Simulation and Cost Analysis of Distillation and Purification Step in

Jul 9, 2017 - Design and operation parameters of the two models are assessed. Aspen Plus version 11.1 is used as the simulation software and the NRTL ...
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Research Article pubs.acs.org/journal/ascecg

Simulation and Cost Analysis of Distillation and Purification Step in Production of Anhydrous Ethanol from Sweet Sorghum Elham Ebrahimiaqda* and Kimberly L. Ogden Department of Chemical and Environmental Engineering, University of Arizona, 1133 James E. Rogers Way, Tucson, Arizona 85721, United States ABSTRACT: Growers often evaluate whether it is economical to double crop their land to increase profit. The aim of the present work is to determine if sweet sorghum (an energy crop) is a reasonable secondary crop to grow in Yuma, Arizona on land that is used to grow lettuce in November−February. Fermentation yields for several varieties of sweet sorghum (Dale, T-Sugar, M81E and 350FS) are compared. Because the sweet sorghum fermentation broth has a high water content, the economic analysis focuses on simulating and optimizing the distillation and purification processes involved in the production of anhydrous ethanol. Two different processes are analyzed: extractive distillation using an entrainer and pressure swing adsorption (PSA) with 3 Å molecular sieves. Design and operation parameters of the two models are assessed. Aspen Plus version 11.1 is used as the simulation software and the NRTL model is used to compute the thermodynamic properties. A flow sheet is proposed containing optimized facility sizing, operating conditions and total annualized cost. At the final stage of the modeling process, highly purified 99.8 wt % ethanol is generated. Applying an extractive distillation method results in a cost that is, on average, 12% less than that of PSA using molecular sieves. KEYWORDS: Bioethanol, Sweet sorghum, Extractive distillation, Pressure swing adsorption, Process simulation, Aspen Plus



INTRODUCTION

To separate the ethanol from the fermentation broth, product distillation and dehydration processes are required, both of which require significant amounts of energy. Employing simple or fractional distillation methods with ethanol−water mixtures as the feed results in a constant boiling mixture bearing a composition of 95 wt % ethanol and 5 wt % water. It is impossible to achieve anhydrous ethanol by sole use of the conventional distillation methods. This shortcoming is a consequence of nonideal behavior of the mixture components (ethanol and water) as well as the occurrence of a minimum of boiling point azeotrope at 78.2 °C. Ethanol dehydration techniques such as vacuum distillation,9 pervaporation membranes,10 extractive distillation with a solvent,11 azeotropic distillation12 and adsorption on molecular sieves13 can be applied to attain ethanol of boosted purity (99.5 mol %). The last three technologies are used for commercial scale production of fuel ethanol, particularly in the US and Brazil.14 One of the two methods studied in the present work is extractive distillation with a solvent. Selection of the solvent as a separation agent has a significant impact in the overall extractive distillation procedure efficiency. The desirable properties of the solvent include a high boiling point,15 nonvolatility, and miscibility in the mixture.16 Hence, glycols

To diminish the ongoing dependence upon fossil fuels, alternative fuel sources ought to be examined. Renewable energy resources have received considerable attention of energy-related research scientists as an environmentally benign replacement for oil and fossil supplies. Bioethanol is a renewable energy source1 produced from fermentable sugar stock in sugar based plants (such as sugar beet, sugar cane and sweet sorghum),2 starched based plants (including corn and wheat) and cellulosic feedstocks (e.g., stalks, leaves and wood chips). It is typically added to fuel across the US at a concentration of 10%3 to lower emissions of some air pollutants. Sweet sorghum is considered as an economically efficient candidate4 for the production of bioethanol due to its compatibility with a variety of soil conditions as well as its rapid growth rate.5,6 This product is also an advantageous choice because it is not a commonplace food source, as opposed to corn and wheat. Sweet sorghum juice possesses a sizable concentration of fermentable sugars (16−18 wt %),7 which varies depending on harvest time, growth conditions and sorghum cultivar. These simple sugars (sucrose, fructose and glucose) can be transformed into ethanol during the fermentation process. The concentration of produced bioethanol is between 5 and 12 wt %,8 hence a significant amount of water must be removed to obtain anhydrous ethanol. © 2017 American Chemical Society

Received: April 10, 2017 Revised: June 24, 2017 Published: July 9, 2017 6854

DOI: 10.1021/acssuschemeng.7b01082 ACS Sustainable Chem. Eng. 2017, 5, 6854−6862

Research Article

ACS Sustainable Chemistry & Engineering are of most interest as solvents in the separation of ethanol utilized by extractive distillation.11 In the current work, adsorption on type 3 Å molecular sieves is the alternative method modeled to separate the remaining water from ethanol−water mixture. Adsorption using molecular sieves as adsorbents at commercial scales became more applicable in 1960s following the discovery of zeolites by Milton.17 The basic adsorption process takes place through pressure swing adsorption (PSA) and temperature swing adsorption (TSA), which are carried out in two fixed beds operating in cyclic adsorption and desorption steps.18 Most of the renewable energy sources rely on sunlight either directly or indirectly. Having the benefit of sunshine makes the state of Arizona an ideal environment to grow energy crops. In particular, the city of Yuma, located in southwest of Arizona, has been reported to have sunshine 90% of the time between sunrise and sunset in a given day.19 Currently, the main crop grown in this city is lettuce for 3−4 months of the year. The rest of the year the cropland is underutilized. Therefore, one of the objectives of this work is to evaluate the economic feasibility of growing additional income crops, specifically sweet sorghum for the production of ethanol. Several studies have been done on the production of ethanol from sweet sorghum and the whole process was evaluated for implementation in China.20,4 In this work, bench scale fermentation data from four varieties of sweet sorghum grown in Arizona formed the basis of the reactor simulations. In addition, extractive distillation with ethylene glycol and pressure swing adsorption using molecular sieves were optimized and compared to understand the best way to remove water from the fermentation broth. Operating, capital and annualized costs were determined for producing ethanol from sweet sorghum in addition to lettuce in Yuma, Arizona.

Table 1. Juice Sugar Composition Profile of Four Sweet Sorghum Varieties Concentration (g/L) Sweet sorghum variety

Sucrose

Glucose

Fructose

Dale Sugar T M81E 350 FS

52.73 66.02 42.22 46.49

41.47 31.59 34.65 33.71

24.59 12.12 20.93 15.46

concentration of fermentation broth was determined based on obtained yield efficiency and initial sugar for all varieties. The fermentation broth is sent to distillation and dehydration processes. A continuous distillation process was simulated to raise the ethanol content to 94(wt %). Two methods were compared to obtain anhydrous ethanol. Major assumptions used for the process calculations are all sugars were treated as glucose and the remaining sugar was ignored in the simulation. Acid and base added to adjust the pH during fermentation and the yeast inoculum were not included in the mass balance.



FERMENTATION Sweet Sorghum Feedstock. The variety of M81E was planted at the University of Arizona West Campus Agricultural Center in Tucson, Arizona. Approximately, 120 days after the planting date, plants were harvested by means of machetes. Stalks were compressed using a modified electric, three-roll sugar cane press and juice was gathered in a collection unit attached to the harvester. Sweet sorghum juice was stored in a −20 °C freezer after harvesting process. Because the same fermentation process is considered for juice extracted from all 4 varieties and there is no major difference among initial amounts of sugar, it is assumed that reported results for M81E are valid for all four specified varieties. Fermentation Experiments. The frozen juice was thawed at room temperature (25 °C) and autoclaved at 121 °C for 20 min and stored at 4 °C in a refrigerator prior to fermentation. Inoculation was completed with the addition of 10 mg of dry Ethanol Red yeast (Saccharomyces cerevisiae) to 1 L of juice. The yeast was provided by Pinal Energy, LLC Maricopa Arizona. Experiments were carried out in a 3 L New Brunswick BioFlo/CelliGen 115 benchtop fermenter for 25 h. Batch fermentations were done at 32 °C at an agitation speed of 200 rpm. NaOH and HNO3 (1 N) were used to maintain fermentation pH at 5 and no other chemicals were added to the media. Throughout the fermentation, 1 mL samples were collected, centrifuged at 12,000 rpm for 10 min, and stored in a −20 °C freezer prior to HPLC analysis. Analysis Method. The amount of sugar in the samples was determined by means of HPLC Shimadzu Prominence UFLC. The column used was a Phenomenex, Rezex ROA-Organic Acid H+ (8%) and 2.5 mN sulfuric acid was the carrier solution in isocratic mode at a flow rate of 0.5 mL/min. Initial and final values of total remaining sugar in the juice (sucrose, glucose and fructose) and ethanol produced during the fermentation time were used to compute the ethanol yield of the process. Fermentation Results. Equation 1 was used to calculate ethanol yield efficiency of fermentation process for M81E juice. The maximum yield for conversion of glucose to ethanol is 0.511 (g/g). Initial and final measurements of ethanol and sugar in the fermentation process were adjusted to account for any reactor volume changes that occurred due to evaporation



PROCESS DESCRIPTION In Yuma, Arizona, annually there are 15 000 acres of double crop land available from mid-February to early-December and 90 000 aces of single crop land from mid-March to end of September. Because sweet sorghum has a growing period of 17 weeks, if the planting is staggered, then 1500 acres of sweet sorghum crops can in theory be harvested weekly. Therefore, the proposed process design is for 22 500 acres of land (15 000 acres or all of the double crop land and 7500 acres of single crop land) to have a continuous weekly feed rate of sweet sorghum. On the basis of data,21 85 000 kg of sweet sorghum stalks is obtained per hectare containing 0.353 (wt %) juice. Calculations were conducted for four varieties of sweet sorghum (Dale, Sugar T, M81E and 350 FS). These cultivars are good candidates for this study because they contain high amounts of fermentable sugar and show good compatibility with the Arizona environment. The maximum amount of sugar 120 days after planting date reported for Dale, Sugar T, M81E and 350 FS were used for process simulation; the values are 119, 110, 98 and 96 (g/L), respectively. The sugar composition profile for the four sorghum varieties is reported in Table 1. Figure 1 contains a schematic of the overall process for producing anhydrous ethanol from sweet sorghum. After harvesting, juice is extracted and separated from bagasse. Sweet sorghum juice is sent to a fermentation unit, the CO2 produced during fermentation is vented, and the solid residuals are filtered and removed. To evaluate yield efficiency of fermentation process, bench scale fermentation was carried out on M81E variety, described in the next section. The ethanol 6855

DOI: 10.1021/acssuschemeng.7b01082 ACS Sustainable Chem. Eng. 2017, 5, 6854−6862

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Figure 1. Schematic for producing ethanol from sweet sorghum.

column, an entrainer is used in the second column to produce absolute ethanol and the entrainer/solvent is recovered in the third column. Figure 3 contains the process flow diagram. On the basis of experimental VLE data22 and phase equilibrium data,11 ethylene glycol is an excellent entrainer. Ethylene glycol (197.3 °C) has a higher boiling point compared to ethanol (78.4 °C and water (100 °C, does not form any new azeotropes, and is the most common solvent used to separate azeotropic mixtures of ethanol and water.8,23 The steady state extractive distillation was carried out using the rigorous method in ASPEN. The feed stream entering the first column is the output stream from the fermenter. It is heated from 32 to 86 °C using energy recovered from the bottom streams of both the regeneration tower (Column 3) and the azeotropic column (Column 1). For this purpose, two heat exchangers are included (E1 and E2). The distillate product from the first tower (stream 4) is an azeotropic mixture of ethanol and water in liquid form. This mixture enters the extractive column (Column 2) and the product from the top of this column (stream 8) is high purity ethanol exiting at the boiling point temperature for pure ethanol. The entrainer, ethylene glycol, enters the extractive column in the upper part of tower (stream 7) in a stage between the distillate tray and the feed tray. The bottom stream from Column 2 enters Column 3 where the high purity ethylene glycol is recovered as the bottom product (stream 11), cooled down and recycled to the extractive column to be used repeatedly. A small amount of the entrainer used in the process exits with the distillate products of second and third columns. To keep the amount of solvent constant, a makeup stream (stream 13) containing a small flow rate of pure solvent is

or pH adjustment. An efficiency of 86% was obtained for fermentation of M81E variety sorghum grown anaerobically at pH of 5 and temperature of 32 °C (Figure 2). ethanol yield efficiency =

mass of ethanol produced mass of sugar consumed × 0.511 (1)

Figure 2. Sugar and ethanol concentration change of M81E variety sorghum juice, during fermentation by Saccharomyces cerevisiae in bioflo115.



EXTRACTIVE DISTILLATION To separate the ethanol from the fermentation broth using extractive distillation, the minimum number of distillation columns required is 3. An azeotrope is formed in the first

Figure 3. ASPEN Flow sheet for distillation and dehydration processes of bioethanol production from sweet sorghum using extractive distillation method. 6856

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type, and the capital cost was calculated based on the surface areas. A major sensitivity analysis for extractive distillation of ethanol and water in the presence of ethylene glycol and CaCl2 has been reported by Gil et al.25 They investigated the impact of different design parameters such as solvent to feed ratio, number of trays, feed stage of azeotropic mixture as well as feed tray of the solvent on purity of final product in the distillate of second column. In this work, a sensitivity of analysis was carried out to show the effects of solvent feed stage, solvent to feed molar ratio, azeotropic feed stage and their interactions on TAC. These factors were varied between 3 and 7, 0.5 to 1, and 16 to 23, respectively. Figures 4a and 5a show the influence of azeotropic feed stage and solvent to feed molar ratio on TAC and energy consumption of reboilers in extractive distillation method for the Dale sweet sorghum variety. As the azeotropic feed stage gets closer to the bottom, the energy for the reboiler increases in order to obtain the specified ethanol purity in the distillate and results in higher TAC. The azeotropic feed stage cannot be close to the top of the column either because sufficient spacing is required between the two feed streams to ensure sufficient contact between the solvent and azeotropic feeds. On the basis of this analysis, the optimum feed stage for the azeotropic mixture is stage number 20. A solvent to feed ratio of 0.65 was obtained as the optimized value to obtain the minimum TAC. Increasing the solvent to feed molar ratio means increasing the input of ethylene glycol to the system, which increases the operating cost of the third column to recover the solvent in bottom stream (stream 11); on the other hand, decreasing it increases the operating cost of second column in order to obtain a high purity product. Varying the design parameters for the second column, such as reflux ratio, and the distillate flow rate confirms that an S/F value lower than 0.50 did not result in an ethanol purity of 99.5%. Figures 4b and 5b show the influence of solvent to feed molar ratio and solvent feed stage on TAC and energy. Solvent feed stage is always located close to the top of the tower and above the azeotropic feed stage. When the solvent feed stage is too close to the condenser and top of the column, there is the possibility of solvent entering the distillate and therefore a

mixed with the recycled stream from the third column and sent to solvent stage of extractive distillation. The specified simulation parameters are given in Table 2 and were applied regardless of which sweet sorghum variety was Table 2. Specified Parameters for Extractive Distillation Process Specified parameters

Value

Pressure (bar) Solvent feed temperature (°C) First column feed temperature (°C) Overall ethanol recovery Ethanol mole fraction in distillate (Column 2) Ethylene glycol recovery in Column 3

1.013 80 86 0.99 0.995 0.9999

simulated as the feedstock. The thermodynamic model of NRTL was applied for all simulations.24−26 According to Carey and Lewis (1932), NRTL is considered to be an appropriate model to validate experimental data on vapor−liquid equilibrium of ethanol and water systems.27 Sensitivity analyses and optimizations were carried out to find the minimum total annualized cost (TAC) for the distillation and dehydration process. TAC is the sum of operating cost and annualized capital cost of the process. The solvent feed stage and molar ratio of solvent to feed (S/F) were optimized for the extractive column and the numbers of stages, feed stage, diameter and reflux ratio (RR) were determined for each column to obtain minimum TAC. TAC = operation cost +

capital cost payback period

(2)

In this work, a payback period of 3 years was applied in eq 2. The minimum TAC for combinations of the three columns for the varieties of sweet sorghum aforementioned is presented in Table 3. Operating and capital costs were determined adopting equations from the book by Turton et al.28 with an updated Chemical Engineering Plant Cost Index.29 Operating costs include cold and hot utility and electricity. The material of construction for the columns and heat exchangers was carbon steel (CS), and the trays were sieve trays made of stainless steel (SS). All the heat exchangers were modeled as shell and tube

Table 3. Cost Evaluation and Configuration of Extractive Distillation Process Parameter

Value

Sweet sorghum variety Initial Sugar (g/L) Column Number Number of stages Feed stage Solvent stage Solvent to feed molar ratio Molar reflux ratio Diameter (m) Height (m) QR (MW) QC (MW) Operating cost (×106$/year) Capital cost (×106$) TAC (×106$)/year) TAC $/kmol ethanol

Dale 119 1 43 25 3.69 1.93 31.45 8.65 −6.94 1.54 3.85 2.82 5.75

2 26 20 4 0.65 0.37 0.98 19.02 2.03 −1.73

T sugar 3 13 6 0.38 0.50 9.51 0.51 −0.30

110 1 43 24 3.94 1.91 31.45 8.48 −6.75 1.49 3.76 2.74 6.05

2 26 20 4 0.65 0.37 0.95 19.02 1.88 −1.60

6857

M81E 3 13 6 0.38 0.48 9.51 0.47 −0.28

98 1 42 22 4.36 1.88 30.72 8.27 −6.53 1.42 3.63 2.63 6.52

2 26 20 4 0.65 0.37 0.89 19.02 1.67 −1.43

350FS 3 13 6 0.38 0.45 9.51 0.42 −0.25

96 1 42 22 4.43 1.87 30.72 8.23 −6.52 1.41 3.61 2.61 6.61

2 26 20 4 0.65 0.37 0.88 19.02 1.64 −1.40

3 13 6 0.38 0.44 9.51 0.41 −0.024

DOI: 10.1021/acssuschemeng.7b01082 ACS Sustainable Chem. Eng. 2017, 5, 6854−6862

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Figure 5. Sensitivity analysis of extractive distillation: (a) effect of variation of S/F and azeotropic feed stage on Qreboiler2+Qreboiler3, (b) effect of variation of S/F and solvent feed stage on Qreboiler2+Qreboiler3.

Figure 4. Sensitivity analysis of extractive distillation (a) effect of variation of S/F and azeotropic feed stage on TAC (b) effect of variation of S/F and solvent feed stage on TAC.

shown in Table 3, the rate of change for capital cost is almost twice as fast as the rate of change for operating cost. Total annualized cost of the separation processes (combination of ordinary distillation and extractive distillation) for production of 1 kmol anhydrous ethanol from all 4 varieties of sweet sorghum is reported in the last row of Table 3. Results show that the annualized cost for production of 1 kmol of anhydrous ethanol increases with decreasing of initial sugar of sweet sorghum variety. Choice of Dale variety with an initial sugar concentration of 119 (g/L) produces the greatest amount of high purity ethanol and is more economic compared to other three varies studied in this paper. Pressure Swing Adsorption on Molecular sieves. Pressure swing adsorption (PSA) combined with distillation was simulated and TAC was determined. A simple PSA system consists of two vertical columns working alternatively in a cycle of pressurization, adsorption, blow down and desorption. The flow sheet in Figure 6 shows column A in the adsorption and column B in the desorption cycle of the process. To be able to compare the dehydration methods, the same flow rate and characteristics as the extractive distillation process were applied for the inlet stream and final product of the system. The feed stream coming from fermentation unit is heated from 32 to 86 °C using the energy from the bottom stream of the distillation column. The overhead stream of the distillation column, consisting of 86 mol % ethanol and 14 mol % water, is superheated and fed to the molecular adsorption

higher reflux ratio (RR2) is required to return the ethylene glycol to the column to obtain 99.5% ethanol in the distillate. As the entering stage of the separating agent approaches the feed stage of the azeotropic mixture, energy consumption in the reboiler of the second column increases and causes a higher operating cost for the second tower resulting in a higher TAC for the entire system. On the basis of these results, the optimized solvent stage is stage number 4 from the top of the column. Graphical results of the sensitivity analysis, Figures 4 and 5, show that changes in solvent to feed molar ratio has more influence on the energy consumption of the reboilers and TAC compared to variation in the entering stage of solvent or azeotropic mixture. Varieties with higher initial sugar concentration result in higher amount of dehydrated ethanol. On the basis of the summarized results reported in Table 3, higher amounts of initial sugar lead to higher capital cost, operating cost and total annualized cost. A comparison between capital and operating cost for all varieties shows that capital cost forms a larger portion of expenses, approximately 72% of total cost. The first distillation column involved in the production process constituted the major portion of capital cost because the concentration of ethanol is between 5 and 6 wt % in the feed stream of this column. Increasing the initial sugar of sweet sorghum from 96 to 119 (g/L) increases both capital and operating cost of extractive distillation and based on the values 6858

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Figure 6. Flow sheet for distillation and dehydration processes in bioethanol production from sweet sorghum using PSA method.

unit from the top at a temperature of 150 °C and a pressure of 3.4 atm. The columns are packed with Zeochem Z3-03 (Zeolite 3 Å).30 Dehydrated ethanol vapor is cooled by heat exchanger E4 and collected at the bottom of adsorption bed. While one bed is used to adsorb the water, the other is regenerated and being prepared for a new cycle. The regeneration step is done under vacuum at 0.3 atm. The amount of anhydrous ethanol required for the purging step was calculated using eq 3:31

Fpurge Ffeed

⎛ t ⎞⎛ P ⎞ = eff⎜⎜ f ⎟⎟⎜ L ⎟ ⎝ t p ⎠⎝ PH ⎠

(3) Figure 7. Concentration profile and breakthrough curves for PSA process for 4 varieties of sweet sorghum.

Where efficiency is in the range of 1.1 to 1.5. F is molar flow rate for feed and purge streams, tf and tp are feed and purge time, respectively. PH and PL refer to adsorption and regeneration pressures. For this simulation, the ratio of Fpurge to Ffeed is 0.15. The purge stream exiting the desorption bed contains 15% of total ethanol produced. A compressor increases the pressure of this stream in order to recycle it to the system. To optimize the system, the heat of the purge stream is recovered in heat exchanger E2 to increase the temperature of azeotropic mixture entering PSA unit. The general mass balance equation to calculate concentration profiles and breakthrough curves for the adsorption process is expressed in eq 4.18 The resulting breakthrough curves are shown in Figure 7. 32

mass of adsorbent. Adsorption of water on molecular sieve particles is represented by a Langmuir isotherm model: q KeqP q = sat 1 + KeqP (5) Where Keq is adsorption equilibrium constant calculated using the correlation obtained by Simo et al.:30 ⎛ Keq ⎞ ⎛ −ΔH ⎞⎛ 1 1⎞ ⎟⎟ = ⎜ ⎟⎜ ln⎜⎜ − ⎟ T0 ⎠ ⎝ Keq0 ⎠ ⎝ R ⎠⎝ T

− DL

(1 − εb) ∂q ∂(uc) ∂c ∂c + + ρb =0 + ∂z ∂t ∂t εb ∂z 2

(6)

In the equations, T0 is the reference temperature, ΔH is heat of adsorption and Keq 0 is adsorption equilibrium constant at reference temperature. To simplify eq 4 and the simulation of the PSA process, the following assumptions were made: negligible axial dispersion and pressure drop in both columns,

2

(4)

Where εb the void fraction of the bed, DL is eddy diffusivity, ρb bulk density and q is mass-average adsorbate loading per unit 6859

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ACS Sustainable Chemistry & Engineering constant fluid velocity, adiabatic operation, isothermal plug flow for adsorption and desorption, ideal gas phase, and no adsorption of ethanol to the molecular sieves. The Linear Driving Force equation was assumed for the mass transfer calculation in the PSA process. The analytical solution for the simplified form of eq 4 is defined as the Klinkenberg Equation:17 ⎡ ⎛ c ≈ 0.5⎢1 + erf ⎜⎜ τ − cF ⎢⎣ ⎝

⎤ 1 ⎞⎥ ⎟⎟ ξ + + 8 τ 8 ξ ⎠⎥⎦

sensitivity analysis was done to determine optimized values for RR, number of stages and feed stage of distillation column. Results are presented in Table 5. Table 5. Cost Evaluation and Configuration of PSA Process Sweet sorghum variety Initial sugar (g/L) First column Number of stages Feed stage Reflux ratio Diameter (m) Height (m) QC (MW) QR (MW) Adsorption/Desorption column Diameter (m) Height (m) Compressor (MW) Economic evaluation Operating cost (×106$/year) Capital cost (×106 $) TAC (×106$)/year) TAC $/kmol ethanol

1

(7)

Where τ is dimensionless time and ξ is dimensionless distance: ⎛ z⎞ τ = k ⎜t − ⎟ ⎝ u⎠ ξ=

(8)

⎛ Kkz ⎞⎛ 1 − εb ⎞ ⎜ ⎟⎜ ⎟ ⎝ u ⎠⎝ εb ⎠

(9)

Where K is the adsorption equilibrium constant for a linear adsorption isotherm (q = Kc) and k is the overall mass transfer coefficient including external and internal resistances calculated from eq 10 adopted from Seider et al.:18

Rp R p2 1 = + Kk 3kc 15De

Sh = 2 + 1.1(Re)0.6 (Sc)1/3

(11)

Table 4. PSA Operation Parameters

Bulk density (ρb) Equilibrium water capacity Particle radius (RP) Reference temperature (T0) Langmuir equilibrium constant at T0 (Keq 0) Heat of adsorption for adsorbent (ΔH)

M81E

350FS

119

110

98

96

43 28 3.28 2.00 31.45 −7.45 9.17

41 26 3.52 1.98 30 −7.26 8.99

40 24 3.86 1.95 29.26 −6.97 8.72

38 23 4.01 1.95 27.80 −7.03 8.72

0.98 4.35 0.076

0.93 4.19 0.070

0.88 3.94 0.062

0.87 3.91 0.061

1.52 4.56 3.06 6.23

1.49 4.65 3.03 6.72

1.41 4.89 3.06 7.56

1.42 4.95 3.06 7.76

On the basis of the summarized cost analysis of separation processes (distillation and PSA) in Table 5, operating, capital and total annualized cost of the process for producing anhydrous ethanol do not vary substantially with sorghum variety. The total cost calculated for the first column constitutes about 80% of cost of the process shown in Figure 6. Feed entering the distillation column has between 5 and 6% ethanol; therefore, a large amount of energy and a high investment in capital cost is needed to prepare the azeotropic feed for the PSA process. Operating cost increases for varieties with higher initial sugar concentration, but capital cost decreases. The last row of Table 5 reports total annualized cost for production of each kmol of dehydrated ethanol. Dale with an initial concentration of 119 (g/L) is the better candidate. According to Teetor et al.,21 Dale is among the varieties that mature fast and also the planting time has no significant effect on its productivity. Another factor that makes this variety a great candidate is that it has a high germination efficiency, which leads to better sustainability during storage.34 Because Dale is the best variety for the desert Southwest, a final comparison of the two dehydration processes demonstrates that extractive distillation is more cost-effective. More specifically, the total annualized cost for extractive distillation is $2.82 million/year compared to $3.05 million/year for the PSA method. The difference is primarily due to the high capital cost of the PSA system. Likewise, the total annualized cost for each kmol of ethanol produced is $5.75 using the extractive distillation process compared to $6.23 for PSA. On average, the costs associated with PSA are 12% higher than the cost of using extractive distillation.

Where Sh is Sherwood number = 2RPkc/Di, Di is molecular diffusivity, Re is the Reynolds number = 2RPρLεbu/μ, μ and ρL are fluid viscosity and fluid density, respectively and Sc is Schmidt number = μ/ρLDi. Design characteristics of columns and absorbing beds were configured based on guide lines provided by Kvamsdal and Hertzberg33 and the adsorbent manufacturer (Zeochem), respectively.32 Table 4 shows the properties of the molecular sieves type 3 Å used in this simulation.

Parameter

T sugar

(10)

Where De is effective diffusivity, RP is the radius of adsorbent particle and kc is the external mass-transfer coefficient, which can be estimated by Sherwood number correlation, eq 11.

Adsorbent porosity (εP) Bed void Fraction (εb) Low pressure (PL) High pressure (PH) Properties of Adsorbent-3 Å molecular sieve30

Dale

Value 0.37 0.40 0.3 atm 3.4 atm Value 729 kg/m3 19.21 wt % 1.59 mm 323 K 0.04 Pa−1 51900 J/mol H2O



CONCLUSION The proposed process uses 22 500 acres of sweet sorghum crop annually in Yuma, Arizona, which allows the plant to operate continuously for 175 days of the year. This region is used to grow lettuce primarily, and there are sufficient water rights to irrigate the proposed acreage. As stated earlier, the focus of this

Equation 2 was applied to determine the TAC for this process. The distillation column, PSA columns, heat exchangers and compressor were considered in calculation of capital cost. Operating cost consists of molecular sieves used as adsorbents and energy consumed in the reboiler and condenser of the distillation tower and heat exchangers and compressor. A 6860

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adsorption equilibrium constant for water in a linear adsorption isotherm Keq Langmuir isotherm adsorption equilibrium constant (pa−1) P pressure (Pa) QC condenser heat duty (MW) QR reboiler heat duty (MW) R universal gas constant (J mol−1 K−1) RR reflux ratio Re Reynolds number Rp particle radius (m) ρb bulk density (kg m−3) ρL fluid phase density (kg m−3) T temperature (K) Sc Schmidt number Sh Sherwood number t time (s) τ dimensionless time u velocity (m s−1) z spatial coordinate (m)

study is on techno-economic calculations of downstream processes of distillation and dehydration to separate ethanol from sweet sorghum fermentation broth. The equivalent cost of this part of an ethanol production facility is between 40 and 50 cents/gal. The operation process, operating cost, capital cost, column configurations and total annualized cost are investigated and optimized by simulation with Aspen Plus software. Optimizing parameters for extractive distillation shows that the solvent to feed molar ratio is the most important factor influencing the purity and TAC of ethanol produced in the second column. The feed entering the distillation column contains small amounts of ethanol and to obtain a high purity product, a significant amount of energy is required to concentrate the ethanol to its azeotrope. Therefore, the capital cost and operating cost of the first column accounts for between 70 and 80% of the TAC in both methods. Comparing the operating and capital costs reported in Tables 3 and 5 for each individual variety shows that the operating cost for either method is approximately the same. However, the capital cost for the PSA method is notably higher than the extractive distillation process. Results presented in Tables 3 and 5 show that the value for TAC per kmol of dried ethanol produced decreases as the initial sugar concentration of the varieties increases. Sweet sorghum varieties with higher amounts of sugar can produce higher amounts of ethanol. However, the cost of production for the varieties investigated containing initial sugar values between 96 and 119 (g/L) was not remarkably different. Higher sugar is always better, but not the major cost driver. Comparing TAC values of pressure swing adsorption with molecular sieves and extractive distillation with ethylene glycol for the four varieties studied demonstrates that extractive distillation with ethylene glycol represents the more economical alternative dehydration method. This method is recommended for further investigation for the Yuma region if energy crops such as sweet sorghum are grown there in the future.





(1) Gray, K. A.; Zhao, L.; Emptage, M. Bioethanol. Curr. Opin. Chem. Biol. 2006, 10 (2), 141−146. (2) Drapcho, C. M.; Nghim, P. N.; Walker, T. H. Biofuels Engineering Process Technology; McGraw-Hill: New York, 2008. (3) Demirbas, A. Biofuels sources, biofuel policy, biofuel economy and global biofuel projections. Energy Convers. Manage. 2008, 49 (8), 2106−2116. (4) Gnansounou, E.; Dauriat, A.; Wyman, C. E. Refining sweet sorghum to ethanol and sugar: economic trade-offs in the context of North China. Bioresour. Technol. 2005, 96 (9), 985−1002. (5) Zegada-Lizarazu, W.; Monti, A. Are we ready to cultivate sweet sorghum as a bioenergy feedstock? A review on field management practices. Biomass Bioenergy 2012, 40, 1−12. (6) Calvino, M.; Messing, J. Sweet sorghum as a model system for bioenergy crops. Curr. Opin. Biotechnol. 2012, 23 (3), 323−9. (7) Wu, X.; Staggenborg, S.; Propheter, J. L.; Rooney, W. L.; Yu, J.; Wang, D. Features of sweet sorghum juice and their performance in ethanol fermentation. Ind. Crops Prod. 2010, 31, 164−170. (8) Huang, H.-J.; Ramaswamy, S.; Tschirner, U. W.; Ramarao, B. W. A review of separation technologies in current and future biorefineries. Sep. Purif. Technol. 2008, 62, 1−21. (9) Black, C. Distillation modeling of ethanol recovery and dehydration processes for ethanol and gasohol. Chem. Eng. Prog. 1980, 76, 78−85. (10) Sander, U.; Soukup, P. Design and operation of a pervaporation plant for ethanol dehydration. J. Membr. Sci. 1988, 36, 463−475. (11) Meirelles, A.; Weiss, S.; Herfurth, H. Ethanol Dehydration by Extractive Distillation. J. Chem. Technol. Biotechnol. 1992, 53, 181−188. (12) Chianese, A.; Zinnamosca, F. Ethanol dehydration by azeotropic distillation with a mixed-solvent entrainer. Chemrcal Engmeerzng Journal 1990, 43, 59−65. (13) Carmo, M. J.; Gubulin, J. C. Ethanol−water adsorption on commercial 3a zeolites: kinetic and thermodynamic data. Braz. J. Chem. Eng. 1997, 14 (3), 1−10. (14) Bastidas, P. A.; Gil, I. D.; Rodríguez, G. Comparison of the main ethanol dehydration technologies through process simulation. In 20th European Symposium on Computer Aided Process Engineering − ESCAPE20, June 6−9, Ischia Porto, Italy; Pierucci, S.; Ferraris, G. B., Eds.; Elsevier: Amsterdam, 2010. (15) Medina-Herrera, N.; Grossmann, I. E.; Mannan, M.; JiménezGutiérrez, A. An approach for solvent selection in extractive distillation systems including safety considerations. Ind. Eng. Chem. Res. 2014, 53 (30), 12023−12031. (16) Perry, P. Chemical Engineer’s Handbook, 7th ed.; McGraw-Hill: New York, 1992.

AUTHOR INFORMATION

Corresponding Author

*E. Ebrahimiaqda. E-mail: [email protected]. ORCID

Elham Ebrahimiaqda: 0000-0002-2929-4810 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work has been supported by the USDA Sun Grant No. 09W-T020. C CF De Di DL ΔH εb εP ξ F k kc

REFERENCES

NOMENCLATURE fluid phase molar concentration (mg L−1) initial concentration in fluid phase (mg L−1) effective diffusion coefficient (m2 s−1) molecular diffusivity (m2 s−1) axial dispersion coefficient (m2 s−1) Heat of adsorption (J mol−1) the column bed porosity adsorbent porosity dimensionless distance Molar flow rate (kmol h−1) overall mass-transfer coefficient (s−1) external mass-transfer coefficient (m s−1) 6861

DOI: 10.1021/acssuschemeng.7b01082 ACS Sustainable Chem. Eng. 2017, 5, 6854−6862

Research Article

ACS Sustainable Chemistry & Engineering (17) Milton, R. M. Molecular sieve adsorbents. Patent US2882243A, April 14, 1959. (18) Seader, J. D.; Henley, E. J. Separation Process Principles; John Wiley & Sons, Inc.: New York, 1998. (19) Osborn, L. Sunniest Places in United States. http://www. currentresults.com/Weather-Extremes/US/sunniest.php (accessed November 2016). (20) Gao, H.; Hu, S.; Li, Y.; Chen, D.; Zhu, B. Life-cycle energy and economic analysis of sweet sorghum ethanol in China. Tsinghua Univ. 2010, 50 (11), 1858−1865. (21) Teetor, V. H.; Duclos, D. V.; Wittenberg, E. T.; Young, K. M.; Chawhuaymak, J.; Riley, M. R.; Ray, D. T. Effects of planting date on sugar and ethanol yield of sweet sorghum grown in Arizona. Ind. Crops Prod. 2011, 34, 1293−1300. (22) Pla-Franco, J.; Lladosa, E.; Loras, S.; Montón, J. B. Phase equilibria for the ternary systems ethanol, water+ethylene glycol or +glycerol at 101.3 kPa. Fluid Phase Equilib. 2013, 341, 54−60. (23) Lynn, S.; Hanson, D. N. Multieffect Extractive Distitaltion for Separating Aqueous Azeotropes. Ind. Eng. Chem. Process Des. Dev. 1986, 25, 936−941. (24) Gil, I. D.; García, L. C.; Rodríguez, G. Simulation of ethanol extractive distillation with mixed glycols as separating agent. Braz. J. Chem. Eng. 2014, 31 (1), 259−270. (25) Gil, I. D.; Uyazán, A. M.; Aguilar, J. L.; Rodríguez, G.; Caicedo, L. A. Separation of ethanol and water by extractive distillation with salt and solvent as entrainer: Process simulation. Braz. J. Chem. Eng. 2008, 25 (1), 207−215. (26) Llano-Restrepo, M.; Aguilar-Arias, J. Modeling and simulation of saline extractive distillation columns for the production of absolute ethanol. Comput. Chem. Eng. 2003, 27 (4), 527−549. (27) CAREY, J. S.; Lewis, W. K. Studies in Distillation Liquid-Vapor Equilibria of Ethyl Alcohol-Wat er Mixtures. Ind. Eng. Chem. 1932, 24 (8), 882−883. (28) Turton, R.; Bailie, R. C.; Whiting, w. B.; Shaeiwitz, J. A. Analysis, Synthesis, and Design of Chemical Processes, 3rd ed.; Pearson Education, Inc.: Boston, MA, 2009. (29) Chemical engineering. http://www.chemengonline.com/pcihome. (30) Simo, M. Pressure Swing Adsorption Process for Ethanol Dehydration. State University of New York at Buffalo, 2008. (31) Ruthven, D. M.; Farooq, S.; Knaebel, K. S. Pressure Swing Adsorption; Wiley-VCH: Hoboken, NJ, 1994. (32) Trent, R. E. Molecular Sieves for Alcohol Drying; ZEOCHEM: Louisville, KY. (33) Kvamsdal, h.M.; Hertzberg, T. A preliminary design study of a multicomponent PSA gas separation system. Chem. Eng. Process. 1996, 35, 213−224. (34) Broadhead, J. H.; Colleman, O. H.; Freeman, K. C. Dale, a new variety of sweet sorghum for syrup production; US Sugar Crop Field Station: Meridian, MS, 1970.

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DOI: 10.1021/acssuschemeng.7b01082 ACS Sustainable Chem. Eng. 2017, 5, 6854−6862