Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106777
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Title: LNG bunkering infrastructure planning at port
Authors: Guo, Y 
Yan, R 
Qi, J 
Liu, Y 
Wang, S 
Zhen, L 
Issue Date: Jun-2024
Source: Multimodal transportation, June 2024, v. 3, no. 2, 100134
Abstract: Ships are traditionally powered by fossil fuels such as heavy fuel oil (HFO) and marine diesel oil (MDO), where the emissions, such as particulates, hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOX) and carbon dioxide (CO2), negatively affect the environment and human health. The International Maritime Organization (IMO) encourages shipping companies to use liquefied natural gas (LNG), which is a green fuel source to power shipping activities and is easy to store, to replace traditional marine fuels. There are three common methods of LNG bunkering: ship-to-ship, truck-to-ship, and port-to-ship. The objective of this study is to determine the optimal bunkering method at a port using an integer linear programming (ILP) model considering three kinds of costs: fixed, variable, and extra. To find the optimal bunkering method, the three methods and their related constraints are modeled into the ILP model. The results indicate that ship-to-ship is the optimal bunkering method for LNG under the scenario of the port considered. Numerical experiments are conducted to validate model performance and generate managerial insights.
Keywords: Clean energy
Integer linear programming (ILP)
Liquid natural gas (LNG) bunkering
Maritime transportation
Vessel fuel
Publisher: Elsevier BV
Journal: Multimodal transportation 
ISSN: 2772-5871
EISSN: 2772-5863
DOI: 10.1016/j.multra.2024.100134
Rights: ©2024 The Authors. Published by Elsevier Ltd on behalf of Southeast University. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
The following publication Guo, Y., Yan, R., Qi, J., Liu, Y., Wang, S., & Zhen, L. (2024). LNG bunkering infrastructure planning at port. Multimodal Transportation, 3(2), 100134 is available at https://doi.org/10.1016/j.multra.2024.100134.
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