Abstract
There is a large financial incentive to minimise operations and maintenance (O&M) costs for offshore wind power by optimising the maintenance plan. The integration of condition monitoring (CM) and structural health monitoring (SHM) may help realise this. There is limited work on the integration of both CM and SHM for offshore wind power or the use of imperfectly operating monitoring equipment. In order to investigate this, a dynamic Bayesian network and limit state equations are coupled with Monte Carlo simulations to deteriorate components in a wind farm.
The CM system has a ‘deterioration window’ allowing for the possible detection of faults up to 6 months in advance. The SHM system model uses a reduction in the probability of failure factor to account for lower modelling uncertainties.
A case study is produced that shows a reduction in operating costs and also a reduction in risk. The lifetime levelised costs are reduced by approximately 6%.
Original language | English |
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Title of host publication | Proceedings of the ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering |
Number of pages | 7 |
Publication date | 2015 |
Article number | OMAE2015-41126 |
Publication status | Published - 2015 |
Event | ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering - St John’s, Canada Duration: 31 May 2015 → 5 Jun 2015 Conference number: 34 |
Conference
Conference | ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering |
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Number | 34 |
Country/Territory | Canada |
City | St John’s |
Period | 31/05/2015 → 05/06/2015 |
Keywords
- Offshore wind
- Cost-benefit analysis
- Condition monitoring systems
- Structural health monitoring
- Operations and maintenance