(27g) CO2 Capture and Conversion to Chemicals Via Syngas: Rigorous Modeling, Intensification, and Superstructure-Based Process Synthesis

Hasan, M. M. F., Artie McFerrin Department of Chemical Engineering, Texas A&M University
Balasubramanian, P., Texas A&M University
Bajaj, I., Texas A&M University
Recent global warming and climate change are attributed to increased CO2 emission from fossil fuels. Significant efforts have been made in the past to develop CO2 capture and sequestration (CCS) technologies. However, large-scale CCS is still not deployed in reality for reasons including high cost, technological barriers and uncertainty in geological storage. A promising alternative to CCS is to convert CO2 to value-added chemicals via syngas (CO and H2), which is an intermediate for many hydrocarbon-based fuels and chemicals. As much as 2 Gt/yr of fuels and 200 Mt/yr of chemicals can be produced from CO2 utilization [1].

In this work, we explore alternative technologies and routes for the thermochemical conversion of CO2 to syngas and then syngas to various oxygenates. We postulate a flowsheet superstructure which includes layers with various alternatives for separation, conversion and upgrading. We allow both pure and dilute raw materials, such as CO2 from flue gas, methane from stranded sources, oxygen from air and water, and hydrogen from renewables and other sources. A novel feature of our superstructure is that it also includes various intensified alternatives. One such example is the inclusion of a tri-reforming membrane reactor which, instead of using pure CO2, uses the mixed flue gas as feed, produces syngas, and separates nitrogen from the product at the same time. Therefore, it does not need a separate CO2 capture section at the upstream. For each alternative, we develop a rigorous model detailing the transport and kinetics to accurately predict the process performance. We use a pseudo-homogenous model for plug-flow reactors (PFR) [2] to describe various alternatives for CO2 reforming (e.g., steam methane reforming, dry-reforming, tri-reforming, partial oxidation, and variants of combined reforming). Using the rigorous simulation platform, we also develop efficient surrogate models [3] for conversion as it changes with reactor type, design and operating conditions. The replacement of the ODE models with their algebraic surrogates allows us to pose the overall synthesis problem as a mixed-integer nonlinear optimization (MINLP) problem, which we solve to optimality using ANTIGONE [4]. We consider different objectives such as maximizing the overall utilization of CO2, minimizing the total annualized cost, and maximizing profit. We also take into account the auxiliary carbon dioxide emissions associated with various processing tasks in the network. In this presentation, we will discuss our overall synthesis framework and the optimization results.


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[2] Aboosadi, Z. A.; Jahanmiri, A. H.; Rahimpour, M. R. Optimization of tri-reformer reactor to produce synthesis gas for methanol production using differential evolution (DE) method. Applied Energy, 88(8):2691â??2701, 2011.

[3] Bajaj, I.; Hasan, M. M. F. Effective Sampling, Modeling and Optimization of Constrained Black-Box Problems. Accepted for publication in proceedings of ESCAPE26, Slovenia, 2016.

[4] Misener, R.; Floudas, C. A. ANTIGONE: algorithms for continuous/integer global optimization of nonlinear equations. Journal of Global Optimization. 59 (2-3), 503-526, 2014.