Adaptive Model Predictive Control of Wave Energy Converters
- Submitting institution
-
Queen Mary University of London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 646
- Type
- D - Journal article
- DOI
-
10.1109/TSTE.2018.2889767
- Title of journal
- IEEE Transactions on Sustainable Energy
- Article number
- -
- First page
- 229
- Volume
- 11
- Issue
- 1
- ISSN
- 1949-3029
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2020
- 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
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A novel adaptive hierarchical control framework for wave energy converters (WECs) is proposed to successfully improve the conversion efficiency of WECs by 10%-40% in varying realistic sea conditions, which significantly reduces the unit cost of electricity. This is a key research output from the Advanced Newton Fellowship jointly funded by the Royal Society and NSFC, China (NA160436) 2017, and also the Stage 2 project (£180K) of Wave Energy Scotland’s control programme in 2018 and led to the award of the final Stage 3 project (£460K) for FloWave tank testing in 2020 (Iain Begg iain.begg@waveenergyscotland.co.uk) https://www.waveenergyscotland.co.uk/news-events/wes-awards-new-advanced-control-system-projects-1m/
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -