Natural Gas to Liquid Transportation Fuels under Uncertainty Using Robust Optimization
Title
Natural Gas to Liquid Transportation Fuels under Uncertainty Using Robust Optimization
Subject
Optimization
Natural gas transportation
Liquefied natural gas
Profitability
Uncertainty analysis
Refining
Costs
Investments
Iterative methods
Description
The current pricing climate for natural gas and liquid transportation fuels adds a significant amount of uncertainty when designing new natural gas to liquid transportation fuel (GTL) refineries. Robust optimization is a useful tool for optimization under uncertainty and can be specifically applied to the problem of GTL process synthesis under feedstock price, product price, and investment cost uncertainty. Using historical data to define uncertain price parameters according to an assumed uniform distribution, a process synthesis superstructure with an uncertain objective function was created to maximize the profit of a GTL refinery. Recently developed, tight probabilistic bounds were used a priori and a posteriori in an iterative method to provide solutions with known probabilities of constraint violation for three different uncertainty sets. The relative impact of price and investment cost uncertainties are discussed, as is the impact of uncertainty on the overall guaranteed profit of a refinery, the refinery topology, and product distributions. The profitability results with probabilistic guarantees provide useful information for potential GTL refinery investors in the current uncertain energy markets. 2018 American Chemical Society.
11112-11129
32
57
Publisher
Industrial and Engineering Chemistry Research
Date
2018
Contributor
Matthews, Logan R.
Guzman, Yannis A.
Onel, Onur
Niziolek, Alexander M.
Floudas, Christodoulos A.
Type
journalArticle
Identifier
8885885
10.1021/acs.iecr.8b01638
Collection
Citation
“Natural Gas to Liquid Transportation Fuels under Uncertainty Using Robust Optimization,” Lamar University Midstream Center Research, accessed May 14, 2024, https://lumc.omeka.net/items/show/26697.