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Unformatted text preview: J. Whale Post—doctoral Research Assocrate.
Department of Aeronautical and Astronautical Engineering Universrty of Illinois at UrbanaChampaign.
306 Talbot Laboratory. 104 South Wright Street. Urbana. IL 618012935 C. J. Fisichella Graduate Student. Department of Mechanical and Industrial Engineering, Unrversrty of Illinois at Urbana—Champaign,
306 Talbot Laboratory. 104 South Wright Street. Urbana, IL 618012935 M. S. Selig Associate Professor. Department at Aeronautical and Astronautical Engineering. Universtty ot lllinois at UrbanaChampaign,
306 Talbot Laboratory, 104 South Wright Street. Urbana, IL 61801—2935 e—mail: [email protected] Introduction A key parameter in aerodynamic models of horizontalaxis
wind turbines tHAWTs) is the angle of attack a deﬁned as the
angle between the chord of the blade airfoil proﬁle and the effec
tive local velocitywthe resultant of the components of axial in
duced and rotational velocities. where the induced velocity is that
produced by the shed wake from the rotor. Measurements of force
coefﬁcients made on rotating wind turbine blades. however. are
typically correlated with measurements of a local inﬂow angle B
obtained by ﬂow angle sensors protruding from the leading edge
of the blade (see Fig. 1). It is desirable to reduce the 3D ﬁeld measurements in terms of
the angle of attack a in order to provide accurate measured blade
element data for comparison with 2D bladeelement momentum
(BEM) and dynamic stall models and other experimental results.
The angle of attack is related to the inﬂow angle by: a=B—a., (1) where a“ is the angle due to the upwash induced at the local
inﬂow point by the bound vorticity on the blade. Calculating a” is
a relatively straightforward procedure in a wind tunnel where a
2D airfoil can be positioned at a particular angle a and a probe
used to measure the local inﬂow angle ,8 at a point. There are
signiﬁcant differences. however. between 2D airfoil ﬂow and 3D
ﬂow on a rotating blade. This is most noticeable at inboard sec—
tions of the blade where the section is experiencing stall. The
Coriolis component of the 3D ﬂow suppresses separation: delay—
ing stall and enhancing lift at the blade section. These effects are
referred to as ‘stalldelay' or 'poststall’ effects [1.2]. Various methods have been proposed for calculating the rela—
tionship between a and B (and hence the 3D upwashl on a rotat—
ing blade. Madsen [3] describes a method that uses BEM to cal Contributed by the Solar Energy Division 01 The American Society 01 Mechani
cal Engineers for publication in the ASME JOL'RNAL 0F SOLAR ENERGY ENGI
N‘EERING. Manuscript received by the ASME Solar Energy Division. April 1999'.
tinal rcvrsron. September 1000. Associate Technical Editor: D. Berg. 196 / Vol. 122, NOVEMBER 2000 Copyright © 2000 by ASME Correcting Inflow Measurements From Wind Turbines Using a
LiltingSuriace Code In order to provide accurate blade element data for wind turbine design codes, measured
threedimensional ( 3D) ﬁeld data must be corrected in terms of the (sectional) angle of
attack. A 3D LiﬁingSmj‘ace Inﬂow Correction Method ( LSIM l has been developed with
the aid ofa vortexpanel code in order to calculate the relationship between measured
local ﬂow angle and angle of attack. The results show the advantages of using the 3D
LSIM correction over 2D correction methods. particularly at the inboard sections of the
blade where the local ﬂow is affected by post—stall effects and the inﬂuence of the blade
root. [SO 1 99623 1 (00l00604—3] culate a HAWT power curve as a function of angle of attack at a
particular spanwise position. The measured inﬂow angles are ad
justed until good agreement is provided between the calculated
and measured power curves. The inverse BEM method [4.5] as
sumes the measured normal and tangential forces are uniform
over an annulus containing the blade section. The wakeinduced
velocities are calculated according to momentum theory. yielding
the effective velocity vector and subsequently the angle of attack.
Brand et al. [6] estimate the angle of attack using a stagnation
point method. The intersection of the chord line and a line normal
to the blade surface at the stagnation point yields a stagnation
angle. which is used as an estimate for the angle of attack. In order to ascertain the B—a relationship for their Combined
Experiment Rotor (CERl. researchers at the National Renewable
Energy Laboratory (NREL) have conducted a series of 2D wind
tunnel experiments [7]. A 2D scale model of the blade section was
ﬁtted with a ﬂow sensor upstream of the section and placed in a
wind tunnel. The 2D upwash obtained from these tests was used
as an estimate for the 3D upwash. The current research aims to improve on these 2D methods by
calculating the ﬂow ﬁeld around a HAWT rotor using a 3D
vortexpanel method. A lifting—surface code is used to model the
vorticity in the wake and along the rotor blades. The 3D upwash Fig. 1
section Angle of attack a and local flow angle B for a blade Transactions of the ASME induced by the ﬂow ﬁeld vorticity is calculated. yielding the ,B—a
relationship at desired spanwise stations as a set of inﬂow correc—
tion curves. This paper shows the initial results of using the code
to correct 3D data from Phase III of the CER tests conducted at
NREL. The Inﬂow Correction Method An inﬂow correction method has been developed at the Univer
sity of Illinois at UrbanaChampaign in order to provide accurate
3D corrections to HAWT aerodynamic data. The method makes
use of a liftingsurface code and is referred to as the Lifting‘
Surface Inﬂow Correction Method (LSIM). The LiftingSurface Code. The liftingsurface code used in
the method is titled ‘LiftingSurface Aerodynamics and Perfor
mance Analysis of Rotors in Axial Flight’ (LSAF). developed by
Kocurek [8]. The code was written for the design and analysis of
helicopter rotors and extended to wind turbines. The code simu
lates the rotor and the wake as a lattice of vortex panels. A pre
scribed wake model is used which allows for roll—up of tip and
root vonices. and these features were used in the current model.
The detailed blade aerodynamics are computed by combining the
lifting—surface model with a bladeelement analysis that requires
as input a table of airfoil performance characteristics. Field veloc
ity routines in the code allow the computation of local ﬂow angles
at speciﬁed points in the ﬂow. Development of the Method. LSIM evolved from the con
sideration of the differences in 2D and 3D upwash due to post—
stall effects. For inboard stations at poststall angles of attack. the
circulation around a 3D blade section is expected to be greater
than that around a 2D section. As Fig. 2 illustrates. the 3D post
stall upwash is thus expected to be greater than the 2D upwash.
Thus, as Fig. 3 shows. for a particular angle of attack past stall the
3D inﬂow angle ,8 is higher than the 2D case (which is higher
than the straight dotted line shown to represent the line of reﬂec
tion B=a). Consequently. for a particular inﬂow angle B past
that of 2D stall. the 3D angle of attack a is lower than the angle
predicted from the 2D correction curve. The application of the 3D
correction to measured 3D lift data in Fig. 3 results in a curve that
has higher lift at a given 01 than the curve that has been corrected
with 2D data. This higher lift in turn would suggest (through a
vortex lattice method and circulation considerations) greater val
ues of inﬂow angle ,8 for that particular a than speciﬁed in the 2D
Ba correction curve of Fig. 3. It is this interplay between the
,B—a relationship and the corrected data curves that leads to the
concept of an iterative inﬂow correction method. The strategy behind LSIM is to use an initial estimate of the 3D
3—01 relationship for each spanwise station of interest and apply
the inﬂow corrections to convert the measured raw data into air
foil performance data according to the equations:1 c,=c,l cos a+c,sina (2) cdp=c,, sin a—c,cosa (3) [it must be noted that the convection used in Eqs. (2) and (3] is consrstent With a
tangential force that rs deﬁned as positive towards the leading edge of the blade. 320 330 > L320
1 MO ‘1‘ f KC) \
I I
(1 F2D a F30 > Pop
2D : 6120 3D : Ciao > 0120 Fig. 2 Difference between 2D and 3D flow physics at a blade
section Journal of Solar Energy Engineering 3D corrected 2D corrected 2D stall Fig. 3 Expected trends for a 3D inflow correction where c, and c,l are taken from measured pressure data on the
blade. and hence the drag coefﬁcient is referred to as the pressure
drag coefﬁcient. The airfoil performance data are then input into the vortex
panel code. and values of a and ﬂ are extracted at each station of
interest to form new Ba relationships. The new corrections are
used to correct the raw data again and the resulting performance
data is input into the code once more. This procedure is repeated
until converged solutions for the 3—6: curves are reached and a
ﬁnal correction can be made to the raw data. Convergence is
determined by the difference in 3 between the current and previ
ous iterations at each span station. When the maximum absolute
value falls below a set tolerance. then the solution is assumed to
have converged. A tolerance of 0.4 deg. 4—5 iterations for conver— Make initial estimate of the ﬁ—oz
relationship at each span station Convert raw cn—ﬂ. ct—ﬁ data to cl—a data and use together with
suitable cd—a data as airfoil tables
for input to LSAF Run LSAF to produce new 3D
,6—a relationship at each station Converged
ﬁ—a Apply [301 corrections to raw
cn—B. Cg—ﬁ data to produce final solutions for cl—a, cdp—a i Fig. 4 Flowchart of LSIM procedure NOVEMBER 2000, Vol. 122 / 197 Table 1 Operating parameters of the Phase III CER tests Machine Operation ‘
Number of blades 3 ‘ Rated power 19.8 kW
Power regulation Stall
Rotor location Downwind I,
i Cutin wind speed 6 m/s :
Cutout Wind speed N/A (stall control) l
Rotational speed 71.63 rpm ‘
l‘ Density 1.025 kg/m3
Coning angle 3.42 deg Blade Parameters :
NREL inhouse 1 Type Proﬁle S809 l Chord 0.4572 in ,
Thickness 0.096 m Length 5.023 m Tip pitch Approx. 3 deg gence and less than l—min cpu time per iteration are typical. The
overall procedure is outlined in Fig. 4. Additional details can be
found in Whale and Selig [9.10]. Testing the Method. Testing of the correction method re
quires measured data that incorporates 3D ﬂow characteristics at
poststall angles of attack. A large amount of 3D data has been
gathered from the IEA Annex XIV Project: Field Rotor Aerody
namics [ll] which involved the coordination of ﬁve fullscale
aerodynamic test programs aimed at capturing 3D data from ex
periments on rotating wind turbine blades. Of these tests. the most
comprehensive body of data has been gathered at NREL due to
the detailed instrumentation on the CER blade. In Phase III of the CER experiment [12], a highly twisted blade
of constant chord was used. With the exception of the root. the
blade has an NREL 5809 proﬁle. an airfoil that has been tested in
wind tunnels at Delft University of Technology (TUDelft), Ohio
State University (OSU) and Colorado State University (CSU) [7].
Table 1 shows the blade geometry and operating parameters for
the CER during Phase III. Measurements of the local inﬂow. at a
distance in front of the leading edge of the blade equal to 79% of
the chord. were made with lightweight ﬂow sensor ﬂags for span
wise stations of 30%, 47%, 63%. and 80% of the blade radius. For
the purposes of testing LSIM. it was desirable to obtain a smooth
set of performance data in which irregularities in the data (e.g..
due to unsteady conditions during measurement) were kept to a  30% span ‘ 1—9 47% span
. —o— 63% span l ‘4 80%span‘ ......... ................. . ................ 1.5 Normal Force, c
O 10 20
Local Flow Angle, B (deg) 30 40 minimum. A ‘hypothetical‘ set of 3D data was produced for the
CER by matching TUDelft 2D wind tunnel data and Phase III
CER 3D data. Performance data from 2D wind tunnel tests on the
S809 airfoil at TUDelft was input into the liftingsurface code and
converted to uncorrected prestall data at 30%. 47%. 63%. and
80% span. Phase III CER 3D performance data was used as a
guide in estimating the poststall behavior of the hypothetical
data. Plots of normal and tangential blade force coefﬁcients versus
local ﬂow angle for the hypothetical 3D data are shown in Figs.
5(a) and 5(b), respectively. LSIM simulations were carried out using the hypothetical data
using the line of reﬂection as an initial inﬂow correction (i.e.. a
= B at iteration [tn 0). In constructing the performance tables to
input to the vortex code. lift values were calculated using Eq. (2)
and drag values were taken from 2D TUDelft data. Results The inﬂow correction curves output from LSIM were found to
converge after 45 iterations of the method and the results are
shown in Figs. 6(al—(d) for the 30%. 47%. 63%, and 80% span
stations. respectively. In each case. the SD curves are compared
with 2D inﬂow correction curves (i.e.. using 2D TUDelft lift and
drag values as input to LSIM). At 30% span. there is a signiﬁcant departure in the post—stall
B—a relationship between the 2D and 3D correction methods.
Figure 6(a) shows 330>Bzo for some post~stall a. as expected
from the theory outlined in Fig. 2. In particular. at B=20 deg
there is a difference of around 4 deg between applying a 2D LSIM
or a 3D LSIM correction to the raw measurement data. At the
47% and 63% span stations. the deviation between the 2D and 3D
curves is less signiﬁcant with a difference of less than 0.5 deg
between applying a 2D or a 3D correction across the range of raw
,8 values. Further outboard. at 80% span. the differences between
the 2D and 3D curves are negligible. The converged 3D inﬂow correction curves were linearly ex
trapolated to higher angles of attack over the entire B range of the
hypothetical input data and extended trendlines were used to ap
ply the 3D LSIM corrections to the data at each spanwise location.
and produce values of lift and pressure drag in accordance with
Eqs. (2) and (3). The errors introduced by extending the inﬂow
correction curves are discussed before the conclusions of this pa
per. From the equations it can be seen that applying the inﬂow
correction will affect both the general slope and intercept of the
3D performance curves. The 3D corrected lift and pressure drag
curves produced by LSIM are shown in Fig. 7. together with
corresponding 2D data from wind tunnel tests at TUDelft
lRe=500.000). 30% span l
47% spani
63% span l
80% span l O 10 20 30 40 Local Flow Angle. (3 (deg) Fig. 5 Hypothetical performance data based on Phase lll CER values: (a) Normal force. (b) Tangential force 198 / Vol. 122. NOVEMBER 2000 Transactions of the ASME A
a:
V
w
o a m E «a. 20 2’ c» C < 3 9 u / a 10 ,, ," .. , 8 ' l _. 1,  2DLSM l
3+ 3DLSM I
l  Line of reflection! 0 10 20 30 Angle of Attack, (1 (deg) A
O
V
(.0
O 20 . ,. .. .. .. (Iva/... .......... 10 ...... Local Flow Angle, (3 (deg) «>~ 20 LSIM
[9 3D LSIM i   Line of reflection 0 10 20 30
Angle of Attack, (1 (deg) (b) 30 B CD 3 . ‘& 2O ‘ m‘ E) C < 3 2 u. ,’ U ,’ 3 0 2D LSlM i + 3D LSlM
‘— Line olreilection
0 ,
0 10 20 30 Angle of Attack, or (deg) ((1)30 B CD ' , I E . n 20 .. . ... . ...... I). .. 2” , at C < B 2 LI. 5 10 8 l _‘ <> 2D LSIM + an LSIM i
  Line of reflection l O 1 0 20 30
Angle of Attack, on (deg) Fig. 6 LSIM inflow correction curves for CER hypothetical lift data: (a) 30% span, (b) 47% span, (c) 68% span, (d) 98% span At the 30% station (Fig. 7(a)), there is a marked enhancement
of the 3D lift as compared with the 2D data. The increase in lift is
as much as 75% at some angles of attack and the converged LSIM
curve shows an lldegrees delay in stall compared with the 2D
data. Figures 7(b)—(d) show that the differences between the 2D
windtunnel lift data and the 3D predictions decrease signiﬁcantly
with spanwise location up to 80% span. In particular. there is
good correlation with 2D data at 63% and 80% span. suggesting
the upwash at these stations is too far outboard to be signiﬁcantly
inﬂuenced by poststall effects and too far inboard to be affected
by the tip vortex. Comparing the 2D windtunnel drag data with the 3D con
verged solutions in Fig. 7. there is a signiﬁcant increase in 3D
pressure drag over 2D values at 30% span and at some angles of
attack. the increase is drag is as much as 120%. This seems con
trary to the theory of poststall suppressed wakeenhanced lift
(outlined in Fig. 2 and used by many researchers in modeling
poststall effects. e.g.. Montgomerie [l]. Du and Selig [13]). The
phenomenon of greater 3D drag at inboard stations than ZD drag.
however. has also been observed in experiments by Madsen [3]
and Bjorck et al. [14] and warrants further investigation. Figures
7(b)(d) show the discrepancies between 3D calculations of pres—
sure drag and 2D data reduce with spanwise location up to 80%
span. In particular. there is a very good agreement between 2D
and 3D values at 80% span. highlighting the 2D nature of the ﬁ0w
at this span station. Comparison with 2D Methods. In order to compare the new
3D method with 2D methods. the converged 3D LSIM perfor Journal of Solar Energy Engineering mance curves of Fig. 7 were compared with a 2D LSIM correction
method. i.e.. using 2D TUDelft lift and drag values as input to the
liftingsurface code. in addition. results are also shown from a 2D
wind tunnel method (WTM) developed from 2D upwash trends
established in OSU/CSU wind tunnel tests and currently used as a
correction method at NREL. The equation for the 2D correction
derived from the windtunnel tests is shown in Eq. (4): a: —5.427>< 10—5133+6.713x 10—3/33+0.6i7a—0.8293
(4) Figures 8(al—(d) show the comparison of corrected lift and pres
sure drag data at each spanwise station. At 30% span. the 3D
LSIM predicts greater poststall lift and pressure drag than the 2D
LSIM. The graph shows differences of as much as 15% in c, and
35% in cl,” between applying a 2D or a 3D correction. For the
47% station (and stations further outboard). the difference be
tween applying a 2D or 3D correction is less than 0.1% and can be
regarded as negligible. Comparisons of the 3D LSIM and 2D WTM curves show lower
LSIM lift values for prestall angles of attack and higher LSIM lift
values for poststall angles of attack. This trend is most evident at
30% span (Fig. 8(a)) and may be explained by considering the
associated behavior in upwash. At prestall angles of attack. the
trend in lift suggests a lower LSlM upwash than the 2D upwash of
the wind tunnel method and is likely to be due to the influence of
the 3D geometry at the root of the blade. At poststall angles of
attack. 3D LSlM predicts greater upwash than the 2D WTM up NOVEMBER 2000, Vol. 122 / 199 '1 . ‘— ZDData ‘ 0 7 10 20 30 4o
Angle of Attack. on (deg) 1 '—~ 20 Data 0.5 ,... ............... ... ............. .................. Lift and Drag Coells., Cr Cdp (—) o 10 20 30 4o
Angle of Attack, on (deg) 7—.— )u ZDData l ................ l_ SDLSIM l 0.5 . ................... ,,,,,, o '10 20 30 4o
Angle of Attack. 0: (deg)  20 Data A ) a.
\_/ N '— 30 LSIM _s
01 _s .0
U1 Lift and Drag Coeils., cl, cdp ( o '10 20 30 4o
Angle of Attack. on (deg) Fig. 7 LSIM corrected performance curves for CER hypothetical lift data: (a) 30% span, (b) 47% span, (c) 68% span. (d) 98% span wash due to the 3D effects outlined in Fig. 2. In terms of pressure
drag, the 3D model predicts high values at 30% span that appear
to be associated with high poststall lift (as discussed previously).
Figures 8(a)—(d) show. as spanwise station increases. there is im—
proved agreement between the LSIM and WTM curves due to the
2D nature of the ﬂow at the outboard stations. Finally, it should be noted that these trends may differ in the
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