fig. 6 shows
the variations of the measured mean (i.e., time-averaged) thrust and bending moment coefficients of the wind
turbine model as a function of the tip-speed-ratio, .. It can be seen clearly that the profiles of mean thrust and
bending moment coefficients were found to have a very similar trend as the tip-speed-ratio of the wind turbine
model increases. The mean thrust and bending moment coefficients would increase gradually with the increasing
tip-speed-ratio of the wind turbine model when the tip-speed-ratio is still relatively small (i.e.,  < 3.0). The mean
thrust and bending moment coefficients were found to reach their peak values at the tip-speed-ratio of   3.2. Then,
the mean thrust and bending moment coefficients of the wind turbine would decrease with the increasing of the tipspeed-ratio of the wind turbine when the tip-speed-ratio of the wind turbine model becomes relatively large (i.e.,  >
3.5). The similar trend was also reported in the experimental study of Boeing (1982) to investigate of the power
coefficient of the wind turbine models as a function of the tip-speed-ratio of the wind turbines.
Fig. 7 shows the schematic of the flow velocity vectors relative to the cross-section of the turbine blade at
different tip-speed-ratio. As suggested by Spera (1994), the left-hand side of the curve in Fig. 6(a) (i.e., with the tipspeed-ratio being relatively small) is controlled by blade stall. Local angles of attack (angles between the relative
velocity and the blade chord line) are relative large. As shown in Fig.7 (a), when the rotation speed of the turbine
blade is relatively low (i.e., the tip-speed-ratio being relatively small), the airflow would be stalled due to the large
angle of attack and a large separation region behind the blade is expected. As the rotor blade starts rotating faster,
the rotation speed contributes significantly in the relative velocity respect to the blade. In an optimal operating
condition, a desired angle of attack is achieved that would enable the large relative velocity to generate tremendous
aerodynamic lift as shown in Fig. 7 (b). A significant part of the lift is projected into the thrust, which is even larger
than the drag generated by the blade stall. The other part of the lift would provide rotation-wise driven force on the
blade. With the increasing tip-speed-ratio, the angle of attack of the relative flow with respect to the blade would
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decrease dramatically. As a result, the aerodynamic lift as well as the thrust acting on the blade would decrease to a
small value as shown in Fig. 7(c) that explains the dropping trend at the right-hand side of the curve in Fig. 6(a).
Fig. 7: Schematic of the flow velocity vectors relative to the cross-section of the turbine blade
3.2 Free run PIV measurement results
As described above, the flow field in the vertical central plane of the wind turbine with the yaw angle fixed at
zero degree was measured using a high-resolution PIV system. The PIV measurement results of the present study
are presented in mainly two different ways: (i) “free-run” flow field measurement results, and (ii) phase-locked flow
filed measurement results. In the “free-run” PIV measurements, the data acquisition rate was pre-selected at a
frequency that is not a harmonic frequency of the rotation frequency of the rotor blades in order to ensure a
meaningful determination of the ensemble-averaged flow quantities.
Fig. 8 shows the “free-run” PIV measurement results at the tip-speed-ratio of the wind turbine of   3.0. As
clearly revealed in the instantaneous PIV measurement result, the contour plots describe the expected pattern from a
cross-section of a helical tip vortex system. The instantaneous PIV contour plot also reveals separate regions of
slightly concentrated vorticity in the wake, located inboard of the tip at approximately 70% span, moving under the
influence of wake expansion, and finally merging with the tip vortex system at approximately 2.0R downstream. A
similar flow feature was also observed by Whale et al. (2000) with separated regions located inboard of the tip at
approximately mid-span merging with the tip vortex system at 2.0R. Note that the fluid separation zone at the
downstream of the nacelle has much greater diameter than it can be expected from the nacelle body only. Because a
series of root vortex structures due to the rotation are present on the external boundary of the separation zone which
was also observed by Massouh and Dobrev (2007). As shown clearly in the ensemble-averaged velocity distribution
given in Fig. 8 (b), obvious velocity deficits were observed in the wake. The loss of the kinetic energy of the flow
was transferred into electric power by the wind turbine. The lowest velocity region has been observed right behind
the nacelle, and it starts recovering rapidly by absorbing the energy from the surrounding flow. This behavior
induces the expansion of the wake as revealed by the joint contour boundaries in Fig. 8(b).
Fig. 8(c) and Fig. 8(d) show the measured turbulent intensity in streamwise (U-component) and vertical
direction (V-component) respectively. A slight increment of the turbulent intensity in U-component was observed in
the flow passing the blade tip, but it showed an increasing trend with the distance downstream of the wind turbine.
In contrast, a distinct increment of the turbulent intensity in V-component was observed near the tip, but decreasing
with the distance. The difference is attributable to the fact that the existence of the blade tip has more effects on the
V-component of the flow. Moreover, the high background turbulent intensity (about 17%) in streamwise made the
increment invisible to some extent. The nacelle and cylinder-shaped tower also induced intense turbulent intensity
mainly due to the vortex shedding. Especially in the region under the nacelle, the high turbulence could be
attributable to the interference from the tower on the wakes of turbine blades.
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American Institute of Aeronautics and Astronautics
Spanwise
Vorticity (1/s)
-50.0 -40.0 -30.0 -20.0 -10.0 0.0
Wind Speed
(m/s)
4.0 m/s
10.0 20.0 30.0 40.0 50.0
150
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
150
4.5
0
4.10
100
Shadow
50
3.70
Region
Y (mm)
Y (mm)
100
1.
303.
1.70
Shadow
30
3.30
50
0
2.902.50
0.9
0.500
10
2.
3.9 m/s
0
0
1.7
1.7
0
1.3
-50
0
50
100
150
200
250
-50
0
50
X (mm)
Turblence intensity
( U - component)
Turblence intensity
( V - component)
0.05 0.07 0.09 0.11 0.13 0.15 0.17 0.19 0.21
200
250
0.05 0.07 0.09 0.11 0.13 0.15 0.17 0.19 0.21
150
100
Shadow
Region
Y (mm)
Y (mm)
150
(b). Ensemble-averaged PIV results
150
50
0
Shadow
Region
50
0
-50
-50
-50
0
50
100
150
200
250
-50
0
50
X (mm)
100
150
200
250
X (mm)
(c). Turbulent intensity in U-component
(d). Turbulent intensity in V-component
Reynolds
Stress -0.005 -0.004 -0.003 -0.002 -0.001 0.000 0.001 0.002 0.003 0.004 0.005
T.K.E.
0.005 0.006 0.007 0.008 0.009 0.010 0.011 0.012 0.013 0.014 0.015
150
150
100
Shadow
Region
Y (mm)
Y (mm)
100
X (mm)
(a). Instantaneous PIV results
100
2.10
-50
-50
100
0
50
Shadow
Region
50
3.9 m/s
0
0
-50
-50
-50
0
50
100
150
200
250
-50
0
50
X (mm)
100
150
X (mm)
(e). Reynolds shear stress distribution
(f). Turbulent kinetic energy distribution
Fig. 8: PIV measurement results at the tip-speed ratio of  =3.0
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American Institute of Aeronautics and Astronautics
200
250
Fig. 8 (e) and (f) show the normalized Reynolds shear stress and turbulent kinetic energy distributions. The high
Reynolds shear stress regions were found to be along with the tip vortex system, the root vortex shedding path and
the separation region around the turbine nacelle. The Reynolds stress plays an important role in the vertical transport
of kinetic energy in the wake. As stated by Cal et al. (2010), the Reynolds stress enables kinetic energy to be
entrained from the aloft into the boundary layer towards the wind turbine. Another separation region at
approximately 70% span also induced a slightly high Reynolds stress and merged with the tip vortex system. It also
revealed clearly that the wake flow at the downstream of the turbine nacelle would be highly turbulent (i.e., with
very high turbulent kinetic energy), corresponding to the unsteady root vortex shedding and flow separations.
Relatively high turbine kinetic energy regions were also found to be along the tip vortex system. The findings
derived from the present study are found to agree with the observations of Chamorro and Porte-Agel (2009).
In the present study, the effects of the tip-speed-ratio of the wind turbine on the turbulent wake flow
characteristics were also investigated. Fig. 9 shows the ensemble-averaged PIV measurement results at four typical
tip-speed-ratios.
Wind Speed
(m/s)
Wind Speed
(m/s)
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
0
4.5
150
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
150
4.10
4.10
1.
33
3.70
1.70
0 .3
Shadow
100
10
2.
Y (mm)
Y (mm)
3.9 m/s
3.3
2.90
2.50
0
1.7
3.9 m/s
0
2.10
0.9
0
0
2.10
0.90
-50
-50
0
50
100
150
200
250
-50
0
50
X (mm)
4.5
150
30
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
0
100
Shadow
3.70
250
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
Y (mm)
3.30
50
2.90
2.50
0
3.70
3.30
2.50
0
0.9
3.9 m/s
1.30
1.7
0
2.10
1.30
Region
3.30 2.90
50
4.1
Shadow
0.50
Region
3.9 m/s
200
150
2.10
1.70
Y (mm)
100
150
(b). =3.5
Wind Speed
(m/s)
0
4.1 3.70 0
2.9 0
2.5
50
09.0
0.
3
100
X (mm)
(a). =3.0
Wind Speed
(m/s)
1.70
1.7
1.30
2.902.50
0.9
0.500
0
1.3
-50
0
50
0.50
0
0.90
1.70
10
2.
3.30
50
3.70
Shadow
3.30
2.
50
Region
2.90
0
Region
0.50
100
0
1.30
0.90
0
0
0 .9
0.5 0
2.1
0
1.70
0.50
2.10
2.50
-50
-50
-50
0
50
100
150
200
250
-50
0
50
100
150
200
250
X (mm)
X (mm)
(c). =4.0
(d). =4.5
Fig. 9: Ensemble-averaged flow field at different tip-speed-ratios
Fig. 10 shows the transverse profiles of the ensemble-averaged streamwise velocity and the normalized
turbulence kinetic energy in the wake of the wind turbine at the location of X/R=1.0 as a function of the wind
turbine tip-speed-ratio. The mean velocity profile of the incoming atmospheric boundary layer wind was also given
in the plot for comparison. It can be seen clearly that, compared with the velocity profile of the incoming
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American Institute of Aeronautics and Astronautics
atmospheric boundary layer wind, significant velocity deficits were found to be generated in the wake flow due to
the installation of the wind turbine in the atmospheric boundary layer wind. The size of the regions with significant
velocity deficits was found to be much greater than that can be expected from the turbine nacelle only. It indicates
that the incoming flow streams would be decelerated greatly as they pass through the rotating disk of the turbine
blades. According to the momentum and energy conservation laws, while the aerodynamic drag force acting on the
wind turbine are proportional to the square of the velocity deficits, the power output of the wind turbine (i.e., the
wind energy harvested by the wind turbine) would be proportional to the cube of the velocity deficits. A larger
velocity deficit in the transverse velocity profiles would indicate stronger aerodynamic loads acting on the wind
turbine model as well as more wind energy harvested by the wind turbine model. As revealed from the transverse
mean velocity profiles shown in Fig. 10, the largest velocity deficit was found at the tip-speed-ratio   3.0~3.5 for
the present study. It would suggest that the wind turbine model used in the present study would experience the
maximum wind load as well as have the best wind energy harvesting capability when operated at the tip-speed-ratio
of   3.0 ~ 3.5. The finding was confirmed from the independent wind load measurement results given in Fig. 6.
The normalized turbulence kinetic energy profiles shown in Fig. 10(b) revealed clearly that the wake flow at the
downstream of the turbine nacelle was highly turbulent (i.e., with very high turbulent kinetic energy levels),
corresponding to the flow separation and unsteady wake vortex shedding from the turbine nacelle as revealed from
the PIV measurement results described above. A region with quite high turbine kinetic energy levels can also be
found along the shedding path of the helical tip vortices in the wake of the wind turbine model. The high turbulence
level in the wake flow would indicate a highly unstable wind loads acting on the wind turbine, which would affect
the mechanical strength and fatigue lifetime of the wind turbine significantly. The findings derived from the present
study are found to agree well with the observations of Chamorro and Porte’-Agel (2009) based on cross-wire
anemometer measurements.
X/D=0.5
X/D=0.5
1.6
1.6
1.5
1.5
Tip height
1.3
Y/D
1.2
1.1
=4.5
=4.0
=3.5
=3.0
1.3
1.2
1.0
1.1
1.0
Hub height
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.4
Tip height
1.4
Probe data(Oncoming flow)
Curve fit
=4.5
=4.0
=3.5
=3.0
Y/D
1.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
0.6
0.002
Hub height
0.003
0.004
U/U0
(a). time-averaged velocity profiles
0.005
0.006
0.007
0.008
0.009
0.010
0.011
0.012
Turbulent Kinetic Energy
(b). Normalized turbulence kinetic energy profiles
Fig. 10: Time-averaged measurement results in the wake of the wind turbine model at X/R=1.0.
3.3 Phase-locked PIV measurement results
In order to provide more information about the time evolution of the helical tip vortex in the wake of the wind
turbine model, the phase-locked PIV measurements were conducted at eight different phase angles for the present
study. The technique effectively produced a “frozen wake” image, from which a cross-section of the vortex structure
was obtained. As mentioned before, the angle between the measurement plane and the position of a pre-marked rotor
blade (i.e., named blade #1), is defined as the phase angle. The phase-locked averaged results at the phase angle
ranging from 0~120deg for  =3.0 are shown in Fig. 11. The “wave-shape” of the streamwise velocity contour can
be observed, which indicates vortical flow characteristics emerging in the tip vortex region. Acceleration with red
color contour can be observed downstream at some spots above the tip height due to the tip vortices, which was also
observed by Massouh & Dobrev (2007). This acceleration was also revealed clearly from the induced velocity
vector field after subtracting the oncoming flow as shown in Fig. 12. The “acceleration region” right behind the
wind turbine is relatively large because of the high vortex strength there. The whole “wave-shape” distribution tends
to move downstream with the increasing phase angle. One needs to keep in mind that all maps shown here are only
cross-sections of the “wave-pipe-like” flow structure.
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American Institute of Aeronautics and Astronautics
Wind Speed
(m/s)
150
150
100
100
100
50
Y (mm)
150
50
Shadow
region
Shadow
region
0
-50
0
-50
-50
0
50
100
150
200
250
-50
-50
0
50
X (mm)
150
200
250
-50
Wind Speed
( m/s)
100
100
Y (mm)
100
Y (mm)
150
0
50
0
Shadow
region
150
200
250
Shadow
region
-50
-50
0
50
X (mm)
Wind Speed
( m/s)
100
150
200
250
-50
0
50
X (mm)
(d). Phase angle,  = 45 deg.
Wind Speed
( m/s)
Wind Speed
(m/s)
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
150
100
100
100
Y (mm)
150
Y (mm)
150
200
250
(f). Phase angle,  = 75 deg.
150
50
100
X (mm)
(e). Phase angle, = 60 deg.
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
250
0
-50
100
200
50
Shadow
region
-50
150
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
150
50
100
Wind Speed
(m/s)
150
50
50
(c). Phase angle,  = 30.0 deg.
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
0
0
X (mm)
(b). Phase angle, = 15 deg.
Wind Speed
(m/s)
Y (mm)
100
X (mm)
(a). Phase angle,  = 0.0 deg.
-50
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
50
Shadow
region
0
Y (mm)
Wind Speed
( m/s)
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
Y (mm)
Y (mm)
Wind Speed
(m/s)
50
0.50 0.90 1.30 1.70 2.10 2.50 2.90 3.30 3.70 4.10 4.50
50
Shadow
region
0
0
Shadow
region
0
Shadow
-50
-50
-50
0
50
100
150
200
250
X (mm)
(g). Phase angle,  = 90 deg.
-50
-50
0
50
100
150
200
X (mm)
(h). Phase angle, = 105 deg.
250
-50
0
50
100
150
200
250
X (mm)
(i). Phase angle,  = 120 deg.
Fig. 11: Phase-locked PIV measurement results at the tip-speed-ratio of  =3.0.
Figure 12 shows the typical phase-locked PIV measurements at different phase angles of a pre-marked turbine
blade in a rotation cycle (i.e., corresponding to different positions of the pre-marked turbine blade in relation to the
vertical PIV measurement plane) as the wind turbine model operated at a tip-speed-ratio of   3.0. As shown in the
figure, at the phase angle of  = 0 deg, the pre-marked turbine blade would be in the most upward position (i.e.,
within the vertical PIV measurement plane). It can be seen clearly that a tip vortex would be induced at the tip of the
pre-marked turbine blade at  = 0 deg. As the phase angle increases, while the pre-marked turbine blade would
rotate out of the vertical PIV measurement plane, the tip vortex was found to shed from the turbine blade and move
downstream, as indicated by the red dashed line shown in the figure. It was also revealed clearly that the tip vortex
induced by the pre-marked blade (also named the 1st blade) would align itself nicely with the other tip vortices
induced by the 2nd and 3rd turbine blade to form a moving tip vortex array in the vertical PIV measurement plane.
The relative velocity vectors (i.e., after subtracting the incoming free stream velocity at the tip of the turbine blade
from the measured flow velocity fields) at phase angle  = 0 deg and  = 60 deg were also shown in the figure in
order to visualize the formation and evolution of the tip vortex array more clearly. It should also be noted that, in
addition to the tip vortex array, the flow separation and unsteady vortex structures shedding from the turbine nacelle
were also visualized clearly form the PIV measurement results.It also can be observed that the separate region,
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American Institute of Aeronautics and Astronautics
although not as significant as the tip vortex, located inboard of the tip at approximately mid-span, moving along
with the wake expansion, and merging with the tip vortex system at approximately 2.0R downstream
The three-dimensional wake flow structures downstream the wind turbine model can be reconstructed based on
the phase-locked PIV measurement results. Fig. 13 shows the reconstructed 3-D wake flow field with the Cartesian
coordinate system fixed to the 1st rotor blade. The track lines of the tip vortex cores, which were generated by
tracking the centers of the regions of concentrated vorticity induced by the three turbine blades at different rotation
phase angles, were also added in the figure in order to clearly elucidate the helical motion of the tip vortices in the
wake of the wind turbine. It can be clearly observed that the tip vortices originated from the tips of the three rotor
blades would form three independent helical vortex tubes as they moved downstream. As mentioned above, the
helical motion of the tip vortices has a reversed rotational direction with respect to the rotation of the turbine blades.
The gap between the helical vortex tubes was found to be a function of the wind turbine tip-speed-ratio. While the
helical vortex structures in the wakes of wind turbines were visualized qualitatively with smoke in the previous
studies (Anderson, 1982; Vermeer, 2001; and Hand et al., 2001), the PIV measurement results given in the present
study are believed to be the first attempt to elucidate the formation and evolution of the helical tip vortex structures
quantitatively.
Fig. 12: Evolution of the tip vortex structures at the tip-speed-ratio of  = 3.0
Fig. 13: Reconstructed 3D wake flow structures in wake of the wind turbine model
15
American Institute of Aeronautics and Astronautics
1.0
Power function fitting
0.8
Measurement data
z(x)/0
0.6
0.4
0.2
0.01
0.1
1
X/R
Fig. 14: The peak vorticity decay of the tip vortex as a function of the downstream distance at the  = 3.0
Figure 14 shows the decay profile of the peak vorticity of the helical tip vortices as a function of the
downstream distance in the near wake of the wind turbine at the tip-speed-ratio of  = 3.0. The measurement data
were obtained by tracking the maximum vorticity of the tip vortex at different phase angles. As shown in the plot, a
power law function was used to fit the measurements data, which indicates that the strength of the tip vortex would
decay as the downstream distance increases following a power law.
Figure 15 shows the tip vortex structures in the wake of the wind turbine at different tip-speed-ratios. It can be
observed that both the vorticity of the tip vortices and the gap between vortices would decrease with the increasing
tip-speed ratios. Such trend is believed to be connected to the vortex formation process, i.e. the pressure difference
between the pressure side and suction side induces the tip vortex. As the tip-speed ratio increases, the angle of attack
with respect to the airfoil cross section would decrease as illustrated in Fig. 7. The smaller pressure difference
between the pressure side and suction side of the rotor blades would result in a weaker tip vortex. However, the
vorticity of the root vortices increased drastically that accounts for the severe separation near the root of the turbine
blade. For λ=4.5, the series of root vortices were mostly combining together and merging with separate region of
the nacelle, and turned out to be a long band region of concentrated vorticity. The separate regions at approximately
70% span become more distinct at high tip-speed ratio, but still tends to merge with the tip vortex system at a shorter
distance downstream. For example, the separate region at 70% span of the blade for λ=4.5 merged to the tip vortex
system at approximately 1.2R downstream of the wind turbine.
Fig. 16 shows the schematic of the trajectory of three helical tip vortices tubes as mentioned above and the
scattering distributions of the tip vortex cores in the vertical plane based on one hundred frames of the PIV results
for the same phase angle  = 0 deg. The unsteady feature of the locations of the vortex cores, mainly induced by the
unsteady boundary layer flow were revealed in the scattering traces of the vortex centers. Three trajectories of
helical curves emerged at wind turbine tips crossed the centers of the regions of concentrated vorticity. It was found
that the vortex centers approximately distributed within a circular with a diameter ranging from 9.3mm~37.2mm
for = 3.0, and ranging from 7mm~30mm for  = 4.0. The centers of these circles align on a straight line for the
case of  = 3.0, but show a meandering behavior for the case of  = 4.0 , which has been discussed by Bingol et al.
(2007) and Larsen et al. (2007). It seems the vortex center distributions are more stable for the high tip-speed-ratio
in terms of smaller diameter of the scattering circles.
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American Institute of Aeronautics and Astronautics
Spanwise
Vorticity 1/s
= 3.0
Spanwise
Vorticity 1/s
-0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05
150
Phase angle=0deg
150
100
100
Y (mm)
Y (mm)
= 3.5
-0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05
Phase angle=0deg
50
0
50
0
Shadow
Shadow
-50
-50
-50
0
50
100
150
200
250
-50
0
50
100
X (mm)
(a). =3.0
Spanwise
Vorticity 1/s
200
250
(b). =3.5
Spanwise
Vorticity 1/s
= 4.0
-0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05
Phase angle=0deg
150
= 4.5
-0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05
Phase angle=0deg
150
100
Y (mm)
100
Y (mm)
150
X (mm)
50
0
50
0
Shadow
Shadow
-50
-50
-50
0
50
100
150
200
250
-50
0
50
100
X (mm)
150
200
X (mm)
(c). =4.0
(d). =4.5
Fig. 15: The evolution of the wake vortex structures at difference tip-speed-ratios
=3.0
R1=9.3mm
R3=27.9mm
=4.0
R1'=37.2mm
R1=7mm
150
100
100
50
50
Y (mm)
Y (mm)
150
R2=18.6mm
0
R2=20mm
0
Track line
of tip vortex center
Track line
of tip vortex center
-50
-50
-100
-100
-50
0
50
100
150
200
250
300
R3=22mm R1'=24mm R2'=32mm
-50
0
50
100
X (mm)
(a). tip-speed-ratios  = 3.0
150
200
X (mm)
(b). tip-speed-ratio  =4.0
Fig. 16: The wandering of the wake vortex structures at different tip-speed-ratios
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American Institute of Aeronautics and Astronautics
250
300
250
IV. Conclusion
An experimental study was carried out to characterize the dynamic wind loads and evolution of the wake vortex and
turbulent flow structures in the downstream of a horizontal axis wind turbine (HAWT), placed in an atmospheric
boundary layer wind tunnel. In addition to measuring dynamic wind load acting on the wind turbine model, a highresolution Particle Image Velocimetry (PIV) system was used to make both “free-run” and phase-locked flow field
measurements to quantify the transient behavior of the helical tip vortex and turbulence flow structures in the near
wake of the wind turbine model. The characteristics of the turbulent wake flow including the evolution of the helical
tip vortices, velocity deficits, and turbulent properties of the wake flow were found to vary significantly as a
function of the tip-speed-ratio of the wind turbine. The dynamic wind loads acting on the wind turbine were
analyzed in correlation with the detailed flow field measurements. The findings derived from the present study can
be used to improve our understanding of the underlying physics for an accurate estimation of the dynamic
aerodynamic loads required for the optimal mechanical design of wind turbines.
References
Architecture Institute of Japan, “AIJ Recommendations for loads on buildings”, 1996.
American Society of Civil Engineering, “ASCE 7-05 Minimum Design Loads for Building and Other Structures”,
ASCE, 2005.
Alfredsson, P. H., Dahlberg, J. A., “A preliminary wind tunnel study of windmill wake dispersion in various flow
conditions”, Technical Note AU-1499, Part 7, FFA, Stockholm, Sweden, September 1979.
Anderson, M. B., Milborrow, D.J., Ross, N. J., “Performance and wake measurements on a 3 m diameter horizontal
axis wind turbine: comparison of theory, wind tunnel and field test data”, Technical report, University of
Cambridge, Department of Physics, Cavendish Lab., Cambridge, U.K., April 1982.
Bingol, F., Larsen, G. C., and Mann, J. (2005) Wake meandering – An analysis of instantaneous 2d laser
measurements. Journal of Physics: Conference Series, vol. 75, 2007, 012059.
Boeing, Mod-2 wind turbine system development final report, vol. II detailed Report, nASACR-168007,
DOE/NASA/0002-82/2, Cleveland, Ohio: NASA Lewis Research Center, 1982.
Chamorro, L. P., Porte-Agel, F., A wind-tunnel investigation of wind-turbine wakes: boundary layer turbulence
effects. Boundary-Layer Meteorol, Vol. 132, 2009, pp. 129-149.
Ebert, P. R., Wood, D. H., The near wake of a model horizontal-axis wind turbine: Part 1: experimental
arrangements and initial results. Renewable Energy, Vol.12, 1997, pp.225–43.
Cal, R., Lebron, J., Castillo, L., Kang, H., and Meneveau, C., “Experimental study of the horizontally averaged flow
structure in a model wind-turbine array boundary layer”, Journal of Renewable and Sustainable Energy, Vol. 2,
2010, 013106-1-25.
Grant, I., Parkin, P. A., “DPIV study of the trailing vortex elements from the blades of a horizontal axis wind turbine
in yaw”, Exp Fluids, Vol. 28, 2000, pp. 368-376.
Larsen, G. C., Madsen, H. A., Thomsen, K., and Larsen, T. J., “Wake meandering: a pragmatic approach”, Wind
Energy, Vol. 11, 2008, pp.377-395.
Massouh, H., and Dobrev, I., “ Exploration of the vortex behind of wind turbine rotor”, Journal of Physics:
Conference Series, Vol. 75, 2007, 012036.
Medici, D. and Alfredsson, P. H., “ Measurements on a wind turbine wake: 3D Effects and bluff body vortex
Shedding”, Wing Energy, Vol. 9, 2006, pp.219-236.
Schreck, S., Lundquist, J. and Shaw, W., “U. S. Department of Energy Workshop Report: Research needs for wind
resource characterization”, National Renewable Energy Laboratory Technical Report, NREL/TP-500-43521,
2008.
Spera, A. D., “Wind Turbine Tchnology”, ASME Press, New York, 1994, pp.219-220.
Tsustui, Y., Matsumya, H., “LDV measurements of flow field around a wind turbine”, Wind Power, 1987, pp. 381–
386.
Vermeer, L., J., “A review of wind turbine wake research at TUDelft”, A Collection of the 2001 ASME Wind
Energy Symposium Technical Papers, New York: ASME, 2001, pp.103–13.
Vermeer, L., J., Sorensen, J., N., and Crespo, A., “Wind turbine wake aerodynamics”, Progress in Aerospace
Science, Vol. 39, 2003, pp.467-510.
Whale, J., Anderson, C. G., Bareiss, R., Wagner, S., “An experimental and numerical study of the vortex structure in
the wake of a wind turbine”, Journal Wind Engineering and Industrial Aerodynamics, Vol. 84, 2000, pp. 1-21.
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