Reduced Rigorous Models for Efficient Dynamic Simulation and Optimization of Distillation Columns

Abstract

In this work, we compare the technique of model order reduction based on weighted residuals in discrete domain with the aggregated modelling method for efficient dynamic simulation and optimization of distillation columns. To compute the weighted residuals, a discrete form of Lobatto-Gauss quadrature was developed in a previous work Ribeiro et al. (2010), allowing a high degree of accuracy on the calculations of the weighted sums of heat and mass balances residuals on real stages. Balances related with upstream and downstream stages are considered as boundary conditions of corresponding difference-differential equations system. The aggregated modelling method is based on the two-step procedure of Linhart & Skogestad (2010). In the first step, aggregation stages are selected to compose the reduced dynamics with the corresponding holdup factors, and in the second step the resulting algebraic equations after applying the quasi-steady-state assumption to the remaining stages are replaced by pre-computed functions. Optimization of start-up policies, Wozny & Li (2004), optimal feed tray location, Kamath et al. (2010), and dynamic simulation of binary and multicomponent distillation columns were solved to compare the performance of both model reduction techniques.