A Performance Monitoring Approach for the Novel Lillgrund Offshore Wind Farm
- Submitting institution
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University of Exeter
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1982
- Type
- D - Journal article
- DOI
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10.1109/TIE.2015.2442212
- Title of journal
- IEEE Transactions on Industrial Electronics
- Article number
- -
- First page
- 6636
- Volume
- 62
- Issue
- 10
- ISSN
- 0278-0046
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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D - Dynamics and Control
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research significantly enhanced the methodology for predictive monitoring of large wind turbine populations. The population-based monitoring concept, which was used for the first time in wind turbines, allowed the operating data from one turbine to be used for the performance prediction of all the rest inside the farm. The work was a collaboration with Vattenfall Wind Power (eoghan.maguire@vattenfall.com) and has led to additional publications and projects (£880k EP/R003645/1). This invited paper for a special issue presents research funded by EPSCRC (£891k EP/J016942/1 & £3.7m EP/K003836/2) and formed part of a keynote IFAC SAFEPROCESS, Paris 2015 (k.worden@sheffield.ac.uk)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -