Cost Assessment of Cellulosic Ethanol Production and Distribution in the US William R Morrow W. Michael Griffin H. Scott Matthews

Cost Assessment of Cellulosic Ethanol Production and Distribution in the US

William R MorrowW. Michael GriffinH. Scott Matthews

Introduction Part I – Optimization Modeling

Modeling Estimation of Parameters

Part II – Optimization Solutions Scenarios Data Trends

Part III – Monetizing the Solutions Freight Rate Calculation Transportation Cost Estimations

Part IV – A Quick Comparison to Petroleum Economics Transportation

Part V – Global Biomass resources Part VI – Conclusions

Part I – Optimization Modeling (Modeling)

Estimate an Extended Corn Based Ethanol Scenario

Model domestic switchgrass energy crop (published data) as the feedstock for cellulosic ethanol production

Estimate transportation costs as domestic cellulosic ethanol production increases

Identify any capacity limitations for a switchgrass based cellulosic ethanol fuel economy

Modeling Goals


Distributes ethanol to MSAs Capable of large blend ratios Expands corn production as far as believable

& makes up remaining required ethanol with switchgrass based cellulosic ethanol

Only considers truck and rail and transport Uses freight rates derived from US Economic

Input Output data, and Commodity Flow Survey

Our Model

Part I – Optimization Modeling (Parameter Estimation)Gasoline Consumption

Top 271 Consuming MSA’s (76% of US Gasoline Consumption)

Part I – Optimization Modeling (Parameter Estimation)Gasoline To Ethanol ConsumptionCurrent (1997 Modeled year) Gasoline Consumption:

→130 Billion Gallons per yr

Fuel Energy Content:

Gasoline: → 120,000 BTU/Gal

Ethanol: → 86,100 BTU/Gal

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Part I – Optimization Modeling (Parameter Estimation)Expanded Corn Ethanol Plants

Current Corn Ethanol Production:→ 3 Billion GallonsExpanded Corn Ethanol Production→ 5 Billion Gallons

Part I – Optimization Modeling (Parameter Estimation)Ethanol by Feedstock

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Part I – Optimization Modeling (Parameter Estimation)

Based on ORECCL – Oak Ridge Energy Crop County Level Database Energy Crop Availability & Yield Production Costs & Land Rents Projects Energy Crop Farmgate Prices

Comprised of 305 “Regions” (Similar to ASD’s) Several counties grouped together (Total of 2,787

Counties) Similar Soil type, moisture, sunlight, terrain, etc.

Estimates Switchgrass: Tons/per year for each region Based on $/ton farmgate prices (e.g. 30$/ton, 35$/ton, etc.)

Switchgrass Availability Modeling

using ORNL POLYSIS Model (published Data)


Switchgrass availability (Acreage as a function of $/ton)

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E85 Estimates

E20 Estimates

Estimated Range:•Upper Bound:

•5 Tons / Acre•85 Gallons / Ton

•Lower Bound:•10 Tons / Acre•100 Gallons / Ton

Part I – Optimization Modeling (Parameter Estimation)Transforming Switchgrass into

Ethanol Gallons

Minimum plant size of 2,200 Ton SWG/day based on the work of Wooley et al. (1999, 1999a)

85 Gallons / Ton SWG (from range of 68 ~ 100 Gallons / Ton SWG) based on the work of Wooley et al. (1999, 1999a)

Question: Can a POLYSIS Region produce enough SWG to support the minimum plant requirement? At what price ($ / Ton SWG)?


Plant Size as a Function of Cost (For Corn Stover)

Source: Lignocellulosic Biomass to Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis for Corn Stover – Aden et. al. 2002


% Usable Switchgrass (as a function of $/ton)

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Part I – Optimization Modeling (Parameter Estimation)Switchgrass Availability (50 $/Ton

SWG)

Part II – Optimization Solutions (Scenarios)

Linear Optimization Scenarios E5 Scenario – 5.2 Billion Gallon Ethanol

Expanded corn-based ethanol production – 5.2 BGY No switchgrass-based cellulosic ethanol production – 0

BGY E10 Scenario – 10.6 Billion Gallon Ethanol

Expanded corn-based ethanol production – 5.2 BGY Switchgrass-based cellulosic ethanol production – 5.4

BGY (30$/ton SWG) E20 Scenario – 22.1 Billion Gallon Ethanol

Expanded corn-based ethanol production – 5.2 BGY Switchgrass-based cellulosic ethanol production – 16.9

BGY (50$/ton SWG)


Forecasted E20 Scenario (50 $/ Ton SWG)


1 1

Objective Function: Minimize: n m

ij iji j

V D

Import demanded by location (Gallons)

Export available from location (Gallons)

$ Freight Rate between locations & ;

Distance between Locations & (Miles)

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Volume of ethanol transported between locations & (Gallons)i j

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V I

Linear Optimization Equations

Variables:

Constraints: Economic Eq.: ( )$ ij ij ij ijR V D


Optimization Solutions Scatter Plot

E20 Scenario

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Part II – Optimization Solutions (Trends)

Optimization SolutionsHistograms

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Trend toward shorter shipments as production expands

Part III – Monetizing the Solutions (Freight Rate Estimation)Freight Rate Dilemma

Problem: Freight industry does not publishes freight rates directly

Solution: Use US Government data sources and extrapolate freight rates

Data sources: US Department of Commerce; Bureau of

Economic Analysis – Input ~ Output Accounts US Department of Transportation; Commodity

Flow Survey

Part III – Monetizing the Solutions (Freight Rate Estimation)Freight Rate Estimation Method EIO Accounts:

Use of Commodities by Industry 1997 – Total Commodity Output. IO Code 482000 – Truck Transportation IO Code 244000 – Rail Transportation

CFS Database: Shipment by Destination and Mode of Transport

1997 Truck Rail

US State to State Distance matrix

Part III – Monetizing the Solutions (Freight Rate Estimation)

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Ton Mile

Freight Rate Equations & Data

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Part III – Monetizing the Solutions (Freight Rate Estimation)

Freight Rate: f (Distance)

Truck = 0.2146 $ / Ton-Mile

Rail = 0.0721 $/ Ton-Mile

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Truck – 26.6 ¢/Ton-Mile (2001) 21.5 ¢/Ton-Mile Class I Rail – 02.2 ¢/Ton-Mile (2001) 07.2 ¢/Ton-Mile

Part III – Monetizing the Solutions (Trans. Cost Estimations)Monetized Optimization Solutions

Transportation Cost ($/yr)

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Transportation Cost ($/Gallon)

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Legend

Truck Freight Rates

Rail Freight Rates

Part IV – Quick Comparison to Gasoline

Economics

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Taxes

Retail

Transportation (toretail)

Refining

Transportation (torefinery)

Feedstock(Gasoline/Biomass)

Source: Aden et. al. 2002Based on Energy Equivalency


Transportation By Mode

Pipelines

Water Carriers

Trucks Rail

Petroleum EthanolTruck

Rail


Petroleum Plant LocationsGeographical Dispersion


Petroleum Pipeline LocationsGeographical Dispersion


Petroleum & E20 Ethanol Locations

Geographical Dispersion


Can not ship ethanol in petroleum pipelines Location of ethanol production is more widely

distributed than refineries locations Ethanol produced at an ethanol plants is small when

compared to gasoline production at refineries CONCLUSION: Ethanol will require its own pipeline

infrastructure Dual fuel economy Build ethanol pipelines for E5, E10, E20, E85, E100?

Ethanol Pipeline Challenges

Part V – Global Biomass Production

Raw Biomass Energy Potential Year 2050 → 440 joules 18 per year Year 2100 → 310 joules 18 per year

Converted to Liquid biofuels (@ 35% efficiency – EIA) Year 2050 → 154 joules 18 per year Year 2100 → 109 joules 18 per year

Converted to Gallons of Gasoline Equivilent Year 2050 → 785 Gallons 9 per year Year 2100 → 555 Gallons 9 per year

Gasoline Consumption (OECD Countries) - EIA ~ 300 Gallons 9 per year

Estimates from IPCC 3rd Assessment Report

Part VI – Conclusions Higher production – higher plant dispersion –

shorter distance – lower transport cost Comparison to gasoline costs

Ethanol Not likely be cheaper to transport in Short Term Domestic Switchgrass Ethanol Limitations

E20 our upper bound for modeling Oak Ridge Data (only goes to 50$/ton) Displaces approximately 20% of existing agricultural products

Additional Biomass is available in the US & Internationally

Documents

Cost Assessment of Cellulosic Ethanol Production and Distribution in the US William R Morrow W. Michael Griffin H. Scott Matthews