ANN-based techno-economic optimization of a hybrid membrane-absorption CO2 capture system under varying power mix and carbon tax conditions

초록

Membrane-absorption hybrid CO2 capture processes are highly sensitive to electricity prices and carbon intensity, making their economic performance strongly dependent on policy conditions such as carbon taxation and power-mix decarbonization. However, most optimization studies have primarily focused on steady-state technical performance, providing limited insight into how economic optimality changes under evolving policy scenarios. In this study, a hybrid membrane-monoethanolamine (MEA) process is optimized using an artificial neural network (ANN) surrogate model coupled with a genetic algorithm (GA). The ANN, trained using Latin Hypercube Sampling data generated from a detailed hybrid process simulation, accurately predicts CO2 recovery, purity, energy consumption, and capture cost. The optimized configuration achieves more than 90% CO2 recovery and over 98% purity, with a specific energy requirement of 1.80 GJ t- 1 CO2 and a capture cost of 45 USD t- 1 CO2. A key contribution of this work is the policy-integrated assessment of process optimality. For each electricityprice, emission-factor, and carbon-price scenario, capture-cost labels were recalculated using detailed simulation outputs, and a scenario-specific Cost ANN was coupled with GA re-optimization. Under carbon taxation, the electricity-intensive membrane section substantially increases capture cost when powered by coal-based electricity, whereas renewable electricity effectively mitigates both cost escalation and indirect emissions. The renewable-electricity hybrid process approached the cost of the fixed MEA-only reference near a crossover of 30 USD t- 1 CO2 and became the lowest-cost configuration beyond this crossover. These results demonstrate that the economic competitiveness of CO2 capture technologies varies significantly depending on policy and energy-mix conditions, highlighting the importance of policy-integrated techno-economic evaluation.

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