The increasing production of shale gas and, consequently, natural gas liquids (NGLs) provides opportunities to expand the U.S. chemical industry, leading to questions about how to best use these resources. We consider targets for the strategic use of ethane, the most abundant of the NGLs, by evaluating the impact of a potential, new catalytic dehydrogenation technology for converting ethane to ethylene and then evaluating potential, new catalytic oligomerization processes for converting ethylene to 1-butylene and to 1-octene. To conduct these evaluations, we introduce a new, nonlinear, industry-wide, optimization-based network model of the U.S. petrochemical and refining industries. Unlike previous linear models of this type, the nonlinear model accounts for changes in intermediate prices and, thus, process costs as new technology is added to the industry network. A method for propagating cost and price changes, permitting the solution of the nonlinear optimization problem as a sequence of linear problems, is developed and utilized. Using network models for this study, we account for and identify the direct and secondary consequences of introducing new technology on the rest of the industry. For each new technology evaluated, we determine the production level of the technology in the optimal industry network. By doing this over a wide range of net process cost points, a maximum adoption cost (the net process cost beyond which the technology would not be adopted) can be identified, and its sensitivity to the assumed product yield determined for each new technology can be studied. The maximum adoption costs can be viewed as targets for future catalyst research, reaction engineering, and process development work. Scenarios in which the ethane supply is constrained to current values and in which it is unconstrained are considered.
The Marcellus Shale region is rich
in natural gas liquids (NGLs)
and a likely future hub for NGL derivatives such as ethylene. A geospatial
network model of the U.S. petrochemicals and refining industry is
developed and utilized to assess the potential for the adoption of
a technology for oligomerization of ethylene to gasoline, or a gasoline
blend stock, as a means to utilize NGL derivatives available in the
region. The model is a mixed-integer linear program with the objective
of minimizing the total annual cost incurred by the regional industry.
Case studies in which this technology is added to the industry network
model are described, and sensitivity analyses are conducted to investigate
the effect of model parameters such as the prices of crude oil and
ethylene. These results can be used as cost target benchmarks for
this new technology. More broadly, this work demonstrates a geospatial
network modeling approach for evaluating new processing technology.
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