Reliability assessment of point-absorber wave energy converters

Kolios, Athanasios and Di Maio, Loris Francesco and Wang, Lin and Cui, Lin and Sheng, Qihu (2018) Reliability assessment of point-absorber wave energy converters. Ocean Engineering, 163. pp. 40-50. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2018.05.048)

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Abstract

Ocean wave energy is a clean and inexhaustible energy resource, capable of providing more than 2 TW of energy supply worldwide. Among all the technologies available to convert wave energy, the point-absorber is one of the most promising solutions today, due to its ease of both fabrication and installation. The floaters of point-absorber WECs (wave energy converters) are generally exposed to harsh marine environments with great uncertainties in environmental loads, which make their reliability assessment quite challenging. In this work, a reliability assessment framework, which combines parametric finite element analysis (FEA) modelling, response surface modelling and reliability analysis, has been developed specifically for the floater of point-absorber WECs. An analytical model of point-absorber WECs is also developed in this work to calculate wave loads and to validate the developed FEA model. After the validation through a series of simulations, the reliability assessment framework has been applied to the NOTC (National Ocean Technology Centre) 10 kW multiple-point-absorber WEC to assess the reliability of the floater, considering the fatigue limit state (FLS). Optimisation of key design components is also performed based on reliability assessment in order to achieve target reliability. The results show that for the considered conditions, the WEC floater is prone to experience fatigue failure before the end of their nominal service life. It is demonstrated that the reliability assessment framework developed in this work is capable of accurately assessing the reliability of WECs and optimising the structure on the basis of reliability.

ORCID iDs

Kolios, Athanasios ORCID logoORCID: https://orcid.org/0000-0001-6711-641X, Di Maio, Loris Francesco, Wang, Lin, Cui, Lin and Sheng, Qihu;