LNG Logistics Model to Meet Demand for Bunker Fuel

Ewelina Orysiak (), Hubert Zielski and Mateusz Gawle
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Ewelina Orysiak: Faculty of Navigation, Maritime University of Szczecin, 1/2 Wały Chrobrego Street, 70-500 Szczecin, Poland
Hubert Zielski: Faculty of Navigation, Maritime University of Szczecin, 1/2 Wały Chrobrego Street, 70-500 Szczecin, Poland
Mateusz Gawle: Faculty of Navigation, Maritime University of Szczecin, 1/2 Wały Chrobrego Street, 70-500 Szczecin, Poland

Energies, 2024, vol. 17, issue 7, 1-22

Abstract: The main objective of this manuscript is to build a model for the distribution of LNG as a marine fuel in the southern Baltic Sea based on a genetic algorithm in terms of cost. In order to achieve this, it was necessary to develop, in detail, research sub-objectives like analysis of the intensity of ship traffic in the indicated area and analysis of LNG demand in maritime transport. In the first part of this study, the authors use data from the IALA IWRAP Mk2 and the Statistical Office in Szczecin to analyse the marine traffic density (by type of vessel) in the southern part of the Baltic Sea. LNG used as marine fuel reduces toxic emissions into the atmosphere. The authors specify the LNG fleet size and locations of LNG storage facilities in a way to ensure that the defined LNG bunker vessels can supply fuel to LNG-powered vessels within the shortest possible time period. The database contains a set of traits necessary to determine the optimal demand for LNG. The traits were developed based on an existing LNG fleet and appropriately selected infrastructure, and they represent existing LNG-powered vessels as well as LNG bunker vessels and their specifications. Based on the created LNG distribution model, were performed in Matlab R2019a software. An LNG distribution model was developed, which uses a genetic algorithm to solve the task. The demand for LNG for the sea area under analysis was determined based on data on the capacity of LNG-powered vessels (by type of vessel) and their distance from the specified port.

Keywords: energy security; transportation safety; transport infrastructure; traffic optimisation; traffic modelling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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