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Asymmetric copula–based distribution models for met-ocean data in offshore wind engineering applications

Fazeres-Ferradosa, Tiago; Taveira-Pinto, Francisco; Vanem, Erik; Reis, Maria Teresa; das Neves, Luciana
Journal article; AcceptedVersion; Peer reviewed
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v2+Fazeres-Ferradosa+Tiago+manuscript.pdf (1.155Mb)
Year
2018
Permanent link
http://urn.nb.no/URN:NBN:no-75787

CRIStin
1592212

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  • Matematisk institutt [2453]
  • CRIStin høstingsarkiv [15978]
Original version
Wind Engineering : The International Journal of Wind Power. 2018, 42 (4), 304-334, DOI: https://doi.org/10.1177/0309524X18777323
Abstract
Joint statistical models for long-term wave climate are a key aspect of offshore wind engineering design. However, to find a joint model for sea-state characteristics is often difficult due to the complex nature of the wave climate and the physical constraints of sea-states phenomena. The available records of wave heights and periods are often very asymmetric in their nature. This article presents a copula-based approach to obtain the joint cumulative distribution function of the significant wave heights and the up-crossing mean period. This study is based on 124-month hindcast data concerning Horns Rev 3 offshore wind farm. The extra-parametrization technique of symmetric copulas is implemented to account for the asymmetry present in the data. The analysis of the total sea, the wind-sea and primary swell components is performed separately. The results show that the extra-parametrization technique with pairwise copulas consistently provided a better goodness-of-fit when compared to symmetric copulas. Moreover, it is demonstrated that the separation of the total sea into its components does not always improve the extra-parametrized copula’s performance. Furthermore, this article also discusses copulas application to offshore wind engineering.
 
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