A Joint Probability Distribution Model for Multivariate Wind and Wave Conditions

• Published in: Volume 2: Structures, Safety, and Reliability
• Main Authors: Vanem, Erik, Fekhari, Elias, Dimitrov, Nikolay, Kelly, Mark, Cousin, Alexis, Guiton, Martin
• Format: Article in Journal/Newspaper
• Language: English
• Published: The American Society of Mechanical Engineers (ASME) 2023
• Subjects: Joint probability distributions; Wind-wave environment; Offshore wind; Renewable energy; Environmental loads; /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy; Arctic
• Online Access: https://orbit.dtu.dk/en/publications/e5ce5d93-a89c-4df6-aa81-a6a7a538d9db; https://doi.org/10.1115/OMAE2023-101961

This paper presents a joint statistical model that has been fitted to data of wind and wave conditions for an offshore location at South Brittany. The data are from a numerical model and contain hourly values for several wind and wave variables over a period of 32 years. The joint distribution presented in this paper considers the variables wind direction, mean wind speed, significant wave height, wave direction and peak period. A conditional model for turbulence given wind speed is introduced to yield an additional variable for the joint model. The joint model is constructed as a product of marginal and conditional models for the various variables. Additionally, the fitted models will be used to construct environmental contours for some of the variables. For significant wave height, various models are used to obtain different extreme value estimates, illustrating the uncertainties involved in extrapolating statistical models beyond the support of the data, and a discussion on the use of non-parametric copulas for the joint distribution is presented. Such joint distribution models are important input for design of offshore structures, and in particular for offshore wind turbines and the influence of the joint model in design is illustrated by a simple case study.