Wagner Brandão Ramos

Optimization of the Design and Operation of Extractive Distillation Processes

The achievement of the optimal operating point of extractive distillation systems involves determining the values of the process variables, such as the solvent flowrate, the reflux ratio of the extractive, and recovery columns. From the point of view of design, the optimum involves defining the number of stages of extractive and recovery columns, as well as the feed stage positions of these columns. The above-mentioned columns are coupled through a recycle stream, which makes obtaining the optimal operating and design points a more complex task. This study arose from a new procedure for the analysis of extractive distillation columns, in which the solvent mole fraction in the solvent feed stage is the primary variable to be analyzed. The procedure allows for determining the values of the process and design variables that provide the global minimum for the total annual cost and the specific energy consumption of the extractive distillation processes (extractive and recovery columns). Furthermore, it is possible to determine the minimum solvent flowrate and the minimum reflux ratio for separation. Obtaining anhydrous ethanol using ethylene glycol as solvent is the case study of this work.

Effect of Solvent Content on the Separation and the Energy Consumption of Extractive Distillation Columns

This article sets out to evaluate the effect of solvent content in the extractive section on the separation efficiency and energy consumption of extractive distillation columns. Contrary to the classical approach, the proposed approach enables a simultaneous evaluation of the effect of the major decision variables (reflux ratio, solvent flow rate, and the number of stages of the extractive section [NSE]). The procedure allows calculating the minimum solvent flow rate for the separation and the minimum specific energy consumption. The results show that the minimum specific energy consumption is obtained for the minimum reflux ratio and not for the minimum solvent flow rate. Moreover, the results show that it is not always the case that a larger NSE results in lower energy consumption. Due to its industrial importance, the dehydration of aqueous mixtures of ethanol using ethylene glycol as solvent has been chosen as a case study.

Control of an Extractive Distillation Column with Thermal Integration

Abstract Knowing the importance and necessity of the existence of a control system in chemical processes, this paper aims to investigate the control performance of an extractive column with thermal integration facing common process disturbances. The dehydration of ethanol using ethylene glycol as a solvent was used as a case study. The extractive column was simulated in steady and dynamic states using the commercial software Aspen Plus® and Aspen Plus Dynamics®, in which it was used a more rigorous model with decoupled condenser and reflux vessel. The technique of control by inference was adopted to control the overhead product composition. The results showed that it is possible to maintain the composition of ethanol near specification using a simple control structure, although the thermal integration lead to deviations in the solvent feed temperature of about 5 degrees, when disturbances in the azeotropic mixture feed flow rate are applied.

Effect of Solvent Content on Controllability of Extractive Distillation Columns

Abstract This paper arose from a new approach to evaluating separation and energy consumption of extractive distillation columns using as primary analysis parameter the solvent content throughout the column. This new approach allows to find a range of possible solutions that contemplates the global optimal point of operation. In view of this, the objective of this paper is to investigate the influence of the solvent content throughout the column and the size (number of stages) of the column on controllability. The results showed that the columns with smaller number of stages operating with lower solvent content have a better controllability when applied disturbances in the composition of the azeotropic mixture that feeds the column. The production of anhydrous ethanol by extractive distillation using ethylene glycol as solvent was used as a case study for this work.

Intelligent control system for extractive distillation columns

We developed and implemented an intelligent control system to be used in an extractive distillation column that produces anhydrous ethanol using ethylene glycol as solvent. The concept of artificial neural networks (ANN) was used to predict new setpoints after disturbances, and proved to be a fast and feasible solution. The developed control system receives data from temperature, flowrate and composition measurements of the azeotrope feed, and the ANN estimates the new set-points of the controllers to maintain 99.5 mol% of ethanol at the top and less than 0.1mol% at the bottom; feed composition was also estimated using an ANN. All ANN were trained to provide output data corresponding to an optimized operating condition. The results showed that the intelligent control system can predict a new operating condition for any disturbance in the column feed and presented superior performance when compared with the control system without ANN.