Superstructure modeling and stochastic optimization of side-stream extractive distillation processes for the industrial separation of benzene/cyclohexane/cyclohexene

Abstract

The non-sharp side-stream extractive distillation (SSED) differs from the sharp one in that it partially, instead of entirely, collects intermediate components through the side stream. Compared to the sharp one, the non-sharp SSED is preferred in some extractive distillation (ED) systems with high boiling-point solvents. However, the number of candidate configurations increases sharply when a design considers both the sharp and non-sharp SSEDs. Correspondingly, it results in a challenge to optimization, particularly in systems with multiple side-stream options. In this study, we propose an adaptive superstructure-differential evolution (DE) method which optimizes the sequences and parameters simultaneously. As a case study, the industrial benzene/cyclohexane/cyclohexene separation is optimized, which has two extractive distillation columns and 30 feasible configurations with different SSED options. Compared to the conventional superstructure-DE approach, the improved method, which selects the feasible flowsheet instead of predetermining a random one, performs better in the optimization. The less computational cost and better solutions demonstrate its superiority. Moreover, the optimized 3-column and 4-column SSED configurations apply non-sharp side-stream options, which proves that the non-sharp SSED options are more competitive for this ternary system. In summary, this study highlights the significance to consider both the sharp and non-sharp SSED configurations and provides a systematic approach to find high-quality configurations from an increased number of candidates.