Effective semicontinuous distillation design for separating normal alkanes via multi-objective optimization and control

Abstract As a process intensification technology, semicontinuous distillation uses less equipment to achieve the separation of multiple components. However, there is still a lack of systematic guidance for the design of semicontinuous distillation. In this paper, we propose a new method to guide the design of semicontinuous distillation via multi-objective optimization (MOO) and control. Conventional continuous distillation, dividing wall column (DWC) distillation and semicontinuous distillation for separation of n-alkanes are optimized through multi-objective genetic algorithm (MOGA). Several different control schemes are proposed for semicontinuous distillation, and the temperature-concentration cascade control scheme CS5 is selected as the optimal control scheme. The economic benefits of semicontinuous distillation based on dynamic simulation are evaluated by the comparison with the conventional continuous distillation and DWC under a series of throughput. It is found that the total annual cost (TAC) of the semicontinuous distillation is smaller than that of conventional continuous distillation when the annual throughput is less than 7.73 × 104 kmol/yr. And the TAC of the semicontinuous distillation is less than that of DWC when the annual throughput is less than 5.29 × 104 kmol/yr. Therefore, we can conclude that the semicontinuous distillation has better economic benefits than the other two configurations within the smaller annual throughput.