A Multi-Objective Optimization Model for Offshore Wind Farm Operations & Maintenance Fleet Selection

Master thesis (2023)

Authors

J.S. Bloothoofd Mechanical Engineering

Contributors

R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (graduation committee member)
X. Jiang Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (mentor)
V. Dighe TNO (graduation committee member)
M.B. Duinkerken Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (graduation committee member)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2023 Jesse Bloothoofd
More Info
expand_more

Published Date

29-03-2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical Engineering

Abstract

Until recently, tenders in Europe were awarded to wind farm developers based on the highest auction prices or the lowest subsidized bids. The wind industry has suggested that non-price-related criteria should be considered for tenders, like plans to reduce greenhouse gas emissions. As a result of the sustainable tender criteria, greenhouse gas emissions are a relatively new KPI for offshore wind farm developers.

Studies have shown that the costs and wind farm availability are sensitive to the fleet composition and were commonly used as criteria in offshore wind fleet optimization models. Offshore wind greenhouse gas emissions were shown to be sensitive to the offshore wind fleet composition as well but thus far not used as criteria for fleet composition decision-making. This study aims to develop an offshore wind O&M multi-objective fleet optimization model that includes GHG emissions as the third criterion for the fleet composition. The model is rendered as a deterministic MIP problem. An epsilon constraint method-inspired approach is proposed to reformulate the multi-objective into a set of perturbed single-objective models, which can be solved using a commercial MIP solver.