Abstract
Knowledge about stochastic environmental loads and the response of the substructure are essential in fatigue damage calculations for offshore wind turbines. Site-specific and high-quality met-ocean data that contains joint measurements of wind and waves however, are not always available. An approach based on copulas was used to generate lumped joint met-ocean data in a location where only marginals (i.e., individual, univariate probability distributions) are known. Empirical copulas were calculated for different stations in the North Sea for pairs of wind speed and wave height variables. These copulas are then combined with marginals from another station to generate lumped data. The generated data is compared with the known lumped joint data, and the difference of two methods is measured. The lumped values are used to estimate fatigue damage based on simple formulas. The results show that the joint behaviour of wind speed and wave height follows a similar pattern around the North Sea. In addition, the mean difference of generated lumped wind speeds based on this technique from lumped wind speeds based on real measurements is less than 5%. The mean difference of the fatigue damage caused by the generated lumped wind speeds relative to lumped wind speeds based on real measurements is less than 5% at two locations, and less than 15% in another location. This suggests that the approach is promising for estimating joint met-ocean data at new locations in the North Sea where only marginals are available, which is of major interest for wind farm planning and design.
Highlights
An adequate representation of site-specific met-ocean data has several important applications in marine and coastal industry
The results show that the joint behaviour of wind speed and wave height follows a similar pattern around the North Sea
The mean difference of the fatigue damage caused by the generated lumped wind speeds relative to lumped wind speeds based on real measurements is less than 5% at two locations, and less than 15% in another location
Summary
An adequate representation of site-specific met-ocean data has several important applications in marine and coastal industry. Cost-efficient and reliable design of offshore wind turbines especially for fatigue damage are highly dependent on high-quality, joint met-ocean data. Reducing uncertainties in environmental data can effectively improve the planning of installation and maintenance-operation of marine structures [1]. The main drawback of offshore wind power is its comparatively high capital cost. This high cost can be attributed to more expensive support structures, grid connections and offshore installations [2]. It is expected that the wind industry will reduce its cost by 40% until 2020. Application of large offshore wind farms and large-sized monopiles in water depths of 25-
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