report maintenance excellence - wind power stations
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We create advantage
ConMoto Consulting Group GmbH ConMoto Short Study: „Maintenance Strategies for Systems in Wind Power Stations“ Munich, December 2011
2 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Content
1. Basic Concept and Objectives of the Short Study „Maintenance Strategies for Systems in Wind Power Stations“
2. Wind Power Stations – Basic Data and Analysis of Fault Data
3. Cost-optimal Maintenance Strategies for Wind Power Stations
4. ConMoto Consulting Group – Facts & Figures
3 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
ConMoto Short Study „Maintenance Strategies for Systems in Wind Power Stations “ (2011) – Scope and Basic Data
Evaluation of Basic Data
Representative survey of wind power station operators
Ø Full load hours per year: 2.141 h (Onshore) Ø Full load hours per year : 3.695 h (Offshore)
Evaluated manufacturers :
□ Enercon □ Vestas □ GE □ Windworld □ Siemens
□ Nordex □ NEG Micon □ RE Power □ HSW / BWU □ Fuhrländer
4 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Instandhaltungs-Strategie
System
Pitchsystem
Windrichtungs-führung
Rotornabe
Rotorblätter
Zust
ands
orie
ntie
rte
Stra
tegi
e
Ant
rieb
*
Elim
inie
rung
s-st
rate
gie
Einf
ache
R
edun
danz
Str
ateg
ie
Meh
rfac
he
Red
unda
nz S
trat
egie
Perio
disc
he S
trat
egie
lä
nger
e In
terv
alle
Perio
disc
he S
trat
egie
kü
rzer
e In
terv
alle
Sequ
entie
lleSt
rate
gie
Cra
shst
rate
gie
52% 1% 1% 10% 31% 4% 1%
51% 3% 1% 10% 34% 1%
72%11% 9% 7%
29% 3% 48% 12% 8%
Methodical Approach – Determination of Target Strategies and Analysis of Maintenance Strategies currently used
► Value creation areas and required actions can be derived from comparison of target vs. currently used Maintenance Strategies. The goal is Maintenance Excellence
Fault data analysis and ConMoto best-practice experience and know-how
Analysis of the short study
Target Maintenance Strategies
Maintenance Strategies currently in use Inquiry of maintenance strategies for the main systems of wind power stations:
Input side Output side Electronics & control
systems
Risk and Reliability (R2) based Maintenance Strategies
5 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Content
1. Basic Concept and Objectives of the Short Study „Maintenance Strategies for Systems in Wind Power Stations“
2. Wind Power Stations – Basic Data and Analysis of Fault Data
3. Cost-optimal Maintenance Strategies for Wind Power Stations
4. ConMoto Consulting Group – Facts & Figures
6 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
2000 2005 2010 2015 2020
Wind Power Stations in Germany – Facts & Figures
Ø Onshore full load hours:** 1.700 - 2.100 h (≙19-24%) Ø Offshore full load hours: 3.800 h (≙ 43,5%) Ø Feed-in compensation*** onshore: 0,075 €/kWh (mean over 20 years) Ø Feed-in compensation *** offshore: 0,13 – 0,15 €/kWh (for the first twelve years)
* 1 GW = 1.000 MW = 1.000.000 kW
** Full load hours = produced energy per year / installed power
*** according to EEG (renewable energies law)
www.windmonitor.iwes.fraunhofer.de
www.wind-energie.de/
www.de.wikipedia.org/wiki/windkraftanlagen
6,1 GW*
18,3 GW
26,8 GW
9.247 21.646 17.323
Number of Wind Power Stations (WPS) in Germany and total installed power
Number of WPS
40,0 GW
Estim
ate
28.000 - 33.000
37.000 - 40.000
54,0 GW
Estim
ate
Trend: WPS > 1,5 MW (Offshore)
Source:
7 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Gear Box18%
Blades24%
Tower24%
Generator10%
Nascelle Module8%
Hub and Main Shaft6%
Cables & Sensor Systems
3%
Hydraulic System
2%
Yaw System2%
Installation3%
Blades and Tower are Main Cost Drivers of a Wind Power Station
* Grid connection, foundation, development, planning, other costs; stated value is applicable for onshore installations only
www.wind-energie.de
Total investment costs: □ 75% Wind power station costs □ 25% Auxiliary investment costs*
Total investment costs per kW installed power □ Onshore: 1.000 to 1.700 €/kW □ Offshore: up to 4.300 €/kW
Ø Annual service and maintenance costs (onshore):
~ 2,6% of the wind turbine costs (turbine and generator) without tower and auxiliary investment costs
Ø Annual operating costs (offshore): 0,02-0,04 €/kWh (thereof 30-50% service and
maintenance costs) Typical investment cost structure of a 1,2
MW Wind Power Station
Source:
8 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
About 2/3 of all Faults result in total Loss of Production or reduced Power Production
Wide Load Range
Vibrations
High Dynamic Loads
Environmental Influences
(Temperature, Salt, Dust)
Cause of Faults and Malfunctions
Impacts of Faults and Malfunctions
Critical Systems Electronics & control systems Blades Pitch system Generator
windmonitor.iwes.fraunhofer.de
General Requirements of a WPS
Source:
9 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Clear Trend to higher Fault Rates on newer / larger WPS An
nual
Fau
lt R
ate
[Num
ber /
Yea
r]
Installed Power
< 500 kW
500 - 999 kW
> 1.000 kW
Years of Operation
Ø Fault rate large installation: 3,5
Ø Fault rate mid-sized installation: 2
Fault rate almost not related to age of installation
Trend to higher fault rates on large installation (high complexity)
Plant Reliability according to Age and installed Power
Hahn,B.; Durstewitz M.; Rohrig K.: Reliability of Wind Turbines; Institut für Solare Energieversorgungstechnik (ISET) Verein an der Universität Kassel e.V., 34119 Kassel, Germany
► Every fault / malfunction leads to an average down time of 6 days
Source:
10 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Electrical and Control Systems cause the highest Fault Rates Fa
ult R
ate
[Fau
lts p
er Y
ear a
nd W
PS]
Rate of Damage
► Mechatronic components (e.g. sensors) as well as hydraulic systems are the second most common causes for down times
www.windmonitor.iwes.fraunhofer.de
Fau
lt R
ate
[%]
Source:
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More than 39% of the annual Down Time is caused by the Pitch System and the Electrical System
Down Times caused by Component Failures
► Five sub-systems (pitch system, electrical systems, generator, control systems, yaw system) cause 71% of the total annual down time
Perc
enta
ge o
f Dow
n Ti
me
(Hou
rs /
Year
) [%
]
Cum
ulat
ed D
own
Tim
e [%
]
http://www.winergy-group.com Source:
12 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Expenditure necessary for the Maintenance of Wind Power Stations
Number of Years between Major Maintenance Expenditure / Replacement
Mai
nten
ance
Exp
endi
ture
/ R
epla
cem
ent I
nves
tmen
t [€/
KW
]
Replacement investment ca. 54% of the WPS total investment (20 years)
Critical Components
Noncritical Components
Medium critical Components
DEWI 2002 Source:
13 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Content
1. Basic Concept and Objectives of the Short Study „Maintenance Strategies for Systems in Wind Power Stations“
2. Wind Power Stations – Basic Data and Analysis of Fault Data
3. Cost-optimal Maintenance Strategies for Wind Power Stations
4. ConMoto Consulting Group – Facts & Figures
14 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
ConMoto Method: Risk and Reliability (R2) Based Maintenance Strategies – the „Cube“ in Detail
Condition-based Strategy (Service + Inspection measures according to actual condition) - Sequential strategy - Condition based strategy (Online) Redundancy Strategy (Functional redundancy – bypass) - Single redundancy - Multiple redundancy Preventive Strategy (Planned maintenance interventions according to maintenance and inspection plans - low frequency - high frequency Break-down Strategy (Deliberate operation until failure) - Crash - Technical optimization strategy
a b
c d
e f
g h
► Determination of cost-optimal maintenance strategy for each component
5
Impa
ct o
f Fau
lts a
nd M
alfu
nctio
ns -
y
3
5
3
5
3
1
a
b
e f
c
d
g h
low
hi
gh
1
Replacement Value - x
low high
15 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Results of Risk and Reliability based Maintenance Strategies
► Reduction of maintenance costs and simultaneous decrease of production losses combined with optimal budget and resources control lead to optimum total costs
Reduced direct costs
Less unplanned breakdown intervention
Improved preventive maintenance
Autonomous maintenance
Technical improvements
Optimized contractor management
…
Improved plant availability
Improved perfor-mance rate
Improved process stability
Less scrap and rework
…
Balanced score card optimized budget planning and day-to-day resource management on all hierarchy levels
Direct Maintenance
Costs Losses in O.E.E.
Cos
ts
Maintenance Effort/Expenditure
Post optimization
Post optimization
Direct costs prior to optimization
O.E.E. losses prior to optimizations
-
Minimum
16 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
MaintenanceStrategy
System
Pitch System
Yaw System
Hub
Blades
Con
ditio
n-ba
sed
Stra
tegy
Inpu
t Sid
e*
Tech
nica
l op
timiz
atio
n
St
rate
gy
Sing
le R
edun
danc
y St
rate
gy
Mul
tiple
Red
unda
ncy
Stra
tegy
Plan
ned
prev
entiv
e M
aint
enan
ce lo
w
Freq
uenc
y
Plan
ned
prev
entiv
e M
aint
enan
ce h
igh
Freq
uenc
y
Sequ
entia
l Str
ateg
y
Bre
ak-d
own
Stra
tegy
52% 1% 1% 10% 31% 4% 1%
51% 3% 1% 10% 34% 1%
72%11% 9% 7%
29% 3% 48% 12% 8%
Results of the Short Study – Maintenance Strategies for Components of the „Input Side“ (currently used Strategies)
* Values rounded
1
2
3
4
17 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Maintenance Excellence by applying Risk and Reliability based Maintenance Strategies to a Wind Power Station – “Input Side” (Current vs. Target Strategies)
Wind Power Station Target Values (x/y/z)
Pitch System (5/5/5)
Yaw System (3/4/3)
Hub (3/1/3)
Blades (5/1/2)
5
Impa
ct o
f Fau
lts a
nd M
alfu
nctio
ns -
y
3
5
3
5
3
1
a
b
e f
c
d
g h
low
hi
gh
1
Replacement Value - x
low high
2
1
3 4
1 52%
1 31%
2 51%
2 34%
3 72%
4 29%
4 48%
* Only the two most commonly used maintenance strategies are displayed in the cube; if value is >70% only the main strategy is listed
1 2 3 4
Three sub-systems of the “Drive System" are not operated with the optimum maintenance strategy
Only for the sub-system “Blades" about 50% of the WPS operators apply the strategy “Planned Preventive Maintenance - low Frequency (cost-optimal maintenance strategy for this sub-system)
%
%
%
Target Strategy
Current Strategies (Ø of all participating WPS Operators)*
Significant Deviation from Target Strategy
Medium Deviation from Target Strategy No Deviation; Current = Target Strategy
Key
18 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
MaintenanceStrategy
System
Drive Train
Gear Box
Mechanical Brake
Hydraulic System
Plan
ned
prev
entiv
e M
aint
enan
ce lo
w
Freq
uenc
y
Con
ditio
n-ba
sed
Stra
tegy
Out
put S
ide*
Tech
nica
l op
timiz
atio
n
St
rate
gy
Sing
le R
edun
danc
y St
rate
gy
Mul
tiple
Red
unda
ncy
Stra
tegy
Plan
ned
prev
entiv
e M
aint
enan
ce h
igh
Freq
uenc
y
Sequ
entia
l Str
ateg
y
Bre
ak-d
own
Stra
tegy
30% 3% 1% 9% 5% 22% 31%
28% 3% 1% 13%22% 33%
51% 1% 11%36%
1% 1%
76%3% 12% 7% 1%
Results of the Short Study – Maintenance Strategies for Components of the “Output Side” (currently used Strategies)
* Values rounded
5
6
7
8
19 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Maintenance Excellence by applying Risk and Reliability based Maintenance Strategies to a Wind Power Station – “Output Side” Current vs. Target Strategies)
5
Impa
ct o
f Fau
lts a
nd M
alfu
nctio
ns -
y
3
5
3
5
3
1
a
b
e f
c
d
g h
low
hi
gh
1
Replacement Value - x
low high
5 6
7 8
5 30%
5 31%
6 33%
6 28% 7
51%
7 36%
8 76%
High scattering of maintenance strategies used for the sub-systems „Drive Train“ and „Gear Box“
Sub-system „Gear Box“ shows the most significant deviation from the target strategy
About 50% of the WPS operators apply the optimum maintenance strategy to the sub-system “Mechanical Brakes”
%
%
%
Target Strategy
Current Strategies (Ø of all participating WPS Operators)*
Significant Deviation from Target Strategy
Medium Deviation from Target Strategy No Deviation; Current = Target Strategy
Key
Wind Power Station Target Values (x/y/z)
Drive Train (2/2/1)
Gear Box (4/2/2)
Mechanical Brake (1/1/4)
Hydraulic System (3/1/2)
5 6 7 8
* Only the two most commonly used maintenance strategies are displayed in the cube; if value is >70% only the main strategy is listed
20 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
MaintenanceStrategy
System
Electrical Systems
Control Systems
Generator
Sensors
Sequ
entia
l Str
ateg
y
Con
ditio
n-ba
sed
Stra
tegy
Elec
tron
ics
& C
ontr
ol S
yste
ms*
Bre
ak-d
own
Stra
tegy
Tech
nica
l op
timiz
atio
n
St
rate
gy
Sing
le R
edun
danc
y St
rate
gy
Mul
tiple
Red
unda
ncy
Stra
tegy
Plan
ned
prev
entiv
e M
aint
enan
ce h
igh
Freq
uenc
y
Plan
ned
prev
entiv
e M
aint
enan
ce lo
w
Freq
uenc
y
83%1% 6% 8% 1%
53% 1% 31% 8% 6% 1%
28%3% 1% 13% 22%
33%
82%1% 5% 2% 8% 1%
Results of the Short Study – Maintenance Strategies for Components of the “Electronics & Control Systems” (currently used Strategies)
* Values rounded
9
10
11
12
21 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Maintenance Excellence by applying Risk and Reliability based Maintenance Strategies to a Wind Power Station – “Electronics & Control Systems” (Current vs. Target Strategies)
5
Impa
ct o
f Fau
lts a
nd M
alfu
nctio
ns -
y
3
5
3
5
3
1
a
b
e f
c
d
g h
low
hi
gh
1
Replacement Value - x
low high
11
12
10
9
9 83%
10 53%
10 31%
11 33%
11 28%
12 82%
All sub-systems of the „Electronic & Control Systems“ show significant deviations from the optimum strategies
Sub-system „Electrical Systems“ and “Control Systems” shows the most significant deviation from the cost-optimal maintenance strategy
%
%
%
Target Strategy
Current Strategies (Ø of all participating WPS Operators)*
Significant Deviation from Target Strategy
Medium Deviation from Target Strategy No Deviation; Current = Target Strategy
Key
* Only the two most commonly used maintenance strategies are displayed in the cube; if value is >70% only the main strategy is listed
Wind Power Station Target Values (x/y/z)
Electrical Systems (4/5/5)
Control Systems (4/4/5)
Generator (4/5/2)
Sensors (4/1/4)
9 10 11 12
22 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Key Findings of the ConMoto Short Study „Maintenance Strategies for Systems in Wind Power Stations“
More than 75% of the participating WPS operators apply to half of all evaluated sub-systems maintenance strategies that deviate significantly from the optimum strategies
► Down times and maintenance costs can be significantly reduced by systematically implementing cost-optimal maintenance strategies
Pitch System Yaw System Drive Train Electrical Systems Control Systems Sensors
More than 30% of the participating WPS operators apply partly optimum maintenance strategies to 1/4 of all evaluated sub systems
Almost 50% of the participating WPS operators apply the near optimum / optimum maintenance strategies to 1/4 of all evaluated systems
Blades Mechanical Brake Generator
Hub Gear Box Hydraulic System
23 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
What does this mean for Onshore Wind Power Stations?
35 x WPS total installed power: 52,5 MW Costs per installed kilowatt: € 1.100 Total investment: ~ 58 Mio.€
Annual service and maintenance costs: 848 k€ (2,6% of the WPS investment costs, w/o tower, w/o auxiliary investment costs)
Reduction of direct maintenance costs by 15%
Cost savings: 127 k€/a
Example 1: Onshore Wind Farm with 35 Wind Power Stations
Assumption full load hours : 1.900 h/a Produced energy / year (theoretical): 99.750 MWh Produced energy / day (theoretical): 274 MWh Ø Feed-in compensation acc. to EEG: 75 €/MWh
Ø Fault rate large WPS: 3,5 per year Ø Down time per fault / malfunction: 6 days Annual loss of feed-in compensation caused by
down time: 432 k€
Reduction of fault rate to 2/year
Cost savings: 185 k€/a
24 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
12 × 5 MW WPS total installed power: 60 MW Total investment: 250 Mio.€ Specific investment costs: 4.100 €/kW
Assumption full load hours: 3.800 h/a Produced energy / year (theoretical): 228.000 MWh Annual operating costs (offshore): 0,03 €/kWh Estimated annual service and maintenance
costs: 2,7 Mio.€ (40% of operating costs)
Reduction of direct maintenance costs by 15%
Cost savings: 405 k€/a
Example 2: Offshore Wind Farm with 12 Wind Power Stations
Produced energy / day (theoretical): 626 MWh Ø Feed-in compensation acc. to EEG: 140 €/MWh
Ø Fault rate large WPS: 3,5 per year Ø Down time per fault / malfunction: 6 days Annual loss of feed-in compensation caused by
down time: 1,8 Mio.€
Reduction of fault rate to 2/year
Cost savings: 700 k€/a
What does this mean for Offshore Wind Power Stations?
25 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Projection of annual Savings Potential for Wind Power Stations in Germany
* Assumption: 1.100 € / kW installed power
** Assumption : 1,5% of total investment (per annum)
*** Realizable through implementation of Maintenance Excellence findings and know-how
www.wind-energie.de/
► The consistent use of cost-optimal maintenance strategies could save up to 100 mio.€ in maintenance costs in the next few years and up to 200 mio.€ per year in down time costs (loss of production)
1) Source:
2011 22.000 28.000 30.800 462
2015 28.000 - 33.000 40.000 44.000 660
2020 37.000 - 40.000 54.000 59.400 891 141 - 211
104 - 156
73 - 109
89 - 134
66 - 99
46 - 69
Total Wind Power Stations Germany
Year1 Number of
WPS1
Installed Power1
[MW]
Total Invest.* [Mio. €]
Maintenance Costs**
[Mio. € / a]
Potential Savings*** Maint. Costs [Mio. € / a]
Down Time Costs [Mio. € / a]
26 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
Content
1. Basic Concept and Objectives of the Short Study „Maintenance Strategies for Systems in Wind Power Stations“
2. Wind Power Stations – Basic Data and Analysis of Fault Data
3. Cost-optimal Maintenance Strategies for Wind Power Stations
4. ConMoto Consulting Group – Facts & Figures
27 ConMoto Consulting Group GmbH We create advantage Maintenance_Excellence_Wind_Power_Stations.ppt
ConMoto basic information
20 years of experience The ConMoto Consulting Group has been supporting companies to secure and improve their competitiveness
and sustainability for more than 20 years. International expertise Around 80 consultants, distributed across our offices in Munich, Stuttgart, Vienna, St. Gallen, Bratislava, Abu
Dhabi and Shanghai, work expertly and with commitment to realize the best possible benefits for our clients.
Implementation strength Our consultants’ high qualifications, supplemented by many years of professional experience, guarantee the
pronounced implementation skill that is necessary to realize the solution concepts we develop together with our clients.
Sustainability Efficient structures and processes, strong innovation skills, effective management and sustainably mobilizing
staff are the project targets pursued within the context of a pioneering strategy.
Practical orientation Years of experience enable us to implement innovative concepts with the knowledge of what is feasible
together with our clients.
We justify your confidence “We create advantage“ is the guiding principle of our successful and implementation oriented approach.
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ConMoto Consulting Group
LEAN Excellence
Innovation Excellence
Lean Production Lean Administration Lean Value Chains Lean Development Lean Enterprise Lean Transformation Working Capital Management
Value oriented Maintenance and Asset Innovation
Risk and Reliability based Maintenance Strategies
Time Management, Scheduling, Capacity Planning
Key Performance Indicators Spare Part Management Contractor Management Value Engineering
Procurement Excellence
Lean Structures and Processes
Significant Price Reductions for goods and services to be produced
Supply Network Management Qualification Offensive
„QAMPUS“
Product Clinic Comprehensive Method Know-
how (QFD, FMEA, TRIZ) Technology Evaluation Business Area and Launch
Strategies Implementation of Product-/
Process Innovation
Value oriented Enterprise Development
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Dipl.-Ing., MBA Nils Blechschmidt Senior Partner & Executive Director for the Consulting Areas Maintenance Excellence and Asset Innovation Tel.: +49 (0)89 780 66 - 114 Fax: +49 (0)89 780 66 - 100 E-Mail: Blechschmidt@conmoto.de ConMoto Consulting Group GmbH Boschetsrieder Str. 69 81379 Munich, Germany
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