Title
Fatigue Load Emulation of Offshore Wind Turbines Using Advanced Surrogate Models
Author
Restrepo Botero, Miguel (TU Delft Aerospace Engineering)
Contributor
Yu, W. (mentor) 
Iliopoulos, Alexandros (mentor)
Stinenbosch, T. (mentor)
Degree granting institution
Delft University of Technology
Programme
Aerospace Engineering
Date
2022-09-25
Abstract
Understanding the fatigue load history of wind turbines is critical for taking decisions regarding the lifetime of a project. However, direct measurement of fatigue loads at each turbine in a wind farm is unfeasible. For this reason, surrogate models offer a useful alternative. In this thesis, a methodology for creating surrogate models for emulating fatigue loads of offshore wind turbines is presented. The methodology is unique in that it accounts for the variability of site-specific conditions that may be present between wind turbines of the same class. First, a method for creating simplified structural models which depends only on a few degrees of freedom is derived. After this, a database of simulation data is assembled by varying the geometric, dynamic, and environmental degrees of freedom within ranges which capture a high degree of variability of possible site-specific conditions. This database is then used to train surrogate models using neural networks.
Subject
Machine Learning
Fatigue Analysis
Surrogate Modeling
Neural Network
Sensitivity Analysis
To reference this document use:
http://resolver.tudelft.nl/uuid:4fde9c1f-9886-4868-8d91-9eb8ec74151a
Embargo date
2024-09-01
Part of collection
Student theses
Document type
master thesis
Rights
© 2022 Miguel Restrepo Botero