Sensitivity analysis of gas supply optimization models

Sergei Schreider (), Jonathan Plummer, Daniel McInnes and Boris Miller

Annals of Operations Research, 2015, vol. 226, issue 1, 565-588

Abstract: The security of gas supply is a crucially important question for the economy of any country. South-eastern Australia has a sophisticated network of gas pipelines that connect the production sites on the ocean shelf and in the inner part of the continent with the major consumers, which are the state capital cities (Adelaide, Melbourne, Hobart, Sydney and Brisbane) and the regional industrial town of Gladstone. Two optimization models were developed in order to test the security of the gas supply system against possible global impacts that affect the demand for natural gas. The modeling research in the present work was focused on the simulation of delivery when demands reach their peak values. The first model minimizes squares of shortfalls in major supply nodes. As major constraints the models used the production levels, supply capacities and the mass balance in pipe junctions. The second model minimizes the total cost of gas delivery, which is a sum of production and transportation costs, while the constraints stay the same. Both models were run for a series of plausible economic scenarios which generated the future values of demand. The potential “bottle necks” in the system components were identified. It was found that the first constraint which became scarce is the pipe providing gas to the port of Gladstone. The capacity of this pipe should be increased in order to meet growing demand. Gladstone is also the site of the liquefied natural gas export industry on the east coast. An increase in pipeline capacity will facilitate the increase of export from Gladstone, but will reduce supply to other consumption nodes. A sensitivity analysis (SA) was implemented for both formulations of the model. The objective was to examine how the key indicators of system security and pipeline flow were impacted by changes (increase and decrease) in peak demands. For this analysis the predicted annual scenarios for peak demand increase for four states (ACT was treated as part of NSW in the present work) were used. For the analysis of the decrease of demand, proportional changes of the same magnitude in demand were used for all demand nodes. It can be concluded that with the current infrastructure the most vulnerable components of the system are industrial gas users in Gladstone and Mt. Isa, whereas amongst the domestic consumers it is Brisbane. This conclusion can be utilized in further decisions on pipeline infrastructure upgrades. Copyright Springer Science+Business Media New York 2015

Keywords: Gas supply; Linear programming; Quadratic programming; Network optimization; Sensitivity analysis (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10479-014-1709-0

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