O&M Cost Modelling, Technical Losses and Associated
Uncertainties
Axel AlbersDipl.-Phys.
Deutsche WindGuard Consulting GmbHOldenburger Straße 65, D26316 Varel
testing- and calibration laboratory with
quality management system according EN ISO/IEC 17025:2005
DAP-PL-3565.99
for power curve measurements,wind measurements,wind resource assessments
for power curve measurements
Contents• Modelling of O&M cost development in time• Comparison of modelled O&M cost with real wind farm data• Development of WT availability in time• Combination of uncertainties of wind resource, expected technical losses and O&M cost
O&M Cost Issues• Questions:
1. How large are maintenance and repair cost?
2. How do maintenance and repair cost develop with the age of WT’s?• Problems
A) analysis of future O&M-cost on component by component basis often impossible
B) accurate public data on O&M cost is rare
C) only limited number of wind farms in high age (15-20a)
D) rapid development of technology and size of WT in last decade• Several studies show rise in Q&M-cost with WT age (BWE, WMEP, University of Durham and TU Delft)
Operational Costs by WT Age According to WMEP 2006
operating year
repair maintenance insurance property other
Source: WMEP 2006
Warranty Period
Rise of Repair and Maintenance Cost BWE 2002 Study
• In second decade cost twice as high as in first decade (BWE study 1999)• 12 €/MWh/a average cost over 20 years (corresponds to BWE 2002 numbers if 2000 full load hours are assumed), well in line with cost of most full service contracts• Often assumed by wind farm developers or financiers:
- no rise with age
- step functions: after 10a or steps every 5th year
0
2
4
6
8
10
12
14
16
18
0 2 4 6 8 10 12 14 16 18 20
Operating Year [a]
O&
M C
ost
[€/M
Wh/
a]
1.8% of invetsment cost per year
3.6% of invetsment cost per year
Improved Approach for Rise in Repair and Maintenance Cost
• There is no reason to assume a step function.• Integrated cost increase in 2nd decade compared to 1st decade overtaken
from BWE 2002 study (double cost in 2nd decade)
0
5
10
15
20
25
30
0 2 4 6 8 10 12 14 16 18 20
Operating Year [a]
O&
M C
ost
C [
€/M
Wh
/a]
acc. BWE 2002 study exponential cost increase physical model
Physical Model for Rise in Repair and Maintenance Cost
• Damage increase per time is inversely proportional to remaining lifetime L-t
- L: total lifetime
- t : age• Damage increase is proportional to increase of cost C
tL
1
dt
dC
21 const)tLln(constC
tL
LlnconstC 00tC condition 1
a2.26L Cdt2
1Cdt condition
a20t
a10t
a10t
0t
Fit of Model for Rise of Repair and Maintenance Cost to Observations
• In single years large outliers are observed, but the cumulated cost is fitted well by model.• Always the same cost rise has been assumed (twice as much cost in 2nd decade than in 1st
decade).
0
5
10
15
20
25
30
35
0 2 4 6 8 10 12
Operating Year [a]
O&
M C
ost
[€/M
Wh
/a]
1.8MW direct drive, pitch, 7€/MWh/a in 20a
1.5MW gearbox, stall, 12€/MWh/a in 20a
2.0MW gearbox, pitch, 12€/MWh/a in 20a
1.3MW gearbox, active stall, 17€/MWh/a in 20a
2.0MW nearshore, Middelgrunden, 24€/MWh/a
gearbox damage
Extrapolation of Repair and Maintenance Cost
• standard approach : 0.012€/kWh/a averaged over 20a assumed (value from BWE-study 2002)
• Estimated standard uncertainty of standard approach: 50% of modelled cost
0
5
10
15
20
25
30
35
0 2 4 6 8 10 12 14 16 18 20
Operating Year [a]
O&
M C
ost
[€/M
Wh
/a]
1.8MW direct drive, pitch, 7€/MWh/a in 20a1.5MW gearbox, stall, 12€/MWh/a in 20a2.0MW gearbox, pitch, 12€/MWh/a in 20a1.3MW gearbox, active stall, 17€/MWh/a in 20a2.0MW nearshore, Middelgrunden, 24€/MWh/astandard approach onshore, 0.012€/kWh/a in 20a
gearbox damage
Observations in Old Wind Farms In Respect to Availability
• Experience based on:
- hundreds of WT’s in age 12-20a in Eastern-Frisia (backyard of WindGuard)
- due diligence in the frame of sales of wind farms
- technical management of wind farms• Availability normally high, but within year 5 to 15 single events with long standstills likely• One event with 3 months standstill leads to 2.5% additional non-availability over 10 years• Consequence: 97% availability hardly possible in 2nd decade in case of only a single extraordinary event
Model for Increase of Availability Losses in Time
• The initialisation is treated case dependent:
- adjustment according to warranties or
- adjustment according to availability of past operating period or
- adjustment according to experience with wind turbine type
0
2
4
6
8
10
12
14
0 2 4 6 8 10 12 14 16 18 20
Operating Year [a]
Exp
ecte
d L
osse
s d
ue
to N
on-A
vaila
bili
ty [
%]
Standard approach initialised with 3% average availability losses in first 10 years.Resulting losses averaged over first 20 years: 4.5%
Example for Increase of Availability Losses in Time
• Model adjusted to observed non-availability losses in past (after initial project stage with teething problems)
0
2
4
6
8
10
12
0 2 4 6 8 10 12 14 16 18 20
Operating Year [a]
Non
-Ava
ilab
ilit
y L
osse
s [%
]
observed non-availability losses, running annual mean fitted model
teet
hing
pha
se: 7
.6%
loss analysed period: 2.2% loss extrapolation period: 4.3% loss
Combination of Uncertainties of Wind Resource (Revenue) and O&M-Cost
• Problem 1: The lower the wind resource, the lower the wear (repair cost)Solution:i) calculate P50-value of O&M-cost and standard uncertainty of O&M- cost on the basis of Px-value of the production estimateii) combine standard uncertainty of wind resource (revenue) and new standard uncertainty of O&M-cost as independent uncertaintiesiii) consider normal distribution of difference of revenue and O&M- cost with the combined standard uncertainty and calculate Px-value of this distribution
0123456789
0 100 200 300 400 500 600
revenue, earnings [k€]
f[%
]
f-revenue f-O&M-cost at P-revenue=50%
f-O&M-cost at P-revenue=90% f of earnings (revenue - O&M-cost)
Combination of Uncertainties of Non-Availability Losses (Revenue) and O&M-Cost
• Problem 2: increase of O&M-cost with age highly correlated with increase of non-availability losses• Solution:
combine standard uncertainty of O&M-cost and standard uncertainty of revenue due to non-availability losses linearly
0
100
200
300
400
500
0 5 10 15 20
age [a]
reve
nue,
O&
M-c
ost,
ear
ning
s [k
€]
revenue with standard uncertainty due to non-availability(bars), no uncertainty of wind resource consideredO&M cost with standard uncertainty (bars)
earnings with combined standard uncertainty (bars)
Result of Combination of Uncertainties
• final result: risk assessment of net earnings
0
50
100
150
200
250
300
350
0 5 10 15 20Operating Year [a]
Dif
fere
nce
Ear
nin
gs -
O&
M C
ost
[k€]
P50 P75 P90
Example:2MW turbine23% capacity factor0.1€/kWh tariff0.012€/kWh/a O&M cost15% other cost14% standard uncertainty wind resource97% average availability in year 1-10
2% other losses than availability
moderate wind resource, high tariff high wind resource, low tariff
0
50
100
150
200
250
0 5 10 15 20
Operating Year [a]
Dif
fere
nce
Ear
nin
gs -
O&
M C
ost
[k€]
P50 P75 P90
Example:2MW turbine34% capacity factor0.05€/kWh tariff0.012€/kWh/a O&M cost15% other cost14% standard uncertainty wind resource97% avergae availability in year 1-10
2% other losses than availability
Conclusions• Individual modelling of expected O&M cost and availability over project lifetime is recommended
• Long-term O&M cost often underestimated in planning phase:- often about 85% EBITDA-margin expected over 20a- latest study of BWE from 2009: 76% EBITDA-margin (average of 66 wind farms)
• Cost modelling often results in positive earnings even after 20 years
• Problem: type certificate valid only 20 years- building permit of WT may lose validity - extension of type certificate to longer period in most cases not possible
i) high costii) WT design often not conform with latest revision of IEC 61400-1
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