Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design

Abstract

Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.

Decoupled Modelling Approaches for Environmental Interactions with Monopile-Based Offshore Wind Support Structures

“…[173] introduced different load case reduction concepts, using Monte Carlo simulations, basing the number of simulations on either the probability of occurrence, the expected damage or the equivalence of load conditions. The sampling approaches proposed by [173] were validated by [174] on the basis of an extensive data set from the Northwind wind farm. The study demonstrated an improved performance compared to standard sampling methods.…”

A model to calculate fatigue damage caused by partial waking during wind farm optimization

“…Improvements in materials and technologies in recent years have allowed for taller towers, longer blades, and more power output (Wiser et al, 2016;Enevoldsen and Xydis, 2019). Because of their large size and associated large loads, as well as the cyclic loading caused by their rotational operation, fatigue is a vital consideration in wind turbine design (Hübler et al, 2019). Turbines must be designed to operate without failure and with minimal maintenance for the duration of their lifetime, which is usually 20-25 years (Hu et al, 2016;Ziegler et al, 2018).…”

A Model to Calculate Fatigue Damage Caused by Partial Waking during Wind Farm Optimization

“…CC BY 4.0 License. is a vital consideration in wind turbine design (Hübler et al, 2019). Turbines must be designed to operate without failure and with minimal maintenance for the duration of their lifetime, which is usually 20-25 years (Hu et al, 2016;Ziegler et al, 2018).…”