4.6 Article

Optimization and Selection of Reforming Approaches for Syngas Generation from Natural/Shale Gas

期刊

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
卷 53, 期 5, 页码 1841-1855

出版社

AMER CHEMICAL SOC
DOI: 10.1021/ie402382w

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资金

  1. Qatar National Research Fund (Qatar Foundation) [5-066-2-023]
  2. Div Of Chem, Bioeng, Env, & Transp Sys
  3. Directorate For Engineering [1140000] Funding Source: National Science Foundation

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Reforming of natural or shale gas is the primary industrial method for the production of syngas. There are four major approaches to reforming: steam reforming, partial oxidation, dry reforming, and combinations of these reforming reactions. The selection of the reforming approach is not a straightforward task. It is highly dependent on process objectives and availability of material and energy resources. Furthermore, the reformer selection has a significant impact on: process yield, energy requirement, CO2 emissions, and wastewater generation. It also has operational implications including: catalyst life, process safety, and control. The purpose of this work is to develop a systematic tool to aid in the modeling and selection of appropriate reformers to achieve an objective. This can include particular process or economic objectives and constraints such as H-2:CO ratio. An equilibrium model is developed and solved using optimization software (LINGO). Economic, energy, and environmental constraints are included in the optimization formulation. Top-level economic scenarios were investigated including the inclusion of carbon tax, natural gas, and energy price fluctuations. The work is also extended to shale gas reforming and shows that the composition of the shale gas has a significant impact on potential yields. Given the potential variability in shale gas composition, the optimization model is also used in selecting a gas reservoir (feedstock) for specific objectives and constraints of the reforming process. The inclusion of strict energy and environmental constraints can favor some reforming options over others.

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