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Last years have been characterized by a worldwide increasing attention towards the reduction of fuel consumption and carbon dioxide emissions. Several industrial fields, as well as the civil and residential sector, have introduced innovative approaches for the design and the operation of energy systems. These actions are aimed to reach higher values of energy conversion efficiency, also including an increase in the use of renewable resources. In this context, especially in the sector of cruise ships, further efforts are required to improve the energy efficiency of the employed energy systems. The aim of this paper is to propose an optimization framework based on genetic algorithms in order to maximize the energy efficiency and minimize both the fuel consumption and the thermal energy dissipation, by optimizing the load allocation of the ship energy systems. To this purpose, different strategies for the energy systems on board of an existing cruise ship are proposed and analyzed. In particular, two main engines configurations have been defined: standard (current logic of operation maintained) and hybrid configuration. For each proposed strategy – being the ship a particular and interesting application of isolated energy grid (i.e. a grid without connections with electric and fuel national grids) – an in-house-developed software has been adapted and applied to optimize the load allocation of the various energy systems. Furthermore, an economic and environmental analysis has been carried out, in order to point out the benefits – or the eventual limits – related to the proposed solutions. The considered approach is based on the concept of introducing economically and structurally suitable modifications to the current cruise energy systems configuration, in order to reach the goal of increasing the energy efficiency. The carried out analysis shows that the hybrid strategies allow to reach the best results in terms of energy (fuel consumption and heat dissipation reduction), economic and environmental points of view
François Maréchal, Julia Granacher
François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos, Réginald Germanier