Process integration of lithium based high temperature CO2 capture in power and industrial plants
Abstract
Lithium orthosilicate (Li4SiO4) sorbents have been reported to show relatively high CO2
capture capacity, high stability and require lower regeneration temperatures than other
high-temperature sorbents. Based on these properties, a CO2 capture plant concept could
be envisaged, aiming for achieving as low as possible CO2 capture penalties.
Accordingly, this work presents a conceptual process integration study and techno-economic assessment that evaluates the integration of Li4SiO4-based looping systems into
a Natural Gas Combined Cycle (NGCC) power plant and Sorption Enhanced Steam
Methane Reforming (SESMR) H2 Production plant for CO2 capture. Based on previously
obtained experiment results, absorption and regeneration temperatures of 525-550 and
700 C, respectively, and a sorbent fractional conversion of 0.2, were used to build NGCC
and SESMR plants process models. The process integration results showed that
implementation of a Li4SiO4-based high temperature carbon capture (HTCC) system into
a NGCC power plant reduces the plant efficiency by 9.2% penalty points. The techno-economic assessment resulted in a levelized cost of electricity (LCOE) and a cost of CO2
avoided equal to 73.9£/MWh and 75.6 £/tCO2, respectively. For the SESMR plant, an
equivalent net hydrogen production efficiency penalty of 8.2% was obtained after the
integration of the Li-based carbon capture plant. A levelized cost of hydrogen (LCOH)
and cost of CO2 avoided equal to 159.3 £/kNm3
and 72.7 £/tCO2, respectively, were
obtained using the same techno-economic assessment method applied in the NGCC case
study. For both case studies, the Li4SiO4-based HTCC integration performance is
compared to other capture technologies, including amine-based solvents and Calcium
looping (CaL) systems, for benchmarking purpose. A parametric sensitivity analysis was
conducted for each case study by varying several techno-economic parameters and by
evaluating the impact of the variation on the plant Key Performance Indicators (KPIs).
Finally, recommendations and guidelines for possible future work are suggested.