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

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.

References:

[1] Quadrelli, E. A.; Centi, G.; Duplan, J.-L.; Perathoner, S. Carbon Dioxide Recycling: Emerging Large-Scale Technologies with Industrial Potential. ChemSusChem. 2011, 4:1194â??1215.

[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.