(628g) Automated Process Design and Techno-Economic Assessment of Membrane-Based CO2 Capture Systems

Considerable efforts from academic and industrial communities have been made to develop cost-effective and energy-efficient CO₂ capture processes. A wide range of separation techniques, for example, amine solvents, dry sorbent and membranes, are available, and Techno-Economic Assessment (TEA) is necessary to evaluate technical feasibility and compare economics in a systematic and fair manner. In this presentation, Techno-Economic Assessment model will be addressed, with which economic evaluation of membrane-based CO₂ capture processes is made and then comparison is made with other capture technologies, for example, amine-based capture process, for gaining conceptual insights in the development required for membrane process in the context of CO₂ capture. Based on TEA model presented, CAPEX and OPEX of membrane-based CO₂ capture process is obtained, subject to economic parameters and process design constraints. CO₂ capture cost and avoidance cost are also estimated. TEA also accommodates economic benefits gained from the application of process integration between CO₂ emitting plant and CO₂ capture process, while process optimization technique is fully used for minimizing overall cost at the capture process level. Sensitivity analysis is made to understand techno-economic impact of process design and their performance on capture cost. The membrane-based CO₂ separation process is simulated and optimized with authors’ in-house process design framework developed in MATLAB^® environment, which can effectively identify the cost-effective configuration of multi-stage membrane systems, together with full consideration of CO₂ liquefaction. Case study will be given to demonstrate the benefits of TEA for critical and systematic evaluation of different capture technologies in a holistic manner.

Acknowledgement

This research was supported by the Korea Carbon Capture & Sequestration R&D Center (KCRC) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, and ICT (NRF-2014M1A8A1049338)