National Renewable Energy Laboratory

Innovation for Our Energy Future 

A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 

Controls Advanced Research 

Turbine: Lessons Learned 

during Advanced Controls 

Testing 

K. Johnson, L.J. Fingersh, and A. Wright 

Technical Report 

NREL/TP-500-38130 

June 2005 
Controls Advanced Research 

Turbine: Lessons Learned 

during Advanced Controls 

Testing 

K. Johnson, L.J. Fingersh, and A. Wright 

Prepared under Task No. WER5.3112 

Technical Report 

NREL/TP-500-38130 

June 2005 

National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393

303-275-3000 • www.nrel.gov

Operated for the U.S. Department of Energy

Office of Energy Efficiency and Renewable Energy

by Midwest Research Institute • Battelle 

Contract No. DE-AC36-99-GO10337
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iii

Contents 

Introduction........................................................................................................................................1 

Turbine and Controller Set-Up ..........................................................................................................1 

C-Code Details...................................................................................................................................5 

Turbinesafety .....................................................................................................................................6 

Solved and Unsolved Problems .........................................................................................................9 

Conclusions........................................................................................................................................13 

References..........................................................................................................................................13 

Figures 

Figure 1. CART commanded torque vs. speed relationship ..............................................................2 

Figure 2. CART’s “Optimize Pitch as Low Tip-Speed Ratios” routine............................................3 

Figure 3. CART’s simulated operation under PI, PID, and PI/ID control with (a) step 

changes in wind speed, and (b) turbulent wind data..........................................................................4 

Figure 4. (a) High speed shaft RPM, (b) Blade Pitch Angle, (c) Tower Bending Moment (Nm), 

and (d) X Accelerometer Output for normal and emergency stops ..................................................7 

Figure 5. (a) Actual commanded and measured pitch rate, and (b) filtered commanded 

and measured pitch rate .....................................................................................................................8 

Figure 6. CART’s commanded pitch rate and blade current before and after changing 

the pitch gearbox oil...........................................................................................................................9 

Figure 7. CART power data...............................................................................................................10 

Figure 8. CART blade crack ..............................................................................................................11 

Figure 9. CART as a wind vane.........................................................................................................12 

Tables 

Table 1. CART Faults: Normal and Emergency Stops....................................................................7 
1

Introduction 

The Controls Advanced Research Turbine (CART) has been installed at the National 

Wind Technology Center (NWTC) for several years now (Fingersh and Johnson 2002). During 

that time, we have encountered numerous problems while implementing several advanced 

control algorithms. We hope that by sharing some of these lessons we can assist others with 

implementation and testing of their own experimental controllers. 

The CART is a 600-KW, 2-bladed, upwind, horizontal-axis wind turbine. It is 36.6 m tall 

at the axis of rotation and has a 43.3-m rotor diameter with full span blade pitch capability. 

Originally installed at Kahuku Point on the island of Oahu, Hawaii, it was moved in 1996 to the 

National Renewable Energy Laboratory’s (NREL’s) National Wind Technology Center in 

Golden, Colorado. Since then, we have used two baseline controllers and four types of advanced 

controllers (Hand et al 2004) for our experiments. Advanced control experiments included the 

use of generator torque to assist rotor speed tracking (Fingersh and Johnson 2004), the use of 

adaptive control to increase energy capture (Johnson 2004, Johnson et al 2004a, Johnson et al 

2004b, Johnson et al 2005), and the use of state-space controls in several different configurations 

to reduce loads. The state-space controls included Disturbance Accommodating Control (DAC) 

and Disturbance Tracking Control (DTC) with variations of constant or periodic gain pitch 

control and collective or individual pitch control (Stol and Fingersh 2004, Street et al 2004, 

Wright and Balas 2004, Wright et al 2005). 

In this paper, we describe the turbine and controller set-up and some of the challenges we 

encountered with it. We also explain some of the peculiarities of the C-code we use to control 

the CART and discuss our fault protection routine, Turbinesafety, and some of its failures. 

Finally, we relate some of the general problems we have encountered during our three years of 

testing. 

Turbine and Controller Set-Up 

We can operate the CART in either constant-speed or variable-speed mode. As a 

research turbine, it is outfitted with many more sensors than would normally be installed on a 

wind farm turbine, including pressure transducers, torque transducers, strain gauges, 

thermometers, position encoders, accelerometers, anemometers, wind vanes, and power, current, 

and voltage meters. The output of each of these sensors is recorded at the control rate of 100 Hz. 

In addition, the CART has two sensors installed inside the nacelle that we use to diagnose 

problems in real time. The first is a microphone, and the second is a remotely controlled video 

camera that is supplemented by a ball-and-string “accelerometer” hanging inside the nacelle. 

The ball and string accelerometer allows us to detect when a new controller excites a towerbending mode and to shut down the controller immediately rather than waiting to analyze a data 

set once the turbine has stopped. 

Standard Control. The CART’s “standard” control technique (Johnson 2004, Johnson et 

al 2004) was used in baseline variable-speed testing. This standard control is based on 

Proportional-Integral-Derivative (PIDpitch control in region 3 and the usual torque-speed curve 

in region 2. Operational regions are defined more clearly in our references, but, briefly, region 1 

consists of the turbine start-up routine, region 2 comprises the time during which it is desirable 

that the turbine capture as much power as possible from the wind, and region 3 is encountered 

when the wind speeds are high enough that the turbine must limit the fraction of the wind power 

captured so that safe electrical and mechanical loads are not exceeded. Region 2.5 is a short 
2

connecting zone between region 2 and region 3 that we added to prevent a discontinuous torque 

control curve. Region 2.5 has a slope that represents an induction generator with a 5% slip and 

connects the standard torque-speed curve to the rated torque, ending at 99% of rated speed. Our 

expected speed regulation error is 1%, so ending region 2.5 at 99% of rated speed reduces the 

switching between controllers that would occur if region 2.5 ended at rated speed. 

The standard torque-speed curve is given by 

2 τ c = Kω (1) 

3

*

3 max

2

1

λ ρ

Cp K = AR . (2) 

However, the CART’s region 2 and region 3 controllers are actually more complex than the 

standard control. We modified the standard torque control to avoid exciting the first towerbending mode and to link regions 2 and 3 at the rated speed and power. In addition, we modified 

the pitch control system to improve operation both at low tip-speed ratios and in the region 2 – 3 

transition. 

CART Torque Control. Figure 1 shows the CART’s torque command vs. speed 

relationship compared to the standard torque control (1). The commanded torque follows the 

bottom half of the hysteresis loop (A) at 1062–1162 RPM when the rotor is accelerating and the 

top half when it is decelerating. These modifications to the standard control reduce the 

excitation of the first tower-bending mode by reducing the time spent operating near the mode. 

In addition, the line segment (B) connecting the standard control curve (1) to the constant torque 

allows the CART to operate at its optimal tip-speed ratio in region 2 and to reach its rated power 

at its rated speed. Operation on line segment (B) corresponds to region 2.5. 

CART Pitch Control. Figure 2 shows the relationship between commanded blade pitch 

and filtered tip-speed ratio in region 2 operation. When the filtered tip-speed ratio falls below 

6.0, we command the blade pitch to a value higher than the normal region 2 pitch value (-1°). 

0 300 600 900 1200 1500 1800

0

500

1000

1500

2000

2500

3000

3500

CART Torque Command vs. Generator Speed Relationship

Generator Speed (RPM)

Commanded Generator Torque (Nm)

Standard Control (τc = kω2)

Modified CART Control

A 

B 

accelerating 

decelerating 

Figure 1. CART commanded torque vs. speed relationship. The 

CART uses a modified version of the standard control curve. 

Note the tower resonance avoidance technique centered at 1112 

RPM and the linear curve connecting regions 2 and 3 at just 

below rated speed (1800 RPM). 
3

The filter is a single pole, low pass filter. Not only does this technique improve the operation of 

the turbine by reducing the amount of time spent at sub-optimal tip-speed ratios, but it can also 

be essential to the start-up of the machine. During another test, we removed the optimize pitch 

routine and discovered that the turbine would no longer start. In lower wind speed regimes, the 

blades pitch from feather to run so quickly that there is no time for the aerodynamic torque to 

accelerate the rotor from the stopped position. When the blades are pitched to run and the rotor 

speed is close to zero, there is insufficient aerodynamic torque to overcome the friction and 

damping in the system. 

A major difference between the CART’s pitch control and the PID frequently used in 

region 3 is the fact that the CART uses a proportional, integral/integrated derivative (PI/ID) 

control. If the controller were continuous, this PI/ID control would be equivalent to a PI 

controller. However, for a discrete system, this is not the case. Although we developed the 

PI/ID control by accident (via a coding error), we have come to appreciate its benefits, 

particularly the lack of rotor speed overshoot we observe when the turbine enters region 3. 

Figure 3 shows the results of six simulations performed for two different wind inputs 

using discrete PI, PID, and PI/ID control on a model of the CART. The equations used in the 

PI/ID simulations are as follows: 

( ) 1

1

k = T k − k− q ψ ψ , (3) 

( ) 4 4

1 1 T Tk kk r e q eq − − =− + − , (4) 

~ *

k k k r = r − r , (5) 

[ ] ( ) 1 1

~ ~ ~ max 1, ∆ k = − ∆ k− + i k + d k − k− β β k T r k r r , (6) 

and [ ] k k p k k r

~ β = max −1,∆β + , (7) 

0 1 2 3 4 5 6 7

0

10

20

30

40

50

Filtered Tip-Speed Ratio

Blade Pitch Angle (deg)

Figure 2. CART's “Optimize Pitch at Low Tip-Speed Ratios” 

routine. This plot shows the relationship between pitch and 

filtered tip-speed ratio used in region 2 operation when the 

filtered tip-speed ratio drops significantly below its optimal 

value. 
4

where q is the unfiltered discrete rpm calculation, T is the time period (0.01 s), ψ is the rotor 

azimuth position, r is the filtered rotor rpm, r

*

 is the desired rpm, r

~ is the error between actual 

and desired rpm, ∆β is the incremental pitch from one time period to the next, β is the pitch 

angle, the subscript k denotes the discrete time step, and kp, ki, and kd are the proportional, 

integral, and derivative gains, respectively. Both (6) and (7) select the largest of the two values, 

0 5 10 15 20 25 30

10

15

20

Wind Speed

(m/s) 

0 5 10 15 20 25 30

1700

1800

1900

Generator

Speed (RPM)

0 5 10 15 20 25 30

0

5

10

15

Blade PitchAngle (deg)

Time (sec)

PI

PID

PI/ID

 (a) 

0 10 20 30 40 50 60

10

12

14

16

Wind Speed

(m/s) 

0 10 20 30 40 50 60

1700

1800

1900

Generator

Speed (rpm)

0 10 20 30 40 50 60

0

5

10

Blade PitchAngle (deg)

Time (sec)

PI

PID

PIID

 (b) 

Figure 3. CART’s simulated operation under PI, PID, and PI/ID control 

with (a) step changes in wind speed, and (b) turbulent wind data. 

Note that the PI and PID controllers are not optimized but rather use 

the same gains that optimized the PI/ID control in the field. 
5

which allows the controller to run throughout regions 2, 2.5 and 3, saturating to a value of –1° 

when not in region 3. 

The equations for the PID simulation are similar in that (3) – (5) remain the same while 

(6) and (7) are modified to: 

∆ = −∆ + β β k k ik max 1, [ −1 kTr% ] (8) 

and 

[ ( )] 1

~ ~ ~ max 1, k = − ∆ k + p k + d k − k− β β k r k r r . (9) 

Finally, PI uses (3) – (5), (8), and 

β β k k p dk max 1, (k kr) = −∆ + +     % . (10) 

Clearly, in these simulations the PI case is not simply the PID case with the derivative term, kd, 

set equal to zero. Because we were trying to compare both the PI and PID case to the PI/ID case 

rather than to each other, it was important that we keep the proportional gain in the PI controller 

equal to the sum of the proportional and integrated derivative gains in the PI/ID control. 

In Figure 3(a), we use a stepwise constant wind speed input, while in Figure 3(b) the 

wind speed input is taken from measured data. For each simulation, the turbine is initially in 

region 2 (pitch angle = -1°), accelerating towards rated speed (1800 rpm). In both (a) and (b), 

the PI/ID controller is able to anticipate reaching rated speed, causing the blades to start pitching 

about a second earlier than the PI and PID controllers upon entry into region 3. This earlier 

pitching upon entering region 3 results in no overshoot of the rated speed for the stepwise 

constant wind input, and less overshoot than the PI and PID controllers for the turbulent wind 

input. Once the region 2 – 3 transition transients are no longer significant, the PI/ID controller is 

equivalent to the PI controller. 

Rotor Radius. After running all of the baseline tests on the turbine, we measured the 

rotor radius and discovered that the measurement shown in the manufacturer’s drawings, 21.0 m, 

was off nearly 3% compared to our measurement of the radius, 21.64 m. Because the radius is 

raised to the fifth power in the standard torque control equation (2), this small error led to a 

significant error (14%) in the torque control gain used in our baseline variable-speed controller. 

We considered this error and the fact that it may have led to sub-optimal operation when making 

future energy capture comparisons between the baseline controller and our advanced controllers. 

C-Code Details 

Because the CART is a research turbine, we use a versatile PC, which we call 

“Dataprimary,” as our controller. We run Dataprimary in DOS, which gives us more stability 

than Windows, but we still employ hardware to take over and shut down the turbine in case of a 

computer failure. We perform most of the simulations involved in developing our advanced 

control techniques in Matlab’s Simulink, then transfer the code by hand into C and compile it 

onto Dataprimary. Problems we encountered during this code transfer, which we found to be 

more complex than it sounds, included: 

• code length problems, 

• stack length problems, 

• making sure arrays and strings have sufficient length, 

and others that are undoubtedly familiar to experienced programmers but not necessarily to wind 

turbine engineers. 
6

Integrated Simulator. To detect these and other errors that might not be caught by the 

compiler, we created a simulation tool within the turbine control program. This simulation tool 

contains a Cp-TSR-Pitch look-up table and allows us to observe the rotor speed as we vary the 

wind speed’s mean and standard deviation along with the mean and standard deviation of the 

yaw angle. In addition to checking for reasonableness in the rotor speed and blade pitch angle, 

we can check for reasonableness in other sensed and controlled values, such as power, blade 

pitch, and yaw angle. When we observe unexpected outputs while running the simulation, we 

can check to ensure that we transferred the code correctly while looking for errors such as those 

listed above. 

Turbinesafety 

Our fault protection routine, Turbinesafety, provides three different levels of faults. The 

first is a warning, which does not stop the turbine but looks for possible non-critical sensor 

errors. Any detected problems are written to the data file along with the sensor outputs and 

control inputs. For example, sensor errors that trigger a warning include out of range teeter 

position, vastly different strain gauge readings over long periods from blade 1 to blade 2, and 

errors between the high and low speed shaft rpm calculations. 

The second fault level is a normal stop. These faults necessitate a stop in the turbine, 

where the stop is performed using PI/ID pitch control with a gradually decreasing rotor speed as 

the reference input. Once the rotor has slowed sufficiently, the blades are pitched at 5°/s until 

they reach the feathered position. In general, normal stops are performed for serious faults that 

do not involve the pitch system but have the potential to damage the turbine if left uncorrected . 

Because the rotor brakes are not used in a normal stop, a normal stop might not succeed in 

stopping the turbine when there are problems with the pitch system. 

The third fault level is an emergency stop. Emergency stops are performed for critical 

faults that could damage the turbine within seconds and those that involve the pitch system. In 

an emergency stop, we command the blades to pitch to feather as fast as possible, disable the 

power electronics, and set the emergency rotor brake, teeter brake, and yaw brake. While normal 

stops may take 30-60 seconds to stop the turbine while it operates at rated speed in region 3 

winds, an emergency stop can stop the turbine in as little as 5 seconds. However, because 

emergency stops put so much stress on the machine, we regard them as last resorts. Table 1 lists 

the normal and emergency stops for which we test in the CART’s software. 

Normal and Emergency Stops. Figure 4 shows time-series plots for a normal stop and an 

emergency stop. Both have been plotted such that the stop occurs at time zero. We also 

removed the means from the accelerometer readings. 

In Figure 4, the normal stop resulted from a teeter brake pressure problem and the 

emergency stop resulted from a blade pitch following error. In each case, the turbine was 

operating at just above rated speed (1800 RPM) when the fault occurred, as shown in subplot (a). 

During the normal stop, the pitch rate stayed low as the blades pitched towards feather in a 

controlled manner as shown in subplot (b). By contrast, during the emergency stop the blades 

pitched towards feather at the maximum pitch rate of 18°/s, reaching a fully feathered position in 

about 5 seconds. The high-speed shaft RPM decreased correspondingly fast for the emergency 

stop. In terms of the loads observed by the turbine structure, both the tower bending and x 

acceleration plots show significant responses to the emergency stop. Neither of these channels 

showed similar jumps in magnitude at the time of the normal stop. However, it is apparent that 

the tower bending and x acceleration grew as the pitch reached about 25° in the normal stop, 
7

though the magnitudes are less than for the emergency stop case. These vibrations are expected 

for a shutdown in high winds. 

Table 1. CART Faults: Normal and Emergency Stops 

Normal Stops Emergency Stops 

Power electronics digital outputs sensor failure RPM sensor or gearbox failure 

Gearbox over temperature X, Y, or Z acceleration extremely high 

Generator over temperature Power electronics power too high 

HSS or LSS torque sensor failure Generator current too high 

Rotor brake sensor failure Generator voltage too high 

Generator frequency sensor failure Grid power outage 

Gearbox oil pressure too low Blade 1 pitch sensor failure 

X, Y, or Z acceleration high Blade 2 pitch sensor failure 

Yaw brake set unintentionally Blade 1 & 2 pitch significantly different 

(collective pitch mode only) 

Teeter brake set unintentionally Overspeed 

Extreme yaw error Blade 1 or 2 not obeying the pitch rate 

command 

Adaptive gain M beyond reasonable limits Blade 1 or 2 drive not ready 

Power electronics drive not ready 

0 20 40

0

50

100

Blade Pitch (deg)

0 20 40

0

500

1000

1500

2000

HSS RPM

0 20 40

-3000

-2000

-1000

0

1000

2000

Tower Bending (Nm)

Time (seconds)

0 20 40

-4

-2

0

2

4

X Acceleration (m/s2

)

Time (seconds) Normal

Emergency

(a) (b) 

(c) (d) 

Figure 4. (a) High Speed Shaft RPM, (b) Blade Pitch Angle, (c) Tower Bending Moment (Nm), and 

(d) X Accelerometer Output for normal and emergency stops. The emergency stop is harder on 

the turbine. 
8

Development of a Pitch Rate Error Fault. Turbinesafety has been a work in progress 

since the early days of the CART commissioning and baseline data collection. While some 

faults, like overspeed and high accelerometer readings, are easy to detect, others, such as pitch 

problems, are more complex. In Table 1, five of the faults listed relate to the pitch system. The 

fourth fault, “Blade 1 or 2 not obeying the pitch rate command,” has required many revisions and 

may require more in the future. As a result of actuator dynamics, saturation, and encoder 

quantization errors, we found it difficult to detect real errors in the pitch rate without triggering 

nuisance faults in various operational regimes 

Figure 5 contains two plots showing pitch rate and filtered pitch rate for 3 seconds of 

CART data. In Figure 5(a), the actual commanded pitch rate and measured rate are shown to 

differ, and the actuator lag is clear. In addition, the quantization error in the position encoder is 

apparent in the measured rate, which is calculated from this sensor. In Figure 5(b), the pitch rate 

command has been filtered twice and the measured rate once. In the moderate pitch rate section 

of the plot, the two curves nearly coincide. When the commanded pitch rate is near its 18°/s 

limit, however, the actual (measured) rate is unable to keep up. 

The two curves in Figure 5(b) are the two primary signals used in our pitch rate following 

fault. The error tolerance is based on the commanded rate, so that a larger error is allowed when 

the rate command is higher. In addition, if the pitch drive current is at its limit, the filtered rate 

error is not required to lie within the error bound as long as the pitch acceleration has the correct 

sign. Analysis of many hours of operational data have shown that our technique will detect a 

fault within a couple of seconds, or much faster for most types of faults, but it rarely results in 

nuisance faults when the pitch system is behaving properly. 

Detection of Actual Pitch Following Fault. Shortly after we implemented the current 

version of the pitch rate following fault, the fault started to occur regularly on start-up and we 

immediately assumed that a poorly written fault routine was causing nuisance faults. Further 

data analysis revealed odd behavior in the pitch system: even when the commanded pitch rate 

was well within the capability of the CART’s pitch actuators, the actuators would draw the full 

current allowable, while still not following the commanded rate closely. The amount of current 

drawn decreased as the pitch system was used for longer time periods, which led us to believe 

111 112 113 114 -20

-10

0

10

20

Time (seconds)

Pitch Rate (deg/s)

(a) 

Commanded Rate

Measured Rate

111 112 113 114

-20

-10

0

10

20

Time (seconds)

Filtered Pitch Rate (deg/s)

(b) 

Commanded Rate

Measured Rate

Figure 5 (a) Actual commanded and measured pitch rate, and (b) filtered commanded and 

measured pitch rate. The maximum pitch rate is 18°/s. The measured rate in (a) clearly lags 

behind the commanded due to actuator lag, even when the rates are low (from 112 – 114 seconds). 

In (b), the actuator lag is included as a second pole in the filtered commanded rate, causing the 

two curves to be very close when commanded pitch rates are modest. 
9

that the cause of the high current was temperature-related. After examining the system, we 

discovered that the oil viscosity in the pitch gearbox was significantly higher than recommended 

by the gearbox manufacturer (molasses vs. WD-40). In fact, we had been using the wrong oil 

since the turbine was installed but had never noticed because our fault detection software was not 

sophisticated enough during the first few years of operation. Figure 6 shows plots of the 

commanded pitch rate, which has an 18°/s limit on the CART, and pitch drive current before and 

after changing the gearbox oil. Both cases occurred near turbine start-up when the gearbox oil 

temperature would have been close to ambient. Clearly, changing the oil allowed for less current 

to be drawn, even with slightly higher commanded pitch rates. 

Other Solutions. Even though we have managed to implement a safety measure for the 

pitch rate error fault, we speculate that it might be better in some situations to limit the control to 

a signal that is attainable by the CART’s hardware. For example, though we have a limit on the 

controlled pitch rate, we lack one on the controlled acceleration. Thus, we can and do demand 

accelerations of 1800°/s/s (from 0°/s to 18°/s in 0.01 s) from the CART’s pitch drives. Since we 

know this acceleration is impossible for the CART pitch actuators, we wonder whether we 

should limit it to more reasonable values. In other words, should the calculation of high pitch 

rate errors caused by impossible commands be eliminated via more sophisticated Turbinesafety 

algorithms or in the turbine’s controller by commanding only attainable rates and accelerations? 

Solved and Unsolved Problems 

During the course of testing on the CART, we have experienced many sensor failures. 

While some failures were easy to fix, we could not identify the cause or find solutions for others. 

Two unsolved sensor failures relate to a speed sensor on the high-speed shaft (“HSS Prox”) and a 

power sensor on the generator (“Generator Power”). The HSS Prox sensor worked as expected 

during the CART’s initial constant-speed tests, but gave a very noisy signal during the initial 

0 0.2 0.4 0.6 0.8 1

-5

0

5

10

15

Commanded Pitch

Rate (deg/s)

0 0.2 0.4 0.6 0.8 1

0

20

40

60

Blade 1 Drive

Current (A)

Time (sec)

Before

After

Figure 6. CART’s commanded pitch rate and blade current 

before and after changing the pitch gearbox oil. We discovered 

that the oil we had been using was much too viscous, causing 

the pitch drive motors to draw high currents until the gearbox 

warmed up. 
10

variable-speed testing. Because the power electronics were energized in variable-speed mode 

but not in constant-speed mode, and the erroneous HSS Prox readings corresponded exactly to 

the variable-speed operation, we concluded that the noise resulted from the power electronics. 

However, we were unable to shield the signal or find another means to eliminate the noise 

problem, so instead we stopped reading the sensor. The high-speed shaft speed was already 

being calculated from the high-speed shaft position encoder, so the HSS Prox sensor was really 

unnecessary. 

Generator Power Sensor Failure. The cause of the generator power sensor failure is 

likely related to the power electronics as well, because the failure corresponded to the transition 

from constant-speed to variable-speed testing. We know the power sensor measurements are 

erroneous because they show lower generator power levels than those measured at the power 

electronics further down the line. The power electronics power measurements are consistent 

with the high- and low-speed shaft power measurements, given the expected losses. Figure 7 

shows the four time-series power plots, with the power electronics power being nearly 50% 

greater than the generator power. Since it is impossible to create power between the generator 

and power electronics, the generator power sensor is clearly wrong. 

Because both the HSS Prox sensor and Generator Power sensor are redundant, we spent 

less time trying to fix the problems than we would have if there were no other sensors 

performing the same or similar measurements. However, we caution that the data from these 

two sensors should be ignored in those data files in which it is present. 

Blade Crack. Another problem we encountered with the CART was a crack in one of the 

blades near the root. Figure 8 shows the 59 cm crack, which we noticed during a routine 

inspection. While we do not know what caused the crack (i.e., a sudden event or wear and tear 

over time), we determined that the crack was only deep enough to damage the blade’s external 

coating. After researching our options for repairing the damage, we decided that, as the crack 

did not pose a structural risk to the blade, it could be repaired it by filling and covering it. We 

20 30 40 50 60 70 80

0

100

200

300

400

500

600

700

800

Time (seconds)

Power (kW)

LSS 

HSS 

Power Electronics 

Generator 

Figure 7. CART power data. The generator power curve is much 

lower than possible compared to the LSS, HSS, and power 

electronics power readings. 
11

have run the turbine for more than a year since the repairs were completed and have seen no 

indicators that it has gotten worse. 

Rotor Positioning for Calibration. The CART has a fairly large rotational inertia, which 

makes positioning the rotor for calibrations a challenge. Fortunately, we can use its induction 

generator as a motor, so we designed a PID controller to position the rotor at any desired azimuth 

position. The PID controller takes azimuth error as its input and controls generator torque as its 

output. We limit the generator torque to 10% of its rated value to prevent excessive speeds 

during calibration routines. While this PID controller performs well for a balanced rotor, for 

pitch and blade strain gauge calibrations we must install a jig on one blade, which causes the 

rotor to become unbalanced. In the case of the unbalanced rotor, 10% of rated torque is not 

always sufficient for positioning the blades. In addition, nonlinear effects, such as gear backlash, 

can become more of a problem when the rotor is unbalanced than when it is balanced. 

Fortunately, we do not run the turbine with the jig installed, so the rotor unbalance is only a 

consideration for the rotor positioning controller. 

Extreme Wind Event Failure. On December 20, 2004, we observed a high-wind failure 

event that began when the NWTC lost grid power because of high winds in the early morning 

before working hours. Although the main NWTC buildings have back-up generators, the turbine 

grid does not; thus, the CART’s Turbinesafety routine performed an emergency stop in response 

to the power outage. As desired, the blades pitched to feather and the emergency brake set. By 

chance, the rotor stopped at a near-vertical azimuth position. The mean yaw error was near zero, 

Figure 8. CART blade crack. The total crack length 

is approximately 59 cm. 
12

though not exactly. In all of these respects, the turbine had behaved properly and the situation 

was similar to ones the CART had experienced in the past. 

We arrived on site within about 30 minutes of the grid power failure. Although the 

CART’s data acquisition system does not collect data when the turbine is stopped, the data 

provided by the other anemometers at the NWTC showed mean wind speeds of almost 35 m/s 

and peak gusts of more than 50 m/s at a 10 m height. The peak speed at 80 m was similar to that 

at 10 m. Noting the CART’s locked and shut-down state, we left the turbine as it was and waited 

for the wind speed to decrease. Within an hour, however, we realized that the CART was 

yawing and went to check on the cause. The yaw brake pressure had decreased from its normal 

2000 psi to 600 psi and could not be charged because it needed power from the grid, which was 

still unavailable. In addition, the emergency yaw brake had very low pressure. Because the 

rotor was locked in a near-vertical position with the blades pitched to feather, the CART was 

behaving like an oversized wind vane and was being pushed downwind by the strong winds. 

Figure 9 shows the CART in its approximate initial (dotted) and final (solid) position relative to 

the wind direction. 

The CART’s pitch system is not designed to endure large forces directed at the blade 

trailing edges. However, because we did not have the power required to reset the yaw brake or 

yaw the machine back upwind, our options were limited. One possibility was to release the rotor 

brake, let the rotor spin, and try to reset it when the azimuth position was near horizontal. This 

would have reduced the wind-vane effects compared to the vertically-positioned rotor, but the 

nacelle had already yawed halfway downwind and the side loading of the nacelle itself may have 

been enough to push it the rest of the way. In this case, the blades would still have been loaded 

from the trailing edges. Because we did not yet understand why we had lost pressure in the yaw 

brake, we were hesitant to release the rotor brake for fear that we would be unable to reset it. 

Thus, we again decided to wait. 

When the wind calmed down, we found the CART was undamaged, and we discovered 

two failures in our yaw brake system. The first was our failure to connect the yaw brake to the 

uninterruptible power supply (UPS) that provides energy to most of the CART’s critical 

components in emergency situations. The second was our failure to understand that the 

Figure 9. CART as a wind vane (top view). A small initial yaw error, locked rotor, near-vertical 

azimuth position, blades pitched to feather, and yaw brake failure resulted in the nacelle being 

pushed by strong winds to point downwind. 
13

emergency yaw brake pressure system required manual recharging. We believed it recharged 

itself automatically, and therefore, the system had not been recharged in years. In the end, we 

corrected these failures and felt fortunate that these lessons did not come at a much higher cost. 

Conclusions 

In the process of installing, calibrating, and running various control schemes on the 

CART, we encountered numerous problems and solved many of them. In this report, our intent 

was to share these problems, both solved and unsolved, with other researchers in the wind 

industry. We hope that our remarks will help new experimentalists set up their own testbeds 

more efficiently and avoid some of the challenges we have faced. 

References 

Fingersh, L. and Johnson, K., 2002, Controls Advanced Research Turbine (CART) 

Commissioning and Baseline Data Collection. NREL Report No. TP-500-32879. 

Fingersh, L. and Johnson, K., 2004, “Baseline Results and Future Plans for the NREL Controls 

Advanced Research Turbine,” Proceedings of the 23rd ASME Wind Energy Symposium, 

Reno, NV, pp. 87-93. 

Hand, M., Fingersh, L., Johnson, K., and Wright, A., 2004, "Advanced Control Design and Field 

Testing for Wind Turbines at the National Renewable Energy Laboratory,” Proceedings 

of the World Renewable Energy Congress VIII, Denver, CO. 

Johnson, K., 2004, Adaptive Torque Control of Variable Speed Wind Turbines, Ph.D. Thesis, 

University of Colorado, Boulder, CO. 

Johnson, K., Fingersh, L., Balas, M., and Pao, L., 2004(a), “Methods for Increasing Region 2 

Power Capture on a Variable Speed Wind Turbine,” Journal of Solar Energy 

Engineering, Vol. 126, No. 4, pp. 1092-1100. 

Johnson, K., Pao, L., Balas, M., Kulkarni, V., and Fingersh, L., 2004(b), “Stability Analysis of 

an Adaptive Torque Controller for Variable Speed Wind Turbines,” Proceedings of the 

Conference on Decision and Control. 

Johnson, K., Fingersh, L., Pao, L., and Balas, M., 2005, “Adaptive Torque Control of Variable 

Speed Wind Turbines for Increased Region 2 Energy Capture,” Proceedings of the 24th

ASME Wind Energy Symposium, pp. 66-76. 

Stol, K. A.; Fingersh, L. J. (2004). “Wind Turbine Field Testing of State-Space Control Designs: 

August 25, 2003--November 30, 2003.” NREL Report No. SR-500-35061. 

Street, B. M.; Balas, M.; Stol, K. (2004). “Periodic and Non-Periodic Disturbance 

Accommodating Control of the Controls Advanced Research Turbine (CART).” 

Proceedings of the 23rd ASME Wind Energy Symposium; pp. 124-132. 

Wright, A. D.; Balas, M. J. (2004). “Design of Controls to Attenuate Loads in the Controls 

Advanced Research Turbine. Journal of Solar Energy Engineering, Vol. 126, No. 4; pp. 

1083-1091. 

Wright, A. D.; Fingersh, L. J.; Stol, K. A. (2005). “Progress in Implementing and Testing StateSpace Controls for the Controls Advanced Research Turbine,” Proceedings of the 24th

ASME Wind Energy Symposium, pp. 88-100. 
F1147-E(12/2004) 

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Controls Advanced Research Turbine: Lessons Learned during 

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This paper describes some of the problems encountered while conducting tests on the Controls Advanced Research 

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