Novel approach to design and optimize heat-integrated distillation columns using Aspen Plus and an optimization algorithm

Abstract

Heat-integrated distillation columns (HIDiC) are sustainable technologies whose optimized designs may reduce up 80% the energy consumption, cooling water and CO2 emissions regard to the traditional columns. This paper shows a novel approach to design and optimize HIDiC columns using Aspen Plus and a stochastic optimization algorithm. This approach was designed to deal with the convergence problems in order to improve the search for the best solutions but also keep a continuous optimization process. The performance of the approach was evidenced through the optimization of the HIDiC columns used to split four close-boiling binary mixtures. Results showed that the design and optimization of these columns was successfully tackled by the approach implemented. As a result, the approach enabled to reduce convergence problems, keep a continuous optimization process and improve the quality of the solutions found. This fact demonstrates that the approach performed an adequate handling of purity specs and temperature driving forces, which were defined as constraints of the optimization problem. Based on the performance determined, this approach may be adapted and used as an approximated short-cut method to design and optimize other binary HIDiC columns. However, through an adequate adaptation, this approach may be extended to design and optimize HIDiC columns for separating ternary mixtures.