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1. 20 Table 18 Financial Information for a 40 MGY plant esee 21 Table 19 Annual Loan Amortization Schedule No Sweep on 34 793 247 Loan 21 Table 20 Annual Loan Amortization Schedule Sweep von 39 986 293 Loan 22 Table 21 Calculation of Annualized NPV IRR and Benefit Cost Ratio No Sweep 22 Table 22 Calculation of NPV IRR and Benefit Cost Ratio w Allowance for Sweep 23 ii Model Users Manual Using the DM model is not complex the user changes input values of interest plant size conversion rates etc and examines the effect of these changes on output values annual profits feed stock requirements etc There are nine worksheets in four modules in the excel workbook assumptions process economics and technology assessment All user inputs are entered in the assumptions module of the model which consists of three worksheets denoted with bright yellow tabs process assumptions economic assumptions and physical assumptions The values that are entered on this page are then used in each of the subsequent modules to calculate hourly flow rates equipment size and cost total costs loan terms and annual profits At the top of each page is a title bar which describes the page the color coding of the cells and pertinent information from the other pages Before each of the pages is discussed an explan2. t sod ot dal ee 6 Moisture Solid P rcentages n d EI Se AREE UM tease 7 1 P 8 Grain 8 Densities Indices Identities RNC PIN ola 9 Distillation and Evaporation Table ecce eee eee teen ete eene etn nen 10 Economic PP 11 i tatus TE eh d tc ALLE d aere p d Reds 11 Financial due edebat asume eum tutem tem uten E eS ES 12 Price Functions Fable eet ene a E sagtad svn REX R 13 Process Module Process PIOWS e CR none a RE RR 15 Process Module Equipment Sizing and Cost Estimation eese 17 Economic Module Revenue Cost Estimation ceescccsscceceeeeeceeeeecsneeeenseeeeaes 18 Economic Module The Finance Page eee 20 Economic Module The Page iecit ettet ttai tee io ee ee er deo 22 ECIGI CHO a se ere 24 List of Figures Figure 1 Theoretical Conversion of Corn to Ethanol eee 5 Figure 2 Conversion Rates as a Percentage of Theoretical Yield Figure 6 Figure 3 Theoretical and Actual Product era lesen tiet ie eti 7 Figure 4 Process Flow Diagram Hourly Flows for a 40 MGY at Full 16 List of Tables Table 1 Description of Cell Color Coding
3. eese nnne 1 Table 2 Dry Mill Process Assumptions Plant Operation esee 5 Table 3 Dry Mill Process Assumptions Equipment RTD Temperature Number 7 Table 4 Dry Mill Process Assumptions Solid Liquid 8 Table 5 Physical Property Assumptions Grain Composition eee 9 Table 6 Physical Property Assumptions Densities Indices Identities 10 Table 7 Dry Mill Process Assumptions Distillation 11 Table 8 Economic Assumptions Prices Values eese 12 Table 9 Economic Assumptions Financial eese seen eene entente 13 Table 10 Economic Assumptions Price Functions Ethanol DDGS and Jet Cooker 14 Table 11 Hourly Flow Rates for Fermentation 2 reni trente repete 16 Table 12 Average Energy and Water Usage per gal of EtOH Produced 17 Table 13 Calculation of Solubles and Insoluble Solids 96 sess 17 Table 14 Equipment Size and Cost Estimation for 40 MGY Plant 18 Table 15 Capital Cost Estimation for 40 MGY Plant eene 19 Table 16 Yearly Real Revenue for 40 MGY Plant esee 19 Table 17 Annual Real Operating Costs esses
4. Brewers Yeast Alpha Amalayse Gluco Amalayse SO2 Antibiotic CO2 Blectricity kWh Natural Gas Mbtu Water K gal Gasoline gal Operation C Total Labor Capital Taxes Net Rev Liscence Fees Rev Misc Rev Source USDA Authors Estimates Financial The financial information table is where users enter values for variables pertaining to the yearly finances of the dry mill plant This table is where users enter values for rates interest inflation and loan term repayment years equity percentage This table also permits the user to decide how profits will be used and in what proportion The user enters values for the percentage of profits that will be paid to shareholders managers or pay down equity The sweep payment is calculated as the share of profits that are not used in all other pursuits The sweep payment allows the plant to use a percentage of the profits to pay more than the required loan payment The sweep payment allows the loan to be paid off in less than the agreed upon number of years Table 9 shows the financial table as it appears in the DM model 12 Table 9 Economic Assumptions Financial Economic Assumptions Financial Information Wrkng Req Op Cost Sweep Factor Profits Initial Equity Req TCI Loan Factor TCI Loan Length Plant Operational Plant Life Span Ist year TCI 2nd year TCI Inflationary Discount Interest Real Discount Source Authors Estimates P
5. 369 9 468 664 de 83 656 330 1 12 284 241 8 914 325 85 327 621 13 491 167 4 040 925 82 746 620 15 4 19 036 732 81 066 866 23 769 987 83 498 872 j 24 483 086 86 003 838 25 217 579 88 583 953 25 974 106 91 241 471 26 753 329 93 978 716 27 555 929 96 798 077 28 382 607 99 702 019 29 234 085 102 693 080 30 111 108 105 773 872 2 31 014 441 108 947 088 31 944 874 112 215 501 32 903 221 115 581 966 2 33 890 317 119 049 425 34 907 027 122 620 908 35 954 237 126 299 535 37 032 865 130 088 521 38 143 851 4 93 133 991 177 49 337 504 NetPresentValue 9061 asasi Benefit Cost Ratio Source DM Model 23 References 1 Alexander R J 1994 Corn Dry Milling Processes Products and Applications Pages 351 371 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 2 BBI International 2003 The Ethanol Plant Development Handbook Edition Four 3 Boyer C D and Shannon J C 1994 Carbohydrates of the Kernel Chapter 8 Pages 253 269 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 4 DOE Energy Information Administration http www eia doe gov 5 Chemical Engineering Plant Cost Index Chemical Engineering May 2005 6 Evans M K 1997 The Economic Impact of the Demand for Ethanol Report
6. Dry Bushel of Corn all vaues in Ibs unless stated otherwise com 47 32 34 73 37 78 37 40 17 19 Unfermentables Unconv Starch Uncony Dext Mass Balance hanol gal Ethanol Ibs wes oo om 2m 1797 Source Authors Estimates Table 3 Dry Mill Process Assumptions Equipment RTD Temperature Number Dry Mill Process Assumptions Process Equipment Specification Hammer Mills Slurry Tank Jet Cooker HP Hold Tube Liquification Tank Fermenters Beer Well Rectifier Stripper Mol Sv Clmns Centrifuge Evaporators 1 2 3 Drum Dryer Storage Tanks Source DM Model RFA 15 Moisture Solid Percentages The user must decide on the moisture solids percentages for each stage of the production process The user can input values for the moisture content of the mash WDG WDGS DDGS and the soluble syrup The moisture content of these flows are important in estimating how much water is needed in the production process and in finding the amount of 7 thermal energy necessitated in the recovery of co products The DM model is closed in its water balance This balance requires that some of the moisture solids percentages be derived from the calculations based on other moisture levels and flows The moisture content of the beer whole stillage and thin stillage are calculated using flow rates and the co product moisture percentages Corn mash and DDGS moisture percentages are
7. Grams per Pound Liters per Gallon Ideal Gas Law R BP for EtOH BP for H20 Molecular Wet Starch Dextrins H20 Glucose EtOH CO2 Sources 13 4 5 Distillation and Evaporation Table Even though the distillation and evaporation table contains some process assumptions it was included in the physical properties page because it contains more physical assumptions The design of the distillation and evaporation equipment is more complex than other stages of the production process in which only a tank is needed The complexity of these systems required a separate table for input value entry It should be noted from a quick examination of this input table shown in Table 7 that a direct user input cell only appears for heat exchange and dryer efficiencies The variables of distillation and evaporation that appear in this table are similar across dry mill plants and should not be changed by the user unless there is a specific reason to do so This table includes a look up table function combination that is used to determine distillation tray sizes The user decides on which tray size to use from the look up table and enters a in the corresponding function cell and a 0 in the other function cells This table also has the specific heats for water and ethanol which are important in determining the thermal heating requirements of the dry mill process 10 Table 7 Dry Mill Process Assumptions Distillation Evaporation Dry Mill Proce
8. Indirect Input As a Of per Annum DM TCC 2 521 622 2 521 622 Taxes 4 073 517 Liscence Fees 1 655 184 Maintenance 1 655 184 Misceleneous Expenses 1 008 649 8 392 533 Source Factors Associated with Success of Fuel Ethanol Producers 15 DM Model Economic Module The Finance Page Project financing of a fuel ethanol plant is one of the greatest challenges for a prospective dry miller Not only is the ethanol market volatile but so too are the markets for the inputs used in the ethanol production process grain and boiler fuel 6 This causes venture capitalists to shy away from dry mill projects because they face a great deal of uncertainty on the expected rate of return from investment Compounding this capital scarcity is the difficulty that investors would have in liquidating the dry mill s assets For these reasons farmer co operatives have become major players in ethanol plant building Grain farmers join the co operative and lend not only capital support but also pledge a portion of their grain harvest to the dry mill This reduces the risk to both the farmer and dry mill from volatile grain markets The building of ethanol plants has also been supported by rural local communities because of the expected benefits that accrue to the community such as increased employment Financers require a large equity payment on a dry mill plant generally 4096 of the total capital cost or greater Investors also may require the plant t
9. all values in dry Ibs Milled Hydrolyzes Cleaves Glucose Ferments 0 40 Ethanol Ibs EtOH gal 006 Theoretical yields are not realized in production To take this into account the user enters conversion percentages in the conversion rate diagram Figure 2 Conversion rates are entered for the hydrolysis of starch to dextrins and dextrins to glucose as well as fermentation Conversion rates are entered as a percentage of theoretical Figure 2 Conversion Rates as a Percentage of Theoretical Yield Figure Conversion Rates of Theoretical Hydrolysis Starch to Dextrin Conversion Starch H O Dextrins alpha amylase C5H1206 10 H O Dextrin to Glucose Conversion Dextrins Glucose gluco amylase C6H1206 10 C6H120 Starch gt Glucose 97 0 Glucose to Ethanol Conversion Glucose Ethanol Yeast CoH 120 gt 2 Starch Ethanol 91 2 Source Authors Estimates The conversion rates entered and other process assumptions are used to calculate the yields of products per bushel of grain input These calculations are carried out in the theoretical versus actual yield diagram on the process assumptions page This diagram is Figure 3 To preserve mass balance both actual and theoretical product yields were necessary in calculation and values are in dry weight pounds Ethanol and CO yields were calculated as a function of the corn composition and conversion rates whi
10. to Midwestern Governors Conference Lombard Illinois 7 Haas D Agbara G 2000 Tax Incentives for Petroleum and Ethanol Fuels GAO RCED 00 301R 8 Maisch W F 1994 Fermentation Processes and Products Chapter 19 Pages 553 572 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 9 May J B 1994 Wet Milling Process and Products Chapter 12 Pages 377 395 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 10 McAloon A Taylor F Yee W Ibsen K Wooley R 2000 Determining the Cost of Producing Ethanol from Corn Starch and Lignocellulosic Feedstocks Report to National Renewable Energy Laboratory Golden CO NREL TP 580 28893 11 Musgrove D Dale M C 2004 Feasibility Study for an Integrated Grain Cellulose Ethanol Plant in Arizona Report to USDA Washington DC USDA 02 025 086019322 12 Orthoefer F T 1994 Corn Starch Modification and Uses Chapter 16 Pages 479 495 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 13 Peters M S Timmerhaus K D and West R E 2003 Plant Design and Economics for Chemical Engineers McGraw Hill New York NY 14 Pimentel D 2003 Ethanol Fuels Energy Balance Economics and Environmental Impacts are Negative Natural Resources Researc
11. 18 155 620 4 249 872 2 78 705 695 82 955 567 9 101 783 352 3I 18 827 785 4 249 872 J 81 066 866 85 316 737 104 836 852 19 520 115 4 249 872 E 83 498 872 87 748 743 107 981 958 7 20 233 214 4 249 872 86 003 838 2 90 253 709 111 221 416 20 967 707 4 249 872 88 583 953 5 92 833 825 114 558 059 21 724 234 4 249 872 5 91 241 471 5 7 95 491 343 1 117 994 801 22 503 458 4 249 872 J 93 978 716 98 228 587 1 121 534 645 23 306 057 4 249 872 J 96 798 077 101 047 949 125 180 684 24 132 735 4 249 872 99 702 019 103 951 891 E 128 936 105 24 984 214 4 249 872 102 693 080 J 106 942 952 132 804 188 1 25 861 236 4 249 872 105 773 872 110 023 744 136 788 313 26 764 569 108 947 088 108 947 088 9 140 891 963 31 944 874 112 215 501 4 112 215 501 1 145 118 722 32 903 221 115 581 966 115 581 966 9 1 149 472 283 33 890 317 119 049 425 119 049 425 9 153 956 452 34 907 027 122 620 908 122 620 908 158 575 145 35 954 237 126 299 535 126 299 535 163 332 400 37 032 865 130 088 521 130 088 521 9 168 232 372 38 143 851 133 991 177 133 991 177 79 183 328 681 49 337 504 Net Present Value 101 718 453 101 718 453 Benefit Cost Ratio 1 45 1 47 Source DM Model 22 Table 22 Calculation of NPV IRR and Benefit Cost Ratio w Allowance for Sweep Payment Year Costs Sweep Benefits Sweep 21 502 394 20 87 21 502 394 17 14 764 977 07 14 764 977 10 593 972 297147 80 522 962 9 9 910 228 10 229 956 7 1 116 82 256 816 D 10 889
12. 4 793 518 3 4 7 553 761 9 3 040 210 2 10 593 972 9 9 910 228 6 534 423 7 849 783 27 239 756 2 7 849 783 1 2 380 173 10 229 956 10 889 369 6 730 456 7 774 394 19 389 974 1 7 7 714 394 1 694 270 1 9 468 664 12 284 241 6 932 369 7 899 371 08 11 615 579 7 899 371 1 014 954 8 914 325 13 491 167 7 140 340 8 035 269 7 3 716 208 3 3 716 208 324 717 4 040 925 3 19 036 732 23 769 987 24 483 086 25 217 570 25 974 106 26 753 329 27 555 929 28 382 607 29 234 085 30 111 108 31 014 441 Source DM Model Economic Module The BCA Page The information from the annual loan amortization is then used in conjunction with annual revenues and costs to calculate the returns to equity in the plant The net present value NPV internal rate of return IRR and benefit cost ratio BCR are all calculated as a measure of project worth This is done in both real and nominal dollar amounts and allows for the allowance of a sweep payment or not Table 21 shows the valuation of the plant under regularly scheduled payments and Table 22 shows the valuation of the plant allowing sweep payments to be made Table 21 Calculation of Annualized NPV IRR and Benefit Cost Ratio No Sweep 21 502 394 21 502 394 7 14 764 977 14 764 977 4 249 872 69 928 990 74 178 862 90 433 190 8 16 254 327 4 249 872 72 026 860 76 216 732 93 146 185 16 869 453 4 249 872 74 187 666 78 437 538 95 940 571 17 503 033 4 249 872 201 76 413 296 3 80 663 168 98 818 788
13. ECONOMIC AND TECHNICAL ANALYSIS OF ETHANOL DRY MILLING MODEL USER S MANUAL by Rhys T Dale and Wallace E Tyner Staff Paper 06 05 April 2006 Agricultural Economics Department Purdue University Purdue University is committed to the policy that all persons shall have equal access to its programs and employment without regard to race color creed religion national origin sex age marital status disability public assistance status veteran status or sexual orientation Table of Contents Model Users EIE M 1 Description of Cells and their Function ao teo eee Bie hi Be Bei 2 Direct User Input Cells Yellow Black Text eene 2 Direct User Constant Cells Yellow Red 2 Value Return Cells siente eti te BRI re IN MENS 2 Function RIS 2 Descriptor Cells Information Cells Tan Light Green eee 2 Calculation Cells Light Yellow ette dot teet tna concede tesa EY Re doe Eo ab eL 3 Flow Rates White Purple and Orange 2 eee teer 3 Look Up Table Bright Green cuocere ce P equ a 3 Description of The DM Model Pages and Their Use seen 3 Process ASSUM PU ONS coo outs aces ceea tesi 4 Plant Operation Input eat ett ere ede 4 PROCESS Assumption DIGSTAITIS Dom ue IRAN PNEU 4 Process Parameters
14. Functionally If N36 1 Then Price EtOH Regression R Sqd 62 IN USE error N us DDGS Price Ton f price of SBM price of Manual Entry 1 Manually If N36 0 Then Price EtOH IN USE entered here 2 Functionally If N36 1 Then Price EtOH Regression Adj R Sq 73 not in use error 9 2 135 N us Jet Cooker f Capacity Manual Entry 1 Manually If N36 0 Then Price EtOH not in use entered here 2 Functionally If N36 1 Then Price EtOH f Price of Gas IN USE Function 2 38 000 10 12 N2 0024 Source DM Model The price function of DDGS was calculated in the same manner using the price of corn and soybean meal as the explanatory variables for the price of DDGS Price DDGS 9 205 1 037 Price Corn 135 Price SBM e t stat 2 2 10 9 4 6 P value 03 0 0 Adj 73 The jet cooker is a piece of equipment used in the dry mill process for which no cost correlations could be found A discussion with representatives of a company which sell jet cookers led to the addition of a look up table included with the price function for a jet cooker The jet cooker price was constructed as a function of plant capacity If the user chooses not the use the price function the user may enter any value for the price of the jet cooker in the manual price cell with or without the assistance of the look up table The jet cooker function is as
15. al Engineers 13 Economic Module Revenue and Cost Estimation The sum of all major equipment is then used to estimate the direct and indirect capital costs associated with a dry mill plant of this magnitude This is done with two different methods FCI and RDE which return different estimates Working capital is then added to the capital costs and an estimate of fixed capital investment is returned Table 15 shows how these costs are estimated note that the same purchased equipment cost that was calculated in Table 14 appears in Table 15 The DM TCC is then calculated using values of plant capacity and FCI and RDE TCC estimates This is shown on the bottom of Table 15 The actual flow rates from the process flow pages are used to calculate the yearly output of co products and the yearly requirement of inputs for this output Yearly revenue is calculated by multiplying the yearly amount of each co product by its price Yearly variable costs are calculated in the same manner multiplying the inputs by their costs Yearly avoidable fixed costs are calculated also on this page These costs include taxes labor and licensing fees The yearly variable cost and avoidable fixed cost are summed to return the total yearly cost of operation Table 16 shows the annual real revenue that the dry mill plant receives form the sale of their co products and government subsidies These are revenues are summed to return an estimate of total annual revenue in re
16. al dollars 18 Table 15 Capital Cost Estimation for 40 MGY Plant Corn to Ethanol Capital Cost Estimation Peters et al 2003 Plant Design and Econ for Chm Eng 251 Fixed Cap Invst FCT Ratio Delvd Equip RDE Error or 30 Error or 20 to 25 Purchased Equip 10 006 438 10 006 438 Instrumentation 4 107 446 3 602 318 3 189 825 6 804 378 2 010 027 1 100 708 2 010 027 1 801 159 Yard Improvement 786 532 1 000 644 Service Facilities 6 030 081 7 004 507 F 277 218 302 125 Construction Expense 4 020 054 k 4 102 640 Legal Expense 786 532 400 258 Contractors Fee 786 532 2 201 416 Contingency 3 189 825 4 402 833 Total Indirect Capital Costs 12 060 161 27 6 14 409 271 144 Tot Capt Cost TCC 43 696 236 50 432 448 Working Capital 3277218 271 218 3 782 434 Tot Capt Invst TCI 46 973 454 973 454 54 214 882 Estmt if Plant Capacity gt 85 RDE Estmt if Plant Capacity gt 85 per gal per gal RDE TCC If Plant Capacity lt 85 mgy and gt 40 mgy then TCC is a linear fnct of the two Tot Cap M gal Functional Value DM Total Capt Cost DM TCC Working Capital 4 799 620 DM Total Capt Invst DM TCI 55 232 068 TCC Total Cap 1 26 Source DM Model Estimates Plant Design and Economics for Chemical Engineers 13 Table 16 Yearly Real Revenue for 40 MGY Plant Yearly Revenues Rev
17. ation of the different types of cells in the model is in order There are several different types of cells in the model each of which is color coded as either an input direct and constant value holder information calculation look up table flow rate or function cell Any of the cells can be changed to suit the specific needs of a user but caution should be exercised when changing any cell value that is not a direct user input bright yellow with black text Cells that are not yellow with black text should only be changed for very specific reasons To mitigate against accidental user input in non input cells they have been password protected The function of each cell is indicated by its color Table 1 shows the different types of cell colors and their corresponding function A detailed explanation of cell nomenclature directly follows This explanation precedes a description of each module of the DM model and how it is to be used Table 1 Description of Cell Color Coding Variable Color Coding Value Holder Information Input Flow Source DM Model Description of Cells and their Function Direct User Input Cells Yellow Black Text These cells are where the user enters or changes values These cells are designed to be manipulated by the user to change the assumptions of the model Changes in values of these cells will directly change the quality and amount of output and financial situation of the modeled dry mill Direct in
18. d the screen displays the process assumptions worksheet by default Users can then enter values for direct user inputs and move from worksheet to worksheet by clicking on the tabs at the bottom of the worksheet The following will briefly describe how each page of the model was constructed and how the user is to manipulate it All user inputs are entered into the DM model on one of the three assumptions worksheets In the assumptions module every type of cell is utilized excepting flow rate cells This module and the values entered by the user drive the rest of the model Users enter values pertaining to three categories the dry mill production process physical properties of inputs and outputs and economic parameters Process Assumptions The process assumption worksheet is the first worksheet in the assumption module This worksheet is composed of three tables and four diagrams that together cover almost all the decisions that a production manager and or owner of a dry mill plant must make in production The user may enter values for plant capacity plant utilization retention times process temperatures enzyme usage and moisture percentages of different streams The most important variables and most likely to be changed are found in the plant operation table Plant Operation Input Table Variables found on the plant operation table drive the model Two of the most critical variables are annual production capacity and the percentage of uti
19. d expected yield of co products from grain Table 5 shows the grain composition table as it appears in the DM model these values are in dry weight percentages Table 5 Physical Property Assumptions Grain Composition Physical Assumptions Grain Composition Starch Sol Sugar Cellulose Hemi Lipids Protein soluble insoluble Ash Other Moisture 15 5 11 Source Corn Chemistry and Technology 18 DM Model Densities Indices Identities The physical properties of water alcohol grain and gasoline are entered in the DII table Table 6 This includes their densities and relative densities which are important in converting hourly flow rates in terms of weight into hourly flow rates in terms of volume The table also allows for entering the Marshall Swift index number This allows for the inflationary rate of chemical equipment to enter the model The energy index used in calculating electrical energy use appears in this table as well Several convenient excel variables are also listed in this table These include the values of 1 000 000 and 60 that are used frequently in conversions in the DM model Table 6 Physical Property Assumptions Densities Indices Identities Physical Property Assumptions Densities Indices Identities Marshal Swift Energy Water Anhydrous EtOH Mash Beer Grain 165 bush Hydrous EtOH Ibs gal Reltv EtOH H20 One Million Minutes per Hour Btu s evaporate 1 Ib H2O
20. enue Product Dollars Yearly Output Annual per gal Ethanol denatured 39 900 000 hydous 41 841 004 anhydrous 38 000 000 DDGS dry 11 072 195 0 29 CO2 and Subsidies co2 252 251 272 756 754 0 02 Subsidies 38 000 000 0 0 82 759 179 2 18 Source Factors Associated with Success of Fuel Ethanol Producers 15 DM Model Estimates Similar to the annual revenue the annual operating costs are also calculated as shown in Table 17 The hourly flow rates of all inputs are multiplied by the number of yearly operational hours to give an estimate of operational costs Indirect costs are found as a percentage of 19 revenue net revenue and total capital costs This table also calculates the average costs per gallon of ethanol produced in a year Working capital is calculated as a percentage of total annual operating cost seen at the bottom of Table 17 Table 17 Annual Real Operating Costs Annual Direct Indirect Operational Costs Annual Direct Operational Costs Costs Direct Input Per Amnt Used Annual per gal Total Yellow Dent 85 00 Ton 390 259 33 172 039 0 873 33 172 039 Electricity 47 795 1 433 837 0 038 Natural Gas 1 314 389 10 515 110 0 28 Denaturant 1 900 000 3 800 000 0 100 H20 133 231 133 231 0 0035 15 882 178 A amalayse 343 740 1 031 221 0 027 G amalayse 401 030 1 203 091 0 032 Chem s Enzyms Yeast 462 834 1 157 085 0 030 502 Antibiotic 254 065 635 163 0 017 4 026 560
21. ess are the fermenters 4 and the beer well The flow rates are found for dry weight pounds and volume when applicable The flow rates of the inputs are shown in purple outputs in white and when output flow is equal to input flow it is shown in orange Densities and energy flows are also calculated when applicable 15 Figure 4 Process Flow Diagram Hourly Flows for a 40 MGY at Full Capacity J Cook HP Tube Liquefaction Tank DeltaT 50 DetaT 70 q 29 q 164 Molecular Sieves i Source DM Model Table 11 Hourly Flow Rates for Fermentation Hourly Flow Rate Fermenters 28 796 27 356 1 833 831 738 0 701 84 232 335 7 70 220 719 28 676 Source DM Model Estimates Energy and mass balances are also calculated on the process page These tables are found below the process flow diagram The per gallon of ethanol energy and water results are shown in Table 12 These averages were found by summing the hourly flow rates for all processes multiplying the sum by the number of operational hours per year and dividing by the number of gallons of ethanol produced in a year 16 Table 12 Average Energy and Water Usage per gal of ECOH Produced Annual Utility Use EtOH Production Energy Avg Use gal EtOH Thermal Mbtu s Electrical kWh s Water Avg Use gal EtOH fresh gal recycled gal Source DM Model Estimates Table 13 shows how the calculation of solubles and insolubles was carried out This infor
22. f outflow In the process module the anhydrous ethanol flow into storage tanks rate is blue the flow of grain to be milled is purple and the flow of mash to the fermentation vessels is orange Look Up Table Bright Green These cells always occur in tabular form and are used to give the user a range of values for an input Look up tables are intended to be used in conjunction with direct user input cells and for this reason these cells only appear in the assumptions module of the model Look up tables appear directly next to the input cell that they provide values for Look up tables are used to give constants for different distillation tray heights as well as jet cooker price suggestions Description of the DM Model Pages and Their Use The DM model contains four modules indicated by the color of their tab assumptions process economic and technology assessment The assumptions module demarked by yellow tabs is made up of three separate worksheets process Asmpl physical Asmp2 and economic Asmp3 assumptions The process module indicated by the tab color light yellow consists of two pages process flows Procl and equipment sizing pricing Proc2 The economic module signified by blue tabs consists of three worksheets revenues and costs Econl financing Econ2 and benefit cost analysis Econ3 The technology assessment module consists of one worksheet Tech1 and is denoted by the tab color of red When the DM model is opene
23. follows Price Jet Cooker 38 500 0024 Capacity 10 Capacity 14 The price of the jet cooker appears in the price function table regardless of whether its function is used or whether a manual price is entered Process Module Process Flows The process page is where the user inputs from the variables page are used to calculate the hourly flow rates The annual ethanol output and yield rates from the process assumptions page are used to calculate flow rates of grain ethanol water and DDGS The theoretical yield of co products and the yearly plant capacity are used to calculate the hourly flow rates of inputs and outputs in each stage of the dry mill process These flow rates are calculated in terms of weight dry weight and volume when possible Hourly flow rates were calculated for full capacity as well as for average actual capacity utilization Flow rates were calculated using the dry mill process assumptions as well as physical property input values Hourly flow rates are displayed in two ways diagrammatically and in table form The flow diagram Figure 4 better expresses the flow of streams while the table form allows for more manipulation of the flows Table 11 Streams of outflows are streams in blue inflows in purple and process in orange The diagram shows flows in pounds at full capacity Table 11 shows the tabular flow rates for the fermentation process The two pieces of equipment utilized in this proc
24. h Vol 12 No 2 June 15 The Renewable Fuel Association www ethanolrfa org 24 16 Shapouri H Gallagher P Graboski M S 2002 USDA s 1998 Ethanol Cost of Production Survey USDA Agricultural Economic Report Number 808 17 Tiffany D G Eidman V R 2003 Factors Associated with Success of Fuel Ethanol Producers Staff Paper P03 7 Department of Applied Economics University of Minnesota 18 Watson S A 1994 Structure and Composition of Corn Chapter 3 Pages 53 78 in Corn Chemistry and Technology Watson S A and Ramstad P E eds American Association of Cereal Chemist St Paul MN 19 Weinkat P C Klaaven E McKenzie B A 1984 Alcohol Distillation Basic Principles Equipment Performance Relationships and Safety www ces purdue edu extmedia AE AE 117 html 20 Zeochem Corporation 2005 Molecular Sieve Adsorbents for the Process Industries and Other Markets 25
25. le DDGS was calculated as the remainder The actual pounds of product per pound of grain input was calculated and used in flow rate estimation Process Parameters Table Parameters including retention time rtd number of pieces of equipment and process temperatures are entered for each step of the production process These are entered in the table titled Equipment RTD Number Temperature as shown in Table 3 These parameters are important in calculating equipment size thermal energy use and process flow rates Many dry mill processes such as hammer milling have no specific rtd These processes operate at whatever flow rate is necessitated by the rest of the system Process stages which do operate at system speed have the number 60 entered as their rtd The longest rtd in the dry mill process is the fermentation process Due to the relatively extensive residence time in this step dry mills commonly employ four fermentation vessels The beer well is a large storage tank in which fermentation continues Beer wells are commonly designed to hold twice the volume of the fermentation vessels Figure 3 Theoretical and Actual Product Yields THEORETICAL Conversion of Corn to Ethanol 1 Dry Bushel of Corn all vaues in Ibs unless stated otherwise 13 97 Milled Starch _Hydrolyzes Cleaves Ferments E q 9 oO eS pM 47 32 34 73 38 55 38 55 18 85 BOR 1970 ACTUAL Conversion of Corn to Ethanol 1
26. lization As can be seen below in Table 2 the plant operation input table also allows for the user to set values for the backset rate percentage solids in the fermentation and the denaturant percentage of denatured ethanol The user should first enter a value for total plant capacity into the first input cell of the table This is the maximum number of gallons of anhydrous ethanol the plant can produce in a single year Most dry mills are within the capacity range of 10 and 100 million gallons of anhydrous ethanol per annum It is suggested that users enter capacities within this range because the DM model has been validated at these production levels Ethanol production facilities run continuously with scheduled shut down periods for maintenance In the DM model there are two ways in which less than full capacity utilization can be entered using a function trigger The user can either enter a utilization of full capacity percentage or enter the number of operational days per year The user should enter a 1 into the function cell and enter the percentage of full capacity utilization or enter a 0 and enter the number of days of plant operation Directly to the right of the trigger tells the user which method is being used BBI s Ethanol Handbook states that the planned number of days of operation should not be more than 360 days of full utilization corresponding to a 99 utilization rate 2 Operational hours are calculated by multiplying days of operati
27. mation was used to calculate the flow of whole stillage into thin stillage and WDG Table 13 Calculation of Solubles and Insoluble Solids Solubles and Insolubles Table Insloubles Non Starch Starch Solubles Glucose Protein Alcohol Source DM Model Authors Estimates Process Module Equipment Sizing and Cost Estimation The third page of the DM model calculates the necessary equipment size for the given flow rates and also estimates the cost of the sized equipment The flow rates that were calculated in the process page and physical property values are used to calculate equipment sizing Equipment size is found in horse power volume area or height The estimated cost of individual pieces of equipment is calculated using their respective size estimates The sum the equipment cost is then used to estimate fixed capital investment associated with the plant In Table 14 we see that the total cost of equipment estimate equals 10 006 438 for a 40 MGY plant This estimate is used to calculate total fixed costs for the plant 17 Table 14 Equipment Size and Cost Estimation for 40 MGY Plant 1 Milling Grain Handling Hammer Mill 610 Jet Cooker Sacharification HP Hold Tube Liq Tank SEEN ERN Beer Well 1 140 20 Rectifier dstlt FR trays Stripper Evap rate trays Mol Sieve Beads Sieve columns 5 Co Prod Recovery 1 380 822 Source DM Model Estimates Plant Design and Economics for Chemic
28. o be quite conservative in their management of risk Information from each of the preceding pages is used to calculate the annual finances that are displayed on page 6 of the DM model This page contains a yearly break down of the loan 20 payments figured with and without a sweep payment included All the pertinent financial information is also displayed on this page The annual profits are now able to be calculated with the available information Table 18 shows the financial table as it appears on page 6 of the model Table 18 Financial Information for a 40 MGY plant Financial Table Information Calculations Loan Info Loan Years Expected Life of Plant Loan Info Invst Total Invst Year 2 Invst Total Invst Initial Equity Capital Invst Initial Loan Capital Invst Sweep Pmnt Profits Working Capital Total 1 Rates Discount Real Discount Inflationary Interest Source DM Model Estimates The information from the financial table is used in to calculate annualized payments principal interest and total as well as expected profits in both real and nominal dollar amounts This information is shown in Table 19 The annualized payments are also calculated allowing a sweep payment shown in Table 20 The annual expected profits are used to calculate how much faster the loan will be paid off than the regular scheduled payment plan The annual profits are also calculated under the allowance of a s
29. on by the number of hours in a day 24 The user can also change the percentage solids of the mash changing the alcohol content of the beer backset rate changing the water balance and the necessary denaturant percentage changing the denaturant input Process Assumption Diagrams Biotic and other parameters of the ethanol production process are entered in the process assumptions diagrams In the theoretical process diagram Figure 1 the user enters parameters for the amount of enzymes yeasts and antibiotics required per pound of corn input This diagram shows theoretical conversion rates per pound of dry weight corn All values are in dry pounds excepting gallons of ethanol Most new ethanol plants are within the range of 30 100 MGY It should be noted that there are huge energy requirements in shutting down and restarting a plant especially in distillation systems 4 Table 2 Dry Mill Process Assumptions Plant Operation Dry Mill Process Assumptions Plant Operation Production Name Plate gal year Utiliz Method ON Capacity Method trigger 1 Op Hours Method trigger 0 Actual gal year 38 000 000 Plant Utilization NP Cap 95 Operational hours day days year hours year Paramaters Backset Rate of H2O Mash Solids of Mash Denaturant of EtOH Source DM Model Figure 1 Theoretical Conversion of Corn to Ethanol Theoretical Conversion of Corn to Ethanol 1 Dry Pound of Corn
30. put cells important in determining the profitability of the dry mill include plant capacity physical conversion rates economic rates etc These are the only cells in the model that are not protected Direct User Constant Cells Yellow Red Text These cells are readily manipulated by the user just as direct input cells are However it is not recommended that these cells be changed because their values do not vary much across time or plants The values in these cells are generally accepted and changing these values is not recommended These cells include the densities of materials indices molecular weights minimum reflux values etc To protect against user error these cells are protected Value Holder Cells Light Blue These cells are the values from other cells in other modules or sheets They take values inputs or calculations from one part of the model and return them in another part of the model to be used or lend clarification They are used to connect the individual sheets together and increase the transparency of the model These cells have labels describing where they come from Function Trigger Cells Pink The function cells allows the user to choose to either input a value as a function of other variables by entering a 1 in the trigger cell or input the value independent of other variables by entering a 0 Functions exist and can be used to calculate conversion rates plant utilization percentage and prices fo
31. r distiller s dried grains with solubles DDGS ethanol and a jet cooker The bright pink cells are used to turn the function on 1 or off 0 and light pink cells describe or are the products of functions Information Cells Tan Light Green These cells simply explain what unit variable or process is being used in the other types of cells These cells are used to describe excel names and also appear in the title page These cells should not be changed Descriptor cells include row and column headings units for other cells and other general information Calculation Cells Light Yellow These cells carry out the calculations that take place in the model Using values from other cells input function or other calculation cells calculations are carried out in these cells Calculation cells return values for densities equipment sizing financing etc These cells are the same for all plant capacities but will return different values according to their functional form and input values In general these cells should not be changed unless there is a specific reason for example to indicate an industry wide change Hourly Flow Rates Blue Purple and Orange Hourly flow rate cells are used in the process module to differentiate between input output and process flows Orange cells represent hourly process flow rates where no output or input takes place purple cells indicate hourly rates of inflow and blue cells signify hourly rates o
32. rice Functions Table The last input table that deals with the economic parameters of the dry mill plant is a price functions table This table is shown below as Table 10 The prices of ethanol DDGS and the jet cooker are calculated as a function of other prices or capacity In this table the user must decide whether to enter the prices of these goods manually by turning the function off or allow these prices to be calculated as a function of other prices capacity by turning the function on The price function is turned on by the user entering a 1 in the adjacent pink cell and it is turned off by the entering a 0 in the same cell The ethanol and DDGS price functions were calculated through regression analysis of their respective markets and substitutable goods The table lists the commodities that were used as explanatory variables in the analysis and their corresponding p values The over all model fit is also listed in the table as the R value The ethanol price per gallon is a function only of the price per gallon of gasoline Price Ethanol 19 37 792 Price Gas e t stat 2 0 11 8 P value 05 0 Adj R 62 Price data for gasoline ethanol corn and soybean meal come from Bloomberg s Electronic Database DDGS prices come from USDA 13 Table 10 Economic Assumptions Price Functions Ethanol DDGS and Jet Cooker Economic Assumptions 1 Manually If N36 0 Then Price EtOH not in use entered here 2
33. ss Assumptions Distillation Evaporation EtOH Water Minimum m3 sec Anhyd EtOH Pressure Ibs in Hyd EtOH Passes Of Heat Exchange Max Avg Delta T Of Drum Dryer Max Avg U Temp Spacing Rectifier Stripper Source DM Manual Alcohol Distillation Basic Principles 19 Economic Variables There are three tables in the variables page of the DM model that deal directly with the economics of the dry mill production process The first of these pages is a price table in which prices for all inputs and outputs are entered The second deals with the finances of the ethanol plant and the third table allows the user to turn three price functions on or off These functions are for the price of ethanol DDGS and one piece of equipment for which no data exists the jet cooker Price Table In the price table Table 8 the user simply enters prices for all inputs outputs and governmental subsidies The user is also asked to enter the price of one good that is neither an input nor an output soybean meal but is used in the DDGS price function The prices that the user enters are either in dollars per volumetric unit gas and water dollars per weight unit corn and CO or as a percentage of revenue net revenue and capital costs taxes labor license fees and miscellaneous expenses 11 Table 8 Economic Assumptions Prices Values Economic Assumptions Prices Values Dent Corn Milo Soy Bean Meal Chemicals
34. transferred from user input cells in other tables The mash moisture comes from the user input of the percent solids in the mash while the corn and DDGS moisture percentages come from the physical properties table This input table shown below as Table 4 is used in the calculation of hourly flow rates water balance and input requirements Physical Properties There are three tables in which physical properties are entered into the model the grain composition table distillation and evaporation table and the densities indices and conversions table These physical assumption values are used in the calculations of flow rates conversion rates and finances Table 4 Dry Mill Process Assumptions Solid Liquid Percentages Dry Mill Process Assumptions Solid Liquid Percentages Corn Mash Beer Whole Stillage WDG WDGS Thin Stillage Syrup DDGS Source DM Model Authors Estimates Grain Composition The grain composition table allows users to input assumptions about the macronutrient components of grain and DDGS The starch fiber protein ash moisture and glucose percentages of grain are entered into the table The percentages are summed and subtracted from 100 to obtain the other percentage DDGS nutrient content is calculated as the amount of starch dextrin and glucose that was not converted to alcohol in the fermentation process These values are used along with conversion rates to determine the theoretical an
35. weep Table 19 Annual Loan Amortization Schedule No Sweep on 34 793 247 Loan Annual Loan Amortization Schedule Principal and Payments 3 34 793 518 8 3 040210 2 7 1 209 662 1 107 4 249 872 35 18 764 247 20 504 199 14 875 012 16 254 327 4 33 583 856 2 934 512 2 1 315 360 4 249 872 8 my 21 119 325 988 29 16 869 453 5 32 268 496 2 819 577 1 430 294 4 249 872 21 752 905 17 503 033 6 30 838 202 2 694 600 1 555 272 4 249 872 22 405 492 18 155 620 7 29 282 930 2 558 703 1 691 169 4 249 872 23 077 657 18 827 785 8 27 591 761 2 410 931 1 838 941 4 249 872 23 769 987 19 520 115 9 25 752 820 2 250 246 1 999 625 4 249 872 24 483 086 20 233 214 10 23 753 194 2 075 522 2 174 350 4 249 872 25 21 919 20 967 707 11 21 578 844 1 885 530 2 364 342 4 249 872 25 974 106 21 724 234 12 19 214 503 1 678 937 2 570 935 4 249 872 26 753 329 22 503 458 13 16 643 568 1 454 292 2195 59 1 4 249 872 27 599 929 23 306 057 14 13 847 989 1 210 018 3 039 853 2 4 249 872 28 382 607 24 132 735 15 10 808 135 944 400 3 305 472 4 249 872 29 234 085 24 984 214 16 7 502 664 4 655 573 3 594 299 4 249 872 30 111 108 25 861 236 17 3 908 364 2 341 508 3 908 364 4 249 872 31 014 441 26 764 569 Source DM Model 21 Table 20 Annual Loan Amortization Schedule Sweep von 39 986 293 Loan Annual Loan Amortization Schedule with a Sweep Principle and Payments Profits 6 344 100 7 553 761 6 3
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