Retrofit of an industrial solvent recovery system: Distillation sequence intensification and simulation-based optimization

• Published in: Chemical engineering research & design 2022-04, Vol.180, p.164-177
• Main Authors: Yang, Minbo, Li, Ting, Feng, Xiao, Rong, Ben-Guang, Wang, Yufei
• Format: Article
• Language: English
• Subjects: Amplification; Distillation; Distillation sequence intensification; Energy conservation; Energy costs; Energy saving; Hexanes; Hydraulic correlations; Optimization; Recovery; Retrofitting; Rubber; Sequences; Simulation; Simulation-based optimization; Solvent recovery system; Solvents
• ISSN: 0263-8762; 1744-3563
• DOI: 10.1016/j.cherd.2022.02.020

[Display omitted] •An evolutionary strategy for retrofitting distillation sequence based on existing columns•A simulation-optimization method to optimize operating conditions of a distillation sequence.•Shortened distillation sequences to the solvent recovery system with notable energy savings.•Insights in energy saving from aspects of distillation sequence and column internals. An industrial solvent recovery system in a rubber process consists of four distillation columns to recover solvent and unreacted 1,3-butadiene monomer. After the solvent is changed from raffinate oil to hexanes, it needs to investigate whether the current system can be retrofitted to reduce the number of columns and save energy. This work presents stepwise retrofit of the solvent recovery system by distillation sequence intensification and simulation-based optimization. Based on insights in distillation columns, an evolutionary strategy is introduced to generate intensified distillation sequences from the current distillation system. Next, a simulation-based optimization method considering comprehensive hydraulic evaluation is developed to obtain the best operating parameters of distillation columns. Seven distillation sequence alternatives to the current solvent recovery system are generated. The result indicates that the most compact sequence with two distillation columns can decrease the energy cost by 41.50%, while the preferred solution is a three-column sequence with the least modifications that reduces the energy cost by 33.13%. The proposed method also gives insights in energy saving and identifies bottlenecks to further improve the energy performance.