current trends of wind farm maintenance

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IN EUROPE

CURRENT TRENDS OF WIND FARM MAINTENANCE

Dipl.-Ing. M.Sc. Stefan Faulstich Dipl.-Wi.-Ing. P. Lyding, M.Sc. Paul Kühn Fraunhofer Institute for Wind Energy and Energy System Technology (IWES)

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The Fraunhofer Society in Germany 60 Institutes at 40 locations

München

Holzkirchen

Freiburg

Efringen- Kirchen

Freising Stuttgart

Pfinztal Karlsruhe Saarbrücken

St. Ingbert Kaiserslautern

Darmstadt Würzburg

Erlangen

Nürnberg

Ilmenau

Schkopau

Teltow

Oberhausen

Duisburg

Euskirchen Aachen

St. Augustin

Schmallenberg

Dortmund

Potsdam Berlin

Rostock

Lübeck Itzehoe

Braunschweig

Hannover

Bremen

Bremerhaven

Jena

Leipzig

Chemnitz

Dresden

Cottbus Magdeburg

Halle

Fürth

Wachtberg

Ettlingen

Holzen

Kassel

Kassel

Bremerhaven

Formerly: Fraunhofer Center for Wind Energy and Maritime Engineering CWMT in Bremerhaven Institute for Solar Energy Technology ISET in Kassel

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Motivation Starting Point: Modern wind turbines achieve high availability

Number of faults cause unplanned downtimes high maintenance efforts and costs

Offshore: drop of availability expected

200

6/2

00

7

200

7/2

00

8

Barr

ow

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Scientific Measurement and Evaluation Program („250 MW Wind‚ (1989-2006))

193.000 monthly operation reports and 64.000 Incident reports from 1.500 wind turbines

1983

2010

Failure Database: WMEP

Reliability

Technology development

Learning curves

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Failure Database: WMEP

© Fraunhofer IWES

Maintenance organisation

Wind Energy Conventional power plants

General

Structure decentralised arranged and centralised

Experience low decades

Operating conditions

operation unmanned, fully automated manned, semi-automatically

Condition assessment exclusively on sensors Senses and experience of staff

External conditions Changing and extreme conditions Constant conditions by enclosing

Load Fluctuating power output and imposed loads Quasi-stationary operation


Staff Often, little own qualified staff Skilled and trained service personnel

Documents deficient, according to the manufacturer's good will contractually agreed part of the delivery

Process optimized to maximize profits from the manufacturer optimized for LCC

Documentation deficient according to the Group's internal requirements

Standardization insufficient, cycling is often reinvented Established standard culture

Information No feedback of experience Evaluating long-term findings

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Maintenance

Strategy

• reactive • time based • condition based • reliability based

Event

• failure • fault • inspection • repair

Documentation

• subassembly • cause • time steps • cost

Archiving • core data (RDS-PP) • in-service data • event data (EMS)

Analysis • MTBF, MTTR • weak points • expenses • life cycle cost

Planning • improvement • consolidation • interval opt. • responsibility

Accurate, detailed documentation Consistent naming of components Unified description of irregularities and activities

Design • verification • modification

Lacking of a closed maintenance loop

Use of operating experiences

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Maintenance strategies The reliability based maintenance tries to find the right time for maintenance measures through analysing a broad data base filled with experiences from the past

The condition based maintenance strategy tries to find the optimum point in time for carrying out the required maintenance actions by monitoring the current state of a specific component

Preventive maintenance strategies try to react before a failure occurs

With the cyclic maintenance strategy components of the wind turbine will be inspected and maintained cyclically, e. g. on semi annual intervals

It can be distinguished between reactive and preventive maintenance strategies

Within the break down maintenance strategy the system will be operated until a major failure of a component will result in a shut down

Maintenance strategies

Reactive Maintenance

Preventive Maintenance

Break down

Cyclic Condition

based Reliability

based

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Value of Experience

12

34

56

7

8

9

10

1

2

3

4

5

0,00,20,40,60,81,01,21,41,61,82,02,22,42,62,83,03,23,43,63,84,0

mea

n a

nn

ua

l fa

ilu

re f

req

ue

nc

y

year of operation year of

production

Optimization of intervals

Optimization of strategies

LCC prediction

Constitute priorities

Source: IZP Dresden

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Appropriate Failure Statistics

Year of operation??? Turbine type???

For differential analysis distinctions regarding size, technical concepts, site conditions, etc. must be made

WMEP-DB

1453 WEAs

>3. year of product ion

527 WEA

1.-3. year of product ion

926 WEA

P<500kW

783 WEA

P≥1000kW

16 WEA

500kW≤P<1000kW

127 WEA

asynchronous

584 WEA

synchronous

199 WEA

Coast line

102 WEA

highlands

33 WEA

lowlands

64 WEA

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Establishing a common database

The project Offshore~WMEP is a follow-up project to the onshore wind energy monitoring program ‘Scientific Measurement and Evaluation Program’ (WMEP) and accompanies the offshore wind energy deployment in Germany

Funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety

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Conclusions

Potential for availability improvement and for reducing maintenance effort exists

Clear trend from reactive to preventive measures

Use of operating experience essential

Common database needed due to parameter diversity

Different concepts necessary

Overall data structure

Standards and definitions (e.g. RDS-PP)

Accessibility of information

Several groups and projects deal with the topic of establishing a common database

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Outlook

TASK 11 IEA Wind: BASE TECHNOLOGY INFORMATION EXCHANGE Topical Expert Meeting #65 (March 30-31, 2011) on ‚INTERNATIONAL STATISTICAL ANALYSIS ON WIND TURBINE FAILURES‛

IEA-Task-proposal ‚Reliability Data - Standardization of data collection for wind turbine reliability and maintenance analyses‛

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Thank you for your attention

Dipl.-Ing M.Sc. Stefan Faulstich [email protected] Reliability & Maintenance strategies R&D Division Energy Economy and Grid Operation Fraunhofer Institute for Wind Energy and Energy System Technology IWES Königstor 59, 34119 Kassel