Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12624
Title: Power performance and dynamic response of the WLC wave energy converter based on hydroelastic analysis
Authors: Michailides, Constantine 
Keywords: Hinge internal axial load;Hydroelasticity;Power performance;Water Level Carpet (WLC);Wave Energy Converters
Category: Environmental Engineering
Field: Engineering and Technology
Issue Date: Sep-2017
Publisher: Elsevier Ltd
Source: International Journal of Marine Energy, 2017, Volume 19, Pages 83-94
DOI: https://doi.org/10.1016/j.ijome.2017.06.001
Abstract: In the present paper, a novel Wave Energy Converter (WEC) named hereafter as Water Level Carpet (WLC) is introduced. Its dynamic response and performance are evaluated based on hydroelastic analysis and are presented for both regular and irregular waves. WLC consists of four floating modules inter-connected flexibly in two directions with hinges and Power Take-Off (PTO) mechanisms with known damping characteristics. The dynamic response (e.g. axial load at hinges, motions) and the estimation of the produced power of the WLC are evaluated through linear hydroelastic analysis in frequency domain with the use of a radiation/diffraction 3D hydroelastic model considering the effect of both the flexibility of the WLC as well as the damping forces associated with the energy extraction by the PTO mechanisms. The results that are obtained demonstrate the relationship between the produced power and the dynamic response of the WLC as well as the relationship between the damping coefficients of the PTO with the axial loads of WLC's hinges. The produced power of WLC obtains its maximum value for wave frequencies close to the resonance of the generalized degrees of freedom irrespectively of the direction that the waves have. Moreover, the results that are obtained emphasize the importance of the hydroelastic analysis for the assessment of the performance of this type of WEC.
URI: http://ktisis.cut.ac.cy/handle/10488/12624
ISSN: 22141669
Rights: © 2017 Elsevier Ltd.
Type: Article
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