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Site selection for offshore renewable energy platforms: a multi-criteria decision-making approach

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posted on 2024-03-13, 03:53 authored by Minghan BaoMinghan Bao

This thesis presents an innovative methodology for site selection of offshore renewable systems, addressing the growing global energy demand and the need for sustainable solutions to climate change. Recognizing waves as a significant, yet underutilized renewable energy source, this research focuses on optimizing Wave Energy Converter (WEC) deployment amidst the uncertainties and costs of offshore environments. The study involves a comprehensive evaluation of potential sites, considering key factors like power generation capacity, mooring system fatigue life, and tether response to extreme loads.

Initial wave data analysis for various locations is followed by numerical simulations of a point absorber WEC under different conditions. A Bayesian Network (BN) model is then employed to integrate uncertainties in multi-criteria decision-making, enhancing the robustness of site selection. This approach facilitates the calculation of utility values for various site and installation options, leading to the identification of the optimal decision alternative based on maximum expected utility.

This work provides a detailed framework for stakeholders in the renewable energy sector, aiding in the assessment of both profitability and survivability of WECs in chosen locations. It significantly contributes to minimizing economic and performance risks associated with WEC installations, promoting efficient and sustainable energy production from ocean resources.

History

Table of Contents

Chapter 1: Introduction -- Chapter 2: Methodology -- Chapter 3: A Case Study of WEC Site-Selection in Australian Southern Sea -- Chapter 4: Conclusion and Recommendations -- Reference -- Appendix: Application of Bayesian Networks and Influence Diagrams in Decision-making

Notes

ADDITIONAL SUPERVISOR 3: Mohsen Asadniaye Fard Jahromi

Awarding Institution

Macquarie University

Degree Type

Thesis MRes

Degree

Master of Research

Department, Centre or School

School of Engineering

Year of Award

2024

Principal Supervisor

Rouzbeh Abbassi

Additional Supervisor 1

Nagi Abdussamie

Additional Supervisor 2

Ehsan Arzaghi

Rights

Copyright: The Author Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer

Language

English

Extent

74 pages

Former Identifiers

AMIS ID: 321518

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