(390r) Hybrid Solvent-Sorbent Post-Combustion Capture with Single and Layered Beds of Functionalized MOF – Process Modeling and Techno-Economic Optimization

High CO₂ capture rates for carbon emissions from industrial sources, such as natural gas power plants, have been studied using different solvent technologies. However, these high capture rates typically come at the cost of exponentially increasing energy requirement in typical absorption systems to regenerate the solvent. This high regeneration energy is enhanced at high capture rates due to the low lean loading needed for the absorption column to make the process feasible. This high energy penalty results in capture costs ranging from 74 to 111 USD/t CO₂ [1]. A common solution to this method is implementing intercooling along the absorption column, which reduces temperatures to improve the thermodynamic favorability at low CO₂ partial pressures. This results in a higher loading of the solvent improving the overall efficiency of the process. Studies have shown that the regeneration energy can be reduced by up to 25% with optimal operation with intercoolers [2]. Another benefit gained from using intercoolers is that packing area in the absorber column can be reduced by upwards of 62% while maintaining the same performance [3].

However, these absorption systems still do reach limitations on the higher range of capture due to these solvents not being designed for very low partial pressures of CO₂. A potential option for reaching very high capture rates is to use an amine appended metal organic framework (MOF). These MOFs perform well even for very low partial pressures of CO₂ due to high affinity for CO₂ and a very high working capacity, even under humid conditions that are found in post combustion processes [4]. However, excessive capital cost results are likely if the MOF is used for both bulk and high capture. In this work, we propose an optimal hybridization of the solvent and sorbent-based capture systems especially for achieving high capture from low concentrated flue gas sources.

Many studies have investigated designing hybrid capture processes, which combine different capture technologies with the goal of improving efficiency and increasing capture. Many of the works utilized membranes in conjunction with amine solvents to utilize both physical and chemical separation technologies, which show that costs can be decreased by upwards of 9% when comparing to solvent absorption alone [5]. However, there has been little to no work in literature that combines solvent absorption for capturing the bulk of CO₂ from post-combustion sources and adsorption beds for polishing the capture to meet high capture targets. In this work, a hybrid capture system design is developed that uses a rate-based MEA solvent absorption system capable of high accuracy in the range of >90% capture [6], and a solid sorbent based capture system that can utilize either or both tetraamine and diamine appended MOFs [4], [7] to boost the overall capture to 99, 99.5, and 99.9% capture. Typically, these MOF sorbents are implemented in fixed-bed systems due to the simplicity of the design, but fixed beds have drawbacks caused by larger pressure drops that result in lower capacity of the bed and require a larger footprint. A potential better bed configuration is a unique rotating packed bed design that operates as a counter current cross flow bed but has separate sections for simultaneous adsorption and desorption. This design allows the process to operate in a steady-state manner while achieving a high working capacity of the sorbent and less complex operation compared to fixed beds.

Different configurations of the sorbent beds are considered for single sorbent and layering of both sorbents being used. Both of these models are implemented within the equation-oriented modeling language Pyomo [8], which has access to state-of-the-art solvers that are required to solve highly nonlinear models and is able to solve rigorous optimization problems with the availability of first and second derivatives. Currently in literature, little work for the techno-economic optimization of either of these technologies has been done, especially with using MEA, due to a lack of rigorous process and cost models that can be applied in an equation-oriented framework. Most works consider surrogate objective function, such as energy consumption minimization, as a replacement for doing a cost of capture optimization. In this work, a cost model for the processes is developed to enable direct optimization of the cost of capture subject to a wide range of decision variables, process constraints, and feed conditions. Results of this optimization show that there can be a significant benefit to utilizing the sorbent polishing capture, especially when targeting 99.9% capture, which can reduce the capture cost by upwards of 15%.

Acknowledgement

The authors graciously acknowledge funding from the U.S. Department of Energy, Office of Fossil Energy and Carbon Management, through the Carbon Capture Program.

Disclaimer

This project was funded by the Department of Energy, National Energy Technology Laboratory an agency of the United States Government, in part, through a support contract. Neither the United States Government nor any agency thereof, nor any of its employees, nor the support contractor, nor any of their employees, makes any warranty, expressor implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or any of their contractors.

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