Decommissioning of Offshore Wind Turbines

A model-based approach to assess cost reducing decommissioning methodologies

Master thesis (2022)

Authors

R.R. Groenewegen Mechanical Engineering

Contributors

J.J. Hopman Ship Design, Production and Operations - Mechanical, Maritime and Materials Engineering (mentor)
H. Polinder Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (graduation committee member)
M. Li Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (coach)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2022 Rik Groenewegen
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Published Date

08-07-2022

Language

English

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Faculty

Mechanical Engineering

Abstract

The first large offshore wind farms installed in the North Sea Region (NSR) soon reach their technical end of lifetime. The wind turbines in these farms will have to be decommissioned after power production has stopped. Currently offshore wind turbines are decommissioned based on a method called reversed installation, a time consuming and therefore costly operation. This report focuses on the situation regarding decommissioning of offshore wind turbines (excluding foundations), and unveils the possibilities of potential decommissioning methods, using a jack-up, in an effort of to obtain a more cost-effective and environmentally friendly method than the currently used reversed installation. The act of decommissioning is explained, together with the expected market of decommissioning in the North Sea Region. Legislation concerning decommissioning of the five largest offshore wind producing countries in Europe are discussed. Using a multi criteria analysis on demolition methods, floating alternatives, and a model (determining the transport configuration), the most economical and least energy consuming combination is chosen. This model shows an economization of up to 66% and cutting the energy consumption by a third. Lastly, these outcomes are applied to three separate business cases including a sensitivity analysis to show the effect that variations in input values have on the results.

Files

TUD_Thesis_RRGroenewegen.pdf
(pdf | 4.6 Mb)
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