Evaluating the efficiency and cost-effectiveness of RPB-based CO2 capture: A comprehensive approach to simultaneous design and operating condition optimization

Despite ongoing global initiatives to reduce CO2 emissions, implementing large-scale CO2 capture using amine solvents is fraught with economic uncertainties and technical hurdles. The Rotating Packed Bed (RPB) presents a promising alternative to traditional packed towers, offering compact design and adaptability. Nonetheless, scaling RPB processes to an industrial level is challenging due to the nascent nature of its application. The complexity of designing RPB units, setting operating conditions, and evaluating process performance adds layers of difficulty to the adoption of RPB-based systems in industries. This study introduces an optimization-driven design and evaluation for CO2 capture processes utilizing RPB columns. By employing detailed process simulation, we aim to concurrently optimize unit design and operating parameters, underscoring its advantage over conventional sequential approaches. Our process design method integrates heuristic design recommendations as constraints, resulting in 9.4% to 12.7% cost savings compared to conventional sequential design methods. Furthermore, our comprehensive process-level analysis reveals that using concentrated MEA solvent can yield total cost savings of 13.4% to 25.0% compared to the standard 30 wt% MEA solvent. Additionally, the RPB unit can deliver an 8.5 to 23.6 times reduction in packing volume. While the commercial-scale feasibility of RPB technology has been established, the advancement of this field hinges on acquiring a broader and more robust dataset from commercial-scale implementations. Employing strategic methods like modularization could significantly reduce the entry barriers for CO2 capture projects, facilitating their broader adoption and implementation.