Identifying Heat-Integrated Energy-Efficient Multicomponent Distillation Configurations

We present a tractable nonlinear programming (NLP) formulation that models a given multi-component distillation configuration and searches for its global minimum heat duty. The novelty in the current model is that it can explore feasible heat integrations with a pre-specified desired minimum approach temperature between various condensers and reboilers while simultaneously optimizing the operating conditions within the configuration. We do not use cumbersome thermodynamic models for the equilibrium temperature calculation of a saturated multicomponent mixture. Instead, we propose a modified version of the well-known Antoine equation that reduces the calculation of the temperature at a given pressure to a simple function of component mole fractions and relative volatilities while retaining the fidelity of more complex models. We explore possible heat integrations by creating a heat exchange network between column condensers, reboilers, and side draw product locations. Considering these integrations along with the heat duty minimization is essential because it is often possible to alter the operating conditions of the columns and reduce energy consumption by admitting more heat integration possibilities. Finally, we demonstrate the power of our framework in identifying optimal configurations that yield large energy savings for several four- and five-component zeotropic distillation systems.