What we can do to Improve the Reliability of Offshore Wind ...

What we can do to Improve the Reliability of Offshore Wind Farms

Peter TavnerEmeritus Professor, Durham University, UK Past President, European Academy of Wind Energy

“I have only one eye; I have a right to be blind sometimes... I really do not see the signal!” Vice-Admiral Horatio Lord Nelson at the battle of Copenhagen

NTNU, EU FR7 MARE WINT ProjectSeptember 2013 1

Keynotes

• Aim to reduce risk, raise turbine Reliability and Availability, Reduce offshore wind Cost of Energy;

• Wind Turbine Reliability from onshore experience;• What we know about WT reliability;• Wind Turbine Availability, what is happening

Offshore?


Bathtub Curve

Useful Life ( = 1)

Time, t

Failure intensity

Early Life( < 1)

Wear-out Period( > 1)

Select more reliable componentsPreventive maintenance

Reliability centred maintenanceCondition based maintenance

Major sub-assemblychangeout

More rigorous

pretesting


Detection, Diagnosis, Prognosis


SCADA & Condition Monitoring in Context

SCADA, < 0.001 HzContinuous signals & alarms

Structural HealthMonitoring,

SHM,< 5 Hz

Not continuous

ConditionMonitoring,

CM,< 35 Hz

Continuous

Diagnosis,>10 kHz

Not continuous

Condition Monitoring in ContextConventional rotating machine

condition monitoringaccelerometers, proximeters

article in oilBlade &

pitch monitoringElectrical Systemmonitoring


WT Condition Monitoring Test Rig-WTCMTR

• 3-phase, 4-pole, 30kW wound rotor induction generator

• 5:1 two-stage helical gears parallel shaft gearbox• 54kW DC motor

• Control Interface• Instrumentation

• Signal Conditioning• Data Acquisition NI LabVIEW

SKF WindCon system


WTCMTR– Synchronous Generator (SG)

Synchronous Generator

Gearbox DC MotorTorque Transducer

~

Resistive Load Banks

Instrumentation& Control Interface

Current & Voltage

Transducers

Variable Speed Drive

DC Tachometer

PC Running NI LabVIEWData Acquisition & Control

X & Y Proximeters

Accelerometer(s)

USB

Synchronous Generator

Gearbox DC MotorTorque Transducer

~~

Resistive Load Banks


Current & Voltage

Transducers


DC Tachometer

PC Running NI LabVIEWData Acquisition & Control

X & Y Proximeters

Accelerometer(s)

USB


SG Electrical Results

100 200 300 400 500 600 700 800 90015

20

25

spee

d / r

ev/m

in

100 200 300 400 500 600 700 800 900150

200

250

300

350

time /s

torq

ue /N

m

original torque signaldenoised torque signal

coilconnected

coilconnected

coilshorted

coilshorted

coilconnected

100 200 300 400 500 600 700 800 9009

10

11

12

13

14

15

time /s

C /

N*m

*min

/rev

using original torque signalusing denoised torque signal

coilconnected

coilconnected

coilconnected

coilshorted

coilshorted


SG Mechanical Results

0 50 100 150 200

24

26

28

30

spee

d / r

ev/m

in

0 50 100 150 200160180200220240260280

time /s

torq

ue /N

m

original torquedenoised torque

with imbalance faultno imbalance fault

20 40 60 80 100 120 140 160 180 2006

7

8

9

10

11

time /s

C / N

*m*m

in/re

v

using original torque signalusing denoised torque signal

no imbalance fault with imbalance fault


WTCMTR- Wound Rotor Induction Generator (WRIG) in open loop control

Wound Rotor Induction Machine

(Generator)

~

Resistive Load Banks (Rotor)

Grid Connection


(NI DAQ Pads)

Current, Voltage & Power

Transducers


PC Running SKF ProCon& NI LabVIEW Data

Acquisition & Control

X & Y Proximeters

Accelerometer(s)

USB Link

Torque Transducer &

Shaft Tachometer

Gearbox DC Motor DC Tachometer

Experimental Balance Plane

3 Phase Supply


Ethernet Link

SKF MasCon16

Unit

Wound Rotor Induction Machine

(Generator)

~~

Resistive Load Banks (Rotor)

Grid Connection


(NI DAQ Pads)

Current, Voltage & Power

Transducers


PC Running SKF ProCon& NI LabVIEW Data

Acquisition & Control

X & Y Proximeters

Accelerometer(s)

USB Link

Torque Transducer &

Shaft Tachometer

Gearbox DC Motor DC Tachometer


3 Phase Supply


Ethernet Link

SKF MasCon16

Unit

NTNU, EU FR7 MARE WINT ProjectSeptember 2013

11

WTCMTR-Comparison of Rig & Model

10-1 100 101 102 10310-8

10-6

10-4

10-2

100

102

Frequency (Hz)

PS

D (P

ower

per

Hz)

MeasuredSimulated

121.3 Hz

0.30 Hz

0.35 Hz

22.90 Hz

23.20 Hz

121.62 Hz


Fault Detection: Previous work• Focus on non-stationary signals

– Wind turbines are variable speed, variable load systems– Test rig driving conditions derived from a highly detailed wind

turbine model and proscribed wind/turbulence conditions

• Mechanical and electrical fault investigation under controlled environment

• Post-processing LabVIEW data collected during the tests

• Development of signal analysis method: Iterative Localised Discrete Fourier Transform (IDFTlocal)


WRIG Electrical Asymmetry Results

Wound rotor induction generator rotor electrical asymmetry– For example, brush gear fault/unbalance

Line current analysis– (1-2s)fse

Total power analysis– 2sfse


WRIG Mass Unbalance Results

High speed shaft mass unbalance– Mass applied near generator drive end

High speed shaft displacement analysis

– frm, machine rotational speed

Gearbox high speed end accelerometer analysis

– frm, machine rotational speed


Current research SKF WindCon unit configured to record and process the measured signals


Why an SKF WindCon System?• Commercially available system used

in wind industry• Flexible analogue inputs• Mechanical frequencies calculated by

machine information• Frequency analysis and alarms• Faults have been successful detected

in the field• Opportunity to investigate the system

in a controlled environment• Could the system be used for power

signal analysis?NTNU, EU FR7 MARE WINT Project

September 2013 17

Tests: Gearbox Gear Tooth DamageAIM: Investigate the effect of High Speed Shaft Pinion missing tooth on the

gearbox vibration signature

Accel 2

Accel 1

Healthy Tooth Damaged Tooth Missing ToothNTNU, EU FR7 MARE WINT Project

September 2013 18

Gearbox Vibration Signature• Fast Fourier Transform (FFT) analysis

• Identify frequencies or harmonic patterns indicative of a specific fault

• HEALTHY GEARS: characteristic fairly stable vibration pattern 2 gear meshing frequencies

fmesh,1 = 13.23 Xfmesh,2 = 58 X

their harmonics small amplitude sidebands

• FAULTY GEARS: what are the changes in the vibration signature?


Healthy Tooth Vibration Results

fmesh,1 2 X fmesh,1 2 X fmesh,2fmesh,2

WindCon (HSS) Accel2 Order Vibration FFT Spectrum(1560 rev/min)


Damaged Tooth Vibration Results




Missing Tooth Vibration Results




Spectra Comparison Harmonic content increase

More prominent 2 X fmesh,2sidebands spaced at the pinion rotational frequency (fHSS = 1X)

caused by the progressive damage introduced

The severity level of the tooth damage affects the

sideband amplitudes

Amplitude increases as a result of the 2 X fmesh,2

modulation by the faulted pinion impact per revolution

Healthy tooth

Damaged tooth

Missing tooth

0 20 40 60 80 100 120 140 160 180 200

0

0.1

0.2

0.3

0.4

0.5

0.6

Frequency (Order)

Am

plitu

de (g

Rm

s)

Healthy tooth

Damaged tooth

Missing tooth

110 112 114 116 118 120 122

0

0.05

0.1

0.15

0.2

0.25

Frequency (Order)

Am

plitu

de (g

Rm

s)

2 X fmesh,2


Power tracking algorithm Avoid time-consuming manual analysis for spectra comparison

Track the spectra power change in the 2 X fmesh,2 sideband narrowband

Power increase even in the case of low severity tooth damage


24

Vibration Results

• The signal harmonic content increases with the progressive gearbox HSS pinion damage

• Experimental data show that the presence of a faulty tooth results in more prominent sideband components of the 2 X fmesh,2 harmonic in

the vibration signal

• A detection algorithm has been proposed to track the overall power in the 2 X fmesh,2 sideband frequency

• Automatic detection may be possible during early stages of fault development using the power algorithm


Doubly-Fed Induction Generator

~

Data Acquisition Hardware

C urrent & Voltage Transducers


Data Acquisition & Control Environment

X & Y Proximeters

Accelerometer

Torque Transducer &

Shaft Tachometer

Gearbox DC Motor


3 phase

Grid Connection


3 phase

Grid Connection

DCTachometer

Converter Controller

~

~

Converter

Incremental Encoder

Torque

WTCMTR–Doubly-Fed Induction Generator in closed loop control


WTCMTR–DFIG Converter

Current & Voltage

Transducers

~

~

Current Transducers Clarke

Transformation(αβ)

ClarkeTransformation

(Ir_αβ)

Stator flux Calculation

(αβ)

Stator flux Angle calculation

(qs)

Magnetizingcurrent

Stator flux speed(ωs)

Rotorspeed(ωr)

Rotorangle(qr)

ParkTransformation

(Ir_dq)

Rotor current Reference

(Iqr_ref)

Rotor current Reference(Idr_ref=0)

PI Controller

Cross-Magnetisatio

n Compensatio

n terms

Rotor voltage Calculation

(Vr_dq)

Rotor voltage transformation

(Vr_abc)

Incremental Encoder

High speed shaft

Converter

Doubly-Fed Induction Generator

3 phase

Grid Connection


DFIG Control Loop Results


Future work • Define magnitude thresholds for various levels of fault severity to

refine the algorithm

• Incorporate the power algorithm in WindCon to automate the detection process

• Investigate electrical fault conditions (i.e. generator electrical asymmetry)

• Investigate mechanical fault conditions (i.e. LSS and HSS mass unbalance)

• Development of fault detection algorithms and their incorporation into WindCon to automatically track faulty frequencies

• Test the developed automated detection processes on data from wind turbines operating in the field


O&M Research• What are the offshore challenges?

• How do SCADA and condition monitoring fit into a wider picture of operations?

• What is the benefit of condition monitoring?

• Is monitoring justified?


Performance: Capacity Factor

Scroby Sands (30 x V80‐2MW ‐ UK Offshore) North Hoyle (30 x V80‐2MW ‐ UK Offshore)

Kentish Flats (30 x V90‐3MW ‐ UK Offshore) Barrow (30 × V90‐3MW ‐ UK Offshore)

Egmond aan Zee (36 × V90‐3MW ‐ NL Offshore)

0

10

20

30

40

50

60

70

80

90

100

Jul‐0

4Aug

‐04

Sep‐04

Oct‐04

Nov

‐04

Dec‐04

Jan‐05

Feb‐05

Mar‐05

Apr‐05

May‐05

Jun‐05

Jul‐0

5Aug

‐05

Sep‐05

Oct‐05

Nov

‐05

Dec‐05

Jan‐06

Feb‐06

Mar‐06

Apr‐06

May‐06

Jun‐06

Jul‐0

6Aug

‐06

Sep‐06

Oct‐06

Nov

‐06

Dec‐06

Jan‐07

Feb‐07

Mar‐07

Apr‐07

May‐07

Jun‐07

Jul‐0

7Aug

‐07

Sep‐07

Oct‐07

Nov

‐07

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8Aug

‐08

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‐08

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Apr‐09

May‐09

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Jul‐0

9Aug

‐09

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Nov

‐09

Dec‐09

Capacity F

actor (%)


Performance: Availability

0

10

20

30

40

50

60

70

80

90

100

Jul‐0

4Au

g‐04

Sep‐04

Oct‐04

Nov‐04

Dec‐04

Jan‐05

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May‐05

Jun‐05

Jul‐0

5Au

g‐05

Sep‐05

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Jan‐06

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Mar‐06

Apr‐06

May‐06

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Jul‐0

6Au

g‐06

Sep‐06

Oct‐06

Nov‐06

Dec‐06

Jan‐07

Feb‐07

Mar‐07

Apr‐07

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Jun‐07

Jul‐0

7Au

g‐07

Sep‐07

Oct‐07

Nov‐07

Dec‐07

Jan‐08

Feb‐08

Mar‐08

Apr‐08

May‐08

Jun‐08

Jul‐0

8Au

g‐08

Sep‐08

Oct‐08

Nov‐08

Dec‐08

Jan‐09

Feb‐09

Mar‐09

Apr‐09

May‐09

Jun‐09

Jul‐0

9Au

g‐09

Sep‐09

Oct‐09

Nov‐09

Dec‐09

Availability (%

)

Scroby Sands (30 x V80‐2MW ‐ UK Offshore) North Hoyle (30 x V80‐2MW ‐ UK Offshore)

Kentish Flats (30 x V90‐3MW ‐ UK Offshore) Barrow (30 × V90‐3MW ‐ UK Offshore)

Egmond aan Zee (36 × V90‐3MW ‐ NL Offshore)


0102030405060708090

100

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

Availability (%)

Wind Speed (m/s)

0102030405060708090

100

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

Availability (%)

Wind Speed (m/s)

0102030405060708090

100

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

Availability (%)

Wind Speed (m/s)

0102030405060708090

100

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

Availability (%)

Wind Speed (m/s)

Availability with Wind Speed


Generated and Lost Energy

0%

20%

40%

60%

80%

100%

5 6 7 8 9 10 11 12 13

Energy (M

Wh)

0%

20%

40%

60%

80%

100%

5 6 7 8 9 10 11 12 13

Energy (M

Wh)

0%

20%

40%

60%

80%

100%

5 6 7 8 9 10 11 12 13

Energy (M

Wh)

0%

20%

40%

60%

80%

100%

5 6 7 8 9 10 11 12 13

Energy (M

Wh)

Energy Generated Theoretical Lost Energy due to Unavailability


Cost of Condition Monitoring• CM often seen as too expensive

• Are the benefits worth the expense?

• SKF WindCon (Observer) ≈ £17,600

• Lost energy from an unplanned 24 hour stop:

• Conventional coal-fired plant with CCS ≈ £486,000

• 2MW onshore WT at 27% capacity ≈ £620

• Impractical


Cost of Failure• 2MW offshore gearbox failure

• Replacement gearbox ≈ £500,000

• Failure rate > 0.134 failures/turbine/year

• A 30 WT offshore farm can expect £2,500,000 failure costs at current rates

• Add £700,600 for generator failures

... ... ...

• SKF WindCon (Observer) ≈ £17,600 per turbine = £528,000

• Is it worth the cost of condition monitoring now...?


Operations Structure• How could we facilitate successful large wind farm operation?


Operations Structure


Future Work• Identify the causes of lost energy

• Are there problems with how we operate WTs?

• Do we fully understand large, multi-gigawatt offshore sites?

• Integration of condition monitoring and SCADA

• Link detection results to operation and maintenance structures

• How can results be presented and utilised?

• Quantify the benefits to industry of monitoring


Conclusions• For onshore WTs 75% faults cause 5% downtime, 25% faults cause

95% downtime• Pitch and Main Converters suffer from many faults but with low

downtimes.• Pitch and Main Converters represent a significant part of the 75%.• This behaviour could be problematic offshore.• WT reliability is affecting offshore performance• Sub-assemblies with high failure rates are consistent• Turbulence seems to be causing failures• Analysis of SCADA wind speeds, torques & shaft speeds is showing

ample evidence of turbulent effects• Link between turbulence and failures is difficult to prove• The mathematical tools to be used are not yet clear


ReferencesTavner PJ, Xiang JP and Spinato F, Reliability analysis for wind turbines. Wind Energy 10(1): 1-18, 2006.Spinato F, Tavner PJ, van Bussel GJW and Koutoulakos E, Reliability of wind turbine subassemblies. IET Renewable, Power Generation 3(4): 1–15, 2009.Wilkinson M, Hendriks B, Spinato F, Gomez E, Bulacio H, Roca J, Tavner P J, Feng Y, Long H, Methodology and results of the ReliaWind reliability field study, Scientific Track, European Wind Energy Conference, Warsaw, 2010.Feng Y, Tavner PJ and Long H, Early experiences with UK round 1 offshore wind farms, Proc Institution of Civil Engineers – Energy, 163(EN4): 167–181, 2010.Tavner, P J, Faulstich, S, Hahn, B, van Bussel, G J W, Reliability & availability of wind turbine electrical & electronic components, European Power Electronics Journal, 20(4): 1-6, 2010.Faulstich, S., Hahn B., Tavner, P. J., Wind turbine downtime and its importance for offshore deployment, Wind Energy, DOI: 10.1002/we.421, published on early view.


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What we can do to Improve the Reliability of Offshore Wind ...

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