(788a) Adsorption Based Process for CO2 Capture and Biogas Purification
Originally presented on: 11/2/2012 8:30:00 - 8:50:00
Technologies based on amines such as MEA and KS-1 have been extensively evaluated and tested for CO2 capture from power plants. They have also been commercialzed for biogas purification. Numerous studies have indicated that the amine-based CO2 capture and removal remains fairly expensive with a CO2 capture cost of over $80/ton for a coal-fired power plant, and an increase in LCOE (levelized cost of electricity) of over 80% over the based plant without CO2 capture. The current development trajectory indicates that the solvent-based CO2 capture is not expected to achieve the DOE target of <35% increase in LCOE with CO2 capture in the near future. Another commercial target, a CO2 capture cost of <$40/ton to enable widespread CO2 use in EOR applications in the absence of any climate legislation, is also likely to remain elusive for the solvent-based processes in the foreseeable future. In this paper preliminary experimental results, and techno-economic analysis of an adsorbent-based CO2 capture process will be presented. The process is based on physical sorption and has the potential to reduce the cost of CO2 capture by more than 40% over MEA resulting in a CO2 capture cost of less than $50/ton. The process also has the potential to limit the increase in LCOE with CO2 capture to less than 50%. With additional process optimization and integration with the power plant the process has the potential to meet the commerical CO2 EOR target of <$40/ton, and the DOE CO2 capture target of <35% increase in LCOE with CO2 capture in a timeframe which is signficantly shorter than the solvent based processes. The technology is also applicable to CO2 removal from raw biogas produced by anaerobic digestion and results in more than 50% reduction in the natural gas purification cost compared to amines in this appliaction. The technology could be potentially commercialized in this application in less than four years with learnings utilized to reduce the CO2 capture costs in power plant applications.