The E-S-T Method Based on the Grand Composite Curve Links Energy Consumption with Number of Stages and Stage Temperatures for Binary Mixture Distillation

Increasing the energy efficiency in industrial processes leads to positive effects for society, such as reduced production costs and improved sustainability. Pinch analysis, which is the most currently used approach to process integration, already includes the column grand composite curve (CGCC) for evaluating the minimum energy consumption in distillation columns. However, the CGCC assumes an infinite number of stages and does not provide any information on the number of stages necessary to achieve a specific energy-saving objective. This paper presents the energy-stage-temperature (E-S-T) method and associated E-S-T diagram for linking energy consumption and stage identification. The CGCC and stage temperatures provided by a single simulation of a distillation column allow drawing the E-S-T diagram to evaluate the number of stages resulting from an energy-saving modification, or the addition of side reboilers or condensers. Analysis results for columns fed by benzene-toluene, ethanol-methanol, and ethanol-water, with one and two reboilers or condensers, are presented. The method identifies the column stages of a column fed by binary mixtures, with any number of reboilers and condensers. Results from the E-S-T method are more accurate than those provided by the Gilliland correlation which is the most widely used empirical approach for evaluating the number of stages. This paper also puts forward insight into the heat cascade through stages and the corresponding exergy change, and proposes two new approaches for evaluating the CGCC. The E-S-T method can be considered the energy-based approach corresponding to the composition-based McCabe-Thiele method, and helps improve energy efficiency by including distillation columns used in industrial processes within the pinch analysis framework.

Automated summary

This paper introduces the energy-stage-temperature (E-S-T) method and its associated diagram for linking energy consumption and stage identification, with application results presented for different scenarios. The method provides more accurate results than the widely used Gilliland correlation, helping to improve energy efficiency.