Effect of Solvent Content on Controllability of Extractive Distillation Columns

Effect of Solvent Content on Controllability of Extractive Distillation Columns

Krist V. Gernaey, Jakob K. Huusom and Rafiqul Gani (Eds.), 12th International Symposium on Process Systems Engineering and 25th European Symposium on ...

455KB Sizes 0 Downloads 75 Views

Krist V. Gernaey, Jakob K. Huusom and Rafiqul Gani (Eds.), 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering. 31 May – 4 June 2015, Copenhagen, Denmark © 2015 Elsevier B.V. All rights reserved.

Effect of Solvent Content on Controllability of Extractive Distillation Columns W. B. Ramos, M. F. Figueirêdo, K. D. Brito, R. P. Brito. Federal University of Campina Grande – Chemical Engineering Department. Av. Aprígio Veloso, 882, Bodocongó, Campina Grande – Brazil.

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. Keywords: Extractive distillation, Solvent content, Dehydration of anhydrous ethanol, Controllability.

1. Introduction and Problem Definition Considering that the design of an extractive distillation column is fixed, the variables that result in major impact on energy consumption are the reflux ratio and solvent flowrate (Bruggemann and Marquardt et al., 2004). Recently, a paper published by Figueiredo et al. (2014) included a new parameter in the analysis of extractive distillation, the solvent content in the extractive section. When evaluating the solvent content, the reflux ratio and solvent flowrate are considered simultaneously. According to the authors, the use of this parameter allows to find the range of possible solutions that will necessarily include the global optimum operating point. The specification of the solvent content in the feed stage of the extractive column together with product specifications represent a new phase for the understanding and search for optimal operating conditions of this process as it eliminates one of the main problems of extractive distillation: the existence of various local optimums. On the results from the analysis procedure suggested by Figueiredo et al. (2014), it was observed that the operating point with higher solvent content in the extractive section provides lower energy consumption by the reboiler of the extractive column. The results also indicate that increasing the solvent content causes the energy consumption to become independent of the number of stages of the column. However, the idea of using the solvent content in the search for the global optimum operation point is recent and still requires additional studies to support its use in extractive distillation problems. The analysis of the dynamic behavior and controllability of the extractive distillation process is very important for the usefulness

1608

W. B. Ramos et al.

of this separation process in an industrial plant. In view of the non-approach in the literature about the influence of the solvent content in the dynamic and controllability of the extractive distillation process and the intention to complement the study of Figueiredo et al. (2014) based on the analysis of the solvent content, this paper proposes to investigate this aspect, more specifically, answer the following question: Is a column with higher number of stages operating at lower EG content easier to control than a column with smaller number of stages operating at higher levels of EG?

2. Dynamic and Control Obtaining anhydrous ethanol by extractive distillation using ethylene glycol (EG) as solvent is the case study of this work. The modeling and simulations at steady state, using Aspen Plus®, were based on Figueiredo et al. (2014). By following the procedure suggested by the authors, the Aspen® design spec tool was used to obtain ethanol in the distillate with the desired specification of 99.5 mol% and recovery fraction of 99.99%. #௦௢௟௩ ), two values As specification of the solvent content in the solvent feed stage ( ‫ݔ‬ாீ were used: 20 % and 75 %, these spoken by the authors as the minimum and maximum solvent content, respectively, that guarantee the specifications of the required product. In addition, the simulations were performed considering two sizes of the column, 24 and 50 stages, in order to be able to respond to the questions that arose from the sequencing of study of the authors. It totaled in four simulated cases, these described in Table 1. The variables that were manipulated to achieve these specifications were: solvent flowrate (S) and reflux ratio (R) in the extractive column. Table 1 also shows the values of the main variables that resulted in lower specific energy consumption (SEC) for the four simulated cases where it can be seen that the lowest specific energy consumption occurs in a column with a higher content of solvent. The simulations (Case I, II, III, IV) were exported to Aspen Dynamics® using the pressure-driven mode. Pump head and valve pressure drops (usually 3 atm) were specified to provide reasonable rangeability so that a 20 % increase in transfer rate is handled without valve saturation. The reflux drum and the sump height of the columns, for all cases, were sized to provide 5 min of holdup when 50 % full, at steady state. Table 1 - Optimal results for minimum specific energy consumption for extractive distillation columns. Case study

Case I

Parameter

Case II

Case III

Case IV

Values

Number of stages

24

24

50

50

0.2

0.75

0.2

0.75

Solvent flowrate, kmol/h

48.86

78.08

33.81

74.36

Reflux ratio

2.6040

1.4504

1.7892

0.2906

Ethylene glycol content (mole fraction):

#௦௢௟௩ ‫ݔ‬ாீ

Number of stages of the extractive section Specific energy consumption, kW/kmol Internal diameter, m

15

15

30

30

42.67

19.41

33.24

19.21

2.0

2.0

0.8

0.8

Effect of Solvent Content on Controllability of Extractive Distillation Columns

1609

Figure 1 shows the basic control structure used for the water-ethanol-ethylene glycol system. All four cases use essentially the same structure with some modifications that account for different temperature profiles and sensitivities to disturbances.

Figure 1. Control structure

The control strategy used in the 4 studied cases was established in accordance with the strategies proposed by Luyben (2008), Gil et al. (2012), Fan et al. (2013) and TututiAvila et al. (2014). The control structure consists of the following loops: (1) The sump level is controlled by manipulating the bottom flowrate; (2) The top pressure is controlled by manipulating the condenser duty; (3) The reflux drum level is controlled by manipulating the distillate flowrate; (4) The reflux ratio was kept constant while the disturbances were applied (Arifin and Chien, 2008; Luyben, 2008; Gil et al., 2012); (5) The ratio between the solvent feed flowrate and azeotropic mixture feed flowrate (S/F) is kept constant by using a multiplier together with a controller in cascade; (6) The temperature control is performed by manipulating the vapor flowrate of the reboiler; (7) A flow controller was added to the azeotropic feed stream in order to apply feed flowrate disturbances. Two criteria were used to determine the best stage to have its temperature controlled: the stage that has the highest slope in the temperature profile, as well as the stage with the highest sensitivity to changes in heat duty, by manipulating the vapor flowrate in the reboiler in ± 0.1 %. It was observed that for the column with 24 stages, the stage 23 is the most suitable to have its temperature controlled for the two solvent contents analyzed. For the column with 50 stages, the results indicated the stage 49 for the column operating with 75 % EG content and stage 39 for the column operating at 20 % EG content.

1610

W. B. Ramos et al.

The level controllers are Proportional olny, with Kc = 2 for the reflux drum level (Luyben, 2002) and Kc = 10 for the sump level (Gil et al., 2012). The pressure controller is Proportional-Integral with Kc = 20 and IJI = 12 min (Aspen Dynamics default values). The flow controllers are Proportional-Integral with Kc = 0.5 and IJI = 0.3 min and the filter time constant F = 0.1 min (Luyben, 2002). The parameters of the temperature controllers were tuned using the Tyreus-Luyben method (Tyreus and Luyben, 1992). The results are shown in Table 2. A dead time block was inserted before the temperature controllers with dead time of 1 minute. 2.1. Dynamic Performance To analyze the effect of the solvent content in the controllability of the the extractive column, disturbances of ±10 % were applied, in the time equal to 2 hours, in the feed flowrate of azeotropic mixture by changing the setpoint of the AZ_FC controller. Disturbances in feed composition of the azeotropic mixture were also applied by changing the mole fraction of ethanol from 0.85 to 0.88 and 0.80. Figure 2 shows the comparison between the dynamic responses to the disturbances in the azeotropic feed flowrate in the the column with 24 stages, for 20 % and 75 % solvent content in the extractive section, where it can be seen that the control system can maintain the purity of ethanol in the distillate close to the specification value for both EG content, with a slightly better performance when the column operates with 75% EG content. However, the column operating with 20 % EG content has reached the steady state faster, in about 2.5 hours, for disturbances in the feed flowrate and approximately 2 hours for disturbances in the composition. Figure 3 shows the dynamic responses related to the temperature control of stage 23, where can be seen that the temperature has returned to its setpoint value in about 1 hour. Figure 4 shows the comparison between the dynamic responses to disturbances in the composition of the azeotropic mixture, where can be seen that the control is more efficient when the column operates with a lower solvent content. The same disturbances were applied to the columns with 50 stages. Similar results were obtained for disturbances in the feed flowrate, as shown in Figures 6 and 7. For disturbances in the azeotropic feed composition, it was also observed that the column operating with lower solvent content has a better controllability (Figure 8). However comparing the results presented in Figures 4 and 8, it is noted that the column with 24 stages is able to better control the composition. The temperature control of the stages 39 and 49 proved to be efficient, as can be seen in Figures 7 and 9. Table 2. Temperature controllers parameters. Case I Controlled variable

Case II

Case III

Case IV

Reboiler vapor flow

Reboiler vapor flow

Reboiler vapor flow

Kc

TI,23 = 381.2 K Reboiler vapor flow 1.9944

1.5767

0.7283

0.5141

IJI

7.92 min

9.24 min

9.24 min

9.24 min

Manipulated variable

TII,23 = 368.7 K TIII,49 = 385.3 K TIV,39 = 371.4 K

Temperature of stage 23, K

Effect of Solvent Content on Controllability of Extractive Distillation Columns

0.9956

24 stages

0.9952

+10% AZEOTR Flow +10% AZEOTR Flow

0.9950 -10% AZEOTR Flow

0.9948

0.9946 EG Content 75% EG Content 20% 0.9944 0

2

4

6

8

(a)

368.4 367.2 366.0 0

10

385.2

Temperature of stage 23, K

80% Mol ETOH

88% Mol ETOH

0.9945

8

10

+ 10% AZEOTR Flow - 10% AZEOTR Flow

382.8 381.6

(b)

380.4 379.2 378.0 0

2

4

6

8

10

24 stages

370.8

0,88 ETOH 0,80 ETOH

369.6 368.4

(a)

367.2 366.0

0

2

4

6

8

10

0.9940 0.9935 EG content 75% EG content 20%

0.9930 0

2

80% Mol ETOH

4

6

8

10

Time (Hours)

Temperature of stage 23, K

Time (Hours) 385.2

24 stages

384.0

0,88 ETOH 0,80 ETOH

382.8 381.6

(b)

380.4 379.2 378.0 0

2

4

6

0.9956

50 stages 0.9954

0.9952 +10% AZEOTR Flow +10% AZEOTR Flow

0.9950

50 stages

376.2

+ 10% AZEOTR Flow - 10% AZEOTR Flow

374.4 372.6

(a)

370.8 369.0 367.2 0

2

4

-10% AZEOTR Flow

0.9948

0.9946 EG Content 75% EG Content 20% 0.9944 4

6

8

6

8

10

Time (Hours)

-10% AZEOTR Flow

2

10

Figure 5. Dynamic responses to disturbances in the azeotropic feed composition for (a) 20% EG content and (b) 75% EG content.

Temperature of stage 39, K

Figure 4. Comparison between the dynamic responses to disturbances in the composition of the azeotropic mixture for 20% and 75% solvent content in the extractive section.

0

8

Time (Hours)

10

Time (Hours)

Figure 6. Comparison between the dynamic responses to disturbances in the azeotropic feed flowrate for 20% and 75% solvent content in the the extractive section

Temperature of stage 49, K

xD (Ethanol)

0.9955

xD (Ethanol)

6

Figure 3. Dynamic responses to disturbances in the azeotropic feed flowrate for (a) 20 % EG content and (b) 75% EG content.

88% Mol ETOH

0.9950

4

Time (Hours)

Figure 2. Comparison between the dynamic responses to disturbances in the azeotropic feed flowrate for 20% and 75% solvent content in the the extractive section.

24 stages

2

24 stages

384.0

Time (Hours)

0.9960

+ 10% AZEOTR Flow - 10% AZEOTR Flow

369.6

Time (Hours)

-10% AZEOTR Flow

Temperature of stage 23, K

xD (Ethanol)

0.9954

24 stages

370.8

1611

50 stages

390.6

+ 10% AZEOTR Flow - 10% AZEOTR Flow

388.8 387.0

(b)

385.2 383.4 381.6 379.8 0

2

4

6

8

10

Time (Hours)

Figure 7. Dynamic responses to disturbances in the azeotropic feed flowrate for (a) 20 % EG content and (b) 75% EG content.

W. B. Ramos et al.

0.9970

50 stages

0.9965

Temperature of stage 39, K

1612

88% Mol ETOH

0.9960

80% Mol ETOH

0.9950 0.9945

88% Mol ETOH

0.9940

50 stages

0,88 ETOH 0,80 ETOH

374.4 372.6

(a)

370.8 369.0 367.2 0

2

4

6

8

10

Time (Hours)

0.9935 0.9930 0.9925 0.9920 EG content 75% EG content 20%

0.9915 0.9910 0

2

80% Mol ETOH

4

6

8

10

Time (Hours)

Temperature of stage 49, K

xD (Ethanol)

0.9955

376.2

50 stages

390.6

0,88 ETOH 0,80 ETOH

388.8 387.0 385.2

(b)

383.4 381.6 379.8 0

2

4

6

8

10

Time (Hours)

Figure 8. Comparison between the dynamic responses to disturbances in the composition of the azeotropic mixture for 20% and 75% solvent content in the extractive section.

Figure 9. Dynamic responses to disturbances in the azeotropic feed composition for (a) 20% EG content and (b) 75% EG content.

3. Conclusions Disturbances in the azeotropic feed composition caused poor performance in controlling the top product purity of the the extractive column operating with high solvent content; this poor performance is even sharper in columns with higher number of stages. Disturbances in the azeotropic feed flowrate had small impact on the control of the top product composition in the four studied cases, however the column with higher number of stages took longer to reach steady state. These results showed that controlling smaller extractive distillation columns is easier than controlling columns with higher numbers of stages, especially columns operating with low solvent content.

References S. Brüggemann and W. Marquardt, 2004, Rapid screening of design alternatives for nonideal multiproduct distillation processes, Comput. Chem. Eng., 29, 165-179. M. F. Figueirêdo, K. D. Brito, W. B. Ramos, L. G. S. Vasconcelos and R. P. Brito, 2014, Effect of Solvent Content on the Separation and the Energy Consumption of Extractive Distillation Columns, Chemical Engineering Communications, 10.1080/00986445.2014.900053. W. L. Luyben, 2008, Comparison of extractive distillation and pressure-swing distillation for acetone–methanol separation, Industrial and Engineering Chemistry Research, 47(8), 2696– 2707. W. L. Luyben, 2002, Plantwide dynamic simulators in chemical processing and control, New York, Marcel Dekker. S. Arifin and I. L. Chien, 2008, Design and control of an isopropyl alcohol dehydration process via extractive distillation using dimethyl sulfoxide as an entrainer, Industrial and Engineering Chemistry Research, 47 (3), 790–803. B. D. Tyreus and W. L. Luyben, 1992, Tuning of PI controllers for integrator dead time processes. Industrial and Engineering Chemistry Research, 31, 2625–2628. I.D. Gil, J.M. Gómez and G. Rodríguez, 2012, Control of an extractive distillation process to dehydrate ethanol using glycerol as entrainer, Comput. Chem. Eng., 39, 129–142. Z. Fan, X. Zhang, W. Cai and F. Wang, 2013, Design and control of extraction distillation for dehydration of tetrahydrofuran, Chem. Eng. Technol., 36, 829–839. S. Tututi-Avila, A. Jiménez-Gutiérrez and J. Hahn, 2014, Control analysis of an extractive dividing-wall column used for ethanol dehydration, Chem. Eng. and Processing, 82, 88-100.