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Design, process simulation and construction of a 100 kW pilot-scale CO2 membrane rig: Improving in situ CO2 capture using selective exhaust gas recirculation (S-EGR)

Authors: GOHARI DARABKHANI, Hamidreza; Jurado, Neila; Prpich, George; Oakey, John; Wagland, Stuart; Anthony, Edward;

Design, process simulation and construction of a 100 kW pilot-scale CO2 membrane rig: Improving in situ CO2 capture using selective exhaust gas recirculation (S-EGR)

Abstract

Carbon capture and storage (CCS) from natural gas fired systems is an emerging field and many of the concepts and underlying scientific principles are still being developed. Cranfield University has worked as part of a consortium on a UK-funded project called Gas-FACTS to enhance the CO2 capture performance from natural gas-fired power plants using exhaust gas recirculation (EGR) and selective EGR (S-EGR) technologies. Preliminary studies suggest this approach can boost the CO2 content in the feed gas up to 3 times compared to the ‘no recycle’ case (CO2 concentration increased to 18% vs. 6%), with a consequent reduction in flow to the post-combustion capture unit by a factor of three compared to conventional, non S-EGR. For this project, Cranfield developed a pilot-scale 100 kW CO2 membrane rig facility in order to investigate simultaneously EGR and S-EGR technologies, the latter being achieved by using a CO2 sweep air polymeric membrane. A bench-scale membrane rig has also been developed to investigate the permeability and selectivity of different polymeric membranes to CO2. Currently a small-scale polydimethylsiloxane (PDMS) membrane module is also being investigated to study its selectivity/permeability. The tests include exploring the performance improvement of the PDMS membrane using different operating conditions with a view to developing scale-up procedures for the membrane unit for the actual 100 kW pilot-scale rig.\ud \ud Process simulations were performed using Aspen Plus software to predict behaviour of the pilot-scale rig using a model developed based on empirical parameters (i.e., mass transfer coefficient of CO2 through the membrane and permeance), measured in the bench-scale membrane test unit. The results show that CO2 concentrations of up to 14.9% (comparable to CO2 level in coal combustion) can be achieved with 60% EGR, with a 90% CO2 removal efficiency of the membrane units. However, the results generated with the membrane model in which specific permeance values to PDMS were applied, predicted concentrations of CO2 in flue gases up to 9.8% (v/v) for a selective recycle of 60%. The study shows that the S-EGR technique is an effective method that can provide similar conditions to that of a coal-fired power plant for the post-combustion capture system operating on natural gasfired units, but also highlights the fact that more research is required to find more suitable materials for membranes that optimise the CO2 removal efficiencies from the flue gas. \ud \ud Keywords: Carbon dioxide capture; Gas-CCS; Exhaust gas recirculation (EGR); CO2 selective membrane, Selective EGR (S-EGR)

Country
United Kingdom
Related Organizations
Keywords

CO2 selective membrane, 660, Selective EGR (S-EGR), Gas-CCS, Exhaust gas recirculation (EGR), Carbon dioxide capture

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green
hybrid