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How does the real world performance of wind turbines compare
with sales power curves?
EWEA: Lyon, July 2012 – Keir Harman
Background
Asset Management and Optimisation Services
(AMOS)
• Turbine performance monitoring
• SCADA-based condition monitoring
• Fault diagnosis and forensic analysis of SCADA data
• Post-construction energy forecasts
• Warranty calculations
• End of warranty inspection analyses
• O&M advice
• Reliability profiling and benchmarking
Over 30 GW of operating wind farms assessed to date
What do we typically see in operating data?
• Power curves rarely lie on the sales power curve
0 5 10 15 20
Nacelle anemometer wind speed [m/s]
Avera
ge P
ow
er
[kW
]
WTG 1
WTG 2
WTG 3
WTG 4
WTG 5
WTG 6
WTG 7
WTG 8
WTG 9
WTG 10
WTG 11
WTG 12
WTG 13
WTG 14
WTG 15
WTG 16
Warranted power
Category Typical range of
loss/gain
(nominal energy %)
Most likely
(nominal energy %)
1) Generic power curve performance
2) Mechanical sub-optimal performance
3) Environmental: icing and dirty blades
4) Wind conditions: turbulence intensity, shear
and flow inclination
Real world power curve losses/gains categorised
???
Category 1: Generic power curve performance
• 115 project power curve tests using IEC guidelines [61400 pt 12-1]
• Average of results = 99%
• IEC measurement uncertainty typically 5%
< 92% 92% to 94%
94% to 96%
96% to 98%
98% to 100%
100% to 102%
102% to 104%
104% to 106%
106% to 108%
>108%
Pro
po
rtio
n o
f d
atab
ase
Percentage of warranted power curve energy achieved (NME/NWE)
Category 2: Mechanical sub-optimal performance – common causes
1) De-rating 3) Component misalignment /
Sensor error 2) Non-optimal controller settings
Power vs.
Wind speed
Power vs.
Rotor speed
Rotor speed [rpm]
Avera
ge P
ow
er
[kW
]
0
10
20
30
40
50
608
0%
81
%
82
%
83
%
84
%
85
%
86
%
87
%
88
%
89
%
90
%
91
%
92
%
93
%
94
%
95
%
96
%
97
%
98
%
99
%
10
0%
10
1%
Nu
mb
er o
f w
inf fa
rm y
ea
rs
Annual Operating Efficiency
Category 2: Mechanical sub-optimal performance - What can be expected?
Mean = 98%
50% of database with OE of
99% or higher (Median)
Database
62 wind farms across Europe
Between 1 and 6 years of operation
134 wind farm years
Definition
Energy produced
Operating Efficiency (OE) =
Energy expected with ‘normal’ power curve
Target
Operating Efficiency =100%
Category 3: Environmental - causes Icing
High impact on some sites
Bugs
High impact for short periods
Dirty blades
Subtle impact but persistent
Wind speed Wind speed Wind speed
pow
er
pow
er
pow
er
• Typical range -3% to -0.2% and very region specific
Category 4: Wind conditions
The power curve is impacted by:
• Flow inclination
• Turbulence intensity (TI)
• Shear profile
• Air density
Influenced by:
• Atmospheric stability (TI, shear, density)
• Complex terrain (flow inclination, TI, and shear)
• Forestry (TI and shear)
1
2
3
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Wind speed [m/s]
Avera
ge p
ow
er
[kW
]
0
30
60
90
120
150
180
210
240
270
300
330
Category 4: Wind conditions:
Flow inclination impact on power curve (Extremes) GLGH validation of Madsen/Pederson research for MW-scale wind turbines
Yaw error observations for MW-scale turbines (GLGH)
Category 4: Wind conditions
Turbulence Intensity (TI) and Shear impact on power curve (Extremes)
0
200
400
600
800
1000
1200
1400
1600
0 5 10 15 20 25
Wind speed [m/s]
Po
wer
[kW
]
0
100
200
300
400
500
600
700
800
900
Distribution
14%
15%
16%
17%
18%
19%
20%
21%
22%
23%
24%
25%
High TI case:
• 2% drop in nominal energy between TI of
14% and 20% due to ‘rounded knee’ for a
high wind speed site
20%
30%
40%
50%
60%
70%
80%
90%
7 8 9 10 11
Po
we
r [%
of
Ra
ted
]
Wind Speed [m/s]
High TI
Mid TI
Low TI
Low TI case:
• 3% drop in nominal energy during periods of
low TI (<8%), which corresponds to stable
atmospheric conditions
Category Typical range of
loss(-ve)/gain(+ve)
(nominal energy %)
Median
(nominal energy %)
1. Generic power curve performance -5% to +3% -1% (model specific)
2. Mechanical sub-optimal performance -5% to +0% -1% (operator specific)
3. Environmental -3% to -0.2% -0.5% (region specific)
4. Wind conditions – turbulence intensity,
shear and flow inclination -5% to +1% -1% (site specific)
Conclusions
• Real world turbine performance does generally deviate from sales power curves
• Causes can be grouped and quantified based on observations from operational analyses
Questions?
Keir Harman
keir.harman@gl-garradhassan.com
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