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Contract No. DE-AC36-08GO28308

Experimental Characterization 

of a Grid-Loss Event on a 2.5-

MW Dynamometer Using 

Advanced Operational Modal 

Analysis

Preprint

J. Helsen and W. Weijtjens

OWI-Lab

Y. Guo and J. Keller

National Renewable Energy Laboratory

B. McNiff

McNiff Light Industry

C. Devriendt and P. Guillaume

Vrije Universiteit Brussel

To be presented at the Conference for Wind Power Drives

Aachen, Germany

March 3‒4, 2015

Conference Paper

NREL/CP-5000-63501

February 2015
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Cover Photos: (left to right) photo by Pat Corkery, NREL 16416, photo from SunEdison, NREL 17423, photo by Pat Corkery, NREL 

16560, photo by Dennis Schroeder, NREL 17613, photo by Dean Armstrong, NREL 17436, photo by Pat Corkery, NREL 17721.

NREL prints on paper that contains recycled content.
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This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Contents

1 Abstract................................................................................................................2

2 Introduction .........................................................................................................2

3 Approach..............................................................................................................3

4 Test article ...........................................................................................................3

5 Dynamic event description.................................................................................4

6 Experimental OMA identification of drivetrain resonance...............................4

7 HSS tooth strains ................................................................................................7

8 Gearbox high speed shaft (HSS) bending.........................................................8

9 Conclusions.........................................................................................................8

10 Future work..........................................................................................................9

11 Bibliography ........................................................................................................9
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1 Abstract

This paper experimentally investigates a worst case grid-loss event conducted on the 

National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative 

(GRC) drivetrain mounted on NREL’s 2.5-MW dynamometer test stand that is connected to a controllable grid interface. The GRC drivetrain has a directly grid-coupled, fixedspeed asynchronous generator. The main goal of the study was to assess the dynamic 

content of the high-speed stage of the GRC gearbox. In addition to external accelerometers, high frequency sampled measurements of strain gauges were used to assess 

torque fluctuations and bending moments both at the nacelle main shaft and gearbox 

high-speed shaft (HSS) through the entire duration of the event. Modal analysis was 

conducted using a polyreference Least Squares Complex Frequency-domain (pLSCF) 

modal identification estimator. The event driving the torsional resonance was identified. 

Moreover, the pLSCF estimator identified main drivetrain resonances based on a combination of acceleration and strain measurements. Without external action during the 

grid-loss event, a mode shape characterized by counter phase rotation of the rotor and 

generator rotor determined by the drivetrain flexibility and rotor inertias was the main 

driver of the event. This behavior resulted in significant torque oscillations with large 

amplitude negative torque periods. Based on tooth strain measurements of the HSS 

pinion, this work showed that at each zero-crossing, the teeth lost contact and came 

into contact with the backside flank. In addition, dynamic nontorque loads between the 

gearbox and generator at the HSS played an important role, as indicated by strain 

gauge-measurements. 

2 Introduction

The wind turbine industry aims to continuously improve turbine designs to reduce 

overall cost. At the same time, turbine reliability needs to be guarded to secure 

predictable operating expenses over the designated product lifecycle of 20 years. 

Loads play an important role in the design of a wind turbine. Field measurements and 

dynamometer testing can be used to validate simulation models for dynamic load 

prediction [Hui 06]. However, simulation models as well as dynamometer test validation 

campaigns require definition of appropriate test cases derived from relevant operational 

tests. For initial model validity analysis, researchers may use quasi-static operating 

conditions. However, dynamic events such as start-ups, shutdowns, and emergency 

events can significantly reduce the overall drivetrain life and should be investigated. 

The main design load cases, including the dynamic ones, are defined in IEC 61400-1

[IEC 05] and linked to the control system. The control strategy used during a grid-loss 

event and the approach used for emergency braking has significant influence on the 

system response. The definition of the control strategy also has significant influence on 

the overall turbine behavior. One of the drivers in this event was the main torsional 

drivetrain resonance.
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3 Approach

This paper identifies this driving resonance frequency on the NREL 2.5-MW 

dynamometer for the Gearbox Realiability Collaborative (GRC) drivetrain [Lin 11]. This 

particular resonance is important for the overall response during several dynamic 

events. To identify the resonance, a severe grid-loss event was simulated. The 

emergency stop of the dynamometer was activated to disconnect the generator from 

the grid after which the dynamometer and drivetrain coast to a stop. In contrast to a

grid-loss event on a field turbine, the speed reduction in the dynamometer was realized 

slowly in order to be able to clearly identify the resonance. During the event, the 

drivetrain was interpreted as having a torsional spring between the rotor inertia and 

generator rotor inertia. The mode shape is characterized by the counter-phase rotation 

of the rotor and generator inertia, as shown in Image 1. The torsional energy stored in 

the system was released during the dynamic event causing decompression of the 

drivetrain equivalent spring. The eigenfrequency and corresponding mode shape were

identified by means of a polyreference Least Squares Complex Frequency-domain

(pLSCF) estimator [Gui 03]. Nonphysical falsely identified poles linked to harmonic 

excitations were taken out of the set. Moreover, gear contact behavior during the 

dynamic event was investigated by means of strain gauges at the root of the highspeed shaft (HSS) teeth.

Image 1 Schematic representation of torsional drivetrain resonance

4 Test Article

This work used the GRC drivetrain that was designed for installation in a stallcontrolled, three-bladed, upwind turbine with a rated power of 750 kW. The full nacelle 

is placed on the dynamometer for testing, as is shown in Image 2. The dynamometer 

consists of a driving electric motor combined with a gearbox to introduce mechanical 

power at the nacelle hub. During testing, the GRC drivetrain produces electricity, which 

is fed back into the local grid, as schematically shown in Image 2. The main advantage 

of this closed loop test configuration is that the nacelle controller stays active and the 

turbine produces energy as if it were in the field. The energy is fed into an electric 

micro-grid managed by a control unit that allows the variation of both grid frequency 

and amplitude. A detailed description of the dynamometer and the instrumentation can 

be found in [Lin 13].
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Image 2 Schematic of the NREL 2.5-MW dynamometer test stand [Lin13]

5 Dynamic Event Description

The test case started with normal operating conditions. At 3.2 seconds, the 

dynamometer emergency stop was activated, resulting in a disconnection of the 

electricity grid. Image 3 shows that the HSS speed decreased in a controlled manner 

and a torque reversal was initiated. The torque signal shown in Image 3 originated from 

the low-speed shaft (LSS) torque sensor. The torque values are scaled between 

-100 and 100 for easy comparison. The initial phase of the dynamic event shows a 

transient with torque pulses between the initial value and a negative maximum equal to 

approximately 80% of the initial value. The torque fluctuations continue until full stop, 

but are less pronounced after the initial 20 seconds. A fast Fourier transform (FFT) was 

performed on the torque reversal part of the signal, and it showed excitation in the 

frequency range below 1 Hz containing the first drivetrain eigenfrequency. An advanced 

operational modal analysis (OMA) was used to identify this mode shape and its 

corresponding eigenfrequency and damping value.

6 Experimental OMA Identification of Drivetrain Resonance

Operational modal analysis is used for systems subjected to environmental or 

mechanically introduced vibrations and is based on output only algorithms for system

identification. This paper used the pLSCF approach [Gui 03]. Because the torque signal 

clearly determines the overall behavior of the system, the first drivetrain torsional 

resonance plays an important role. The corresponding mode shape, characterized by 

counter phase rotation of the rotor and generator inertia, is mainly determined by rotor 
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and generator inertia values and drivetrain flexibility. The mode shape is illustrated in 

Image 1. To perform modal identification, an operational modal analysis was performed 

on the decay of three torque signals: the torque signal measuring the dynamometer 

response, the LSS torque signal, and the HSS torque signal.

Image 3 Normalized torque and RPM signal during event

Eigenfrequencies, mode shapes, and damping estimates are generated directly by the 

pLSCF estimator. Image 4 shows the FFTs of the torque signals over a broad 

frequency range up to 60 Hz. A clear broadband excitation is present between 18 and 

30 Hz and between 37 and 60 Hz, which was caused by smearing of the nominal 

harmonic excitations at 30 Hz and 60 Hz. Harmonic excitations are a challenge for the 

modal identification algorithms because modal estimators often misinterpret the 

harmonic excitations, especially when they are smeared, as resonance frequencies. 

Image 5 shows the pLSCF estimator stabilization diagram for a frequency band up to 5

Hz. The y-axis shows the model order of the fitted modal model. Broader frequency 

band analyses up to 60 Hz were performed but showed no modes between 30 Hz and 

60 Hz indicating that in this frequency range, the modes might be masked by the 

harmonics. The influence of model order was also investigated. Three poles were

found. Two poles, respectively at 0.64 Hz and at 2 Hz, were stable for multiple model 

complexity levels in both analyses. The first pole at 0.49 Hz only had stable 

identification for a limited number of model orders. Corresponding damping values are 

shown in Image 6. The main characteristic of the torsional modes was the counter 

phase behavior of the rotor inertia and generator rotor inertia. The identified modes 

showed a phase difference of about π radians, corresponding to the behavior shown in

Image 1. Details on the sensitivity analyses are not discussed in this work for brevity 

reasons, but are detailed in [Hel 14]. Based on [Hel 14], the low number of stable model 

orders for the pole at 0.49 Hz in the stabilization diagrams and the clear overlap with 

the harmonic excitation regions, it is concluded that this pole is not a physical 
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resonance. The same reasoning holds for the pole estimated at 2 Hz. Therefore, it can 

be concluded that the grid-loss event driving torsional mode shape has a corresponding 

eigenfrequency at 0.64 Hz.

Image 4 FFT spectra of dyno, LSS, and HSS torque for frequency range [0-60 Hz]

Image 5 pLSCF Stabilization diagram for frequency range for model order 64 [0-5 Hz]
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Image 6 Estimated damping values for the first three identified poles

7 HSS Tooth Strains

During the torque reversals, contact between the teeth was lost. The mesh went 

through the backlash and contact was reestablished between the coast-sides. In the 

GRC gearbox, strain was measured in the root of four teeth, covering the complete line 

of action for one mesh cycle. Image 7 shows these strains versus time for the first 

torque reversal. Each signal has a different color and all quantities are normalized for 

easy comparison. The first part of the graph shows the behavior during the decreasing 

positive torque period. Subsequently, the system went through the backlash and is subjected to negative torque. The backlash is clearly visible in the strain gauge signals.

Image 7 HSS tooth strain, rpm, and torque evolution during transient event
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Moreover, it can be seen that the strain gauge with dominant amplitude changed from 

the black one at positive torque to the green one at negative torque. Similar behavior is 

seen for the red and blue strain gauge signals. This illustrates the changing loading pattern in which the other tooth flank is contacted during torque reversal.

8 Gearbox HSS Bending

The loading induced during the grid-loss event was not strictly torque related. Image 8

shows the main shaft torque and corresponding total HSS bending. At the grid-loss 

event, the loads on the gearbox were reduced by the significant decrease in torque. 

Similar behavior can be seen in the HSS bending. After the torque increased, bending 

was experienced. When the system went through the backlash again, it was released. 

The subsequent positive torque pulse resulted in a smaller bending. Similar behavior 

was seen for the following reversals. Based on these measurements, it can be concluded that for this particular drivetrain architecture, the HSS loading during grid loss 

was not strictly torque driven and had significant bending loading, particularly during the 

negative torque periods. Further investigation should focus on whether misalignments 

between gearbox and generator are inducing these bending loads or if they originate 

from another source.

Image 8 Torque and overall bending evolution during transient event 

9 Conclusions

This paper examined a grid-loss event conducted on the GRC drivetrain in the 2.5-MW 

NREL dynamometer. Behavior during this event was characterized by torque reversals 

inducing nontorque bending at the HSS and resulting in the HSS gear mesh disengaging, going through the backlash, and engaging the coast-side flanks for each torque 

reversal. Moreover, by means of a pLSCF based operational modal analysis, it was 
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shown that the driving resonance was the first drivetrain mode at 0.64 Hz characterized 

by counter-phase rotation of the rotor and generator inertia.

10 Future Work

These experimental results will be used for further analysis of HSS bearing behavior.

The combination of torque and bending load is expected to load the HSS tapered roller 

bearings in a way that differs from the steady state loading. Particular focus will be on 

slip characterization by means of the strain gauges in the bearing outer rings. Moreover, additional dynamometer testing conducted at different load levels will help in understanding the loads induced by these grid-loss type events. However, to have correct 

loads during the event, extensive field testing should be conducted so that representative event load cases can be applied during dynamometer testing.

11Bibliography

[Hui 06] L. Hui, M. Steurer, K.L. Shi, S. Woodruff, Da Zhang:,

Development of a Unified Design, Test, and Research Platform 

for Wind Energy Systems Based on Hardware-in-the-Loop RealTime Simulation

In: Industrial Electronics, IEEE Transactions on , vol.53(4), 

pp.1144,1151, 2006

[IEC 05] International Electrotechnical Commission (IEC) Standard. Wind 

turbines - part 1: Design requirements, 2005

[Lin 11] H. Link, et al

In: Gearbox Reliability Collaborative Project Report: Findings 

From Phase 1 and Phase 2 Testing, NREL Technical Report: 

NREL/TP-5000-51885, Available online at 

http://www.nrel.gov/docs/fy11osti/51885.pdf , 2011

[Gui 03] P. Guillaume, et al

A poly-reference implementation of the least-squares complex 

frequency-domain estimator

In: Proceedings of IMAC vol. 21, p.183--192, 2003

[Lin 13] H. Link, J. Keller, Y. Guo, B. McNiff: 

Gearbox Reliability Collaborative: Phase 3 gearbox 2 test plan

In: NREL Technical Report NREL/TP-5000-58190, 2013

[Hel 14] J. Helsen, C. Devriendt, W. Weijtjens, P. Guillaume

Experimental Dynamic Identification Of Modeshape Driving Wind 

Turbine Grid Loss Event On Nacelle Testrig

In: Submitted to Renewable Energy, 2014