Optimum design under uncertainty of CO2 capture, utilization, mineralization and sequestration networks using rotating packed beds

This study presents a comprehensive framework for the optimal design of integrated CCUS networks within industrial clusters. The framework incorporates rotating packed bed (RPB) reactors for solvent-based CO₂ capture, CO₂ capture by mineralization and CO₂ utilization for precipitated calcium carbonate (PCC) nanoparticles production, as well as SNG production, pipeline transportation, and geological sequestration. Rigorous models for these processes are used to derive linear or piece-wise linear surrogate models, through a systematic approach that ensures accurate process predictions. The derived models are integrated into a mixed-integer linear programming (MILP) model for efficient network optimization. The framework is applied to a case study involving an industrial cluster, comprising of 5 emitters (power generation, refinery, quicklime, cement and paper plants), 3 sequestration sites, and one minerals deposit site. The framework is tested under both deterministic and uncertain conditions, accounting for fluctuations in CO₂ capture costs, CO₂ utilization raw material and product market prices, and carbon permit price. The CO₂ capture cost is the most influential factor in the operation of the entire network, with mineralization becoming favorable beyond a specific threshold. SNG synthesis becomes viable with modest raw material price decrease and product market price increase, whereas PCC production is consistently selected as the most favorable utilization route. Under high carbon permit prices, partial CO₂ capture may be economically optimal, with the remainder offset through purchasing carbon permits. The findings provide strategic insights into economic viability of alternative CO₂ pathways and support informed decision-making for future CCUS infrastructure deployment under real-world complexities.