Title: Modelling and simulating of GTCC system with CO₂ removal plant using Aspen Plus

Authors: Rongrong Zhai, Yongping Yang, Liqiang Duan, Qin Yan

Addresses: Beijing Key Laboratory of Safe and Clean Energy Technology, Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing, 102206, China. ' Beijing Key Laboratory of Safe and Clean Energy Technology, Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing, 102206, China. ' Beijing Key Laboratory of Safe and Clean Energy Technology, Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing, 102206, China. ' Beijing Key Laboratory of Safe and Clean Energy Technology, Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing, 102206, China

Abstract: CO₂ capture and storage (CCS) from power plants is drawing increasing interest as a potential method for the control of greenhouse gas emissions. A technical parameter study for a CO₂ removal plant from flue gas of a gas turbine combined cycle (GTCC) syngas-fired power plant was performed, based on absorption/regeneration process with monoethanolamine (MEA) solutions, using Aspen Plus. The efficiency drop due to CO₂ removal plant is approximately 12.9 percentage points, from 55.5% to 42.6%. The research results show that the stripper pressure, MEA inlet flow rate, MEA inlet weight percentage, distillate rate and reflux ratio have great impacts on the performance of the CO₂ removal plant.

Keywords: CO2 removal plant; gas turbine combine cycle; GTCC; Aspen Plus; reboiler duty; modelling; simulation; carbon dioxide; carbon capture; carbon storage; greenhouse gases; GHG emissions; flue gas; monoethanolamine; stripper pressure; MEA inlet flow rate; MEA inlet weight percentage; distillate rate; reflux ratio.

DOI: 10.1504/IJMIC.2009.027890

International Journal of Modelling, Identification and Control, 2009 Vol.7 No.4, pp.365 - 370

Published online: 14 Aug 2009 *

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