Bi-Objective Optimization of Techno-Economic and Environmental Performance of CO2 Capture Strategy Involving Two-Stage Membrane-Based Separation with Recycling
Nobuo Hara, Satoshi Taniguchi, Takehiro Yamaki, Thuy T.H. Nguyen, Sho Kataoka
TL;DR
This paper optimizes CO2 capture using a two-stage membrane process, balancing cost and environmental impact while considering different membrane performance levels.
Contribution
The study introduces a bi-objective optimization framework combining machine learning and genetic algorithms for CCUS membrane design.
Findings
Electricity consumption significantly affects both operating costs and CO2 emissions.
Improving α*(CO2/N2) enhances process performance more than increasing membrane permeability.
Pareto solutions reveal trade-offs between techno-economic and environmental objectives.
Abstract
To effectively implement complex CO2 capture, utilization, and storage (CCUS) processes, it is essential to optimize their design by considering various factors. This research bi-objectively optimized a two-stage membrane-based separation process that includes recycling, concentrating on minimizing both costs and CO2 emissions. The implemented algorithm combined experimental design, machine learning, genetic algorithms, and Bayesian optimization. Under the constraints of a recovery rate of 0.9 and a produced CO2 purity of 0.95, six case studies were conducted on two types of membrane performance: the Robeson upper bound and a tenfold increase in permeability. The maximum value of α*(CO2/N2), used as a constraint, was adjusted to three levels: 50, 100, and 200. The analysis of the Pareto solutions and the relationship between each design variable and the final evaluation index indicates…
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Taxonomy
TopicsMembrane Separation and Gas Transport · Carbon Dioxide Capture Technologies · Green IT and Sustainability