Article pubs.acs.org/IECR
Economic Optimum Design of the Heterogeneous Azeotropic Dehydration of Ethanol William L. Luyben*,† †
Department of Chemical Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States ABSTRACT: Several processes are available for the important operation of dehydrating ethanol/water mixtures to concentrations above the azeotrope (90 mol %). Heterogeneous azeotropic distillation has been studied using several entrainers: benzene, cyclohexane, isooctane, ethylene glycol, etc. A pioneering paper by Ryan and Doherty [Ryan, P. J.; Doherty, M. F. Design optimization of ternary heterogeneous azeotropic distillation sequences. AIChE J. 1989, 35, 1592−1601.] explored several alternative process configurations and concluded that the three-column flowsheet with a preconcentrator (beer still), an azeotropic column, and a recovery column was the economic optimum. They used approximate ternary diagram methods. It appears that they arbitrarily assumed a beer still distillate composition with an ethanol concentration of about 88 mol %, which is quite close to the azeotropic composition of 90 mol %. Energy consumption in the beer still increases as its distillate composition gets closer to the azeotrope. On the other hand, energy consumption in the azeotropic-recovery column section of the process decreases as the feed to this section becomes richer in ethanol. It appears that this fundamental trade-off has not been studied in the literature. This paper examines quantitatively, using rigorous simulations, how this design parameter affects the energy and capital investment of the entire system. The focus is the distillate composition trade-off. The example used is the heterogeneous azeotropic distillation process, but the same issue applies in any of the other methods (such as extractive distillation) in which a preconcentrator column is used.
1. INTRODUCTION The production of high-purity ethanol from the ethanol−water mixture coming from batch fermenters in biorefineries is complicated by the occurrence of an azeotrope with a composition of 90 mol % ethanol at atmospheric pressure. Typical ethanol concentration in the fermenter broth is 5 mol % ethanol. The concentration needed for blending into gasoline is 99.5 mol % ethanol. One method for ethanol dehydration is heterogeneous azeotropic distillation, which has been used for many decades.1 A suitable light entrainer component (benzene, cyclohexane, isooctane, ethylene glycol, etc.) is added to modify the relative volatilities. The water is driven overhead with the entrainer, and a high-purity ethanol bottoms stream is produced in the azeotropic column. The overhead vapor is condensed and fed to a decanter. The organic phase is refluxed back to the column. The aqueous phase is fed to another column that produces a bottoms product of high-purity water and a distillate that is recycled back to the azeotropic column. A third column in the front end of the process is used to preconcentrate the lowconcentration stream from the fermenter up to a concentration closer to the azeotrope before feeding this into the azeotropic column. In addition to heterogeneous azeotropic distillation, several alternative methods are available for ethanol dehydration such as extractive distillation, adsorption, and pervaporation. A comprehensive review of the subject, including 302 references, has been presented by Vane.2 A recent paper3 by Kiss and Paul claims that the heterogeneous azeotropic distillation process is more economical than adsorptive drying because of the large amount of energy required to regenerate the adsorbent. A pioneering paper by Ryan and Doherty4 explored several alternative heterogeneous azeotropic configurations using © 2012 American Chemical Society
benzene as the entrainer. They examined two-column and three-column flowsheets and concluded that the three-column flowsheet with a preconcentrator (beer still), an azeotropic column, and a recovery column was the economic optimum. They used approximate ternary diagram methods of analysis. Figure 6 in the Ryan−Doherty paper shows a binary feed composition to the azeotropic column of about 88 mol % ethanol. There is no discussion in the paper of the impact of this parameter on the optimum design. Fairly detailed information is given for the azeotropic column and the recovery column, but essentially nothing is provided about the beer still. The 88 mol % ethanol concentration is quite close to the azeotropic composition of 90 mol %. Energy consumption in the beer still could be reduced by designing for ethanol concentrations further away from the azeotropic composition. However, lower ethanol concentrations in the feed to the azeotropic column will increase energy consumption in the azeotropic column. Clearly there is an optimum beer still distillate composition. Other papers have also arbitrarily assumed beer still distillate compositions. For example, Martinez et al.5 specify a beer still feed flow rate of 45.36 kmol/h with 10 mol % ethanol. Then they set the beer still distillate flow rate at 5.41 kmol/h. With negligible losses of ethanol in the bottoms, the distillate composition is 4.536/5.41 = 0.838, which is about 6 mol % Received: Revised: Accepted: Published: 16427
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away from the azeotropic composition. Li and Bai6 select a 85 mol % distillate. The purpose of this paper is to explore this interesting tradeoff. In addition, each of the distillation columns is optimized in terms of the number of stages, which leads to columns that are significantly different than those given by Ryan and Doherty. It should be emphasized that this composition trade-off exists in any other process, such as extractive distillation, that uses a preconcentrator. An additional contribution of this paper is to demonstrate an effective homotopic method for converging the two recycle loops that occur in this very nonlinear system.
diameters decrease as more stages are used. The capital cost of the column vessel increases as more stages are used, but the capital cost of the heat exchangers (condenser and reboiler) decrease. The 46-stage column has the minimum TAC for the 85 mol % case. Tables 2 and 3 give results for the 80 and 75 mol % cases. As the beer still distillate composition is moved further from the Table 2. Beer Still Optimization: 80 mol % Casea
2. OPTIMIZATION OF THE BEER STILL (PRECONCENTRATOR) Three different distillate compositions are considered, and the optimum beer still configuration for each is determined, using total annual cost (TAC) as the economic objective. For all cases, the operating pressure is set at 1 atm in the reflux drum. Tray pressure drop is assumed to be 0.1 psi per tray, so base pressure varies as the number of trays is changed. Base pressure affects the base temperature for a fixed composition, which impacts the required reboiler heat-transfer area and resulting capital investment. Low-pressure steam (433 K and $7.78 per GJ) is used since the base temperature is never greater than 382.3 K in all cases. Cooling water inlet and outlet temperatures are assumed to be 305 and 315 K, respectively. Reflux-drum temperature varies slightly with distillate composition. Overall heat-transfer coefficients in the condenser and reboiler are 0.852 and 0.582 kW m−2 K−1, respectively. Column vessel and heat-exchanger capital costs are given by the equations found in ref 7. Aspen Plus UNIQUAC physical properties are used. A total condenser, partial reboiler, and theoretical trays are assumed. The optimum feed tray location is determined for each selected number of total trays by finding the feed location that minimizes reboiler duty. The feed of fermentation broth is assumed to be 1000 kmol/ h with a composition of 5 mol % ethanol and 95 mol % water. The two design specifications in the beer still are a bottoms ethanol concentration of 50 ppm (molar) and a distillate ethanol concentration that is set for the three cases: 75, 80, and 85 mol % ethanol. The variables that are manipulated to achieve these two specifications are the distillate flow rate and the reflux ratio. Table 1 gives results for the 85 mol % distillate composition case for a range of total stages. Energy costs and column
NT1
36
46
56
29 3.422 2.124 1.084 379.3
39 3.326 1.996 1.050 380.8
48 3.302 1.538 1.047 382.3
0.2122 0.2590 0.4712 0.8396 0.9966
0.2037 0.3062 0.5099 0.8160 0.9860
0.1728 0.3586 0.5313 0.8100 0.9872
energy TAC a
(MW) (MW) (m) (K) (106 $) HX column total (106 $/y) (106 $/y)
21 13 3.067 1.823 1.056 376.5
16 2.906 1.644 1.030 377.6
22 2.853 1.538 1.047 379.3
0.1922 0.1611 0.3532 0.7525 0.8702
0.1797 0.1878 0.3675 0.7130 0.8355
0.1734 0.2409 0.4143 0.7000 0.8381
energy TAC a
(MW) (MW) (m) (K) (106 $) HX column total (106 $/y) (106 $/y)
26
36
Reflux-drum = 351.4 K.
Table 3. Beer Still Optimization: 75 mol % Casea NT1 NF1opt QR1 QC1 ID1 TB1 capital
energy TAC a
16 (MW) (MW) (m) (K) (106 $) HX column total (106 $/y) (106 $/y)
21
26
8 3.047 1.821 1.029 375.9
10 2.906 1.996 1.050 376.5
13 2.853 1.538 1.047 377.6
0.1916 0.1286 0.3202 0.7476 0.8543
0.1755 0.1564 0.3318 0.6938 0.8045
0.1729 0.1853 0.3582 0.6898 0.8092
Reflux-drum = 351.6 K.
azeotropic composition, energy and capital costs decrease, as does the optimum number of stages. It is clear that lower beer still distillate compositions reduce costs in the beer still. In the next section we see what the effect is in the azeotropic and recovery columns.
3. OPTIMIZATION OF THE AZEOTROPIC AND RECOVERY COLUMNS The beer still considered in the previous section can be optimized in isolation given a specified distillate composition. The downstream columns do not affect the beer still since there is no recycle back to it. However, the other two columns must be optimized together because of the recycle of the recovery column distillate back to the azeotropic column and the recycle of the organic phase from the decanter back to the azeotropic column. In the Ryan−Doherty paper the number of stages in the azeotropic column is given as 36, and the number of stages in the recovery column is given as 30. A similar flowsheet was used in a control study7 of these two columns. No consideration of the steady-state economic optimum design was considered in that study. The feed stage locations assumed in that study (using Aspen notation) were as follows:
Table 1. Beer Still Optimization: 85 mol % Casea NF1opt QR1 QC1 ID1 TB1 capital
NT1 NF1opt QR1 QC1 ID1 TB1 capital
Reflux-drum = 351.3 K. 16428
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Then the feed stage location in the recovery column was changed from Stage 11 to Stage 4, which lowered its reboiler duty from 0.7122 to 0.7033 MW and lowered the organic reflux further to 68.86 kmol/h. B. Optimum Number of Stages. The next issue is to find the economic optimum number of stages in each column. The locations of the feeds were scaled up or down directly with the total number of stages using the results for the 32-stage columns. Note that the distillate of the recovery column (D3) is fed to the top of the azeotropic column in all cases. The right three columns in Table 4 give results for the azeotropic column with varying number of stages. The number of stages in the recovery column is fixed at 32. Adding more stages reduces the amount of organic reflux required to meet the specification, which reduces energy consumption. A 62stage azeotropic column gives the minimum TAC of the twocolumn portion of the process. Note that this is almost twice the number of stages recommended by Ryan and Doherty. Then the number of stages in the recovery column is varied with the number of stages in the azeotropic column fixed at 62. Table 5 shows that the optimum number of stages (12 is selected as the minimum practical number) is much smaller than recommended in the Ryan and Doherty design.
1. Beer still distillate (D1) was fed on Stage 15 of a 32-stage azeotropic column. 2. Recycle of recovery column distillate (D3) was fed on Stage 10 of the azeotropic column. 3. The organic phase from the decanter plus a very small benzene makeup was fed at the top of the azeotropic column. 4. The aqueous phase was fed on Stage 11 of the 32-stage recovery column. The azeotropic column feed flow rate was adjusted from that used in the previous study (216 kmol/h) to correspond to the 1000 kmol/h of fermenter broth fed to the beer still used in the present study. With a distillate composition of 85 mol % ethanol, this feed flow rate is 62.44 kmol/h. With this flow rate and with the number of trays and feed locations stated above, the reboiler duty (QR2) in the azeotropic column is 1.597 MW and the reboiler duty in the recovery column is 0.7122 MW. These results are based on designing the azeotropic column for 0.02 mol % benzene and 0.026 mol % water in the bottoms, giving an ethanol product with 99.54 mol % ethanol. The two variables adjusted to achieve these specifications were organic reflux (R2) and bottoms flow rate (B2). The organic reflux for this design is 82.7 kmol/h. The design specification in the recovery column is a bottoms purity of 99.9 mol % water. The separation is quite easy, so the reflux ratio is set at a very small value (RR = 0.1). An Aspen Flash3 model is used for the decanter, so a small vapor stream is required. The decanter is adiabatic, and the heat duty in the overhead condenser is adjusted to give a very small flow rate of gas with the decanter temperature of 322 K and pressure of 0.56 atm. The column labeled “base” in Table 4 gives the economic results for this base-case design. Note that the TAC of the two columns (not including the beer still) is $820,500 per year.
Table 5. Recovery Column Optimization: 85 mol % Case; NT2 = 62
Table 4. Azeotropic Column Optimization: 85 mol % Case; NT3 = 32 base NT2 NF2 organic reflux R2 QR2 QC2 ID2 TB2 QR3 capital azeotropic column recovery column energy azeotropic column recovery column TACa
(kmol/h) (MW) (MW) (m) (K) (MW) (106 $)
32 12 82.70 1.597 1.595 0.868 373.0 0.7122
52 20 62.12 1.280 1.270 0.7643 374.5 0.5944
62 24 60.91 1.255 1.241 0.7643 375.2 0.5773
72 28 60.29 1.243 1.227 0.7443 376.4 0.5692
0.4236 0.3381
0.4468 0.3248
0.4762 0.3228
0.5068 0.3218
0.3918 0.1747 0.8205
0.3140 0.1458 0.7170
0.3079 0.1416 0.7158
0.3050 0.1396 0.7208
12
22
32
3 62 60.99 1.255 1.242 0.7523 381.0 0.5771
3 62 60.98 1.255 1.242 0.7523 379.2 0.5775
4 62 60.91 1.255 1.241 0.7523 375.2 0.5773
(kmol/h) (MW) (MW) (m) (K) (MW) (106 $)
0.4764 0.1986 (106 $/y)
(106 $/y)
0.3079 0.1416 0.6745
Azeotropic and recovery columns: decanter − 322 K, 0.56 atm; azeotropic column − 62 stages, 2 atm; recovery column − 1.1 atm.
a
Remember that these results are for a 85 mol % ethanol beer still distillate. Combining all three columns is considered in the next section. We assume that the optimum numbers of stages in the azeotropic and recovery columns do not change significantly as the beer still distillate composition varies over the range of 75 to 85 mol % ethanol.
(106 $/y)
(106 $/y)
NT3 NF3 NT2 organic reflux R2 QR2 QC2 ID2 TB3 QR3 capital azeotropic column recovery column energy azeotropic column recovery column TACa
Azeotropic and recovery columns: decanter − 322 K, 0.56 atm; azeotropic column − 2 atm; recovery column − 32 stages, 1.1 atm.
a
4. OPTIMIZATION OF THE ENTIRE PROCESS The optimum beer still designs with their associated capital and energy costs are now combined with the azeotropic and recovery column designs for the three values of beer still distillate composition. Table 6 summarizes the results using the previously found optimum designs of the beer still for each distillate composition (xD1) and finding the required organic reflux and reboiler duties in the other two columns for each value of xD1.
A. Optimum Feed Locations. The first issue is to find the optimum feed locations, which were not optimized in the original control study. Changing feed stage locations from Stage 15 and Stage 10 in the azeotropic column to Stage 12 and Stage 1 (top tray in the Aspen stripping Radf rac column) lowered the reboiler duty from 1.597 to 1.456 MW. The flow rate of organic reflux dropped from 82.70 to 69.89 kmol/h. 16429
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Table 6. Overall Optimization: NT2 = 62; NT3 = 12a xD1 D1 organic reflux R2 aqueous phase B3 D3 NT1 QR1 QR2 QR3 capital
energy
TAC
(mol % ethanol) (kmol/h) (kmol/h) (kmol/h) (kmol/h) (kmol/h) (MW) (MW) (MW) (106 $) beer still azeotropic column recovery column total (106 $/y) beer still azeotropic column recovery column total (106 $/y)
75
80
85
66.60 72.86 60.11 16.60 43.51 21 2.828 1.450 0.5826
62.44 65.69 55.61 12.36 43.25 26 2.906 1.333 0.5699
58.76 60.11 53.34 8.733 40.32 46 3.326 1.255 0.5771
0.3318 0.5300 0.1936 1.0454
0.3675 0.4851 0.1970 1.0496
0.5099 0.4764 0.1986 1.1849
0.6938 0.3559 0.1429 1.1926 1.541
0.7130 0.3270 0.1398 1.1799 1.5297
0.8160 0.3079 0.1416 1.2655 1.6605
(D3), which is recycled back to the azeotropic column, decreases slightly. The net result of all these effects on the total capital cost is an increase with increasing beer still composition. The net result of all these effects on the total energy cost is a minimum at a beer still composition of 80 mol % ethanol. Total annual cost also is minimized at 80 mol % ethanol. Figure 1 gives the flowsheet for this case with details of the equipment sizes, stream conditions, and operating conditions. Figure 2 shows the ternary diagram at 2 atm. The overhead
Decanter − 322 K, 0.56 atm; beer still − 1 atm; azeotropic column − 62 stages, 2 atm; recovery column − 12 stages, 1.1 atm. a
The beer still distillate flow rate decreases slightly as distillate composition is increased and less organic reflux (R2) is required. This reduces reboiler duty in the azeotropic column (QR2). However, the reboiler duty in the beer still (QR1) increases as distillate composition is increased, as does the optimum number of stages in the beer still (NT1). So beer still capital and energy costs increase, while those costs in the azeotropic column decrease. The energy and capital costs in the recovery column are less affected by the beer still distillate composition. The flow rate of the feed to the recovery column (Aqueous) decreases since less water needs to be removed from the bottom of the column (B3 decreases as xD1 increases). The recovery column distillate
Figure 2. Ternary diagram at 2 atm.
vapor from the azeotropic column is located in the narrow wedge at the bottom of the upper region. The bottoms of the azeotropic column is located at the ethanol corner. Figure 3 gives the temperature and composition profiles in the azeotropic column. It should be noted that the total energy consumption in the proposed design is 7500 kJ per kg of ethanol product. The Ryan and Doherty flowsheet was stated as 8200 kJ/kg. No
Figure 1. Flowsheet of 80 mol % case. 16430
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Table 7. Comparison of Benzene and Cyclohexane Entrainer Processes (80 mol % Case)a benzene
cyclohexane
organic reflux R2 QR2 QR3 total organic phase
(kmol/h)
65.69
51.71
(MW) (MW) (MW) (mol %)
aqueous phase
(mol %)
1.333 0.5699 1.903 81.85 mol % benzene 7.94 mol % benzene
1.137 0.5215 1.658 92.95 mol % cyclohexane 2.83 mol % cyclohexane
Beer still distillate composition −80 mol % ethanol; azeotropic column − 62 stages, 2 atm; recovery column − 12 stages, 1.1 atm; decanter − 322 K, 0.56 atm.
a
the additional advantage over benzene of avoiding the problem of carcinogenic properties.
6. FLOWSHEET RECYCLE CONVERGENCE Recycle streams can present problems in process simulations. The process studied in this paper has two recycles and is very nonlinear, both of which complicate the convergence of the flowsheet simulation. Up to this point the only successful solution of the problem discussed in the literature7 for this process used the approach of converting the simulation into a dynamic one and then closing the recycle loops with a plantwide control structure in place to drive the process to the desired steady state. During the course of the present study, a different approach was used, which proved quite effective and avoided the conversion to a dynamic simulation. The method uses "homotopy” to slowly converge each recycle loop. For example, in the recycle of recovery column distillate back to the azeotropic column, a temporary flow splitter is installed in the line with the loop closed. A fraction of the total stream (∼5%) is initially specified to be purged out of the process. This makes the closing of the loop less difficult because the numerical convergence algorithm does not have to find the solution where the process equations are perfectly balance so as to precisely match the feed streams fed into the system and all the other fixed variables. Once this initial solution is found, the fraction of the stream split is slowly reduced getting closer and closer to no purge. In the limit as the specified split fraction is made negligibly small, the solution is the desired one. This method was directly and successfully applied to the recovery column distillate recycle loop. The same basic approach was used for the organic recycle loop with some modification. One of the Aspen Design spec/ vary functions used in the azeotropic column manipulated the flow rate of the organic reflux (R2) to attain the specified composition of benzene in the bottoms (0.2 mol % benzene). So the flow rate of this stream could not be independently set. It was also necessary to make a guess of the composition of this stream. To get around this problem, a second flow splitter was inserted in the line after the organic phase from the decanter and the very small benzene makeup stream had been mixed. The loop was not closed. A small fraction of this total stream was purged off. What remains is compared with the R2 flow rate (determined by the design spec/vary function) and the guessed composition of R2. The fraction split is adjusted to make the two flow rates the same, and the composition of R2 is
Figure 3. A. Temperature profile in azeotropic column. B. Liquid composition profiles in azeotropic column.
comparison of capital investment can be made since insufficient information was provided in their paper.
5. CYCLOHEXANE ENTRAINER Benzene has been used in the cases studied in the previous sections. To see the effect of entrainer choice, the same basic process configuration was examined with cyclohexane substituted for benzene. The beer still is not affected. The number of stages and feed locations in the other two columns are kept the same as that used for benzene. The specifications are the same except that the 0.2 mol % impurity in the ethanol product stream is now cyclohexane. The simulation was easily converted to the different solvent. Table 7 gives a comparison of the benzene and the cyclohexane processes. The latter uses less total energy than the former (1.658 versus 1.903 MW) in the reboilers of the azeotropic and recovery columns. The organic phase has a higher cyclohexane concentration than it does in the benzene case (92.95 mol % cyclohexane versus 81.85 mol % benzene). The aqueous phase has a lower cyclohexane concentration than it does in the benzene case (2.82 mol % cyclohexane versus 7.94 mol % benzene). This reduces the required flow rate of the organic solvent from 65.69 kmol/h in the benzene process to 51.71 kmol/h in the cyclohexane process. Of course, cyclohexane has 16431
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adjusted with each iteration to match that calculated. When the loop has converged, there is nothing purged, and the guessed and calculated compositions of R2 are identical.
7. CONCLUSION The main contribution of this paper is pointing out that an important design optimization variable has been neglected in many papers that explore heterogeneous azeotropic distillation for ethanol dehydration. The economic optimum flowsheet has been developed for the benzene entrainer system. The threecolumn configuration proposed by Ryan and Doherty is used. The number of stages in the columns and the feed locations are adjusted to arrive at the most economical design in terms of total annual cost. The composition of the distillate from the beer still is demonstrated to be a key design optimization variable. Ryan and Doherty assume a composition (88 mol % ethanol) quite close to the azeotropic composition. Other authors select compositions around 85 mol %. This paper demonstrates that the optimum is much lower (80 mol %) so that the capital and energy costs of the two sections of the process are economically balanced.
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AUTHOR INFORMATION
Corresponding Author
*Phone: 610-758-4256. Fax: 610-758-5057. E-mail: WLL0@ Lehigh.edu. Notes
The authors declare no competing financial interest.
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REFERENCES
(1) Black, C. Distillation modeling of ethanol recovery and dehydration processes for ethanol and gasohol. Chem. Eng. Prog. 1980, 76 (9), 78. (2) Vane, L. M. Separation technologies for the recovery and dehydration of alcohols from fermentation broths. Biofuels, Bioprod. Biorefin. 2008, 2, 553−588, DOI: 10.1002/bbb. (3) Kiss, A. A.; Suszwalak, D. Enhanced bioethanol dehydration by extractive and azeotropic distillation in dividing-wall columns. Sep. Purif. Technol. 2012, 86, 70. (4) Ryan, P. J.; Doherty, M. F. Design optimization of ternary heterogeneous azeotropic distillation sequences. AIChE J. 1989, 35, 1592−1601. (5) Martinez, A. A.; Saucedo-Luna, J.; Seqovia-Hernandez, J. G.; Hernandez, S.; Comez-Castro, F. I.; Castro-Monteya, A. J. Dehydration of bioethano by hybrid process liquid-liquid extraction/ extractive distillation. Ind. Eng. Chem. Res. 2012, 51, 5847−5855. (6) Li, G.; Bai, P. New operation strategy for separation of ethanolwater by extractive distillation. Ind. Eng. Chem. Res. 2012, 51, 2723− 2729. (7) Luyben, W. L. Distillation Design and Control Using Aspen Simulation, 2nd ed.; Wiley; 2013.
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