Aggregate models based on improved group methods for simulation and optimization of distillation systems

This note deals with aggregate models for complex distillation systems in large-scale flowsheets. Group methods were originally devised for simple absorber and stripper calculations with no major extensions for handling distillation. In this work, group methods are systematically analyzed and further improved by modifying some of the previously proposed approximations. As a result, the improved group method exhibits accurate predictions and this is demonstrated using simulation and optimization case studies for a variety of chemical systems and operating conditions. It is observed that the prediction of output variables is in close agreement with that of the rigorous equilibrium stage model. In case of optimization problems, the optimal number of trays and feed locations differ by only one or two trays. The aggregate model can be applied in a sequence of steps in order to improve the reliability and robustness of the solution procedure. A rounding heuristic is also proposed which can provide near-optimal solutions with a significant reduction in computational time.