Mixed integer linear programming optimization of gas supply to a local market

A1 Journal article (refereed)


Internal Authors/Editors


Publication Details

List of Authors: Markéta Mikolajková, Henrik Saxén, Frank Pettersson
Publisher: American Chemical Society
Place: Washington, D.C.
Publication year: 2018
Journal: Industrial & Engineering Chemistry Research
Journal acronym: Ind. Eng. Chem. Res.
Volume number: 57
Issue number: 17
Start page: 5951
End page: 5965
eISSN: 1520-5045


Abstract

Remote or stranded areas that cannot be supplied by natural gas through transmission pipelines can access gas through terminals for liquefied natural gas (LNG), from where LNG is distributed by trucks or compressed and regasified into regional distribution networks. The gas supply may be further augmented by local biogas or synthetic natural gas. A model for optimization of such regional gas supply chains is presented in the paper, considering a combination of pipeline and truck delivery to a set of customers with given energy demands. After linearization, the task is formulated as a mixed integer linear programming (MILP) problem and is solved by state-of-the-art software. The model is illustrated on a regional energy supply problem considering seasonal variations in the demands. The results of the study demonstrate the role of the price of the local and alternative fuels and the price margins at which it is feasible to build an extensive pipeline network instead of supplying the fuel by trucks to storages connected to pipeline islands. The findings also give information about the influence on investment versus operation costs on the optimal design of the supply chain. The sensitivity of the optimal supply chain on the price of local and alternative fuels as well as on the unit price of pipes and storage tanks is studied to illustrate how optimization can be used to shed light on the feasibility of investment in new infrastructure and to support the decision making processes in the energy sector.


Keywords

LNG, MILP, Natural gas network, Optimization

Last updated on 2019-08-12 at 03:11