Data-driven condition monitoring approaches to improving power output of wind turbines
- Submitting institution
-
The University of Lancaster
- Unit of assessment
- 12 - Engineering
- Output identifier
- 254771345
- Type
- D - Journal article
- DOI
-
10.1109/TIE.2018.2873519
- Title of journal
- IEEE Transactions on Industrial Electronics
- Article number
- -
- First page
- 6012
- Volume
- 66
- Issue
- 8
- ISSN
- 0278-0046
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper comprises results from a collaboration with Zhejiang University. It describes the first report of methods for identification and control of the impact of health conditions on the turbine’s power output numerically and practically. As commented by reviewers of the paper, the results should revolutionise the ways of scheduling and dispatching wind power for wind industry. The research has led to further international collaborations on offshore renewable energy developments combining wind and wave funded by Royal Society (IEC\NSFC\170294), and on array configuration of offshore wind turbines funded by China NSFC (grant no. 51905472) to explore potential global impacts.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
