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D Cost Analysis Methods STRUCTURE OF ANALYSIS Most of the structure of the cost analysis is explained in Chapter 3, but a few details are further elaborated here. Cost estimates are based on the best available data in the literature. Obviously, there could be plant-specific variations in costs for different fuels and changed future circumstances. However, this analysis gives a reasonable estimate of relative costs for the purposes of ranking the various processes as to economic attractiveness. With regard to the economic assumptions delineated in Chapter 3, prices for the various energy and nonenergy feedstocks are expressed, where ap- propriate, as a function of the prevailing crude oil price. For each technol- ogy, the cost per equivalent barrel of oil, measured in 1988 dollars, is calculated as the summary cost measure based on the assumed oil price environment. This calculation begins with the crude oil price, here defined as the average price of U.S. imported crude oil. The crude oil price implies prices of energy and nonenergy inputs to the various production processes. In particular, prices of natural gas, electricity, and corn (as a feedstock) are assumed to increase with crude oil prices (see Table D-1~. In calculating cost per equivalent barrel of oil, per-gallon product costs are first calculated by adding together feedstock costs, operation and main- tenance (O&M) (energy plus nonenergy) costs, and annual capital charge and subtracting by-product credits, all on a per-gallon basis. Per-gallon feedstock costs are calculated by multiplying feedstock quantity per gallon times the price per unit of the feedstock. Energy O&M costs are calculated in the same manner. Nonenergy O&M costs are directly added. The per- gallon capital charge is calculated by dividing the annual capital cost by the annual production of the product. The annual capital cost is simply the 146

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APPENDIX D TABLE D-1 Economic Assumptions Used in the Cost Estimates 147 Natural Gas Pricea ($/Mc0:b Corn price ($1bu): Corn by-product price ($/bu): Electricity price (bought) ($/IcWh):C Gasoline refining (credit) ($/bbl): Gasoline distribution/marketing (credit) ($/bbl): Distribution/marketing for product ($1bbl): Coal price ($/ton): Oil shale feedstock ($/ton): Tar sands feedstock ($/ton): Wood price ($/dry ton): Oxygen ($/ton): Form coke ($/ton): Capital charge rate (%tyear): Consumer discount rate: Automobile efficiency: Natural gas delivery cost: $3.91 ~ 0.05857 x (Poi~- 28) $2.500 + 0.01786 x (Pail - 28) $1.200 + 0.01136 x (Poi, - 28) $0.049 + 0.00020 x (Pail - 28) $7.000 + 0.18182 x (Pail - 28) $4.000 ~ 0.02 x (Pail - 28) $4 x EQ + 0.02 (Pcq - 28) $38.00 $6.02 $8.04) $32.40 $57.05 $100.00 16.0~o and 24% 10% and 15% 27 mpg $0.94ticf NOTE: Pcq = cost per equivalent barrel of oil, net of the additional vehicle cost; Pail = price of petroleum in 1988 dollars; EQ = 1.8 for methanol; 1.5 for ethanol. aIn the present analysis, natural gas prices are not allowed to exceed $5.00/Mcf (1988 dollars) because coal gasification becomes competitive above this price. bEIA Base Case forecast for the year 2000 has $28/barrel petroleum and $3.91/ Mcf for natural gas; High World Oil Price Case has $351barrel petroleum and $4.32/ Mcf natural gas. Hence, ($4.32 - $3.91)H = 0.05857 is the slope in the equation for projecting gas price as a function of petroleum price. CEIA Base Case forecast of $0.04896/IcWh for the year 2000 arid High World Oil Price Case of $0.05038/kWh for electricity. Hence, He slope in He equation is (0.05038 - 0.04896~/7 = 0.0002. investment cost multiplied by the annual capital charge factor. By-product credits are calculated as a price per unit multiplied by the by-product quan- tity produced (per gallon of primary product) or are directly estimated. SPECIFIC FACTORS Table D-1 summarizes the specific input factor assumptions for the eco- nomic analysis of the various fuel production technologies. The relation- ships between crude oil price and other energy prices were calibrated from

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148 APPENDIX D the Base Case Forecasts and the High World Oil Price Forecasts published by the Energy Information Administration (EIA) in its 1989 Annual Energy Outlook (EIA, 1989a; see Table Dub. The EIA Low World Oil Price Scenarios were not used for the calibrations. The Base Case Forecasts and High World Oil Price Forecasts assumed for the year 2000 are $28Jbarrel and $35/barrel (1988 dollars), respectively. The EIA estimated prices of coal delivered to industrial users at $38/short ton under either of these scenarios. The committee's analysis used this price for all world oil pnces. The EIA estimated wellhead natural gas prices as $3.91/Mcf in the Base Case and $4.32/Mcf in the High World Oil Price Case. Costs of gas deliv- ered to industrial users were assumed to be $0.94/Mcf higher in both cases. In the present analysis this relationship between oil prices and wellhead natural gas prices is linearly extrapolated as oil prices increase, but natural TABLE D-2 Prices of Energy in the Year 2000 from the Energy Information Administration's Forecasts in 1988 Dollars Year 1990 1995 2000 Low World Oil Price Case World oil price ($/bbl~a 12.89 16.70 1.70 Natural gas ($IMcf~b 1.69 2.49 3.52 Coal ($/ton)C 23.76 24.61 25.42 Electricity ($/kWh~d 0.0487 0.0461 0.0472 Base Case Forecasts World oil price ($/bbl) 15.00 20.60 28.00 Natural gas ($/Mcf) 1.75 2.80 3.91 Coal ($/ton) 24.00 24.95 25.87 Electricity ($/kWh) 0.0489 0.04704 0.04896 High World Oil Price Case World oil price ($/bbl) 18.00 24.40 35.00 Natural gas ($/Mcf) 1.85 3.90 4.32 Coal ($/ton) 24.34 25.41 26.14 Electricity ($/kWh) 0.049 0.04798 0.05038 aCost of imported crude oil to U.S. refiners. "Average wellhead price. CMine-mouth price. Price for industrial users. SOURCE: EIA (1989a).

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APPE~D[X D 149 gas prices are not allowed to exceed $5.00/Mcf (1988 dollars) because coal gasification becomes competitive above this price. Natural gas used as a feedstock is assumed to reflect the wellhead price, reflecting a conversion plant operating on the Gulf Coast near to both natural-gas-producing wells and the distribution system for final products. Natural gas used as an operating cost, but not as a feedstock, is assumed to reflect a cost equiva- lent to that facing average industrial users. The EIA estimated average electricity price delivered to industrial users in the year 2000 as $0.04896/l`Wh and $0.05038/kWh in the Base and High World Oil Price cases, respectively. A linear relationship between oil and electricity prices was derived for the present analysis from these points. Corn prices and corn by-product prices were also assumed to be linearly related to oil prices, and prices for oil shale feedstock, wood? and oxygen were assumed. The relationship between corn price and crude oil price was based on the assumption that every bushel of corn requires three-quarters of a gallon of oil in farming. Refining costs of gasoline were assumed to increase with the price of crude oil. The relationship was calibrated so that the spread between gaso- line and crude oil price would be $7/barrel when the crude oil price was $28/barrel and would increase by $2/barrel for every $11/barrel increase in the crude oil price. This gave a refining credit for methanol, ethanol, and compressed natural gas (CNG). Distribution and marketing cost (per actual barrel) was assumed to be $4/ barrel of product when crude oil was $28/barrel. The same cost per actual barrel (or per gallon) was applied to gasoline, methanol, and ethanol. Dis- tribution costs were also related to the value of the product being distrib- uted. Distribution costs were assumed to increase by $0.02/barrel for every $1/barrel increase in product costs. This increase was meant to reflect additional inventory costs of the higher-valued product. The same relation- ship was applied to all methanol, gasoline, and ethanol. An equivalency factor of 1.80 was used to convert a given volume of methanol to the volume of gasoline that would give the same work output as a methanol-fueled automobile. This factor arose from the assumption that for a specially designed methanol vehicle there would be a 10 to 18 percent energy efficiency advantage over today's gasoline-fueled automo- biles. This energy advantage could vary from approximately zero, for first- generation dual-fueled automobiles to 30 percent or more for future, highly optimized, methanol-fueled systems. For zero efficiency difference the equivalency factor would be from 2.02 to 2.06 (2.06 is used in the present study) (based on the heat of combustion in American Petroleum Institute Report 4621 t19761~. For 30 percent efficiency advantage the equivalency factor would be from 1.55 to 1.57 (1.57 is used in the present study). Distribution and marketing cost for CNG was separately analyzed, since

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150 APPENDIX D the compressor station and the distribution station would typically be one unit. Thus, capital cost for this technology was the cost of a single filling station that would deliver a gasoline equivalent of 1200 gaVday and would use 0.12 MMBtu of natural gas per equivalent gallon of gasoline. Annual operating and maintenance costs (nonenergy) were estimated as 7 percent of the original investment cost. No separate additional distribution and mar- keting costs were assessed. For two fuels, methanol and CNG, the capital cost for new cars was anticipated to be greater than for the other fuels. For these fuels this addi- tional capital cost was translated to an equivalent per-mile additional oper- ating cost, where the per-mile equivalent cost was derived so as to give the same discounted present value of costs to the consumer as would the one- time additional capital cost. For this calculation it was assumed that a typical car was driven 15,000 miles per year over the course of 7 years. The per-mile equivalent cost was then translated to a per-gallon cost by multiplying by the average fuel efficiency of new cars, assumed to be 27 mpg. The specific equation to calculate the per-mile equivalent cost is as follows: K = 15,000 x Car [1 - 1/~1 + r)7] (1 + r) r 1 where K is the additional capital cost of a new automobile, Car is the per- mile equivalent cost, and r is the consumer discount rate, assumed to be 10 percent annually (real). The right-hand side of the equation discounts the 7 years of annual costs (equal to 15,000 x Car each year) back to the time that the car is purchased. The left-hand side is simply the additional purchase price. The equation can be solved for Car. The per-gallon equivalent cost is thus the product of Car and the fuel efficiency (in mpg) of future automo- biles. Discount Rate A point of some uncertainty is the appropriate discount rate assumptions to use in analyzing the cost of capital-intensive projects, such as those considered in the study. One perspective is that the appropriate discount rate for a policy planning study should be equal to the estimated cost of capital facing corporations of the types that might consider investing in such projects. A second perspective is that the discount rate should be equal to the estimated typical hurdle rates for investments made by such corporations. The first perspective has led to the 10 percent real discount rate used in the base case. An analysis of the average historical returns to equity capital

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APPENDIX D 151 in financial markets and of the historical returns on physical capital in- vested in United States industry suggests a real cost of capital ranging between 8 and 12 percent. Variations in the estimate depend on the riski- ness of an industry and the degree to which the risks are correlated with returns to the overall economy. The 10 percent figure has been selected as typifying that range. The second perspective, that discount rates should be based on "typical" corporate hurdle rates, has led to the IS percent real discount rate also used. The hurdle rate is the minimum estimated rate of return required by a corporation in order to approve a prospective investment. Hurdle rates are chosen within corporations so as to guide investment decision making. Since they are corporate policy instruments, hurdle rates can vary widely among corporations and can vary within a corporation based on the nature of the prospective investment. Thus, hurdle rates might well be higher than 15 percent, particularly for projects seen to be particularly risky. Hurdle rates can be lower than IS percent, particularly if a project is not seen as being more risky than typical other investments. The perspective based on typical hurdle rates leads to a higher discount rate because a firm's hurdle rates typically exceed its costs of capital. Rea- sons for this difference between discount rate and cost of capital vary among firms. Hurdle rates are often applied not to the expected value of revenues and costs but to estimated values of revenues and costs based on some risks but ignoring others that cannot be reasonably quantified. Hurdle rates ex- ceeding the cost of capital can compensate for the inability to include some of the downside risks. However, evaluations based on estimations of ex- pected value already account for the important quantifiable risks. In addi- tion, some firms increase the hurdle rate to compensate for the natural tendency for project advocates within a corporation to present the econom- ics of their projects using rather favorable or optimistic assumptions. Fi- nally, increased hurdle rates can compensate for a "winner's curse" phe- nomenon in which random variations in cost estimates lead the given project to be pursued dominantly by those groups that happen to most overestimate its profitability and to be rejected by those that happen to most underestimate its profitability. The study used 10 and IS percent discount rates. Summary discussions make primary use of the 10 percent cases, which past studies indicate are typical of industrial returns under relatively stable conditions. Also, for the purpose of government R&D planning, the Office of Management and Budget specifies a 10 percent cost of capital based on considerations detailed above. Early application of any of these technologies will entail risks because of uncertainties in technology and oil price fluctuations and, in the case of alternative fuels, consumer acceptance. These pioneer plants would require either a high hurdle rate or risk reduction mechanisms by the government.

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152 APPENDIX D Without such mechanisms the construction of such pioneer plants would wait for higher calculated returns on investment or reduction of perceived risks. For a mature and developed industry the costs of capital should approximate those typical for refinery resid conversion processes plus a premium to reflect the risk of lower than anticipated crude oil prices. This would suggest a 15 percent cost of capital. Annual Capital Charge Factors Annual capital charge factors are calculated so that the net present value of the stream of capital charges, after taxes, is just equal to the initial investment cost, using the cost of capital as the discount rate. A project life is chosen as 20 years, plus the construction time. It is assumed that the median of investment costs is incurred 2 years before the middle of the first year of plant operation or, equivalently, 1.5 years before the project begins operating. (More precisely, it is assumed that investment costs are spread over time so that the present value of these expenditures, discounted to a point 1.5 years before the project begins operating, is equal to the total investment cost.) In developing these factors it is assumed that the various processes face tax rules consistent with the current tax laws. In particular, it is assumed that the corporation pays a 34 percent tax rate on profits and that the invest- ment is depreciated over time using a 10-year, double-declining balance depreciation schedule. Depreciation allowances depend on the nominal value of historical investment costs and are not adjusted upward for infla- tion. The tax deductibility of interest payments is incorporated implicitly in the analysis through the use of the after-tax cost of capital. (When present- value calculations are conducted using the after-tax cost of capital, no addi- tional deductions for interest payments should be included explicitly.) Plant Investment Costs Plant investment costs are based on the committee's estimates of costs that might characterize a developed industry. Even though these technolo- gies in many cases have not been fully demonstrated and have not been commercialized, the committee has not based its estimates on costs of the first demonstration or pioneer plant. In these technology assessments the committee has tried to assess the median value of the capital costs for a project. No explicit probabilistic analysis was conducted by the committee. Capital investment cost estimates have been adjusted to 1988 constant dollars to be consistent with the other economic factors. Table D-3 displays estimates of these investment costs (denoted as capital or capital/capacity) for each technology. In calculating investment costs an attempt has been

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APPENDIX D 153 made to include all of the relevant costs of the investment, including those for process (onsite) and offsite construction, infrastructure development (where needed), planning, environmental compliance, site preparation, and contingencies. Plant capacities have been chosen based on the economically efficient sizes for the various technologies. The committee has attempted to stan- dardize the capacities across venous technologies when economies of scale appeared to be important in influencing overall costs; however, all capaci- ties are not standardized to one common level. Table D-3 displays the capacities assumed for the various technologies. Capacities are expressed both in terms of actual barrels per day and in teens of oil equivalent barrels per day. To provide some comparability among the technologies, it is useful to calculate the ratio of investment costs to capacities to obtain an investment cost per daily barrel of capacity. The ratio can be based on either actual barrels or capacity of oil equivalent barrels. Both of these ratios are pro- vided in the output tables. Figure D-1 shows the investment cost per oil equivalent daily barrel of capacity for each technology. In what follows, this ratio will be referred to as the "per-barrel investment cost." These figures can be interpreted as the NG > Methanol Coal > Methanol UCG > Methanol Wood > Methanol NG, MTG Coal, MTG NG, Shell MDS Compressed NG Corn > Ethanol Oil Shale Tar Sands, Pyrolysis Tar Sands, Extraction Direct Liquefaction 1 1 1 1 1 1 ~7~ ~ 1 1 1 1 1 1 1 r - 1 1 1 1 ~~ 1 ~ ~,,,,,,,,,,,,,,,,,,,,,,,,,,,,,~ ~: ~=L ~1~ Tang- ~/~ ~/////~/////~////1///-///1///2 1 1 1 HI No Demonstration C: Demonstrated ~ Commercial $0 $10 $20 $30 $40 $50 $60 $70 $80 $90 COST: CRUDE OIL EQUIVALENT ($ per barrel) FIGURE D-1 Investment cost per equivalent daily barrel of oil (thousands of dollars at 1988 prices). New estimated capital cost for coal-to-methanol could be 40 percent lower.

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154 APPENDIX D initial investment cost for each 1 barrel per day of capacity to produce a fuel that would substitute for 1 barrel per day of oil. As can be seen, there is wide variability in the estimates of the per-barrel investment cost. In general, these per-barrel investment costs exceed the $10,000 to $20,000 range typical of investments for crude oil exaction in the United States, ranging from a low of $20,000 for production facilities for methanol from natural gas to a high of $102,000 for gasoline produced from coal using methanol-to-gasoline conversion processes. While the CNG investment cost is shown as lower than the range cited, these figures include the investment cost only for a CNG delivery station and do not include the additional costs of the vehicles themselves or the investment cost of natural gas wells. COST ESTIMATES FOR THE VARIOUS TECHNOLOGIES Tables D-3 to D-8 show cost estimates for the various technologies. Table D-1 provides a detailed statement of the various assumptions for each NG > Methanol Coal > Methanol UCG > Methanol Wood > Methanol NG, MTG Coal, MTG NG, Shell MDS Compressed NG Corn > Ethanol Oil Shale Tar Sands, Pyrolysis Tar Sands, Extraction Direct Liquefaction ;;; ~ 1 `:~:~:~:~::::::~:::~:~:~:~:~:~:. ~ ~ ~- ~- ,;,,;,.,,,, -.-, ,. J I ................................ 1 ; ~ .;;;;;;.;;;;;;;;; :;:::::::: :::::::::-::::::-:-:- :-:-:-:-::;:;:;: :7 .~ :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: :---:-:-:-:-:-:-:-:-.-. :-:-:-::::: ~ ] - -- r- -'1 - ......................... ................................... _ ........................ ........ , ........ .~ ;-;-;-;-; ;-;-;-;-;-;-;-;' . ~:-:-:-:-:-:-:-:-:-:-:~ :-:-:-:-:-: ...................................... - . ! -.l. ~~ l . TTT~ ~ . . - _:::::::::::::::-::::::::::::-:::j:::-:-: :-:: :--,:-:3 J - , .......... ~ _ , - - - - -1 $0 $10 $20 $30 $40 $50 $60 $70 $80 INVESTMENT COST (1 000s $ per Oil Equivalent Barrel) FIGURE D-2 Estimated costs of alternative fuels (15 percent discounted cash flow, endogenous price calculation).

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APPENDS D 155 technology and Table D-3 shows the resulting costs on a disaggregated basis. Table D-4 shows results based on 10 and 15 percent real discount rates and the endogenous determination of energy prices. Tables D-4 to D-8 show costs under a number of combinations of the various inputs. These sensitivity studies show variations of costs win re- spect to the discount rate, the crude oil price, and the natural gas price function. Additional details on source data used in the economic analysis are provided in Table D-9. Graphs showing cost estimates and their components are presented in Chapter 3. Figure D-2 shows cost data similar to the data in the body of this report for the 15 percent discount rate. Plant capacities for the coal to methanol, coal to methanol and gasoline, and the natural gas to methanol to gasoline technologies were adjusted by the committee to the larger plant scale of 50,~0 bbl/day oil equivalent. This scale is consistent with the scale used for the natural gas to methanol technology. A conservative scaling factor of 0.85 was used. However, the scaling exponent could be as low as 0.7 if the same econo- mies of scale apply based on Bechtel's recent analyses of natural gas to methanol plant investments. In addition to estimating the cost of an 80,000- bbVday methanol plant (in the California Fuel Methanol Study [19891), the cost for a 20,000-bbl/day plant was estimated. If the investments for the 50,000-bbl/day plants using the above three technologies were estimated using a 0.7 rather than 0.85 scaling exponent, the capital investment would be 15 to 20 percent lower. The cost estimates are summarized as follows: Process: Coal to Methanol Coal, MTGa Natural Gas, MTGb Scaling exponent 0.85 0.7 0.85 0.7 0.85 0.7 Capital investments 34,122 26,800 82,460 69,900 39,320 33,320 Cost ($/barrel~d 53 45 62 55 60 57 aCoal as feedstock, with Mobile methanol-to-gasoline (MTG) process. bNatural gas as feedstock, with We MTG process. CCapital investment is dollars per actual barreVday. dCost is per crude oil equivalent barrel, 10 percent discount rate, and endogenous price calculation.

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APPENDIX D 177 TABLE D-9 Technologies and Source Data Used in the Economic Analysis 1. Natural gas to methanol: California Fuel Methanol Study (1989~. 2. Coal to methanol: Data from Schulman and Biasca (1989) were adjusted by the committee to larger plant sizes of 50,000 bbVday of oil equivalent using a scaling component of 0.85. This size plant is consistent with the scale used for natural gas to methanol, oil shale conversion, and direct coal liquefaction. 3. Underground coal gasification: Schulman and Biasca (1989~. 4. Wood to methanol: Data from Reed and Graboski (1989~. Methanol production from biomass and municipal waste: Process Design and Economics, Syn-Gas, Inc., Golden, Colorado. 5. Natural gas to gasoline through Mobil's fluid bed MTG process: Data of Schulman and Biasca (1989) adjusted by the committee from 16,600 bbVday to a larger plant size of 50,000 bbVday of oil equivalent using a scaling exponent of 0.85. This size plant is consistent with the scale used for natural gas to methanol, oil shale conversion, and direct coal liquefaction. 6. Coal to methanol to gasoline via the Mobil MTC; process: Data of Schulman and Biasca (1989) modified. The size was scaled up from 16,600 bbl/day to 50,000 bbl/day, and capital investment was reduced 5 percent because of the fluid bed MTG design in comparison to the fixed bed design. 7. Shell middle distillate process: Schulman and Biasca (1989~. 8. Compressed natural gas: Schulman and Biasca (1989~. 9. Ethanol from corn: Schulman and Biasca (1989~. 10. Oil shale pyrolysis: Schulman and Biasca (1989~. 11. Tar sends pyrolysis: Schulman and Biasca(1989~. 12. Solvent extraction of tar sands: Estimates made by committee based on design and capital estimates by Bechtel, Inc., using bench-scale experimental data for the process basis. 13. Direct coal liquefaction: Estimates made by committee based on design and capital estimates by Bechtel, Inc., using recent data from the Wilsonville pilot plant. 14. Other technologies: Schulman end Biasca (1989~.