Techno-economic Optimization of a Green-Field Post-Combustion CO2 Capture Process Using Superstructure and Rate-Based Models

Journal Article (2016)
Author(s)

Ung Lee (RWTH Aachen University)

Jannik Burre (RWTH Aachen University)

Adrian Caspari (RWTH Aachen University)

Johanna Kleinekorte (RWTH Aachen University)

Artur Schweidtmanna (RWTH Aachen University)

Alexander Mitsos (RWTH Aachen University)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1021/acs.iecr.6b01668
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Publication Year
2016
Language
English
Affiliation
External organisation
Issue number
46
Volume number
55
Pages (from-to)
12014-12026

Abstract

A techno-economic optimization of a commercial-scale, amine-based, post-combustion CO2 capture process is carried out. The most economically favorable process configuration, sizing and operating conditions are identified using a superstructure formulation. The superstructure has 12 288 possible process configurations and unit operations in the superstructure are described using rigorous, rate-based models. In order to simplify the optimization problem, the problem is decomposed and process simulations are explicitly handled in the process simulator. Optimization is performed externally using a genetic algorithm. The best found process configuration includes the absorber intercooling, the rich vapor recompression, and the cold solvent split. The result of this study is compared in terms of the cost of capture basis and shows 38% reduction on the annual operation cost, compared to the conventional amine-based CO2 capture process. Moreover, the savings on the total annualized cost is ∼13%, which is an increase of 30% on the annualized investment cost resulting from additional unit operations. (Figure Presented).

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