A Comprehensive Review of Modeling and Optimization Methods for Ship Energy Systems

Journal Article (2023)
Author(s)

Foivos Mylonopoulos (TU Delft - Marine and Transport Technology)

Henk Polinder (TU Delft - Transport Engineering and Logistics)

Andrea Coraddu (TU Delft - Ship Design, Production and Operations)

Department
Marine and Transport Technology
Copyright
© 2023 F.M. Mylonopoulos, H. Polinder, A. Coraddu
DOI related publication
https://doi.org/10.1109/ACCESS.2023.3263719
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 F.M. Mylonopoulos, H. Polinder, A. Coraddu
Department
Marine and Transport Technology
Volume number
11
Pages (from-to)
32697-32707
Reuse Rights

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Abstract

This paper presents a comprehensive literature review of the state-of-the art modeling and optimization methods for the power and propulsion systems of ships. Modeling is a tool to investigate the performance of actual systems by running simulations in the virtual world. There are two main approaches in modeling: physics-based and data-driven, which are both covered in detail in this survey paper. The output from the simulations might not be optimal in terms of certain performance criteria such as energy consumption, fuel cost etc. Hence, it is vital to optimize the systems considering the efficient interaction between the components, to yield the optimal performance for the integrated vessel's powertrain. In this paper, the optimization case studies, for the ship energy systems, will be divided in terms of a) optimal design (topology and sizing), b) optimal control and energy management strategies, c) combined optimal design and control. Tables that summarize the literature review outcomes will also be presented at the end of each section. The main outcome is that limited literature is available for optimizations of ship powertrains using data-driven models, especially surrogate models. Surrogate-assisted optimizations for integrated ship energy systems can yield optimal solutions at fast computational speeds, with sufficient accuracy, even for complex, nested, multi-level, multi-objective optimizations.