(706d) CO2 Capture and Conversion to Chemicals Via Syngas: Reactor Modeling, Process Synthesis and Optimization

Balasubramanian, P., Texas A&M University
Bajaj, I., Texas A&M University
Hasan, M. M. F., Artie McFerrin Department of Chemical Engineering, Texas A&M University
CO2 emissions from electricity generation increased by 50% between 2000 and 2013 [1]. CO2 capture and storage (CCS) has drawn wide attention in the recent past but a full-scale power plant with an integrated CCS facility would cost much more than a conventional power plant [2]. CO2 conversion for utilization can be an alternative to CCS. CO2 is a source of both carbon and oxygen and, if combined with a hydrogen source, can produce valuable hydrocarbons. Methane, from various sources, such as natural gas and shale gas, has been considered for this purpose for the conversion of CO2 to synthesis gas. This approach to capture and convert CO2 has several possibilities that can be analyzed in a systematic manner by proposing a superstructure network with all the alternatives embedded in it. The challenge is to characterize each process in the superstructure with an accurate model for a holistic analysis. We have approached this challenge by trying to strike a balance between model accuracy and complexity by analyzing the trade-offs in different models and building simpler surrogate models that can retain the model predictability. Reactor models such as stoichiometric, equilibrium, pseudo-homogeneous and heterogeneous models have been considered in this analysis. Process and design variables are taken into consideration while optimizing the process synthesis model for different objective functions such as maximum possible CO2 utilization and minimum cost of utilization. We also consider the net CO2 utilization possible by considering the auxiliary emissions from any of the processes in the superstructure. The superstructure model is generic and robust and can accommodate additional alternatives without having to change the model. Different syngas ratios and different applications based on these ratios are discussed as well. The superstructure model is formulated as a mixed-integer nonlinear optimization (MINLP) model and is solved to optimality using the global solver ANTIGONE [3]. In this presentation, we will discuss our overall synthesis framework and the optimization results.


[1] I. E. A. (IEA), "CO2 Emissions From Fuel Combustion - Highlights - 2015 Edition," 2015.

[2] Z. Yuan, M. R. Eden, and R. Gani, "Toward the Development and Deployment of Large-Scale Carbon Dioxide Capture and Conversion Processes," Industrial & Engineering Chemistry Research, vol. 55, pp. 3383-3419, 2016/03/30 2016.

[3] R. Misener and C. A. Floudas, "ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations," Journal of Global Optimization, vol. 59, pp. 503-526, 2014.