Optimization of a small-scale LNG supply chain

Due to an increased interest in small to medium scale liquefied natural gas (LNG) use, a mathematical model has been developed to aid the decision making on tactical aspects in the design of such LNG logistic chains. The focus of the work is on inter-terminal maritime transportation between a set of...

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Veröffentlicht in:Energy (Oxford) 2018-04, Vol.148, p.79-89
Hauptverfasser: Bittante, A., Pettersson, F., Saxén, H.
Format: Artikel
Sprache:eng
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Zusammenfassung:Due to an increased interest in small to medium scale liquefied natural gas (LNG) use, a mathematical model has been developed to aid the decision making on tactical aspects in the design of such LNG logistic chains. The focus of the work is on inter-terminal maritime transportation between a set of supply ports and a set of sparsely distributed receiving ports with given demands. Similar problems have been largely studied in literature, but our approach differs in including simultaneously load splitting features, multi depots and a multiple journeys between ports on the same route. The model, which considers the LNG distribution by a heterogeneous fleet of ships, applies mixed integer linear programming to find the supply chain structure that minimizes costs associated with fuel procurement. A case study illustrating the features of the model is presented, where a base case is initially solved. An extensive sensitivity analysis is presented which demonstrates how the optimal solution evolves under different conditions (i.g. LNG price in the supply ports, time horizon and berthing time). A preliminary attempt to tackle uncertainty in the demand is also made. Finally, the performance of the model on a set of larger problems is reported, demonstrating its efficiency. •An MILP for optimal design of a small-scale LNG supply chain is presented.•LNG supply in the Caribbean region is optimally solved.•The robustness of the solutions is illustrated in a sensitivity analysis.•The feasibility of the model is demonstrated on larger problems.
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2018.01.120