Optimization of Extractive Distillation Process with a Single Column for Anhydrous Ethanol Production

Optimization of Extractive Distillation Process with a Single Column for Anhydrous Ethanol Production

Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering...

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Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24 June 15-18, 2014, Budapest, Hungary. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of Extractive Distillation Process with a Single Column for Anhydrous Ethanol Production Wagner B. Ramos*, Marcella F. Figueiredo, Romildo P. Brito Chemical Engineering Department, Federal University of Campina Grande, Av. Aprigio Veloso, 882, Bodocongo, Campina Grande – PB – CEP 58429-140 , Brazil [email protected]

Abstract Distillation is one of the oldest and most used separation processes that exist in chemical industries worldwide. In cases of azeotropic mixtures, simple distillation is unable to perform separation at a certain composition, so they are separated using azeotropic distillation. Traditionally, there are two different configurations used to produce anhydrous ethanol by azeotropic distillation. One of them is the heterogeneous azeotropic distillation and the other one is the homogeneous azeotropic distillation. In both configurations, it is necessary to add a third component (solvent) to promote separation and it is also necessary to use a second distillation column in order to recover the solvent. This paper deals with homogeneous azeotropic distillation (also called extractive distillation) and the process of obtaining anhydrous ethanol was chosen as a case study. For this case, the solvent used to break the azeotrope was ethylene glycol. The purpose of this work is to determine the optimal conditions of a new configuration of extractive distillation process for producing anhydrous ethanol using only one column with a sidestream withdrawal, using the process simulator Aspen Plus ®. After optimization, it was possible to achieve a reduction of 18.53 % in the reboiler heat duty. A comparison, in terms of energy consumption of the reboilers, between the traditional extractive configuration and the new configuration, was also assessed. Keywords: Distillation; optimization; extraction; ethanol.

1. Introduction In all petrochemical industries worldwide, distillation is the most important and most used separation process. According to the U.S. Department of Energy, there are more than 40,000 distillation columns in North America, and they consume about 40 % of the total energy used to operate a plant. Regarding to this, the optimal operation of distillation columns is the objective of several studies all over the world. The fundamental principle of the distillation process is the difference in volatility of the components forming the mixture. However, there are cases in which occurs the presence of azeotrope points. When such case occurs, conventional distillation may not be able to promote a separation with the desired degree of purity. Azeotropic mixtures can be separated by azeotropic distillation, which can behomogeneous or heterogeneous. In both cases, a third component, called solvent, is added to promote separation. The general purpose of this work is to optimize, in terms of energy reduction, the process of dehydration of aqueous mixtures of ethanol using only one distillation column. The optimization procedure uses a process simulator (Aspen Plus ®), in a systematic way, in order to obtain the optimal operational conditions of an extractive distillation column

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(Figueiredo et al., 2010).The production of anhydrous ethanol was chosen as a case study due to its increasingly importance as a sustainable biofuel. According to SegoviaHernández et al. (2012), Brazil and the United States are major users and producers of bioethanol and together, they were responsible for 88 % of the world´s ethanol fuel production in 2010. Several recent studies assessing optimization of anhydrous ethanol distillation can be found in literature. Kiss et al. (2011) showed that the use of an extractive dividing wall column configuration can lead to energy savings, however, in spite of the recovery column be eliminated, this type of configuration requires two condensers. Alcántara-Avila et al. (2012) proposed a multiobjective optimization procedure using MILP (Mix Integer Linear Programming) that evaluates various distillations structures, entrainers and energy conservation methods in order to optimize the total annual cost, but the authors do not consider the column with sidestream withdrawal in their studies and the optimization procedure used does not use a rigorous process simulator. Vázquez-Ojeda et al. (2013) used a stochastic global optimization algotithm to optimize the conventional and an alternative configuration, but both configurations use solvent recovery columns. Studies that assess optimization of extractive columns with sidestream withdrawal for production of anhydrous ethanol, which is what this paper proposes, was not found in literature. The main advantage of the configuration presented in this work is that the use of a solvent recovery column is not necessary, which implies in a reduction in investment costs and utilities (reboiler and condenser).

2. Problem Definition Normally, in extractive distillation, the lighter component is removed at the top of the extractive column. At the base of the column, the solvent and the intermediate component are collected and pumped to the recovery column. As in the azeotropic distillation, a second column is required in order to recover the third component, as shown in Figure 1. However, considering the simplicity of the recovery column, attention is often focused only on the extractive column. Figure 2 shows the composition profiles (liquid and vapor) normally obtained by the extractive distillation column of the flowchart presented in Figure 1, where it is possible to observe that, below the feeding stage, the vapor phase contains virtually only water. This behavior suggests that a sidestream may be used, so that a single column can be used to obtain all three components with high purity. Figure 3 shows the extractive distillation column with a sidestream withdrawal.

MAKE-UP

B3 ETOH

ENTRAIN

H2O RECOV

EXTRACT

AZEOTR

ETOH+H2O

SOLVREC

Figure 1. Simplified process diagram used for the dehydration of aqueous ethanol mixture using ethylene glycol as solvent.

Optimization of Extractive Distillation Process with a Single Column for Anhydrous 1413 Ethanol Production 1.0

1.0

Ethanol Water Glycol

0.8

0.6

Mole fraction

Mole fraction

0.8

0.4

Ethanol Water Glycol

0.6

0.4

0.2

0.2

0.0

0.0 0

5

10

15

20

25

0

5

10

15

20

25

Stage

Stage

(a)

(b)

Figure 2. Composition profiles in liquid phase (a) and vapor phase (b) obtained by the extractive distillation column of the flowchart presented in Figure 1.

However, if there is a considerable difference between the boiling points of the components, it may be economically possible to obtain the intermediate component at the sidestream with high purity (Rooks et al., 1996). The objective of this work is to perform the optimization of the column shown in Figure 3 in order to find the operational conditions that provide the lowest energy consumption. A comparison of the energy consumption between the two configurations (the one presented in Figure 1 and the one presented in Figure 3) will also be presented.

3. Process Modeling Steady state simulations were performed using the commercial software simulator Aspen Plus®, version 7.2, following the flowchart shown in Figure 3.The extractive distillation column (EXTRACT) aims to produce anhydrous ethanol, as top product, with a composition of 99.5 mass% of ethanol, as a function of the azeotropic mixture (ethanol-water) which has molar composition of 85.0 mol% of ethanol. The solvent used, ethylene glycol, was chosen based on studies that showed it to be the most favorable for this process (Dias, 2008). MIXER MAKEUP ETOH ENTRAINE

3

EXTRACT

AZEOTROP

H2O

EXCHANGE

PUMP 2 EGLYCOL

Figure 3. Extractive distillation column with a sidestream withdrawal.

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The flowchart in Figure 3 was implemented in Aspen Plus ® using RadFrac routine and the Fract1 model for defining the distillation column. The input data of the feed streams and sidestream withdrawal, as well as the extractive column specifications were taken from literature (Brito, 1997). The extractive column has 24 stages (including reboiler and condenser), the azeotropic mixture is fed on stage 13, the solvent is fed on stage 5 and the sidestream is connected at stage 19.The feed streams data are shown in Table 1:

4. Steady-State Results and Optimization The optimization process analyzes all the variables simultaneously, searching for optimal values that provide the lowest energy consumption. Once the objective function and constraints are defined, the variables reflux ratio, solvent flow rate, distillate flow rate, sidestream flow rate, feed streams (AZEOTROP and ENTRAIN) and sidestream (H2O) positions will vary until the minimum value of the objective function is reached.The optimization procedure was performed using the Model Analysis Tools/Optimization in Aspen Plus®, which uses the Sequential Quadratic Programming (SQP) method to search for the optimal point. The objective function J was defined as the reboiler heat duty (Qr).Ethanol mass fraction of 0.995 at the top ( x Detoh ), ethylene glycol mass fraction of 0.999 at the bottom ( x Beg ) and watermass fraction of 0.956 at sidestream ( y Swt ) were defined as constraints. Mathematically we have: Objective function to be minimized: MinJ = Qr

(1)

Sunject to:

x Detoh t 0.995

(2)

x Beg t 0.999

(3)

y Swt t 0.956

(4)

The manipulated variables used for optimization are represented here by SF (solvent feed flow), R (reflux ratio), D (distillate flow rate), SS (sidestream flow rate), SFS (solvent feed stage), AFS (azeotrope feed stage) and SWS (sidestream withdrawal stage).First, using the Model Analysis Tool/Optimization, the optimization procedure was performed using the continuous variables SF, D, SS and R. The results are shown in Table 2. The optimization involving variables SF, D, SS and R was able to reduce the Table 1. Feed Streams Input Data Stream Azeotropic (AZEOTROP) Solvent (ENTRAIN)

Variable Temperature (qC) Ethanol mole fraction Molar flow (kmol/hr) Temperature (qC) Ethylene glycol molar fraction Molar flow (kmol/hr)

Value 40.0 0.85 100.00 80.0 1.00 70.0

Optimization of Extractive Distillation Process with a Single Column for Anhydrous 1415 Ethanol Production Table 2. Optimization Results Variable SF (kmol/hr) D (kmol/hr) SS (kmol/hr) R Reboiler heat duty (GJ/hr)

Initial Value 70.0 85.43 14.7 0.85 8.72962

Final Value 74.62 86.08 13.84 0.346 7.1119

reboiler heat duty by 18.53 %. Due to convergence problems using the Model Analysis Tools/Optimization tool to evaluate the influence of feed streams and sidestream positions (discrete variables), the sensitivity analysis tool Model Analysis Tools/Sensitivity of Aspen Plus® was used to find these optimal values. The solvent feed position varied from stage 3 to 10, the position of the azeotropic feed varied from stage 11 to 19 and the sidestream position varied from stage 18 to 22. However, the results of this simulation showed that the influence of these variables on the reboiler duty was insignificant and they were not taken into account.

5. Comparison between the two configurations To compare energy consumption between the two configurations, data were collected from the literature (Figueiredo et al., 2010). The flowchart used is similar to that shown in Figure 1 and the results are optimized. The specifications of the feed streams are the same as described in Table 1 of this paper. The number of stages of the extraction column is also the same, as well as the purity of the ethanol obtained as distillate product. The comparative results are shown in Table 3. It was observed an increase in energy consumption by approximately 23% for the configuration with sidestream column with respect to the conventional configuration, but remember that only the extractive column was evaluated. So in order to have a more accurate comparison, another simulation was made in order to evaluate the energy consumption of the reboiler of the recovery column. The results of this simulation showed that the total energy consumption of the conventional configuration (two columns) was 0.08112 GJ/kmol of ethanol produced. With this result, the difference in energy consumption of the two configuration drops to about 1.5%. It is important to mention that an optimization procedure to the recovery column was also carried out, where the distillate flowrate and reflux ratio were manipulated in order to obtain the lowest heat duty on the reboiler so that the required purity for the ethylene glycol recovered at the bottom of the column was equal to or higher than 99.9 mass%. Table 3. Energy consumed per kmol of ethanol produced. Comparison between the two configurations. Configuration Conventional extracitve column Sidestream column

Qr/D (GJ/kmol) 0,06690 0,08262

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6. Conclusions By using this configuration, the product compositions at the sidestream and bottom stream are as important as the composition at the top where ethanol, the product of interest, is recovered, since all three components should be separated with high purity. After performing the optimization procedure, the energy consumption of the reboiler was reduced by 18.5 %. The optimized values of the variables are close to the values of the initial condition, except for reflux ratio, which had a considerable reduction. The comparison between the two configurations showed that the extractive distillation column with sidestream withdrawal can be competitive when compared to conventional configuration in terms of energy consumption of the reboiler.

Acknowledgement The authors thank the National Council for Scientific and Technological Development (CNPq) for the financial support.

References J. R. Alcántara-Avila, M. Kano, S. Hasebe, 2012, Environmental and economic optimization of distillation structures to produce anhydrous ethanol, Computer Aided Chemical Engineering, 30, 712-716. R. P. Brito, 1997, Processo de destilação extrativa: modelagem dinâmica, simulação e avaliação de nova configuração, 202 f, Tese (Doutorado em Engenharia Química) – Faculdade de Engenharia Química, Universidade Estadual de Campinas, Campinas-SP. M. O. S. Dias, 2008, Simulação do processo de produção de etanol a partir do açúcar e do bagaço, visando a integração do processo e a maximização da produção de energia e excedentes do bagaço, 253 f. Dissertação (Mestrado em Engenharia Química) – Faculdade de Engenharia Química, Universidade Estadual de Campinas, Campinas-SP. M. F. Figueirêdo, B. P. Guedes, J. M. M. Araújo, L. G. S. Vasconcelos, R. P. Brito, 2010, Optimal design of extractive distillation columns – A systematic procedure using a process simulator, Chemical Engineering Research and Design, 89, 341-346. A. A. Kiss, D. J-.P.C. Suszwalak, 2011, Enhanced bioethanol dehydration by extractive and azeotropic distillation in dividing-wall columns, Separation and Purification Technology, 86, 70-78. R. E. Rooks, M. F. Malone, M. F. Doherty, 1996, Geometric Design Method for Side-Stream Distillation Columns, Ind. Eng. Chem. Res., 35, 3653-3664. J. G. Segovia-Hernández, M. Vázquez-Ojeda, S. Hernández, A. Hernández-Aguirre, A. A. Kiss, 2012, Design and optimization of an ethanol dehydration process using stochastic methods, Separation and Purification Technology, 105, 90-97. M. Vázquez-Ojeda, J. G. Segovia-Hernández, S. Hernández, A. Hernández-Aguirre, A. A. Kiss, 2013, Optimization of an Ethanol Dehydration Process Using Differential Evolution Algorithm, Computer Aided Chemical Engineering, 32, 217-222. U.S. Dept. of Energy, Office of Energy Efficiency and Renewable Energy, Distillation Column Modeling Tools, DOE, Washington, DC, Accessed on 20/10/2013.