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Forecasting Wind Farm Component Failures and Availability Post-Warranty. Steve Buckley. Team Leader, Wind Consultancy. Key Message. Limited historic data available – forecasting availability and costs is an inexact science - PowerPoint PPT Presentation
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Forecasting Wind Farm Component Failures and Availability Post-WarrantySteve BuckleyTeam Leader, Wind Consultancy
This presentation has been prepared by Sinclair Knight Merz (SKM) and comprises slides for a presentation concerning SKM. All views expressed are those of the presenter.
Except as advised, copyright and any other intellectual property rights in this presentation including text, graphics and layout rests exclusively with the Sinclair Knight Merz Group.
Except as advised, you may reproduce or distribute content from this presentation for personal and non-commercial purposes, or for purposes permitted by law, provided any reproduction is unaltered and a full attribution of the source is provided. If you wish to make any other use of this material, you must seek prior written permission. To ask for permission or for further information please contact: [email protected]
The SKM logo is a trade mark of Sinclair Knight Merz Pty Ltd.
Copyright © 2009 Sinclair Knight Merz Pty Ltd. All rights reserved.
Key Message• Limited historic data available – forecasting
availability and costs is an inexact science• Historic data can be used to help inform the O&M
and condition monitoring strategy• Experience with two older wind farms demonstrates
how refined forecasts can improve on generalised assumptions
Background• What are the post warranty O&M options?
– Extend existing contract
– 3rd party provider
– Scheduled O&M only
– Scheduled O&M plus minor unscheduled O&M
– Full service O&M (scheduled + unscheduled)
• How to decide which option is most appropriate?
• Sources of data e.g.:–ReliaWind/Supergen Wind
–Upwind–IEST/Windstats etc.
Using Existing Data
• Larger WTGs less reliable but lower downtime
• Electronics are a significant cause of failures
• Drivetrain failures rarer but cause significant downtime
• Failure rates increase with higher wind speeds
Calculating Sculpted Availability and Costs
Inputs
Component
MTBF
MTTR
Part Cost
Fitting Cost
Variables
Wind speed
Environment
Site
O&M provider
Type of fault5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
0.8
0.85
0.9
0.95
1
Base Case Annual Average AvailabilityWorst Case Annual Average Availability
Year
Availability (%)
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425 £-
£2,000,000
£4,000,000
£6,000,000
£8,000,000
Base case O&M Worst case O&M
Year
O&M Costs
Experience With Two Older Wind Farms
Gearbox
Generator
Pitch system
Bathtub curve?
Learning
Electrical
SCADA
Experience With Two Older Wind Farms
Bathtub curve?
Pitch system
Yaw system
General WTG
Linking Historic Data with Condition Monitoring
• When to use condition monitoring• Where to target condition monitoring• Using condition monitoring data to inform
maintenance options• Using historic data to inform condition monitoring
strategy
Key Message• Limited historic data available – forecasting
availability and costs is an inexact science• Historic data can be used to help inform the O&M
and condition monitoring strategy• Experience with two older wind farms demonstrates
how refined forecasts can improve on generalised assumptions