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Design and Economic Analysis of the Process for Biodiesel Fuel Production from Transesterificated Rapeseed Oil Using Supercritical Methanol Youngsub Lim, Hong-shik Lee, Youn-Woo Lee,* and Chonghun Han* School of Chemical and Biological Engineering, Seoul National UniVersity, San 56-1, Shillim-dong, Kwanak-gu, Seoul, 151-742, Korea
A supercritical process for biodiesel fuel production is generally known to be less profitable than the alkalicatalyzed process due to high temperature and pressure requirements for the supercritical reaction. Only a few approaches have been proposed using experimental results to design a supercritical biodiesel process and to assess its profitability compared to the alkali-catalyzed process. In this study, a design for a supercritical biodiesel process was suggested and its economic performance with three different reaction conditions was simulated in the comparison with the conventional alkali-catalyzed process. It was found that the total capital cost was higher in all three cases of the supercritical process than in the alkali-catalyzed process due to the high cost of pumps, heaters, and heat exchangers. However, the total manufacturing cost of the supercritical process was lower than that of the alkali-catalyzed process due to the higher glycerol credit and the lack of a requirement for catalyst or solvent. The supercritical process can produce high-purity glycerol more easily that does not contain any water, which is unavoidable in the washing step of the alkali-catalyzed process. The higher steam cost in the supercritical process was compensated for by catalyst and solvent costs in the alkali-catalyzed process. Overall, one of the supercritical processes resulted in shorter payout time than the alkali-catalyzed process even when virgin oil was used as one of the raw materials, because the lower total manufacturing cost made up for the increased total capital cost. 1. Introduction As worldwide energy consumption has been increased, so has concern over the depletion of natural resources like petroleum. This concern has sparked growing interest in biodiesel fuel (BDF).1-6 BDF is a group of fatty acid methyl esters (FAMEs), a diesel-equivalent fuel derived from biological sources; it is biodegradable and nontoxic and produces less carbon dioxide than petroleum diesel. Conventional BDF is commonly produced from vegetable oil via transesterification reaction with an alkali/acid catalyst as shown in Figure 1. In recent years, alternative BDF production process using supercritical methanol has been suggested. Meanwhile, the conventional BDF production process requires neutralization units, catalyst separation units, and washing and drying units to remove water as shown in Figure 2.7,8 However, the noble supercritical process does not require catalysts, and therefore, the neutralization, washing, and drying steps can be also omitted from the process. Furthermore, the supercritical process can increase the yield and allow the waste oil to be used as a raw material, negating the need to pretreat free fatty acids (FFAs) or water. However, due to the high temperature and pressure requirements for the supercritical reaction, high capital and manufacturing costs are expected. It has therefore been generally understood that the supercritical process would not be as profitable as the alkali-catalyzed process where virgin oil is used as the raw material.9-17 Table 1 summarizes the above differences between the supercritical BDF production process and the conventional BDF production process. Many researchers have studied the supercritical BDF production process in comparison to the alkali-catalyzed process, in experimental aspects as well as economical aspects. Saka and co-workers10,11,13,14,18,28,29 have studied the reaction conditions * To whom correspondence should be addressed. Tel.: 82-2-8801887. E-mail:
[email protected] (C.H.); Tel.: 82-2-880-1883. E-mail:
[email protected] (Y.-W.L.).
and kinetics of the supercritical BDF production process. Cao et al.19 reported the effect of cosolvent in supercritical reaction conditions. All these studies are purely experimental work and did not consider the economic aspect of the supercritical process.
Figure 1. Transesterification reactions of oil (glycerides) with methanol to produce BDF.
Figure 2. Diagram illustrating the conventional BDF production process. Table 1. Differences between Conventional and Supercritical Processes for BDF Production
catalyst reaction time reaction temp (°C) reaction pres (bar) FFA sensitive water sensitive pretreatment catalyst removal
conventional process
supercritical process
yes minutes-hours 50-80 1 yes yes yes yes
no minutes 200-400 200-400 no no no no
10.1021/ie8005287 CCC: $40.75 2009 American Chemical Society Published on Web 04/22/2009
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The economic analyses have been performed by simulation works.20-24 Van Kasteren and Nisworo20 evaluated the cost of BDF production from waste cooking oil using supercritical methanol with waste cooking oil as the raw material; they used the experimental results from Cao et al. and analyzed the economic competitiveness of the supercritical process and compared it to the results of Zhang et al.,21,22 which compared the economic feasibility of alkali- and acid-catalyzed BDF processes. West et al.23 analyzed four continuous BDF processes using supercritical methanol and waste oil: traditional homogeneous alkali-catalyzed process, homogeneous acid-catalyzed process, heterogeneous acid catalyst process, and supercritical process. They showed that supercritical process ranked the second best in economical efficiency among four processes. Marchetti and Errazu24 also analyzed the four processes using supercritical methanol and waste oil. In both studies, no experiment to verify the simulation results was performed as well and they adopted the experimental results from Saka and co-workers. Yet, to the authors’ knowledge, there has been no report to date that combined an analytical study with verifying experiments. Also, previous works did not consider the effect of unwanted residue that is produced when the waste oil is used as raw material. It has been also claimed that high temperature and pressure of the supercritical process could generate polymerized or decomposed impurities even when the virgin oil is used as raw material18,25 and the need of combined study is hereby clearly stated. The objective of this study is therefore to design the supercritical process for BDF production considering actual experimental data as well as the unwanted residue. The supercritical process and our own experimental data will be described in sections 2 and 3. Then, the economic performance of the supercritical process using three different conditions including ours will be analyzed and compared to the alkalicatalyzed process in section 4. In section 5, the results are discussed. 2. Process Design and Modeling A hierarchical conceptual design26 was adopted based on the experimental data which will be described in a later section and shown in Figure 3. First, a continuous plug flow reactor (PFR) was selected for level 1 because considering production rate and market forces, there was no need to use a batch reactor for the BDF process. At level 2, the input-output structure and flow rates were decided based on the mass balance. As raw material, rapeseed oil and methanol were supplied and it was assumed that no feed impurities exist. To move the equilibrium of reaction toward forward reaction, excess methanol is needed. The plant capacity of the BDF process was assumed to be at 1000 kg/h, the same as 8000 ton/y in the work of Zhang et al. Then, the feed rates of oil and methanol were calculated from the reaction yield and the capacity of the BDF process. The reaction yields for FAMEs, FFAs, and residue were obtained from the experimental data. At level 3, we added recycle structure after a reactor to recycle excess methanol. Since remaining methanol decreases the purity of products and recycled methanol could be used as raw material, it is better to recycle all possible excess methanol in the process using a separation system. At level 4, basically three separation units were placed: one to to recycle excess methanol; one to separate glycerol from main stream as a byproduct; and the last one to refine BDF and remove residues. For the efficient recycling of methanol, a distillation column was used as a separation system. A decanter was used to separate the glycerol from FAMEs by the density difference between glycerol and FAMEs. A distil-
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Figure 3. Hierarchical conceptual design of the supercritical BDF production process.
lation column was needed to separate the BDF and the residues were disposed as waste. At level 5, considering heat exchange between hot streams after reaction and cold streams before reaction, the process flow diagram (PFD) was designed. Figure 4 shows the PFD for BDF production using Aspen Plus 2006. Table 2 shows the unit models employed. Rapeseed oil (1FEED-O1, O2, O3) and methanol (1FEED-M1, M2, M3, M4) were used as raw materials. Since the content of triglyceride (TG) in natural fat is usually more than 97%, the TG content of the rapeseed oil was assumed to be 100% for making the model simple. As shown in Table 3, triolein (C57H104O6) and trilinolein (C57H98O6) take approximately 86% of the rapeseed oil, and it was also assumed that rapeseed oil has only those two components. Two streams of oil and methanol were pumped up to reach the reaction pressure using pumps (PUMP1, PUMP2) and preheated through heat exchangers (HX1, HX2). A shortcut model was used to calculate the heat duty under the assumption of the minimum temperature difference, 15 °C. Then, the oil and methanol streams were mixed together at the MIXER1 and heated to the reaction temperature by the heater, H1. This mixed feed stream (1MIXF-2) flew into the supercritical reactor (REACTOR). On the basis of the results of the experiments, the RYield model with normalized component yields was used as a reactor model. The reactor effluent flow (2RXOT-H1) contained excess methanol, glycerides, FFAs, and residues as well as the product, FAMEs. This reactor effluent flow was cooled down when going through heat exchangers (HX1, HX2) and cooler (C1) and went into the first distillation column for methanol separation (MEOHCOL). The RadFrac unit model was used as a rigorous distillation column model. The four-stage atmospheric pressure column was used to separate the methanol efficiently from the main stream. The distillate rate and the reflux ratio were decided to satisfy the constraints such as purity, recovery, and methanol specification for the BDF product. Excess methanol was removed as a
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Figure 4. Process flow diagram for BDF production using supercritical methanol. Table 2. Unit Models for Modeling name
model used
name
model used
MIXER-1,2 PUMP-1,2 HX-1,2 H1, C-1,2
mixer pump heat exchanger heater
REACTOR DECANTER MEOHCOL BDFCOL
RYield decanter RadFrac RadFrac
Table 3. Contents of Rapeseed Oil and FAME Product carbon chain number
chemical name in rapeseed oil
C16:0 C18:0 C18:1 C18:2 C18:3 other total
tripalmitin tristearin triolein trilinolein trilinolenin
chemical name of FAME product methyl methyl methyl methyl methyl
palmitate stearate oleate linoleate linoleneate
composition (%) 3.5 0.9 64.1 22.3 8.2 1.0 100.0
distillate (MeOH) at the top of the column. Then, the bottom flow of the methanol column (3FLOT-H1) including glycerol, gylcerides, residues, and FAMEs was cooled down to 40 °C. The glycerol was separated out using a decanter (DECANTER) as a byproduct (GLYCEROL). After that, the remaining crude BDF stream (4CRDBDF) was refined using a distillation column (BDFCOL). The required number of stages was 14. The reflux ratio was set to satisfy the specification of glycerides and the residues for BDF product. Although the major component of the residues was not identified, most of the residues were assumed to be polymerized material because the experiment showed that these residues were efficiently removed as a bottom stream by distillation. Therefore, N-hexatriacontane (C36H74) was selected to represent the residues, since the representative FAMEs, methyl oleate, and methyl linoleate have 18 carbons. Because methanol and glycerol are polar components, the electrolyte nonrandom two liquid (NRTL) model was used as the main property method. The universal functional activity coefficient (UNIFAC) model with the Redlich-Kwong equation of state was used as a subproperty model. 3. Experiments In the experiments, rapeseed oil was used as raw material. A system with a continuous-type reactor for BDF production was constructed as shown in Figure 5. Rapeseed oil and
Figure 5. Schematic diagram of the experimental setup for supercritical BDF production.
methanol were fed by pumps and preheated by external electric furnaces before mixing. The mixture was introduced into the reactor and heated to the target temperature. The reaction pressure was controlled by a back-pressure regulator. The molar ratio and the reaction time of reactants were determined by flow rates. The reaction temperature was ranged 250-400 °C, and the reaction time was 5-60 min. The molar ratio of methanol to oil and reaction pressure was fixed at 40:1 and 350 bar because those parameters do not affect the yield of FAMES significantly above those values. An evaporator was used to separate large amount of excess methanol from the reactor effluent. After separating methanol, the reactor effluent was then centrifuged to separate glycerol as a byproduct. The contents of the FAMEs and glycerides were analyzed by gas chromatograph (GC, Agilent, HP-6890) according to European Standard (EN) 14103 and EN 14105. The content of free fatty acids was measured by the titration method presented in EN 14104. Figures 6 and 7 show the gas chromatograms of FAMEs and glycerides, respectively.
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Figure 6. Gas chromatogram of FAMEs.
Figure 7. Gas chromatogram of glycerides. Table 4. Reaction Conditions of Various Processes and their Yields process
temp pres methanol to reaction yield (°C) (bar) oil molar ratio time (min) (%)
alkali-catalyzed process21,22 60 supercritical-Case 1 300 (our experiments) supercritical-Case 210,11 350 310 supercritical-Case 325
4 350
6:1 40:1
90 30
95 95.1
430 350
42:1 40:1
4 25
95 96
From a series of experiments, it was found that the maximum reaction yield is achieved when reaction temperature is 300 °C and the reaction time is 30 min. Under this condition, the reaction yield was 95.1% for FAMEs, 1.5% for monoglycerides, 0.2% for free fatty acids, and 3.2% for residues, respectively. Diglycerides and triglycerides were not detected. 4. Economic Analysis For economic analysis, reaction temperature, pressure, molar ratio of methanol to oil, reaction time, and the resulting yield of FAMEs were used as key manipulated variables. The reaction yield is the most important variable among them because the cost of BDF production processes strongly depends on the cost of raw materials. The reaction conditions for supercritical process and the alkali-catalyzed process are compared in Table 4. The alkalicatalyzed process that Zhang and his co-worker adopted21,22 is the conventional process using alkali-catalysis, which requires the lowest reaction temperature (60 °C), pressure (4 bar), and molar ratio of methanol to oil (6:1). The reaction yield of this process was reported to be 95%.19 Case 1 is a supercritical process using our experimental data as mentioned above. Case 2, suggested by Saka and Kusdiana10,11 in 2001, requires higher reaction temperature (350 °C), pressure (430 bar), and molar ratio of methanol to oil (42:1) even compared to other
Table 5. Costs of Chemicals and Utilities19,20,23,27 item
price ($/ton)
glycerol (pharmaceutical grade) methanol rapeseed oil NaOH H3PO4 cooling water (400 kPa, 6 °C) electricity low-pressure steam high-pressure steam waste treatment (liquid)
1200 180 500 4000 340 $0.007/m3 $0.062/kWh $7.78/GJ $19.66/GJ 150
supercritical conditions. However, the reaction time is much shorter, only 4 min compared to 25-90 min in other conditions. In case 3, suggested by He et al.25 in 2006, reaction conditions are close to those in case 1. They reported that the reaction yield could be improved to 96% by gradual heating. Economic analysis was performed on these supercritical process conditions using the model we have suggested and the method of Turton et al.27 The plant capacity of each process was assumed to be the same: 8000 ton/y and 8000 operating h/y. The equipment size of each process unit was estimated based on the pump power, heat exchanging area, fluid volume, and the flow rate. To estimate the total capital cost including direct cost and indirect cost, the bare module equipment cost, CBM, was calculated for each equipment. CBM ) C0pFBM The purchase cost for base conditions, 2.
(1) Cp0,
is calculated by eq
log10 C0p ) K1 + K2 log10(A) + K3[log10(A)]2
(2)
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Table 6. Stream Table for Various Supercritical Processes Case 1 (Our Experiments) stream temp (°C) pres (bar) mass flow (kg/h)
1MIXF-2
2RXOT-H1
300.0 350.0 2564.4
299.7 350.0 2564.4
3FLOT-H1
4CRDBDF
190.6 1.0 1163.2
40.0 1.0 1056.6
GLYCEROL 40.0 1.0 106.6
BDF 231.9 1.0 1000.0
RESIDUES 468.3 1.0 56.6
composition (wt %) MeOH Gly BDF TG MG FFA residue
0.592 0.000 0.000 0.408 0.000 0.000 0.000
0.548 0.040 0.389 0.000 0.007 0.001 0.014
0.004 0.089 0.858 0.000 0.015 0.002 0.031
0.001 0.000 0.945 0.000 0.017 0.002 0.035
0.026 0.973 0.000 0.000 0.002 0.000 0.000
0.002 0.000 0.988 0.000 0.008 0.002 0.000
0.000 0.000 0.186 0.000 0.170 0.000 0.644
Case 210,11 stream temp (°C) pres (bar) mass flow (kg/h)
1MIXF-2
2RXOT-H1
350.0 350.0 2640.3
349.7 350.0 2640.3
3FLOT-H1
4CRDBDF
188.1 1.0 1163.4
40.0 1.0 1056.7
GLYCEROL 40.0 1.0 106.7
BDF 229.0 1.0 1000.0
RESIDUES 470.0 1.0 56.7
composition (wt %) MeOH Gly BDF TG MG FFA residue
0.604 0.000 0.000 0.396 0.000 0.000 0.000
0.561 0.039 0.378 0.000 0.007 0.001 0.014
0.004 0.089 0.857 0.000 0.016 0.002 0.032
0.001 0.000 0.944 0.000 0.017 0.002 0.035
0.027 0.971 0.000 0.000 0.002 0.000 0.000
0.002 0.000 0.988 0.000 0.008 0.002 0.000
0.000 0.000 0.169 0.000 0.175 0.000 0.655
Case 325 stream temp (°C) pres (bar) mass flow (kg/h)
1MIXF-2
2RXOT-H1
310.0 350.0 2530.0
309.7 350.0 2530.0
3FLOT-H1
4CRDBDF
190.8 1.0 1147.6
40.0 1.0 1041.4
GLYCEROL 40.0 1.0 106.1
BDF 233.2 1.0 1000.0
RESIDUES 475.1 1.0 41.4
composition (wt %) MeOH Gly BDF TG MG FFA residue
0.592 0.000 0.000 0.408 0.000 0.000 0.000
0.548 0.041 0.393 0.000 0.006 0.001 0.012
0.004 0.090 0.866 0.000 0.012 0.002 0.026
0.001 0.000 0.955 0.000 0.014 0.002 0.028
0.025 0.973 0.000 0.000 0.001 0.000 0.000
0.002 0.000 0.988 0.000 0.008 0.002 0.000
0.000 0.000 0.146 0.000 0.150 0.000 0.704
Table 7. Heat Duty Per Unit Process in Various Supercritical Processes case 210,11
case 1 (our experiments)
case 325
unit Name
energy (Gcal/h)
unit name
energy (Gcal/h)
unit name
energy (Gcal/h)
PUMP1 PUMP2 H1 C1 C2 MEOHCOL-C MEOHCOL-R BDFCOL-C BDFCOL-R
66.6 109.0 0.04 -0.15 -0.09 -0.37 0.43 -0.17 0.28
PUMP1 PUMP2 H1 C1 C2 MEOHCOL-C MEOHCOL-R BDFCOL-C BDFCOL-R
86.0 (kW) 134.0 (kW) 0.04 -0.20 -0.09 -0.39 0.45 -0.18 0.29
PUMP1 PUMP2 H1 C1 C2 MEOHCOL-C MEOHCOL-R BDFCOL-C BDFCOL-R
65.7 (kW) 107.6 (kW) 0.04 -0.15 -0.09 -0.36 0.43 -0.15 0.26
K1, K2, and K3 are constants to the equipment type and A is the parameter for the capacity or the size of the equipment. The bare module cost factor, FBM, the function of operating pressure and the construction materials is calculated by eq 3. FBM ) B1 + B2FMFP
(3)
B1 and B2 are constants depending on the equipment type, and FM is the material factor decided by the equipment type. Carbon steel was chosen as the main construction material, since strong acid material was not used. Stainless steel was
used for the supercritical reactor, also considering high pressure and temperature. FP is the pressure factor given by the following eq 4. log10 FP ) C1 + C2 log10 P + C3(log10 P)2
(4)
C1, C2, and C3 are constants depending on equipment type and P is pressure. The actual values for Ki, Bi, and Ci were borrowed from the literature.27 The total manufacturing cost was estimated from the mass balance, heat duty, the price of chemicals, and the utility costs. Table 5 shows amount of chemical costs and utility costs. Water and superheated high-pressure steam were used as the cooling and heating media. The payout time,
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Table 8. Total Capital Cost for Various Processes ($10 ) alkalicatalyzed case 1 (our process21,22 experiments) case 210,11 case 325
($106) reactor neutralization methanol distillation column washing distillation column FAME refining column heat exchangers pumps others total bare module cost, CBM contingency fee, 0.18CBM total module cost, CTM ) CBM + CCF auxiliary facility cost, CAC ) 0.27CBM fixed capital cost, CFC ) CTM + CAC working capital cost, CWC ) 0.15CFC total capital cost, CTC ) CFC + CWC
0.29 0.02 0.14
0.51
0.29
0.48
0.17
0.17
0.16
0.16
0.21
0.21
0.21
0.00 0.05 0.05 0.81
0.14 0.17 0.10 1.30
0.21 0.21 0.11 1.20
0.13 0.17 0.11 1.26
0.14
0.23
0.22
0.23
0.95
1.53
1.42
1.49
0.22
0.35
0.32
0.34
1.17
1.88
1.74
1.83
0.17
0.28
0.26
0.27
1.34
2.16
2.01
2.10
0.10
Figure 8. Subitems and their proportions in the total production cost for the supercritical process, case 3.
Table 9. Total Manufacturing Cost for Various Processes ($106/y)
6
($10 /y) oil feedstock methanol catalysts and solvents operating labor supervisory and clerical labor steam electricity cooling water waste disposal maintenance and repair operating supplies laboratory charges patents and royalties overhead local taxes insurance depreciation administrative costs distribution and selling cost research and development total production cost glycerol credit (-) total manufacturing cost
alkalicatalyzed process21,22
case 1 (our experiments)
direct manufacturing cost 4.20 4.18 0.17 0.17 0.32 0.00
case 2
10,11
case 3
4.18 0.17 0.00
4.12 0.17 0.00
0.62 0.09
0.62 0.09
0.58 0.09
0.62 0.09
0.09 0.02 0.01 0.01 0.07
utility costs 0.32 0.09 0.00 0.07 0.11
0.34 0.11 0.00 0.07 0.10
0.31 0.09 0.00 0.05 0.11
0.01 0.09 0.20
0.02 0.09 0.20
0.02 0.09 0.20
0.02 0.09 0.20
0.49 0.03 0.01 0.17
0.49 0.03 0.01 0.18
general expense 0.11 0.12
0.12
0.12
0.68
0.68
0.68
0.67
0.34
0.34
0.34
0.33
7.59
7.84
7.85
7.72
0.73
1.02
1.02
1.02
6.86
6.81
6.82
6.70
indirect manufacturing cost 0.44 0.50 0.02 0.03 0.01 0.01 0.12 0.19
25
which is commonly used and defined as shown in eq 526 below, was used as an economic index to compare the economic
Figure 9. Sensitivity analysis for total manufacturing cost to oil, glycerol, and steam cost in the supercritical process, case 3. The cost of each material varied 25% at each step. Table 10. Payout Time for Various Processes, When the Payout Time for the Alkali-Catalyzed Process Was Set at 4 y
fixed capital cost ($106) selling price ($106) profit after tax ($106) payout time (y)
alkali-catalyzed process21,22
case 1 (our experiments)
case 210,11
case 325
1.17
1.88
1.74
1.83
7.03
7.03
7.03
7.03
0.29
0.42
0.40
0.53
4.00
4.63
4.56
3.55
benefits of the processes. In this study, for the purpose of comparison, the payout time of the alkali process was fixed at 4 y because the selling price and after-tax profit of BDF are different depending on the country. payout time )
fixed capital cost profit after taxed + depreciation
(5)
5. Results and Discussion Tables 6 and 7 show the stream mass balance and the heat duty at each supercritical condition obtained from the simulation. As in Table 6, all the supercritical processes satisfied the standard specification for BDF; the composition of the product stream BDF were above 96.5% for FAMEs, below 0.2% for methanol, below 0.8% for monoglyceride, and below 0.2% for free fatty acid. The purity of glycerol as a byproduct was more than 97% in all supercritical processes. The total capital costs of all three supercritical processes were higher than that of alkali-catalyzed process, as shown in Table 8; the costs were $2.01-2.16 × 106 for supercritical processes, and this is 1.5-1.6 times higher compared to $1.34 × 106 of the alkali-catalyzed process. Even though the neutralizing units and washing column were not needed, the
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Figure 10. Sensitivity analysis for payout times based on BDF price, when oil cost is (a) increased by 10% or (b) decreased by 10%.
supercritical process required extra capital to build a reactor, heat exchangers, and pumps to achieve high reaction pressure and temperature. In case 2, the cost of the reactor was similar to that in the alkali-catalyzed case due to short reaction time. However, the total capital cost was still higher compared to the alkali-catalyzed process since the highest reaction temperature and pressure increased the costs of heat exchangers, pumps, and others. All the supercritical processes had lower total manufacturing costs ($6.70-6.82 × 106/y) than the alkali-catalyst process ($6.86 × 106/y), as shown in Table 9. There are two reasons for the lower manufacturing cost of the supercritical process; the first one is the glycerol credit. Glycerol credit in the supercritical processes was $1.02 × 106/y, higher than $0.73 × 106/y of the alkali-catalyzed process, because the supercritical process is capable of producing high-purity glycerol at the lower cost. The water impurity from washing process in the alkali-catalyzed process decreases the purity of glycerol and gives 85% glycerol and 15% water.22 But, water is not involved in the transesterification supercritical process, and high purity glycerol is easily obtained. From the simulations, all the purities of the glycerol product from the supercritical processes were estimated to be greater than 97%. The second reason for low manufacturing cost of supercritical process is the lower utility cost, since it does not require any catalysts and solvents that are needed in alkali-catalyzed process. The total utility cost for supercritical processes were about $0.45-0.52 × 106/y, more than three times higher than that of the alkali-catalyzed process, $0.13
× 106/y. However, if the costs of catalyst and solvents are added to the utility cost, the sum becomes $0.45 × 106/y, and it is similar to the total utility cost of supercritical process. The resulting payout times of supercritical processes were 4.63 y for case 1, 4.56 y for case 2, and 3.55 y for case 3, respectively, while it was set at 4.0 y for the alkali-catalyzed process as shown in Table 10. Although the total manufacturing costs for case 1 and 2 were lower, the higher total capital cost made the payout time longer than that in the alkalicatalyzed process. However, in case 3, the lowest total manufacturing cost compensated for the higher total capital cost and made the payout time shorter than that in the alkalicatalyzed process. This is because the highest yield of case 3 (96% compared to 95% in other cases) left the lowest raw material cost of oil and waste disposal cost. As shown in Figure 8, the raw material cost of oil takes the biggest proportion in the total manufacturing cost of BDF: 53.4%. Meanwhile, the utility cost takes only 5.9%. Figure 9 shows the results of sensitivity analysis. The total manufacturing cost ($/BDF ton) is more sensitive to the oil cost than glycerol or steam cost, where the total manufacturing cost was changed by $6.4/percent for oil cost variation, $1.6/percent for glycerol cost variation, and $0.5/percent for steam cost. Another sensitivity analysis considering the uncertainty of oil (raw material) cost and BDF (product) price is shown in Figure 10. Figure 10a shows the payout time depending on the BDF product price when the raw material cost of oil is increased by 10%. If the BDF price is fixed, all processes
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have no profit due to the increased manufacturing cost. When BDF price increases less than 6%, the alkali-catalyzed process has the longest payout time due to small profit margin; since it has the smallest profit margin and capital cost, its payout time is more sensitive to the profit margin in the small margin range. On the other hand, supercritical process has larger profit margin than alkali-catalyzed process due to lower oil cost and higher glycerol contribution. As product price increases, however, the payout time of the alkali-catalyzed process becomes shorter than that of supercritical process because the profit margin is also increased and the effect of profit margin gets attenuated. Consequently, the payout time of alkali-catalyzed process becomes shorter than that of supercritical process when the BDF price is increased by more than 8.5%. For the same reason, in Figure 10b, the payout time of alkali-catalyzed process is increased faster than that of supercritical process as the product price decreased, when the raw material cost of oil is decreased by 10%. 6. Conclusions Process design and an economic analysis were performed to assess the profitability of the supercritical process for BDF fuel production. It was found that the total capital cost for supercritical processes for BDF was 1.5-1.6 times higher than that of the conventional alkali-catalyzed process. The total manufacturing cost of the supercritical processes including indirect cost and general expense, however, was lower than that of the alkali-catalyzed process due to the higher glycerol credit and zero cost of both catalysts and solvents. The payout time of case 1 (supercritical, our experiments) and case 2 (supercritical10,11) were longer than that of the alkali-catalyzed process because the lower total manufacturing cost could not compensate for the higher total capital cost. However, case 3 (supercritical25) had a shorter payout time owing to the lowest total manufacturing cost. The higher yield of case 3 made the cost of the raw material and the waste disposal lower and the total manufacturing cost lowest by using a lesser amount of oil for raw material. Consequently, the supercritical process can be more profitable than the alkali-catalyzed process, even when using virgin oil as a raw material. Acknowledgment The authors gratefully acknowledge the numerous financial supporting institutions for this study: the program of ETI (2007-M-CC23-P-05-1-000) by MKE; the program for EIP by KICOX and MKE; research grant from KOSEF through the Advanced Environmental Biotechnology Research Center at POSTECH; BK21 project by the Ministry of Education; R&D programs (2005-N-FCI2-P-01-3-040-2007, 2006-EID11-P-16), Strategic Technology Development project and Manpower Development program for Energy & Resources under MKE; fund from Ministry of Land, Transport and Maritime Affairs. Y.L. thanks Chul-Jin Lee for sharing sincere discussion, Nahn Ju Kim for kindly reviewing and revising the manuscript grammatically, and Yun-ki Yeo for providing initial background knowledge. Nomenclature BDF ) biodiesel fuel FAME ) fatty acid methyl ester FFA ) free fatty acid NRTL ) electrolyte nonrandom two liquid model
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UNIFAC ) universal functional activity coefficient model CBM ) bare module equipment cost CP0 ) purchase cost for base condition K1, K2, K3 ) purchase cost constants A ) parameter of the capacity or size B1, B2 ) material factor constants FM ) material factor FP ) pressure factor C1, C2, C3 ) pressure factor constants P ) pressure TG ) triglyceride DG ) diglyceride MG ) monoglyceride
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ReceiVed for reView April 3, 2008 ReVised manuscript receiVed March 31, 2009 Accepted April 7, 2009 IE8005287
