A methodology for the heuristic optimization of solvent-based CO2 capture processes when applied to new flue gas compositions: A case study of the Chilled Ammonia Process for capture in cement plants

Publication date

2020

Authors

Pérez-Calvo, José Francisco
Sutter, Daniel
Gazzani, MatteoORCID 0000-0002-1352-4562ISNI 0000000492887250
Mazzotti, Marco

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Advisors

Supervisors

Document Type

Article
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Abstract

Solvent-based post-combustion CO2 capture technologies are key to timely decrease industrial CO2 emissions. However, the flue gas composition differs among different industries so that different optimal operating conditions are expected. This work provides a methodology to determine the operating conditions that minimize energy consumption and maximize productivity of the capture process, for given flue gas composition and process specifications, while keeping the time required for process development at a minimal level. Firstly, it carries out a comprehensive selection and calibration of the model. Secondly, it applies a step-wise heuristic optimization procedure. In this work, this methodology has been demonstrated by means of the Chilled Ammonia Process (CAP) applied to cement plants. The optimal CAP operation has led to reboiler duties as low as 2.1 MJth kgCO2captured-1, while maintaining the productivity of the CO2 absorber, thus the column height, at values similar to those typical of the power plant application.

Keywords

Aqueous ammonia, Cement plants, CO capture, Process optimization, Rate-based model, Reactive absorption, General Chemistry, General Chemical Engineering, Industrial and Manufacturing Engineering, SDG 9 - Industry, Innovation, and Infrastructure, SDG 13 - Climate Action

Citation

Pérez-Calvo, J F, Sutter, D, Gazzani, M & Mazzotti, M 2020, 'A methodology for the heuristic optimization of solvent-based CO 2 capture processes when applied to new flue gas compositions : A case study of the Chilled Ammonia Process for capture in cement plants', Chemical Engineering Science: X, vol. 8, 100074. https://doi.org/10.1016/j.cesx.2020.100074