Windt, Christian, Faedo, Nicolás, Penalba, Markel and Ringwood, John (2019) Assessment of the Evaluation Framework for Energy Maximising Control Systems for the Wavestar Wave Energy Converter. In: 2019 American Control Conference (ACC). IEEE, pp. 4791-4796. ISBN 9781538679265
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Abstract
During the design process and evaluation of energy maximising control systems (EMCSs) for wave energy converters (WECs), control techniques rely heavily on numerical
modelling. For fast computation, these numerical models are
mostly based on low-fidelity boundary element method (BEM)
codes and linear hydrodynamic models. However, to ensure
optimal performance in a physical environment, more realistic,
high-fidelity numerical frameworks, such as Computational
Fluid Dynamics (CFD) based numerical wave tanks (CNWTs),
should be considered during the evaluation of EMCSs. This paper investigates the influence of different numerical evaluation
frameworks on the performance evaluation of EMCSs. The
Wavestar WEC, subject to three different EMCSs with varying
aggressiveness, i.e. resistive, reactive and moment-based control,
is chosen as the case study. Results show that more aggressive
EMCSs require high-fidelity numerical modelling to correctly
evaluate their performance.
Item Type: | Book Section |
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Additional Information: | Funding: This paper is based upon work supported by Science Foundation Ireland under Grant No. 13/IA/1886. Cite as: C. Windt, N. Faedo, M. Penalba and J. V. Ringwood, "Assessment of the Evaluation Framework for Energy Maximising Control Systems for the Wavestar Wave Energy Converter," 2019 American Control Conference (ACC), Philadelphia, PA, USA, 2019, pp. 4791-4796, doi: 10.23919/ACC.2019.8814713. |
Keywords: | Assessment; Evaluation; Framework; Energy Maximising Control Systems; Wavestar; Wave Energy Converter; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research Faculty of Science and Engineering > Electronic Engineering |
Item ID: | 14283 |
Identification Number: | 10.23919/ACC.2019.8814713 |
Depositing User: | Professor John Ringwood |
Date Deposited: | 30 Mar 2021 13:24 |
Publisher: | IEEE |
Refereed: | Yes |
Funders: | Science Foundation Ireland (SFI) |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/14283 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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