Economic analysis of condition monitoring systems for offshore wind turbine sub-systems
(2015) In IET Renewable Power Generation 9(8). p.900-907- Abstract
The use of condition monitoring systems on offshore wind turbines has increased dramatically in recent times. However, their use is mostly restricted to vibration based monitoring systems for the gearbox, generator and drive train. A survey of commercially available condition monitoring systems and their associated costs has been completed for the blades, drive train, tower and foundation. This paper considers what value can be obtained from integrating these additional systems into the maintenance plan. This is achieved by running simulations on an operations and maintenance model for a wind farm over a 20 year life cycle. The model uses Hidden Markov Models to represent both the actual system state and the observed condition... (More)
The use of condition monitoring systems on offshore wind turbines has increased dramatically in recent times. However, their use is mostly restricted to vibration based monitoring systems for the gearbox, generator and drive train. A survey of commercially available condition monitoring systems and their associated costs has been completed for the blades, drive train, tower and foundation. This paper considers what value can be obtained from integrating these additional systems into the maintenance plan. This is achieved by running simulations on an operations and maintenance model for a wind farm over a 20 year life cycle. The model uses Hidden Markov Models to represent both the actual system state and the observed condition monitoring state. The CM systems are modelled to include reduced failure types, false alarms, detection rates and 6 month failure warnings. The costs for system failures are derived, as are possible reductions in costs due to early detection. The detection capabilities of the CM systems are investigated and the effects on operational costs are examined. Likewise, the number of failures detected 6 months in advance by the CM systems is modified and the costs reported.
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- author
- May, Allan ; McMillan, David and Thöns, Sebastian LU
- publishing date
- 2015-11-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IET Renewable Power Generation
- volume
- 9
- issue
- 8
- pages
- 8 pages
- publisher
- Institution of Engineering and Technology
- external identifiers
-
- scopus:84947279511
- ISSN
- 1752-1416
- DOI
- 10.1049/iet-rpg.2015.0019
- language
- English
- LU publication?
- no
- id
- 8419c593-7fe1-4cc1-8667-071ec563f08f
- date added to LUP
- 2020-09-09 10:07:33
- date last changed
- 2022-04-03 04:48:03
@article{8419c593-7fe1-4cc1-8667-071ec563f08f,
abstract = {{<p>The use of condition monitoring systems on offshore wind turbines has increased dramatically in recent times. However, their use is mostly restricted to vibration based monitoring systems for the gearbox, generator and drive train. A survey of commercially available condition monitoring systems and their associated costs has been completed for the blades, drive train, tower and foundation. This paper considers what value can be obtained from integrating these additional systems into the maintenance plan. This is achieved by running simulations on an operations and maintenance model for a wind farm over a 20 year life cycle. The model uses Hidden Markov Models to represent both the actual system state and the observed condition monitoring state. The CM systems are modelled to include reduced failure types, false alarms, detection rates and 6 month failure warnings. The costs for system failures are derived, as are possible reductions in costs due to early detection. The detection capabilities of the CM systems are investigated and the effects on operational costs are examined. Likewise, the number of failures detected 6 months in advance by the CM systems is modified and the costs reported.</p>}},
author = {{May, Allan and McMillan, David and Thöns, Sebastian}},
issn = {{1752-1416}},
language = {{eng}},
month = {{11}},
number = {{8}},
pages = {{900--907}},
publisher = {{Institution of Engineering and Technology}},
series = {{IET Renewable Power Generation}},
title = {{Economic analysis of condition monitoring systems for offshore wind turbine sub-systems}},
url = {{http://dx.doi.org/10.1049/iet-rpg.2015.0019}},
doi = {{10.1049/iet-rpg.2015.0019}},
volume = {{9}},
year = {{2015}},
}