Analysis and Comparison 

of Test Results from the 

Small Wind Research Turbine 

Test Project 

Preprint 

November 2004 • NREL/CP-500-36891 

D. Corbus and D. Prascher 

To be presented at the 43rd AIAA Aerospace Sciences 

Meeting and Exhibit 

Reno, Nevada 

January 10-13, 2005 

National Renewable Energy Laboratory 

1617 Cole Boulevard, Golden, Colorado 80401-3393 

303-275-3000 • www.nrel.gov 

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by Midwest Research Institute • Battelle 

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1

Analysis and Comparison of Test Results from the Small 

Wind Research Turbine Test Project 

David Corbus* and Dan Prascher†

National Renewable Energy Laboratory, Golden, Colorado 80401 

 Most small wind turbines furl (yaw or tilt out of the wind) as a means of limiting power and rotor speeds 

in high winds. The Small Wind Research Turbine (SWRT) testing project was initiated in 2003 with the goal 

of better characterizing both small wind turbine loads (including thrust) and dynamic behavior, specifically as 

they relate to furling. The main purpose of the testing was to produce high-quality data sets for model 

development and validation and to help the wind industry further their understanding of small wind turbine 

behavior. Testing was conducted on a modified Bergey Excel 10-kW wind turbine. A special shaft sensor was 

designed to measure shaft loads including thrust, torque, and shaft bending. Analysis of 10-minute mean data 

showed a strong correlation between furling and center of thrust location, as calculated from the shaft-bending 

and thrust measurements. Data were collected for three different turbine configurations that included a 

change in the lateral furling offset and the blades. An analysis of inflow conditions indicated that organized 

atmospheric turbulence had some impact on furling. 

I. Introduction 

any small wind turbines use furling, whereby the rotor either tilts and/or yaws out of the wind, to protect from 

overspeed and over-power during excessive winds. In the past, most small wind turbine designers used trialand-error approaches, often using variable geometry test platforms to vary furling offsets. Recent upgrades in the 

FAST and ADAMS with AeroDyn wind turbine areoelastic simulation models [1] have incorporated furling into the 

models. FAST's new furling-related features include a lateral offset and skew angle of the rotor shaft, rotor- and tailfurling degrees-of-freedom, up- and down-furl stops, and tail fin aerodynamics and inertia [2, 3]. However, to date 

there has been a limited amount of test data available for model validation of small furling wind turbines [4]. 

Acquiring good test data for a small furling wind turbine was a recommended action of the National Wind 

Technology Center (NWTC) Furling Workshop held in July of 2000 [5] and has been mentioned in previous papers 

on furling [6]. The Small Wind Research Turbine (SWRT) project was initiated to provide reliable test data for 

model validation of furling wind turbines and to help understand small wind turbine loads. The measurements of 

thrust and furling are of particular importance to the model validation effort and are unique to this test. 

II. Experiment Overview 

A. Test Turbine 

 The SWRT is a modified Bergey EXCEL 10-kW turbine that furls horizontally out of the wind. The 

rotor/generator/main-frame assembly is connected to a tail boom at a furling pivot joint by a pin connection. The 

axis of the furling pivot joint is inclined laterally at a small angle to the vertical yaw axis and produces a gravity 

restoring moment. A main frame stop keeps the tail boom from furling more than about 68 degrees. There is a lateral 

offset between the yaw axis and the rotor axis. As the wind speed increases, so does the thrust and the aerodynamic 

normal force on the nominally aligned vertical tail at the end of the tail boom. Furling occurs when the rotor 

moments exceed the gravity restoring moment. The furl damper provides very little resistance to furling but a high 

resistance to unfurling. 

 The Bergey EXCEL is a three-bladed upwind turbine rated at 10-kW output at 13.0 m/s. The EXCEL uses a 

permanent magnet alternator to produce three-phase variable frequency output at a nominal 240-volts. Inside the 

Gridtek inverter, the three-phase output is rectified to DC power and then converted to single-phase 240-volt 60-hz 

AC power. The turbine blades are constant chord and made from pultruded fiberglass, and the direction of rotation is 

 

*

 Senior Mechanical Engineer, National Wind Technology Center, MS3811, AIAA Member. 

†

 Student Intern, National Wind Technology Center, MS3811. 

This paper is declared a work of the U.S. Government and is not subject to copyright protection in the United States. 

M 
2

Figure 1. SWRT at the National Wind Technology 

Center. 

Table 1. Measured parameters and sensor list. 

Parameter Measured Sensor Type 

Flap and edge bending 

all three blades 

Full bridge strain gage 

Shaft thrust, 0/90 degree 

bending, and torque 

Full bridge strain gage 

on load-fixture 

Shaft RPM and position Encoder 

Yaw position and rate Encoder 

Wind speed/direction Sonic anemometer 

Tail wind speed/direction Sonic anemometer 

Power from turbine Watt transducer 

Tower top bending Load cell on each tower 

top leg 

Furl Rotary Variable 

Inductance Transducer 

Mid-tower and 3-m wind 

speed 

Mechanical anemometer 

Temperature Temperature transducer 

Pressure Pressure transducer 

Figure 2. Shaft load fixture. 

counter-clockwise when looking downwind. The 

turbine shaft has an 8-degree tilt, and the turbine 

is mounted on a Rohn SSV, 24.4-m (80-ft), 

freestanding lattice tower. The turbine was 

modified in several ways to allow for test 

instrumentation to be installed. One significant 

modification was that the turbine main shaft was 

shortened approximately 0.18 m (7 in.) to allow 

for installation of a 0.18-m (7-in.) load fixture, 

in line with the non-rotating shaft, to measure 

shaft loads. Other modifications include changes 

to the weight of the turbine from the DAS 

components and changes to the blade length. 

 The SWRT test is located at the NWTC as 

shown in Fig. 1. The turbine was installed in 

May of 2003, and preliminary testing was 

conducted until January of 2004. The testing for 

the data sets described in this paper began in 

January of 2004 and concluded in June of 2004. 

 It should be noted that the SWRT is modified 

from the commercial Bergey EXCEL turbine 

and that the test results in this paper are not 

necessarily representative of the Bergey EXCEL 

turbine. 

B. Measured Parameters 

Table 1 lists the measured parameters for the 

test. Of particular importance is the shaft load 

fixture that was built specifically for the test to 

measure thrust, shaft 0 and 90-degree bending, 

and torque. Fig. 2 depicts the shaft load fixture, 

opened up to show the four strain-gaged posts 

that carry all of the rotor loads. The shaft sensor 

is located on the non-rotating shaft at 

approximately 0.51 m (20.35 in.) from the rotor 

center. 

Flap and edge signals are measured on all 

blades and then amplified (50x and 166x, 

respectively) on the data acquisition system 

(DAS) where they are digitized. A sonic 

anemometer is located at hub height at a distance 

of 19.8 m (64.9 ft) upwind from the turbine, 

which is 3.4 rotor diameters. A sonic 

anemometer is also located on the tail of the 

turbine just upwind of the tail fin. AC variablevoltage power is measured at the output of the 

turbine upstream of the inverter. 

C. Data Acquisition System 

The data acquisition system used is Zond’s 

Advanced Data Acquisition System (ADAS), 

which is a distributed multi-source, 

synchronous, multi-channel data recorder. By 

employing remote Data Acquisition Modules 

(DAMs), the ADAS records data near the source 

of the measurement. A PC-based computer 
3

Table 2. SWRT configurations. 

 A B C 

Airfoil SH3052 SH3052 SH3055

Lateral shim 4 degree none none 

Blade swept area 

m2

/rotor diameter 

(m) 

26.4/ 

5.8 

26.4/ 

5.8

35.3/ 

6.7

Blade pitch 

(degrees) 

11.5 11.5 9.5 

system acts as the host, performing all set-up, programming, data display, and downloading duties. All channels are 

synchronized, and data acquisition occurs simultaneously without multiplexing. Data are sampled at 160 hz, and a 

40-hz, 6-pole low-pass Butterworth filter is used to filter the data. Records of 10 minutes in length are stored. 

D. Pre-Test Turbine Characterization 

To supply inputs for aeroelastic models of the SWRT, the turbine tail assembly and main frame were weighed 

and center of gravities (Cgs) were determined. Tests were also conducted to calculate the moment of inertia about 

the tail axis and the yaw axis. Tail damper properties were measured and all turbine geometries noted. A modal test 

was conducted for a blade to determine mode shapes and frequencies for flap and edge. 

E. Calculated Parameters 

Calculated channels were used for a wide range of parameters based on the measured data. Calibrations were 

performed for flap and edge bending on the blades, and the results were used to calculate the 2-by-2 crosstalk matrix 

for blade flap and edge-bending moments. The shaft sensor was calibrated by the manufacturer, Sensor 

Developments, and the A2LA-accredited calibration was confirmed at the NWTC in a special test rig with the 

turbine mounted on the upper tower section in a high bay. The results of the Sensor Development calibration were 

used to calculate the four-by-four crosstalk matrix for shaft thrust, 0- and 90-degree bending moments, and torque. 

A post-test calibration conducted by Sensor Developments verified that the sensor stayed in calibration during the 

test. 

III. Turbine Testing 

A. Turbine Configurations 

 Data were collected for three turbine configurations, A, B, and C, as summarized in Table 2. Configuration A 

and B differ by the lateral offset distance between the rotor centerline and the yaw axis, which is 0.106 m in 

Configuration A and 0.083 m in Configuration B (a 22% change). The change in the lateral offset for Configuration 

A was implemented by placing a 4-degree shim between the alternator and the shaft sensor. Configuration C has a 

greater swept area (about 20%) than Configurations A 

and B and different blade pitch, and it is representative 

of the current version of the Bergey EXCEL turbine 

blades. 

In addition to all configurations running with a 

shaft tilt of 8 degrees, all three turbine configurations 

ran at an average yaw error of between 13 and 23 

degrees, resulting in a significant skewed wake. 

A total of 514 10-minute records were collected, 

200 for configuration A, 78 for B, and 236 for 

configuration C. An additional 248 2-minute record 

data sets were collected for configuration B prior to 

the 10-minute data sets and were used for data verification during turbine start up. 

The number of test records for each configuration was affected by unexpected test results. For example, the test 

started with the SH3052 blades without a shim as the baseline configuration, but the turbine did not furl at a lowenough wind speed, and the inverter went off-line from high-power or voltage faults. A 2-degree, then a 4-degree, 

lateral shim was introduced to try to prevent these fault conditions by getting the turbine to furl at lower wind speeds 

and, hence, prevent over-power conditions. However, this did not prevent the faults, as the turbine would not always 

furl fast enough in high wind conditions. The inverter torque-RPM curve in the software was finally changed to 

minimize the inverter faults, but some data with high wind speed inverter faults needed to be excluded from the final 

data sets. Another drawback to the inverter controller for this experimental testing was that it would unload the 

turbine in very low winds so data sets below 5 m/s were missing, which is not important for furling data but can be 

important for characterizing turbine operation. All final configurations were run with the same inverter torque-RPM 

curve. 

The change to a new blade configuration was prematurely introduced into the test matrix because the strain 

gages for the flap signals on the first set of blades reached the rated cycle life of between 10P

6 Pand 10P7

P cycles. The 

high average rotation speed of the turbine, coupled with the fact that the turbine does not have a brake so it is always 

spinning, resulted in the high number of cycles within 1 year of testing. The degradation of the strain gages may 
4

-10

0

10

20

30

40

50

60

70

80

5 10 15 20

Mean Wind Speed m/s

Furl, deg

Max Furl Furl

Figure 5. Furl versus mean wind speed. 

-150

-100

-50

0

50

100

150

200

5 10 15 20

Mean Wind Speed m/s

Yaw rate, deg/s

Max yaw rate Mean yaw rate Min yaw rate

Figure 6. Yaw rate versus mean wind speed. 

have been exacerbated by blade flutter from unloaded operation of the turbine during inverter fault conditions and 

special test conditions. The strain gage failure is the reason Configuration B has only 78 test records. 

B. Inverter Torque Control 

Hysteresis in the inverter controller software for torque control resulted in some scatter in the torque-RPM 

curves. Fig. 3 shows a plot of torque versus RPM for Configuration C in bins of 5 RPM for 10-minute data sets. The 

coordinate system conforms to the IEC standard, so torque is shown as negative because the turbine rotates 

counterclockwise. For model validation data sets, scatter in the torque-RPM curve is undesirable, so for each 

configuration a limited number of data sets were taken with a fixed resistance load that reduced the torque-RPM 

scatter. Fig. 4 shows a plot of torque versus RPM from one 10-minute data set for Configuration C and a fixed 

resistance load. 

C. Turbine Dynamics 

Power spectral densities (PSDs) were measured with the turbine operating at different rotor speeds. The PSDs 

showed one per revolution (1P) and 3P in all shaft and blade signals at different magnitudes. Of particular interest 

was the first mode tower frequency showing up in the thrust. 

IV. Data Analysis 

A. 10-Minute Data Sets 

Figs. 5 through 8 show scatterplots of furl, yaw rate, electrical power, and rotor speed for configuration A. The 

data show mean, maximum, and minimums plotted against mean wind speed. The average yaw error for 

Configuration A is between 15 and 20 degrees depending on wind speed. Because of space limitations, only 

scatterplots for Configuration A are shown, but comparisons between the configurations are shown later in this 

paper. The plots give a good overview of the operating characteristics of the SWRT: high rotor speeds, up to 500 

RPM, with high maximum yaw rates and mean yaw errors. 

Test Configuration C

-400

-350

-300

-250

-200

-150

-100

-50

0

0 100 200 300 400 500 600

RPM

Torque, Nm

torque mean

Upper STDev

Lower STDev

Figure 3. Torque RPM curve for 

Configuration C. Figure 4. Torque versus RPM 

for fixed resistance load. 
5

0

2

4

6

8

10

12

14

5 10 15 20

Mean Windspeed, m/s

Mean Electric Power, kW

Max Power Mean Power Min Power

Figure 7. Electrical power versus 

mean wind speed. 

0

100

200

300

400

500

600

5 10 15 20

Mean Windspeed, m/s

RPM

RPM mean RPM max RPM min

Figure 8. Rotor speed versus 

mean wind speed. 

 

-2000

-1000

0

1000

2000

3000

4000

5000

6000

0 5 10 15 20

Mean Windspeed, m/s

Thrust - N.

Maximum ShftThrus2 Minimum

 

-500

-450

-400

-350

-300

-250

-200

-150

-100

-50

0

0 5 10 15 20

Mean Windspeed, m/s

Torque - N-m

Maximum Shft Tor Minimum

 Figure 9. Thrust versus mean wind speed. Figure 10. Torque versus mean wind speed. 

-10

0

10

20

30

0 500 1000 1500 2000 2500

Thrust, N

Furl, deg

Mean Furl versus Thrust

Figure 11. Furl versus thrust. 

 Figs. 9 through 11 show similar scatterplots from the same data set for shaft thrust and torque. Also shown is a 

plot of mean furl versus mean thrust. There is a significant amount of scatter in the plots of both mean furl versus 

mean wind speed and mean furl versus mean thrust. 

B. Edge-Bending Moments 

Testing results showed a large discrepancy between the 

sum of the three edge-bending moments when adjusted for 

strain gage location and compared with the torque signal. At 

rated wind speed, the sum of the three edge signals was 

300% to 500% greater than the torque! Yet analysis of the 

blade signals during “slow rolls” of the rotor showed good 

agreement between test data and the predicted in-plane and 

out-of-plane blade-bending moments from gravity loads, 

which were significant because of the 8-degree shaft tilt. 

 The reason for the discrepancy was a small moment arm, or chordwise offset, between the blade Cg and the 

centerline of rotation and between the blade Cg and the edge gage neutral axis, as shown in Fig. 12. Although care 

was taken to align the edge gages along the neutral axis, with a complex airfoil shape there will always be some 

offset from the neutral axis, which creates a moment arm. As a result of the high speed of the rotor, centrifugal 

loading acts on this moment arm, so that the edge aerodynamic moments can be relatively small compared to the 

total edge-bending moment, especially at higher rotor speeds. 
6

R2 = 0.9986

R2 = 0.9989

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 20000 40000 60000 80000 100000 120000 140000 1

omega ^2 (RPM^2)

Blade Edge Bending, volts

Mean Blade 3 Mean Blade 1

Linear (Mean Blade 1) Linear (Mean Blade 3)

Figure 13. Edge bending versus RPM squared 

for unloaded operation. 

-2000

-1500

-1000

-500

0

500

0 5 10 15 20

Mean Windspeed, m/s

Blade 3 Edge Bending, N-m

Maximum Mean Minimum

Figure 14. Edge-bending moment versus 

mean wind speed. 

-500

-400

-300

-200

-100

0

100

200

300

400

500

600

700

800

0 2 4 6 8 10 12 14 16 18 20

Mean Windspeed, m/s

Blade3 Flap Bending, N-m

Maximum

Mean

Minimum

Figure 15. Flap-bending moment 

versus mean wind speed. 

The error in the edge-bending moment from centrifugal 

loading caused by the offset between the edge gage neutral 

axis and the center of rotation is a test phenomena that has been largely overlooked to date in many test procedures. 

This effect will be more apparent with smaller turbines that operate at higher RPMs, but may also have some effect 

on larger turbines. 

To calculate aerodynamic edge-bending moments, testing was conducted with the rotor unloaded and 

correlations between the square of rotor RPM and edge-bending moments were developed (as shown in Fig. 13) for 

two of the blades. This correlation was then slightly adjusted for the friction losses that are included in the unloaded 

torque test data by using dynamometer data of torque versus RPM for the unloaded condition. 

Fig. 14 shows a scatterplot of the measured blade three-edge moment without any correction. Fig. 15 shows a 

scatterplot of the flap moment for blade three of the SWRT. Flap-bending response is relatively flat with wind speed 

and decreases at the higher wind speeds as a result of centrifugal stiffening of the blades at the high rotor speeds. 

C. Time Series Data 

 Because furling is a transient phenomena, analysis of time-series data can be more useful than that of 10-minute 

mean data. In the time-series data, thrust and furl are often correlated, but not always. For example, the second 

furling event in Fig. 16 of about 14 degrees occurs when the thrust is relatively low and the rotor speed is 

decreasing, whereas the large furling event of 36 degrees occurs when the thrust is high and the rotor speed is 

increasing immediately preceding the furl, as would be expected. Yaw error changes occur rapidly and affect furl. 

 Calculated channels for shaft thrust and shaft 0- and 90-degree bending moments are used to calculate the 

center of thrust angle (CenThrAng) and center of thrust length (CenThrLen) as follows: 

CenThrAng = ArcTan2 (shaft tilt moment/thrust, 

shaft yaw moment/thrust) (1)

CenThrLen = Sqrt ((shaft tilt moment/thrust) 2

 + 

(shaft yaw moment/thrust) 2

) (2) 

Figure 12. Moment arm between Blade Cg and center of 

rotation for edge-bending moments. 
7

0

5

10

15

20

25

30

35

40

45

50

5 7 9 11 13 15 17 19 21

Time, seconds

Furl, Yaw Error (degrees)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Center of Thrust (meters)

furl yaw error center of thrust

Figure 17. Furling with center of thrust. 

These equations are only valid when inertial forces can be ignored during steady state operation with negligible 

yaw rate; otherwise the gyroscopic forces on the shaft have too large an effect and invalidate the equations. Fig. 17 

shows a time-series furling event with low yaw rate before the furling event and how CenThrLen plots in 

relationship to furling. Additional data analysis is needed to further evaluate using equations (1) and (2) to 

characterize the effect of aerodynamic thrust on furling behavior during low yaw rates. 

Figure 16. Time series furling events. 
8

V. Comparison of Data Sets 

 A comparison of 10-minute scatterplots for the different configurations shows the effect of parameter changes 

between the configurations. Fig. 18 shows the ratio of 10-minute mean meteorological tower wind speeds to tail 

wind speeds for Configuration A and C plotted against wind speed. The greater solidity (about 16% higher) and 33% 

greater swept area of Configuration C results in a significantly reduced tail wind speed as compared to 

Configuration A. Because the data are for a very narrow power coefficient (Cp) range, the ratios for a given 

configuration do not change much with wind speed until the higher wind speeds where the turbine is furled a large 

percentage of the time and the sonic tail anemometer is partially out of the wake. Rotor speeds for Configuration C 

are about 25 RPM greater than that of A and B until furling. 

Fig. 19 shows a comparison of 10-minute mean furling versus wind speed for configuration A, B, and C. The 

data show only those data points with furl greater than 1.5 degrees and is fitted with a third-order polynomial 

resulting from the high degree of scatter. The data show that Configuration C furls the most, predominantly because 

of the higher thrust resulting from the higher solidity of the 

blades and larger swept area, followed by A with a 4-

degree shim and lower solidity and shorter blades, and then 

B with the same blades as A, but without the shim. 

Figs. 20-22 show data for thrust, shaft-yaw moment, 

and shaft-tilt moment for the different configurations. 

Configuration C has a significantly higher thrust and also 

higher yaw and tilt moments. The data for Configurations 

A and B are similar and hard to differentiate. (The 

coordinate system conforms to the IEC standard, so the xaxis is parallel to the main shaft and positive downwind; 

the z-axis is perpendicular to the main shaft and positive 

up; and x-y-z form a right-hand system. The shaft tilt moment (My) is the moment about the y-axis and shaft yaw 

moment (Mz) is the moment about the z-axis. Note that the overhang moment for shaft tilt is not included in the 

data.) 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

5 10 15 20

Wind Speed, m/s

Ratio Tail/Met WS, %

Ratio Tail/Met WS Config A

Ratio Tail/Met WS Config C

Figure 18. Ratio of tail/met wind speed 

versus wind speed. 

0

5

10

15

20

25

30

35

40

45

50

9 11 13 15 17 19 21

Mean Windspeed, m/s

Furl Degrees

Mean Config A

Mean Config B

Mean Config C

Configuration C

Configuration B

Configuration A

Figure 19. Furl versus wind speed for 

different configurations. 

0

500

1000

1500

2000

2500

3000

3500

5 7 9 11 13 15 17 19 Mean Windspeed, m/s

Thrust N

Mean Config A

Mean Config B

Mean Config C

Figure 20. Shaft thrust versus wind
9

 

-250

-200

-150

-100

-50

0

0 5 10 15 20 Mean Windspeed, m/s

Shaft Yaw Bending, N-m

Mean Config C

Mean Config A

Mean Config B

 

-600

-500

-400

-300

-200

-100

0

100

0 5 10 15 20 Mean Windspeed, m/s

Shaft Tilt Bending, N-m

Mean Config A

Mean Config B

Mean Config C

 Figure 21. Shaft yaw moment versus wind Figure 22. Shaft tilt moment versus 

 speed for different configurations. wind speed for different configurations. 

VI. Correlation Between Inflow and Furling 

A. Inflow Data Processing Equations 

In recent years, significant work has been conducted showing the relationship between inflow parameters and 

fatigue loads for wind turbines [7, 8]. To better understand the relationship between coherent or organized 

turbulence and the potential impact on furling, calculated channels were developed for several different inflow 

parameters based on the data measured from the sonic anemometer on the meteorological tower. 

 The following inflow parameters were calculated for each data set. 

( ) | ( ) cos ( )sin | 1 2u f ti up ti β up ti β H= + (3) ( ) ( ) cosφ ( )sinφ 1 3 f i f i p i u t u t u t H= + (4) 

( ) ( )sin β ( ) cos β 2 1 2 f i p i p i u t = − u t + u t (5)

( ) ( )sinφ ( ) cosφ 3 3 f i p i p i u t u t u t H= − + (6)

where 1

f u , 2f u , and 3f u are wind vectors rotated from those measured in the sonic probe coordinate system 

( p1,2,3 ) to ones aligned with the flow ( 1,2,3 f ) and in the direction of the mean shearing stress, and 

arctan ( / ) 2 1 p p β = u u (7)

arctan ( / ) 3 H p p φ = u u (8)

and 1 p u and 2 p u are the horizontal velocity components measured along the sonic probe x-axis and y-axis, 

respectively, and 3 p u is the vertical velocity component measured along the sonic probe z-axis. The turbulent or 

fluctuating (i.e., zero-mean) component velocities (i.e., longitudinal, transverse or crosswind, and vertical velocities) 

for which only the longitudinal (i.e., streamwise) component aligned with the flow vector 1 u f has a non-zero mean, 

are defined as 

( ) 1 ( ) ( ) ( ) 1 1 1 1 ∑ 1

=

′ = − = −

N

i

i f i f f i f i u t

N u t u t u u t (9) 

( ) ( ) 2 i f i v′ t = u t (10) 

( ) ( ) 3 i f i w′ t = u t (11) 

The turbulent Reynolds stress components are 

( ) ( ) ( ) i i i u′w′ t = u′ t ⋅ w′ t (12) 

( ) ( ) ( ) i i i u′v′ t = u′ t ⋅ v′ t (13) 

( ) ( ) ( ) i i i v′w′ t = v′ t ⋅ w′ t (14)
10

Hub Mean Wind Speed (m/s)

4 6 8 10 12 14 16 18

Furling angle (deg) 0.001

0.01

0.1

1

10

100

0.001

0.01

0.1

1

10

100

Hub σw (m/s)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Furling angle (deg) 0.001

0.01

0.1

1

10

100

0.001

0.01

0.1

1

10

100

Hub Mean Coherent TKE (m2/s2)

0 10 20 30 40 50 60 70

Furling angle (deg) 0.001

0.01

0.1

1

10

100

0.001

0.01

0.1

1

10

100

SWRT Config "A" Furling Angle vs Inflow Parameters

Figure 23. Furling and inflow. 

Figure 24. Furling versus Richardson Number. 

and the mean shearing stress or friction velocity is defined as 

u* = u' w' (15) 

and the turbulence kinetic energy (TKE) is 

TKE = 0.5 * [(u’)P

2

P + (v’)P

2

P + (w’)P

2 P] (16)

and coherent TKE (CoTKE) = 0.5 * SQRT [(u’w’)P

2

P + (u’v’)P

2

P

+ (v’w’)P

2 P]. (17) 

 In addition to the inflow parameters listed in equations 3 

through 17, the gradient Richardson number (Ri) for a height of 

2-80 m was obtained from a meteorological tower at the 

NWTC and included in the data sets for the SWRT. The 

Richardson number can be useful in explaining turbulence 

because it represents the ratio of turbulence generation by 

buoyancy (i.e., thermal) to wind shear (i.e., mechanical) forces. 

A negative value of Ri represents unstable or convective 

conditions, a value of zero represents neutral, and positive 

values signify a stable flow. 

 A correlation analysis was conducted to determine whether 

inflow parameters have a significant impact on furling. Using 

the inflow parameters described in equations 9 through 17, a 

single variable correlation analysis was done for each test 

configuration, which yielded a list of variables that are highly 

correlated to furl angle. A multivariate correlation was then 

done on each test configuration to determine how sensitive the 

variables are to furl. Space limitations in this paper prevent 

presentation of all the detailed results, but a summary of the 

multivariate regression is provided below. 

Configuration A: The highest correlation (correlation 

coefficient, rP

2

P, is 0.65) was obtained between furl and the 

combination of coherent turbulent kinetic energy (CoTKE), 

standard deviation of the vertical wind component of the inflow 

(w′ ), and mean wind speed. 

 Configuration B: The highest correlation (correlation 

coefficient, rP

2

P, is 0.72) was obtained between furl and the 

combination of max CoTKE, max wind speed, and wind speed. 

Configuration C: The highest correlation (correlation 

coefficient, rP

2

P, is 0.79) was obtained between furl and w′ , 

local friction velocity u*, wind speed, and rotor speed. The 

introduction of rotor speed made the correlation coefficient 

change dramatically and, even though it is a machine variable, 

it was left in. When it was taken out, the rP

2 Pvalue went down 

significantly. 

 Configuration B, the configuration that is hardest to furl, is 

most sensitive to the maximum wind speed and maximum 

CoTKE. The same configuration without the shim (i.e., A) furls 

easier and is sensitive to the mean CoTKE and mean wind 

speed, as well as w′ . Configuration C, the easiest to furl 

configuration, is not sensitive to CoTKE. 

 Fig. 23 shows a plots of furling versus wind speed, w′ , 

and CoTKE; Fig. 24 shows a plot of furling versus Ri for 

Configuration A. Note that the maximum furling occurs at 
11

Cycles/min

0.1 1 10 100

RMS Coh TKE (m2/s2

)

0

2

4

6

8

10

12

Coherent TKE

Frequency (Hz)

0.001 0.01 0.1 1 10

RMS Coh TKE (m2/s2)

0

2

4

6

8

10

12

Furl

No Furl

Wavelength in Rotor Diameters

1 10 100 1000

RMS Coh TKE (m2/s2

)

0

2

4

6

8

10

12

Vertical Gust Velocity Variance

Frequency (Hz)

0.001 0.01 0.1 1 10

w' Variance Spectra (m2/s2

)

0.0

0.1

0.2

0.3

0.4

0.5

Wavelength in Rotor Diameters

1 10 100 1000

w' Variance Spectra (m2/s2

)

0.0

0.1

0.2

0.3

0.4

0.5

Cycles/min

0.1 1 10 100

w' Variance Spectra (m2/s2

)

0.0

0.1

0.2

0.3

0.4

0.5

 

Figure 25. CoTKE and vertical gust variance for two files 

 with same wind speed and different furl. 
12

about an Ri of 0.13. This is indicative of a site with a lot of coherent turbulence. The maximum load response from 

another test turbine at the NWTC, the ART, is also shown on the graph for comparison. 

 As a last indicator of the importance of looking at inflow when analyzing furling, Fig. 25 shows plots of the 

RMS CoTKE and RMS w′ (vertical gust velocity variance) versus frequency, cycles/minute, and wavelength in 

rotor diameters. The data are for two different time series plots from Configuration A with a wind speed of 14 m/s 

for both, but different turbulence parameters. In one file, the mean 10-minute furl is zero, whereas the other is 4 

degrees. The mean wind direction for each file is within one degree of each other. CoTKE and w′ were chosen as 

the variables to plot based on the correlation analysis. Mean wind speed, the other highly correlated variable, is the 

same for both files. The data show the effect of coherent turbulence and w′ on furling. The data also show a range 

of time for when the maximum energy is occurring and an indication of the wavelength of the maximum CoTKE 

and w′ in relation to the rotor diameter (this was calculated by dividing by the mean wind speed). 

VII. Conclusions 

The SWRT test has provided modelers with unique data sets to validate the FAST aeroelastic simulation model 

with furling and to understand small wind turbine dynamics and loads. The test resulted in a better understanding of 

aerodynamic and inertia edge-bending moment measurements. Analysis of statistical and time-series data shows the 

complex interaction of thrust, center of thrust, yaw rate, RPM, and how these variables relate to furl. Finally, it is 

shown that turbine furling can be affected by the vertical velocity gradient and the coherent turbulence. 

Future SWRT data analysis will include further analysis of the shaft thrust and bending loads to determine the 

usefulness of center of thrust calculations in regard to inertial and aerodynamic forces, more analysis of time-series 

data, additional comparisons of FAST model results with SWRT data for all configurations, and further examination 

of the effect of inflow on furling. 

 

Acknowledgments 

The authors thank everyone who helped with this work, including Mark Meadors of NREL, whose invaluable 

assistance with the testing made this paper possible; Todd Hanley of Bergey Windpower and Charles Newcomb of 

NREL for their help in the design of the SWRT; Marshall Buhl of NREL, who assisted in data manipulation and 

answered our CRUNCH and GPP questions with patience; Neil Kelley of NREL, who helped us with the inflow 

analysis; Craig Hansen of Windward Engineering, who provided insights into furling and helpful analysis of the 

SWRT data as well as comparisons of the SWRT data to ADAMs and FAST modeling results; Jason Jonkman of 

NREL for his development of the FAST furling model; and to Ruth Baranowski of NREL for making this paper 

much more readable. 

References 1

Jonkman, J.M., and Hansen, A.C., “Development and Validation of an Aeroelastic Model of a Small Furling Wind 

Turbine,” Collection of the 2005 ASME Wind Energy Symposium Technical Papers Presented at the 43rd AIAA 

Aerospace Sciences Meeting and Exhibit, 10-13 January 2005, Reno, NV, Washington, D.C.: American Institute of 

Aeronautics and Astronautics, January 2005, NREL/CP-500-36776. 

2 Jonkman, J.M., Buhl, M.L., (March 2004). “FAST User’s Guide”. NREL/EL-500-29798. Golden, CO: National 

Renewable Energy Laboratory, 105 pp. 

3 Jonkman, J.M., Buhl, M.L., (January 2004). “New Developments for the NWTC's FAST Aeroelastic HAWT 

Simulator,” Collection of the 2004 ASME Wind Energy Symposium Technical Papers Presented at the 42rd AIAA 

Aerospace Sciences Meeting and Exhibit, 5-8 January 2004, Reno, NV, Washington, D.C.: American Institute of 

Aeronautics and Astronautics, pp. 181-191; NREL/CP-500-35077. 

4 Davis, Dean A., Hansen, A. Craig, and Laino, David J. (2003). “Estimates of Maximum Design Loads for a 

Whisper H40 using Extrapolation Methods.” Proceedings of the Windpower 2003 Conference, 18-21 May, 2003, 

Austin, TX. Iwashington D.C.: American Wind Energy Association; session 4C. 
13

5 NWTC Furling (Furling Workshop by Buhl, M.L.,). http://wind.nrel.gov/Furling/workshop.html. Last modified 

November 21, 2002; accessed August 19, 2004. 

6

 Eggers, A.J., Chaney, K., Holley, W.E., and Ashley, H. (2000). “Modeling of Yawing and Furling Behavior of 

Small Wind Turbines,” Collection of the 2000 ASME Wind Energy Symposium Technical Papers Presented at the 

38th AIAA Aerospace Sciences Meeting and Exhibit, 5-8 January 2000, Reno, NV, Washington, D.C.: American 

Institute of Aeronautics and Astronautics. 

7 Kelley, N.; Shirazi, M.; Jager, D.; Wilde, S.; Adams, J.; Buhl, M.; Sullivan, P.; Patton, E., “Lamar Low-Level Jet 

Program Interim Report,” NREL TP-500-34593, 2004. 

8 Sutherland, H. J.; Kelley, N. D.; Hand, M. M. (2003). Inflow and Fatigue Response of the NWTC Advanced 

Research Turbine. Collection of the 2003 ASME Wind Energy Symposium Technical Papers at the 41st AIAA 

Aerospace Sciences Meeting and Exhibit, 6-9 January 2003, Reno, Nevada. New York: American Institute of 

Aeronautics and Astronautics, Inc. (AIAA) and American Society of Mechanical Engineers (ASME); pp. 214-224; 

NREL Report No. CP-500-35270. 
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Analysis and Comparison of Test Results from the Small Wind 

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14. ABSTRACT (Maximum 200 Words)

Most small wind turbines furl (yaw or tilt out of the wind) as a means of limiting power and rotor speeds in high winds. 

The Small Wind Research Turbine (SWRT) testing project was initiated in 2003 with the goal of better characterizing 

both small wind turbine loads (including thrust) and dynamic behavior, specifically as they relate to furling. The main 

purpose of the testing was to produce high-quality data sets for model development and validation and to help the 

wind industry further their understanding of small wind turbine behavior. Testing was conducted on a modified Bergey 

Excel 10-kW wind turbine. A special shaft sensor was designed to measure shaft loads including thrust, torque, and 

shaft bending. Analysis of 10-minute mean data showed a strong correlation between furling and center of thrust 

location, as calculated from the shaft-bending and thrust measurements. Data were collected for three different 

turbine configurations that included a change in the lateral furling offset and the blades. An analysis of inflow 

conditions indicated that organized atmospheric turbulence had some impact on furling. 

15. SUBJECT TERMS

wind energy; wind turbine; small wind research turbine project; SWRT; Bergey Excel 

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