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Introduction to Wind Turbines and their
Reliability & Availability
Dr. Yanhui Feng, Prof. Peter Tavner
Energy Group, New & Renewable Energy Subgroup
“When one recognises how much the sum of our
ignorance exceeds that of our knowledge, one is less
likely to draw rapid conclusions.”
Louis de Broglie
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Overview
• Wind Conditions, Turbine Taxonomy & Technology
• Basic reliability
• Wind power Cost of Energy, Availability and Reliability
• What we know about wind turbine Availability &
Reliability Onshore & Offshore
• Conclusions
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Wind Conditions
Turbine Taxonomy
& Technology
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Variation of turbine forces, time & space
Turbulent forces
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Scale
Boeing 74722 kW 95 kW 450 kW 2.3 MW 3.6 MW
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Already the world’s largest rotating machines
Boeing 747
Wind Turbine
Configurations
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Geared Drive Wind Turbine, R80
Basic Reliability
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Failure
Intensity,
l
Early Life
(b < 1)
Useful Life
(b = 1)
Wear-out Period
(b > 1)
The Bathtub Curve
Time, t
Most turbines
lie here
(years) Period Operating
Population Turbine
failures ofnumber Total
al
te)t( bbl -
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Useful Life (b = 1)
The Bathtub Curve
Time, t
Failure
Intensity,
l
Early Life(b < 1) Wear-out Period (b > 1)
Select more reliable components
Preventive maintenance
Reliability Centred Maintenance
Condition Based Maintenance
Major subassembly
changeoutMore rigorous
pretesting
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Root Causes & Failure Modes
Example: Main Shaft Failure
How?
SCADA
Analysis
CM
& Diagnosis
Why?
Root Cause
Analysis
Root Causes
Failure Mode
Main Shaft Failure
Fracture Deformation
High Cycle Fatigue CorrosionLow Cycle Fatigue or
OverloadMisalignment
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Wind Power Cost of Energy,
Capacity Factor and Availability
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Availability, Inherent
Time
Operability
100%
0%
MTTF
MTTR
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MTBF
Availability, Operational
Time
Operability
100%
0%
MTBM
MTTR
Logistic Delay
time
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MTBF
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Availability & Reliability• Mean Time To Failure, MTTF
• Mean Time to Repair, or downtime MTTR
• Mean Time Between Failures,
MTBF≈MTTF
MTBF≈MTTF+MTTR=1/ l +1/ mMTBF=MTTF+MTTR+LogisticDelay Time
• Failure rate, l l = 1/MTBF
• Repair rate, m m=1/MTTR
• Inherent Availability,
A=(MTBF-MTTR)/MTBF=1-(l/m)• Operational or Technical Availability,
A=MTTF/MTBF < 1-(l/m)• Typical UK values
– Operational Availability 97%,
– Inherent Availability 98%
Capacity Factor
• Energy generated in a year= C x Turbine rating x 8760
• Capacity Factor, C
• 8760 number of hours in a year
• Therefore:
• C=Energy generated in a year/ Turbine rating x 8760
• C incorporates the Availability, A, and therefore the
MTBF, 1/l• Typical UK values
– Onshore, C 27.3%
– Early offshore, C 29.5%
• Typical EU values
– Offshore, C 35%16 of 35
Cost of Energy, COE
• COE, £/kWh=
(ICC×FCR + O&M)/AEP
– ICC=Initial Capital Cost, £
– FCR=Fixed Charge Rate, interest, %
– O&M=Annual Cost of Operations & Maintenance, £
– AEP=Annualised Energy Production, kWh
• COE , £/kWh =
(ICC×FCR + O&M(1/l, 1/MTTR))/AEP(A(1/l, 1/MTTR)}
• Reduce failure rate l, Reliability MTBF 1/l improve and Availability Aimprove, O&M cost reduces;
• Reduce Downtime MTTR, Availability A improve, O&M cost reduces;
• Therefore COE, reduces
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Impact of the Reliability on COE
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What we know about wind turbine
Reliability
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Sources of Failure Data
• Eurowin data
• EPRI data from California
• Windstats data from Germany and Denmark
• LWK data from Germany
• WMEP data from Germany
• Data from UK Round 1 offshore wind farms
• Data now coming from RELIAWIND WP 1, see later
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Trend in Turbine Failure Rates
with time
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Reliability & Size, EU
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Reliability & Downtime &
Subassemblies, EU
Drive Train
Generator
Gearbox
Rotor Blades
Mechanical Brake
Rotor Hub
Yaw System
Hydraulic System
Other
Electrical Control
Electrical SystemLWK Failure Rate, approx 5800 Turbine Years
WMEP Failure Rate, approx 15400 Turbine Years
LWK Downtime, approx 5800 Turbine Years
WMEP Downtime, approx 15400 Turbine Years
1 0.75 0.5 0.25 0 2 4 6 8 10 12 14 Failure/turbine/year Downtime per failure (days)
Failure/turbine/year and Downtime from 2 Large Surveys of European Wind Turbines over 13 years
Reliability & Weather, WS DK
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Wind Speed
Failure Rate
Reliability & Time, LWK
0 20 40 60 80 100
0.0
0.2
0.4
0.6
0.8
1.0
LWK, E66, converter
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 9
ye
ars
industrial range
demonstrated reliabilitydemonstrated reliabilitydemonstrated reliability
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Reliability & Time, LWK
Generators
0 100 200 300 400 500
0.0
0.2
0.4
0.6
0.8
1.0
LWK, E40, generator
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
1 ye
ars
industrial range
0 20 40 60 80
0.0
0.2
0.4
0.6
0.8
1.0
LWK, E66, generator
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 7
ye
ars
industrial range
0 100 200 300 400
0.0
0.2
0.4
0.6
0.8
1.0
LWK, V27/225, generator
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
2 ye
ars
industrial range
0 100 200 300 400 500
0.0
0.2
0.4
0.6
0.8
1.0
LWK, V39/500, generator
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
1 ye
ars
industrial range
Figure 4.4: Variation between the failure rates of generator subassemblies, in the LWK population of German WTs, using the PLP model.
The upper two are low speed direct drive generators while the lower two are high speed indirect drive generators.
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Reliability & Time, LWK
Gearboxes
0 100 200 300
0.0
0.2
0.4
0.6
0.8
1.0
LWK, TW600, gearbox
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
2 ye
ars
industrial value
0 100 200 300 400 500
0.0
0.2
0.4
0.6
0.8
1.0
LWK, V39/500, gearbox
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
1 ye
ars
industrial value
0 20 40 60 80 100
0.0
0.2
0.4
0.6
0.8
1.0
LWK, N52/N54, gearbox
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 7
ye
ars
industrial value
0 50 100 150 200 250
0.0
0.2
0.4
0.6
0.8
1.0
LWK, Micon M530, gearbox
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
2 ye
ars
industrial value
Figure 4.5: Variation between the failure rates of gearbox subassemblies, using the
PLP model, in the LWK population of German WTs. 27 of 35
Reliability & Time, LWK
Electronics
0 100 200 300 400 500
0.0
0.2
0.4
0.6
0.8
1.0
LWK, E40, electronics
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 1
1 ye
ars
industrial range
0 20 40 60 80
0.0
0.2
0.4
0.6
0.8
1.0
LWK, E66, electronics
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 7
ye
ars
industrial range
0 10 20 30 40 50
0.0
0.2
0.4
0.6
0.8
1.0
LWK, TW 1.5s, electronics
total test time [turbines * year]
failu
re in
ten
sity
[fa
ilu
res /
ye
ar]
actu
al e
lap
se
d tim
e: 5
ye
ars
industrial range
Figure 4.6: Variation between the failure rates of electronics subassemblies, or converter,
using the PLP model, in the LWK population of German WTs. The upper two are low speed direct drive generators with fully rated converters while the lower
two are high speed indirect drive generators with partially rated converters.
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Reliability of Power Electronics
Failure root cause distribution for power electronics
from E Wolfgang, 2007
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Onshore Availability & Wind speed, World
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40%
energy
produced
at wind
speeds
>11m/s
Offshore Availability & Wind speed, UK
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Offshore Capacity Factor & Wind Speed, UK
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Root Causes
Failure Modes
& Effects
Analysis,
FMEA
Failure Location
Condition
Monitoring
Signals
SCADA
Signal
Analysis
Results of
survey data WP1
Wind condition
Weather
Faulty design
Faulty materials
Poor maintenance
Results of
WP3 analysis
Results of
WP2 analysis
How?
SCADA Analysis
& Diagnosis
Why?
Root Cause Analysis
Wind Turbine
Reliability Analysis
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Conclusions
• WT reliability is improving
• WT concepts have different reliabilities
• Generally failure rates are constant
• The subassemblies with high failure rates are consistent
• Downtime or MTTR and cost are also important
• Failure rates of subassemblies can improve with time
• Definitions of Availability are important and need to be standardised
• Offshore availability Ai is worse than onshore
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Thank you• P. J. Tavner, C. Edwards, A. Brinkman, and F. Spinato. Infuence of wind
speed on wind turbine reliability. Wind Engineering, 30(1), 2006.
• P. J. Tavner, J. P.Xiang, and F. Spinato. Reliability analysis for wind turbines. Wind Energy, 10(1), 2007.
• F. Spinato, P. J. Tavner, and G.J.W van Bussel. Reliability-growth analysis of wind turbines from field data. Proceedings of AR2TS conference, Loughborough, 2007.
• Tavner, P J, van Bussel, G J W, Spinato, F, Machine and converter reliabilities in WTs. Proceedings of IEE PEMD Conference, Dublin, April 2006.
• Hansen, A D., Hansen, L H. ,Wind turbine concept market penetration over 10 years (1995–2004), Wind Energy, 2007; 10:81–97
• Ribrant J., Bertling L.M.: Survey of failures in wind power systems with focus on Swedish wind power plants during 1997–2005, IEEE Trans. Energy Conversion, 2007, EC22 (1), pp. 167–173
• Wolfgang, E. Examples for failures in power electronics systems, in EPE Tutorial ‘Reliability of Power Electronic Systems’, April 2007.
• Beckendahl, P, Skiip, an Intelligent Power Module for wind turbine inverters, EPE Wind Chapter Mtg, Stockholm, May 2009.
• Feng, Y, Tavner, P J, Long, H, Early Experiences with UK Round 1 Offshore Wind Farms, accepted by Proceedings of the Institution of Civil Engineers, Energy, 2010.
• E. Echavarria, T. Tomiyama, G.J.W. van Bussel, B. Hahn How has reliability of technology developed through time?, EWEC2007, Milano.
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