jo ur nal homep age: www.elsev ier .com/ locate / indcrop
rocess modeling of the Quick-germ/Quick-fiber process: Energy, water,nd economics
ao Lina,1, Luis F. Rodríguezb,∗, Steven R. Eckhoff c,2
University of Illinois at Urbana-Champaign, 374 Agricultural Engineering Sciences Building, MC-644, 1304 W. Pennsylvania Avenue, Urbana, IL 61801, United StatesUniversity of Illinois at Urbana-Champaign, 376C Agricultural Engineering Sciences Building, MC-644, 1304 W. Pennsylvania Avenue, Urbana, IL 61801, United StatesUniversity of Illinois at Urbana-Champaign, 360C Agricultural Engineering Sciences Building, MC-644, 1304 W. Pennsylvania Avenue, Urbana, IL 61801, United States
r t i c l e i n f o
rticle history:eceived 21 December 2010eceived in revised form 1 March 2011ccepted 3 March 2011vailable online 6 May 2011
a b s t r a c t
A process simulation model was developed on the SuperPro Designer® platform for a Quick-germ/Quick-fiber (QQ) modified dry grind ethanol fractionation facility. This paper compares energy and waterdemands, product quality, and economic performance between the QQ and the dry grind ethanol pro-cesses. Results showed that the QQ process reduces energy demand by 31.6% and water demand by17.9%, produces more value-added coproducts, and improves the economic viability. The QQ process hasa lower ethanol yield (0.405 vs. 0.414 L of ethanol per kg of corn) because of starch loss at the front-end
Currently, corn is the primary feedstock source providingthanol in the US; however, it has been widely debated whetherthanol produced from corn is sustainable in the long term (Farrellt al., 2006; Pimentel et al., 2007). Environmentally, the majoroncern is that producing ethanol from corn demands intensiveater and energy consumption. Economically, recent fluctuations
n petroleum, ethanol, and corn prices have driven several largeroducers of ethanol into bankruptcy or acquisition.3 The ethanol
ndustry is vulnerable to periods of economic weakness becausets product value varies with oil prices but its raw material (corn)ost varies with food prices. When ethanol prices are strong, dryrind processors focus on how to improve ethanol yield, because
oproduct values are not as significant (Rodríguez et al., 2010).owever, when corn prices are high and ethanol prices are low,
he dry grind processors lose money rapidly (Tiffany and Eidman,
2003; Rodríguez et al., 2010). Wet milling is a more stable methodfor ethanol production because its coproduct values usually fol-low corn price trends. When corn prices are high, coproduct valueincreases to offset the lower ethanol prices. To stabilize ethanolproduction, dry grind ethanol processors need to develop theircoproducts in order to get through the times when ethanol pricesare low and corn prices are high.
In response to this need, several modified dry grind pro-cesses have been developed to improve the profitability of ethanolproduction; significant improvements have been observed onthe processing efficiency and the nutritional characteristics ofcoproducts at the laboratory scale (Singh et al., 2005). The Quick-germ/Quick-fiber (QQ) process (Singh and Eckhoff, 1996; Singhet al., 1999) is one of these modified dry grind processes. It adaptsa part of the wet milling process (the germ and fiber recoverysystem) for the dry grind process. This process has three keyadvantages: recovered fiber and germ can be further processedto generate value-added coproducts such as germ oil, corn fiberoil, and corn fiber gum; removal of germ and fiber can increasethe protein content of distiller’s dried grains with solubles (DDGS),making this coproduct suitable as a feed for non-ruminant ani-mals such as swine and poultry; separating the nonfermentable
fractions before fermentation will improve the process efficiencyby 14% (Singh et al., 1999, 2005). Recently, Li et al. (2010) andRodríguez et al. (2010) developed a detailed engineering economicspreadsheet model that showed that the QQ process improves
T. Lin et al. / Industrial Crops and Products 34 (2011) 986– 993 987
Saccharification
Liquefaction
Soaking
Fermentation
Centrifugation
DehydrationDistillation
CO2 Scrubber
Evaporation
DDGS
CO2
Ethanol
Fresh Water
Germ & Fiber Separator
Germ and Fiber
Clean Corn
Grinding
Jet Cook
Cooler
Separator
DryerVent
Whole Stillage
Thin StillageWet Cake
Dryer
Vent
Liquid
Slurry
Gas
w she
ts
nwpwPcUtcg
2
2
U(edt
Fig. 1. A simplified flo
he economic viability of the dry grind process at the commercialcale.
Although these previous studies showed the QQ process is eco-omically viable, there is no analysis that details the energy andater consumption of the QQ process and compares the processerformance to the dry grind process. The objective of this studyas to develop a simulation model of the QQ process on the Super-
ro Designer® platform to predict operating performance at theommercial scale using a continuous process and compare it to theSDA’s dry grind model (Kwiatkowski et al., 2006). This study iden-
ifies and compares the energy consumption, water usage, productompositions, and economic performance of the QQ and the dryrind processes.
. Methods
.1. Process model description
The QQ process model developed in this study is based on theSDA’s dry grind (Kwiatkowski et al., 2006) and wet milling models
Ramirez et al., 2008); the previous dry grind and wet milling mod-ls are developed on the SuperPro Designer platform as is the modeleveloped here. This work is augmented by the previous work ofhe investigators (Li et al., 2010; Rodríguez et al., 2010). The dry
et of the QQ process.
grind model developed by USDA is designed to process 1.12 mil-lion kg of corn per day (43,800 bu/day) (Kwiatkowski et al., 2006).Because of the separation of corn germ and fiber at the front end,a higher rate of corn input can be processed with the same size ofequipment used in the dry grind process (Singh et al., 2005). Byadding a germ and fiber separation system to the dry grind pro-cess, a QQ process model is developed to process 1.34 million kgof corn per day (52,500 bu/day), without increasing the size of theequipment used in the dry grind process designed by Kwiatkowskiet al. (2006). Both plants operate 24 h per day and 350 days peryear, with time set aside for maintenance and repairs.
The QQ process consists of six major sub-systems: grain clean-ing, germ and fiber recovery, liquefaction and saccharification,fermentation, distillation, and DDGS recovery. A simplified flowsheet is provided in Fig. 1. Detailed information regarding processrequirements are available in Kwiatkowski et al. (2006); only sig-nificant changes specific to the QQ process model are detailed here:the consideration of corn composition as impacted by the germ andfiber recovery sub-system, and the fermentation sub-system.
2.1.1. Corn compositionAssuming 14.5% moisture content, 1 bushel, or 25.5 kg, of corn
will have 21.8 kg (48.0 lb) of dry materials (Watson, 1987). Cornkernels can be divided into three major parts: pericarp and tip cap;
988 T. Lin et al. / Industrial Crops and Products 34 (2011) 986– 993
Hydrocyclone 1
Hydrocyclone 2
1st Grinding
1st Screen
2nd Screen 3rd Screen
1st Grind Tank
Corn Slurry
Dewatering Screw
Mixer
Mixer
Blending Tank
Washing Water
Send to the fluidized bed dryer
2nd Grind
Soaking Tank
Corn
Process Water
Germ and Fiber Stream
Corn slurry after separation
erm a
epcbplrp
2
igaTs
bhfgotsooataf
sfi
Fig. 2. A detailed view of the g
ndosperm; and germ. Starch, oil, neutral detergent fiber (NDF),rotein, sugars, and ash are the major constituents making up theorn kernel and are each distributed throughout the three parts. Toetter describe the coproducts recovered via the QQ process, therotein and NDF are further divided based on solubility and their
ocation within each part of the corn kernel. Detailed informationegarding the corn composition is provided in Table S1 in the Sup-lementary Material on the Web.
.1.2. Germ and fiber recovery sub-systemThe germ and fiber recovery sub-system, shown in Fig. 2,
nvolves the soaking of the corn kernel for 8 h, a two-stage grind,erm and fiber recovery using hydrocyclones, three-stages of germnd fiber washing, and germ and fiber separation and dewatering.he moisture content of corn increases from 14.5 to 57.4% duringoaking.
The separation system is based on the density differenceetween the constituent parts of corn. It consists of two stages ofydrocyclones and three stages of wash screens. The diluted slurry
rom the mill is pumped to hydrocyclones, where the lighter parts,erm and fiber, are floated off the top. The washing system consistsf three gravity screens used to wash the loose starch and pro-ein from the germ and fiber. Water is recycled from the last twotages of washing. The wash water finally leaves in the underflowf the first screen with the free starch and protein. The detailedperational information of the equipment, such as top flow rationd output dry mass, is provided in Table S2 in the Supplemen-ary Material on the Web. Based on the ratio set in this model,pproximately 95% of pericarp fiber and 90% of germ are separated
rom the corn slurry.
After washing, the germ and fiber are then dewatered in thecrew press to an average of 50% moisture content. Germ andber are further dried and separated via a fluidized bed dryer (not
Send to fermentation
nd fiber recovery sub-system.
pictured) to 3% and 10% moisture content, respectively. The out-let stream of germ and fiber are produced at a rate of 4228 and3871 kg/h, respectively.
2.1.3. Fermentation sub-systemFermentation is a conversion step where glucose is converted
into ethanol and carbon dioxide with yeast. Urea is added at therate of 0.3% (wet basis) of corn input to provide a nitrogen source forthe yeast propagation. The fermentation simulated in this processis continuous, and the residence time is set at 60 h. In this model,91.9% of total glucose is assumed to be converted to ethanol andcarbon dioxide, on a mass basis:
C6H12O6 → 0.511 C2H5OH + 0.489 CO2. (1)
In addition to the glucose consumed in Eq. (1), 3.28% of the initialglucose is consumed for the yeast propagation, and carbon dioxideis produced via yeast metabolism:
0.88C6H12O6 + 0.12(NH2)2CO
→ 0.742YeastDryMatter + 0.258CO2. (2)
The remaining 4.82% of the glucose is not involved in the conver-sion and remains in the DDGS. The extent of conversation is basedon industrial data and research data.
2.2. Cost model description
A cost model was developed on the SuperPro Designer® plat-form to evaluate the economic performance of the QQ process.Capital investment costs, operating costs, and product values arevital for the economic analysis.
T. Lin et al. / Industrial Crops and Products 34 (2011) 986– 993 989
Table 1Total capital investment costs for the QQ process.
Factor of purchased equipment costa Cost (Million $) Cost ($/L) Cost ($/gal)
Purchased equipment 100% 24.13b 0.12 0.47Purchased equipment installation 40% 9.65 0.05 0.19Piping 30% 7.24 0.04 0.14Instrumentation and control 10% 2.41 0.01 0.05Electrical equipment and material 15% 3.62 0.02 0.07Building 40% 9.65 0.05 0.19Yard improvement 15% 3.62 0.02 0.07Total direct costs 250% 60.33 0.31 1.18
Fixed capital costs 320% 77.22 0.40 1.51Working capital costs 48% 11.24 0.06 0.22Startup capital costs 32% 7.72 0.04 0.15
d here
2
ceicSa2f
2
urcmca
laotadfipvt
TU
h
Total capital investment costs 400%
a Douglas (1988).b The purchased equipment cost is estimated by the QQ process model develope
.2.1. Capital investment costsCapital investment costs are estimated based on the purchased
osts of each piece of operating equipment. Based on the coststimation factors developed by Douglas (1988), the total capitalnvestment cost would be four times the total equipment pur-hased costs (Table 1). The equipment costs are based on theuperPro Designer® equipment cost estimating parameters as wells USDA’s dry grind and wet milling models (Kwiatkowski et al.,006; Ramirez et al., 2008), and the equipment costs are adjustedor capacity using standard engineering scaling factors.
.2.2. Operating costsOperating costs of an ethanol plant consist of raw materials,
tility, labor, and facility dependent costs. Based on the processingate, the amount of raw materials and utilities required by the plantan be calculated by the model simulation. The unit costs of the rawaterials and utilities are the input values, shown in Table 2. These
osts are based on the market prices observed in April 2009 as wells the literature (Kwiatkowski et al., 2006; Li et al., 2010).
Facility dependent costs include maintenance costs, insurance,ocal taxes, and other factory expenses. Maintenance costs aressumed to be 3% of direct fixed capital costs, while insurance andther factory expenses are at 0.85% and 0.7% of direct fixed capi-al costs, respectively (Kwiatkowski et al., 2006). Depreciation andmortized loan payments are generally associated with the facilityependent costs. The QQ plant considered here is assumed to be
nanced without any external loans, and thus no amortized loanayment is needed. The plant has a 15-year lifetime with zero sal-age value at the end. The annual depreciation cost is calculated viahe straight-line method.
able 2nit operating cost and product value of raw materials, utilities, and products in the QQ p
Unit Cost
Raw materials Utilities
Corn $4.2/Bua Natural gas
Alpha amylase $2.25/kgb Steam
Glucoamylase $2.25/kgb Electricity
Yeast $1.86/kgb Cooling Water
Urea $0.31/kgc
Succinic acid $0.11/kgb
Process water $0.35/kLb
Denaturant $0.475/kgc
a Market prices as observed in April 2009: corn price: http://www.ams.usttp://www.ams.usda.gov/mnreports/sj gr225.txt (accessed on May 14, 2009); ethanol prb Kwiatkowski et al. (2006).c Li et al. (2010).d Purchased at 1.25 times the natural gas cost.
96.18 0.50 1.88
.
Eight operators and one supervisor are assumed to work fulltime in this QQ ethanol facility, and five operators are assumed towork in the dry grind plant (Kwiatkowski et al., 2006). The unitlabor costs of an operator and a supervisor are at an all-inclusiverate of $69/h and $105/h, respectively.
2.2.3. Products valuesIn the QQ process, ethanol, DDGS, germ, and fiber are the four
products marketed, whereas CO2, a potentially marketable prod-uct, is assumed to be purged to atmosphere. The prices of ethanol,DDGS, and corn oil in this analysis are based on the market pricesas observed in April 2009 and are shown in Table 2. The value ofthe fiber fraction is set at $0.08 per kg based on its fraction withinthe DDGS and DDGS prices. The value of the germ fraction is setat $0.37 per kg, based on the corn oil and protein values and oilextraction costs (A detailed germ value calculation is provided inthe Supplemental Materials).
2.3. Energy demand analysis
The stream data related to the heating demand includes the spe-cific heat capacity of raw materials, temperature, and flowrate foreach process stream, as well as the residence time of each unit oper-ation. With the aid of simulation software (SuperPro Designer®),the model calculates the specific heat of each stream based onits composition. Corn is the single major dry matter input in the
process. To facilitate the comparison of two dry grind models con-sistently, the specific heat capacity of each corn component in theQQ model is based on the assumptions used in the USDA’s dry grindmodel (Kwiatkowski et al., 2006). Under these assumptions, the QQ
rocess model quantifies the heating duty of each unit operationased on its operational requirements. The operational parame-ers, such as temperature, moisture content and residence time, arenput values and can be easily modified to suit user preferences. Theemperature and moisture content of several major streams in theQ process are provided in Table S3 in the Supplementary Materialn the Web. Steam and cooling water are used to adjust workingemperature of each unit operation, while natural gas is exclusivelysed for the dryer unit operation.
.4. Water demand analysis
The water demand of corn-to-ethanol production can be com-osed of two parts: process water and non-process water demand.he process water is the water directly mixed with ground corn toorm the slurry. For the process water demand analysis, based onhe feedstock input rate and the moisture content requirement ofach processing stream, the simulation model would quantify therocess water input rate.
Cooling water and steam water are two types of non-processater in ethanol production. As steam is purchased as a utility,ot generated at the site in this model, steam water is not consid-red in this analysis. Based on the previous study, steam water onlyccounts for less than 3 percent of total water demand (Wu et al.,009). Therefore, the exclusion of steam water demand would notave a major impact on the total water demand analysis.
The cooling water considered here is a recirculating non-ontact system, where the cooling water losses mainly occur inhe cooling tower via evaporation, blowdown, and drift. In a well-perated recirculating cooling system, blowdown and drift wateross account for only a small portion of cooling water usage (Asanot al., 2007). To simplify the analysis, the cooling water demand isased on the cooling water evaporation rate. Based on the coolingequirement in each unit operation, the simulation model quanti-es the circulation flowrate of the cooling water. In the QQ processodel, the supply and return temperature of cooling water are
esigned at 15 and 26 ◦C, respectively. Based on a simplified massnd energy equation (Asano et al., 2007),
300Qe = 4.2Qc�T (3)
he evaporation rate would be 2% of the circulation rate.4 Qe is thevaporation rate (kg/h); Qc is the circulation rate (kg/h); �T is theemperature change (◦C). Without considering the blowdown andrift loss in this analysis, the makeup cooling water usage consistsf 2% of the circulation flowrate.
.5. Economic analysis
A baseline scenario is selected based on the input informationescribed in the cost model description section. No external loansr dividend is assumed for the baseline analysis. Therefore, thennual cash flow is determined by the sum of the income after tax asell as depreciation. The analysis does not consider the impacts of
nflation during the lifetime of the facility, thus it would be con-idered in real terms. The payback period for the QQ facility isetermined as a ratio of total capital investment cost to annualash flow.
Two additional economic scenarios are considered as well. First,n ownership group is presumed to provide 100% of the capital
equirement. The investors are presumed to collect dividends ratedt 8% of the original equity invested. Dividends are subtracted fromhe cash flow calculation described above. Second, building from
4 Note: 2300 kJ is required to evaporate 1 kg of water, while 4.2 kJ is required toool 1 kg of water by 1 ◦C.
Fig. 3. A comparison of the energy demand in the QQ and dry grind processesdetermined here, as compared to previous industrial surveys: USDA 2002 survey:Shapouri and Gallagher (2005); RFA 2007 survey: Wu (2008).
the investor scenario, those investors are presumed to provide40% of the initial capital, thus requiring the remaining funds to beacquired via loan. The interest rate of the load is assumed to be 10%,with payments amortized over the period of 15 years. Amortizedloan payments are presumed to be operating costs for the facility,thus affecting net profit. The payback period is determined as a ratioof the equity by the investors to annual cash flow.
3. Results and discussion
3.1. Energy demand
Based on the QQ simulation model, the QQ process utilizes8.7 MJ of energy to produce each liter of ethanol (31,342 BTU/gal)(Fig. 3). Steam is the largest required energy resource in the process,accounting for more than half of the total energy demand. A signif-icant amount of steam is used to provide heat in the distillationand liquefaction unit operations. Natural gas is the second largestenergy source used to dry the coproducts including germ, fiber, andDDGS, which accounts for approximately 3.6 MJ/L (12,880 BTU/gal).Approximately 0.6 MJ/L (2100 BTU/gal) of electricity are requiredto run the pumps, motors, and certain unit operations such as themolecular sieve and dewatering press.
Comparing to the dry grind process, the results demonstratedthat the QQ ethanol process achieves a 31.6% reduction in totalenergy use (Fig. 3). While the QQ process runs more unit operationsand has a higher electricity demand than the dry grind process,the significant steam savings in the QQ process offset its higherelectricity demand.
The energy demand results derived here are comparable to twopreviously published industrial surveys (Shapouri and Gallagher,2005; Wu, 2008). The results showed that the energy demandof the dry grind process derived from the simulation is higherthan both in the survey results. This can be explained by the factthat many plants do not dry the stillage before selling DDGS, dueto the huge energy requirement. The lower energy demand in2007 survey compared to 2002 survey is partially because it wasreported that more than one third of the DDGS are sold as wetfeeds (Wu, 2008). If there were no DDGS drying in the simula-tion model, the energy demand of the dry grind process will belower than that from Wu (2008), as effectively there would be nonatural gas requirement and only steam and electricity demands
would remain. The comparison validates that the simulation modelis capable of representing industrial performance. Consideringthe lower energy demands by the QQ process, it is anticipatedthat the energy demand for ethanol production can be further
T. Lin et al. / Industrial Crops and Products 34 (2011) 986– 993 991
Table 3Operating data for the distillation sub-system in the QQ and conventional dry grindprocesses.
educed if more plants adopt and continue to develop this novelechnology.
Due to the germ and fiber recovery, the ethanol concentra-ion of the inlet stream of the beer column is improved to 15%m/m) from 10.9% (m/m) in the dry grind process (Table 3). Thencreased ethanol concentration is the major contributor for thenergy demand reduction achieved by the QQ process. A detailednergy demand comparison between the two processes is providedn Fig. S1 in the Supplementary Material on the Web.
.2. Water demand
The total water demand of the QQ process is reduced to 3.49 L forach liter ethanol production (3.49 L/L), as compared to 4.25 L/L inhe dry grind process. The results derived from simulation modelsre comparable with industrial surveys, as shown in Fig. 4. Becausehe water used for the germ and fiber washing can be recycled andeused, the QQ process does not require higher process water inputate—0.43 kg of water per kg of corn processed—despite the facthat it adds a germ and fiber recovery system at the front end.owever, because of its lower ethanol yield, the process wateremand of the QQ process is effectively a little higher than thatf the dry grind process: 1.06 as compared to 1.04 L/L, respectively.he detailed input-output analysis of process water is shown inig. 5. There is only one major fresh process water input, and it ised into the CO2 scrubber. After recovering the emitted ethanol inhe CO2 scrubber, this process water is routed back to the soak-ng tank to provide the water for soaking and the following unitperations. In addition, corn is brought into the system with 14.5%
oisture content that provides 0.36 L/L of water to the system.The cooling water demand of QQ process has been reduced to
.43 L/L, compared with 3.21 L/L by the dry grind process (Fig. 6).
ig. 4. A comparison of consumptive water usage in the QQ and dry grind pro-esses determined here and contrasted with previous surveys: (†) Keeney and Muller2006). (The results were derived from a survey of average water use by ethanollants located in Minnesota); (‡) Shapouri and Gallagher (2005). (The results wereased on USDA 2002 survey); (�) Wu (2008). (The results were based on RFA 2007urvey, which indicated that the water consumption ranges from 2.65 to 4.9 L/L,ith an average of 3.45 L/L).
Germ(0.02 liter/liter)
Fiber(0.02 liter/liter)
DDGS(0.04 liter/liter)
Fig. 5. The process water input–output analysis in the QQ process.
The savings of cooling water used for evaporator vapor recapture aswell as distillation are the major contributors for the cooling waterreduction in the QQ process. Due to the germ and fiber recoveryat the front end, the amount of thin stillage loading to the evapo-rator in the QQ process is considerable lower than that in the drygrind process. Because the cooling water demand is proportionalto the vapor loss rate, the lower loading rate of evaporator in theQQ process results in a lower vapor loss, and it thus leads to a lowercooling water demand to recapture the vapor loss. Approximately0.42 L/L savings are achieved in the QQ process.
The higher ethanol concentration facilitates the separation inthe distillation system. Approximately 0.22 L/L of cooling watersavings are achieved in the beer column of the QQ process. How-ever, due to its lower loading rate, the savings in the rectifier columnare lower than that in the beer column. Because ethanol concen-trations are similar, the cooling water demands are comparable inthe stripping column.
To facilitate the yeast propagation, a cooler is set to cool themash down to 30 ◦C before feeding into the fermentation tank. Theseparation of germ and fiber at the front end reduces the materialsprocessed to the cooler before fermentation, therefore providing0.07 L/L savings of cooling water in the QQ process.
3.3. Product evaluation
Regarding dry matter input, 100 kg of corn dry matter is fed intothe process with 0.36 kg of urea. The total output of the QQ pro-
cess is produced at the rate of 107.98 kg per 100 kg corn dry matterinput. The difference between the input and output is due to thesaccharification reaction where approximately 7.49 kg of processwater are consumed for every 100 kg of dry corn.
Fig. 6. A cooling water demand comparison between the QQ and the conventionaldry grind processes.
992 T. Lin et al. / Industrial Crops and P
Table 4A coproduct quality comparison between the QQ and the conventional dry grindprocesses.
Ethanol and CO2 are the major products, each accounting forpproximately one third of the total output. The remaining onehird of the dry matter is incorporated in the solid coproducts:erm, fiber, and DDGS. Among these products, ethanol yield rate ishe most important economic factor for an ethanol facility. Ethanols produced at the rate of 0.405 L/kg of corn input (2.72 gal/bu) inhe QQ process, which is lower than 0.414 L/kg (2.78 gal/bu) by thery grind process. This is due to starch losses in the germ and fiberecovery process.
After separation, the germ fraction contains 43% oil (d.b.) andan be further used for oil extraction; the fiber fraction is com-osed of 70% NDF (d.b.). In addition, a small amount of starch andugars is recovered in both the germ and fiber streams. The starchccounts for 8% of germ fraction and 10% of fiber fraction, respec-ively. After germ and fiber recovery, all other nonfermantable
aterials along with some unconverted starch and sugar end inDGS. Detailed compositions of germ, fiber, and DDGS streams are
hown in Table 4.
able 5n economic comparison between a conventional dry grind plant and a QQ plant.
Conventional dry-grind plant
$1000/yr ¢/L
Fixed capital costs 60,283 36.52
Capital investment costs 76,443 46.31
Raw materials:Corn 64,226 38.91
Enzymes 1500 0.91
Yeasts 190 0.12
Other chemicals 474 0.29
Process water 63 0.04
Denaturant 1237 0.75
Subtotal 67,690 41.01
Utilities:Electricity 1989 1.21
Natural gas 2555 1.55
Steam 5521 3.34
Cooling water 181 0.11
Subtotal 10,246 6.21
Labor dependent 2898 1.76
Facility dependent 2743 1.66
Depreciation 4019 2.43
Operating costs 87,596 53.07
Products:Ethanol 74,991 45.43
DDGS 17,632 10.68
Corn germ – –
Corn fiber – –
Revenues 92,623 56.11
Gross profit (A) 5027 3.05
Taxes (40%) (B) 2011 1.22
Depreciation (C) 4019 2.43
Annual cash flow (A − B + C) 7035 4.26
Payback period (years) 10.9
roducts 34 (2011) 986– 993
Table 4 also compares the composition of DDGS produced inthe dry grind and the QQ process. The prefractionation in the QQprocess produces DDGS with higher protein and lower fiber con-tent, thus making it an amenable feed for non-ruminant animals.In addition, the improved nutritional characteristics of DDGS maydemand a premium price, further improving the economics of theethanol facility if an optimistic market rewarding higher quality ofDDGS comes to exist.
3.4. Economic performance
3.4.1. Baseline analysisAn economic performance comparison between the dry grind
plant and the QQ plant is given in Table 5. The comparison showedthat the QQ plant requires a total capital investment of $96.2 mil-lion, 26.5% higher than that of the dry grind plant. The higher capitalinvestment costs for the QQ plant are due to the additional germand fiber recovery system. The annual raw material costs for theQQ plant are 20% higher than that for the dry grind plant, whichcorresponds to an increased processing capacity. Due to the lowerethanol yield rate, the QQ plant increases its unit raw material costby 2.2%.
Despite its increased processing capacity, the QQ plant demandsless annual utility costs than the dry grind plant. Although the QQprocess requires more electricity to power additional equipment, itprovides significant savings in steam demand of distillation due tothe germ and fiber recovery. The QQ plant reduces its utility costsfor each gallon of ethanol production by 21.4%, which corresponds
The QQ plant requires higher annual operating costs due to itsincreased processing capacity. However, the unit operating costsfor these two plants are comparable, both of which are approx-
Annual cash Flow (A − B + C − D) 920 0.56 2.11 3966
Payback period (years) 83.1 24.3
mately 54 ¢/L. This is due to the significant utility savings ofhe QQ plant, which offset higher depreciation and raw materialosts.
The coproducts provide a significant revenue boost for the QQlant as compared to the dry grind plant. Although the revenue ofDGS in the QQ plant is reduced because of the prefractionationrocess, more value-added coproducts, such as germ and fiber, areroduced. These factors taken together with the increased ethanolroduction cause the total revenues of the QQ plant to increase bylmost $23 million.
Assuming no external loans are required for both ethanol plants,he QQ plant has a higher annual cash flow. Despite its higher capitalnvestment cost, the payback period of the QQ plant is reduced to.3 years, compared to 10.9 years for the dry grind plant. Increasedrocessing capacity, more value-added coproducts, and reducedtility costs are three major factors boosting economic performancef the QQ plant.
.4.2. Scenario analysisTable 6 outlines the results from two additional economic
cenarios beyond the baseline case. These results suggest thathe QQ facility will be considerably better in both scenarios.
hen investors seek outside funding, gross profits are reducedue to the additional amortized payments, while cash flow is
ncreased because of the significant reduction of the dividends.he impact of seeking outside funding is particularly attractiveor the QQ facility if the loan interest is 10% and dividend rates 8%, where the payback period is reduced to 9.6 from 24.3ears.
. Conclusion
Comparing the QQ and the dry grind process models, the resulthows that the QQ process reduces energy demand by 31.6% andater demand by 1.76 L/L, significantly as a result of its increased
thanol concentration in the beer. The QQ process produces morealue-added coproducts, but has a lower ethanol yield rate (0.405s compared to 0.414 L/kg). Because of its reduced utility costs andncreased revenue by its value-added coproduct sell, the QQ processas a shorter payback period as compared to the conventional dryrind process.
cknowledgements
The authors would like to thank Dr. Madhu Khanna and Dr. K.C.ing for their help in preparing this work. This work was funded by
the Illinois Council on Food and Agricultural Research (C-FAR) andUniversity of Illinois.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.indcrop.2011.03.003.
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