Optimization of vessel fleet size and mix for offshore wind farm maintenance based on a simulation method

Master thesis (2023)

Authors

K. WU Mechanical Engineering

Contributors

X. Jiang Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 1)
M. Li Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 2)
M.B. Duinkerken Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2023 KANGJIE WU
Optimization Simulated annealing Simulation model Operation and maintenance Offshore wind farm Fleet size and mix problem Salabim
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Published Date

25-05-2023

Language

English

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Faculty

Mechanical Engineering

Abstract

The research on sustainable energy is growing, among which, wind energy catching growing attention and the potential has been supported by more and more countries. Compared with onshore wind farms, offshore wind farms have more advantages including the abundant wind resource at the offshore location and more possible construction areas. While for an offshore wind farm, the operation and maintenance cost is the most significant part and fleet management contributes a lot to it.

In order to optimize the fleet size and mix problem for an offshore wind farm based on a simulation method, this thesis has performed a few research steps. Firstly, a literature view on the modeling methods of fleet size and mix problems for offshore wind farms is finished. Different modeling methods and different factors considered in the model are viewed. Then, two simulation models, the open-loop simulation model and the feedforward simulation model, are introduced, including the model inputs, model agent and process, and model outputs. Afterward, the simulation-optimization methodology is introduced and the optimization algorithm used in this research is introduced. Next, one case study using two models separately for a long-term optimization and a short-term optimization is executed and followed by the results of these two simulation models as well as the comparison of the results from them.

This thesis aims to combine the optimization method with a simulation model for offshore wind farms, which can be regarded as a decision support tool for fleet size and mix problems and is expected to be a practical technology for the operator/researcher of the offshore wind farm in the future.