Abstract
A mathematical model for the design of small-scale supply chains for liquefied natural gas (LNG) has been developed. It considers the maritime delivery of LNG from supply ports to satellite terminals and land-based transports from the terminals to consumers on or off the coast. Both tactical and strategic aspects in the supply chain design are addressed by optimizing the maritime routing of a heterogeneous fleet of ships, truck connections, and the locations of the satellite terminals. The objective is to minimize the overall cost, including operation and investment costs for the selected time horizon. The model is expressed as a mixed-integer linear programming problem, applying a multi-period formulation to determine optimal storage sizes and inventory at the satellite terminals. Two case studies illustrate the model, where optimal LNG supply chains for a region with sparsely distributed island (without land transports) and a coastal region at a gulf (with both sea and land transports) are designed. The model is demonstrated to be a flexible tool suited for the initial design and feasibility analysis of small-scale LNG supply chains.
Highlights
The model is demonstrated to be a flexible tool suited for the initial design and feasibility analysis of small-scale liquefied natural gas (LNG) supply chains
Natural gas can be liquefied at atmospheric pressure by cooling it below −162 ◦ C, which increases the density by a factor of 600 and yields what is called liquefied natural gas (LNG)
The model developed in this paper is based on earlier work by the authors [7,8], where a single-period model was developed for the design of small-scale LNG supply chains
Summary
Natural gas can be liquefied at atmospheric pressure by cooling it below −162 ◦ C, which increases the density by a factor of 600 and yields what is called liquefied natural gas (LNG). The model developed in this paper is based on earlier work by the authors [7,8], where a single-period model was developed for the design of small-scale LNG supply chains The formulation addresses both strategic and tactic decisions, where the location of the satellite terminals, the size of the fleet of vessels, and their routing and deliveries are optimized. We apply an exact method but neglect some operational aspects that are not essential for initial planning of supply chains: we do not consider scheduling, supply availability according to production rate or inventory, boil-off loss, time windows at the ports, or load-dependent fuel consumption in the transportation vehicles With these simplifications, a MILP model was formulated that can solve real problems within a few hours of computation time. At the end of the paper, some conclusions concerning the applicability of the model are drawn and future potential directions of research in the field are proposed
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