Yeter, B.; Garbatov, Y. Optimal Life Extension Management of Offshore Wind Farms Based on the Modern Portfolio Theory. Oceans2021, 2, 566-582.
Yeter, B.; Garbatov, Y. Optimal Life Extension Management of Offshore Wind Farms Based on the Modern Portfolio Theory. Oceans 2021, 2, 566-582.
Yeter, B.; Garbatov, Y. Optimal Life Extension Management of Offshore Wind Farms Based on the Modern Portfolio Theory. Oceans2021, 2, 566-582.
Yeter, B.; Garbatov, Y. Optimal Life Extension Management of Offshore Wind Farms Based on the Modern Portfolio Theory. Oceans 2021, 2, 566-582.
Abstract
The present study aims to develop a risk-based approach to find optimal solutions for life extension management for offshore wind farms based on Markowitz’s modern portfolio theory, adapted from finance. The developed risk-based approach assumes that the offshore wind turbines (OWT) can be considered as cash-producing tangible assets providing positive return from the initial investment (capital) with a given risk attaining the targeted (expected) return. In this regard, the present study performs a techno-economic life extension analysis within the scope of the multi-objective optimisation problem. The first objective is to maximise the return from the overall wind assets, while the latter aims to minimise the risk associated with obtaining the return. In formulating the multi-dimensional optimisation problem, the life-extension assessment considers the results of a detailed structural integrity analysis, free-cash-flow analysis, and probability of project failure, local and global economic constraints. Further, the risk is identified as the variance from the expected mean of return on investment. The risk-return diagram is utilised to classify the OWTs of different classes using an unsupervised machine learning algorithm. The optimal portfolios for the various required rate of return are recommended for different stages of life extension.
Keywords
Offshore wind; life extension; modern portfolio theory; unsupervised machine learning; monopile; risk management
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
