General Lecture 1. Modeling and Sustainability CE5504 Surface Water Quality Modeling.
Modeling Energy Security and Economic Sustainability Issues of the U.S. Biofuel Industry
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Transcript of Modeling Energy Security and Economic Sustainability Issues of the U.S. Biofuel Industry
Modeling Energy Security and Economic Sustainability Issues of the U.S. Biofuel Industry
Rocío Uría-MartínezPaul N. Leiby
Gbadebo Oladosu30th USAEE Conference
Washington, DC. October 10, 2011
Research sponsored by the Laboratory Directed Research and Development Programof Oak Ridge National Laboratory, managed by UT-Battelle, for the U.S. Department of Energy
OBJECTIVES
Exploring energy security and economic sustainability implications of U.S. biofuel industry configurations and policies using system analysis tools
Abiding national objectiveCentral motivation for 2007
EISA legislation
How could future boom and bust cycles in biofuel infrastructure
be avoided/mitigated?
Long-run optimization &
Short-run simulations
Where in the supply chain issupport most needed?Should it be taxes, subsidies, mandates, loan guarantees?
Combinations of-feedstocks-logistics designs-conversion technologies-biofuel types-…
ENERGY SECURITY
How correlated are ethanol and gasoline prices? For parity pricing on a gge basis,
Pethanol = 0.67* Pgasoline
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unleaded 87 octane gasoline ethanol
WHOLESALE GASOLINE AND ETHANOL PRICESCHARLOTTE (NC)
It is not just about displacing gasoline but also about creating reliable supply chains that are resilient to market shocks
Cross-Correlations of Monthly Commodity Price Changes, 1990-Jan to 2008-Dec
1990+ Crude Oil Sugar Wheat Maize Softwood
Crude Oil 100% 3% 5% -1% 1%
Sugar 100% 20% 10% 2%
Wheat 100% 46% -23%
Maize 100% -10%
Softwood 100%
Biofuels link agricultural and energy commodities
Correlation coefficient = 71%
Data: IMF/IFS database, Commodity Prices & Indices,
Ethanol Plant Operating Margins Volatile, and Collapsed to Near Minimum Sustainable
Sources: Renewable Fuels Association, Official Nebraska Government Website
Net corn cost
Other Operating Costs
Gasoline Price
Capacity Installed
Capacity Idled
Capacity Under Construction
U.S. Grain Ethanol Capacity vs. Gasoline Price
Plant “margin”
Ethanol price
Line indicates minimum sustainable returns (“margin”) to Ethanol Production Plant. Actual returns highly variable.
ECONOMIC SUSTAINABILITY
Market volatility has been very challengingfor the developing biofuels industry
Diesel, middle & heavy cuts, chemicals
Imported Ethanol
Petroleum Refineries
Imported Crude Oil
Domestic Crude Oil
Gasoline
Conventional Vehicles
Light Heavy
Imported Gasoline Biorefineries
Long Run Vehicle Choice
Co-products
Short Run FFV Fuel
Choice
FFVs
Ethanol
E85
Blending & Retail
Inventories
CornCellulosicfeedstocks
Inventories
E10
balesuniformformat
SYSTEM CONFIGURATION MATTERS FOR ENERGY SECURITY AND ECONOMIC SUSTAINABILITY
BioTrans model accounts for two types of inventories:
INVENTORIES
Speculative inventories- held only when the market signals arbitrage opportunities
Working inventories- held for operational reasons(typical stock-to-use ratio is 15%)
0 , 0)(0 , 0)(
1
1
tttt
tttt
SPkPESPkPE
Net marginal cost of storage = marginal cost – convenience yieldConvenience yield is the benefit from holding a physical commodity
Will biomass/ethanol speculative inventories keep probability of stockout sufficiently low?Is 15% a reasonable stock-to-use ratio for biomass feedstocks and/or ethanol?
End-of-cropyear US stocks of wheat as a function of CBOT futures spreads
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million bushels
May
/Jul
y fu
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s ca
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ge in
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cent
as
of M
ay
U.S. Petroleum Stock Variation 2005-2009 (Including SPR): - Typical within-year stock variation: 6% (9% excl SPR).
- Max variation over 5 years: 22%.- Stocks are ~16% of annual demand (~25% incl SPR)
Source: IAF Advisors, Feb. 4, 2009
These 5-year peak levels set in 2006 & 2007
5-year Ave.
5-year Min.
1,500,000
1,800,000
Corn production, and stocks fluctuate widely, (seasonally, and year to year), far more than oil
- Typical within-year stock variation of 4X (400%).- Year-to-year peak variation over 5 years: 33%.
- Stocks are ~80% of annual demand
Source: USDA, ERS, Feedgrains database
Corn Stocks, Production and Consumption (quarterly/seasonal)
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ion
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hels
Beginning stocks
Production
Consumption
Long Term StorageBales stacked along
edge of field$5.36/dry ton
TransportBales on flatbed truck
$4.61/dry ton; $0.12/dry ton-mile
Conventional Design
Long Term StorageBales stacked along
edge of field$4.7/dry ton
TransportBales on flatbed truck
$4.61/dry ton; $0.12/dry ton-mile
PreprocessingSingle grind
$13.03/dry ton
HandlingConveyors, dust control
$0.21/dry ton
DensificationPelleting
$22.37/dry ton
TransportPellets in train$5.23/dry ton,
$0.027/dry ton-mile
Short Term QueuePellets in bins
FARM
BIOREFINERY(optimal size = 0.69 M dry tons)
FARM
DEPOT
Baled switchgrass
Uniform format Design
Baled switchgrass
PreprocessingSingle grind
$13.03/dry ton
HandlingConveyors, dust control
$2.38/dry ton
Short Term QueueBales on asphalt pad
Short Term QueuePellets in binsBIOREFINERY
(optimal size = 6.38 M dry tons)
Averagedistance =10 miles
Averagedistance =71 miles
Averagedistance =205 miles
BIOMASS FEEDSTOCK LOGISTICS SYSTEM DESIGNUniform format biomass as a way of reducing risk for biorefineries:• by broadening
feedstock base• by offering
homogeneous quality
FLEXIBLE BIOREFINERIES
Feedstocks Ethanol conversionprocesses
Co-products
corn
stover
switchgrass
forest residues
dry milling
biochemical
multifeedstockbiochemical
multifeedstockthermochemical
DDGs
electricity
higher alcohols
carbon fiber
Biorefinery feedstock costs i
ii ZcC **
j
jj QPR **Biorefinery revenue
i= feasible feedstock setJ=feasible output set=feedstock i fraction=output j fractionZ= total input (dry tons)Q=total output (gallons)
0.60.70.80.91.01.11.21.31.4
0%
10%
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60%
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01
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2009
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Etha
nol/
Suga
r Re
lativ
e Va
lue
Etha
nol/
Suga
r Ex
port
Qua
ntity
Fraction of sugarcane used for ethanol versus relative export revenues (2006:M1 - 2009:M8)
"percent of cane used for ethanol"
relative export value: ethanol/sugar
Brazilian sugarcane mills allow for changes in biorefinery product mix in response to relative product value
FLEXIBLE BIOREFINERIES
FLEXIBLE FUEL VEHICLES
How much retail capacity is needed if RFS-2 advanced cellulosic biofuel objectiveIs attained entirely/partially with ethanol?How much would it cost to build that capacity?
20092011
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20172019
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RFS2 Volumetric Requirements and Ethanol Demand Potential
RFS2 Conventional BiofuelsRFS2 Conventional Plus Advanced Cellulosic BiofuelRFS2 Conventional Plus Total Advanced BiofuelE10 BlendwallFFV Max E100 use
Billi
on G
allo
ns
Needed to increase consumption of ethanol beyond what can be absorbed in E10 blend
BioTrans Stochastic Short-Run SimulationsSimulate monthly over 1 year (Python) -Shocks from oil producer behavior, disruptions and accidents-Shocks to yields from weather events: droughts, floods, pests-Infrastructure reliability
APPROACH: BioTrans System Design is Novel, While Building on Existing Capabilities
POLYSYSSimulate bioenergy crop production given changes in policy, economic, or resource conditions
BLMModeling framework developed at INL to simulate bioenergy feedstock supply logistics from the field to biorefinery
TAFV, HyTrans ORNL Dynamic market optimization to balance
motor fuel supply to demand
Oil Security Metrics ModelProvide framework for quantifying and measuring energy and economic security impacts
BILTBiofuel supply chain transportation and optimization model developed at ORNL
Other Measures of Sustainability- Long run economic costs- GHG Emission Coefficients (GREET)- Water Use Coefficients
BioTrans-Long-Run ModelIntegrates summary representations from each of above- Dynamic Optimization by GAMS- Annual, 20 years- 9 Census Divisions- Multiple sectors- Balances markets and determines fixed capital (biorefineries, retail capacity)
Petroleum SectorSimple supply, Refineries (ORNL-RYM, NEMS runs)
Electric SectorExternal runs for demand (NEMS, ORCED)
2015
2025
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CRN.DRYMILL.D4 STV.BCHEM.D4 PER.TCHEM.ROC
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Conversion costLogistics costFeedstock cost$/
gallo
n
FEEDSTOCK VOLUMES USED INETHANOL PRODUCTION
BASECASE RESULTS: FEEDSTOCK SUPPLY MIX & COST
COST PER GALLON OF ETHANOL
Balanced set of cellulosic feedstocksis optimal at the national level althoughthere is regional specialization
Cellulosic ethanolcost is expected to be below that of grain ethanolfor most pathways
20102012
20142016
20182020
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20300
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perennialscorn stoverforest residuecorn
mill
ion
dry
tons
BASECASE RESULTS: FEEDSTOCK LOGISTICS DESIGN COSTS
Feedstock cost
Preprocessing cost
Transportation cost
Storage cost
Biorefinery capital cost
Biorefinery conversion cost
0 50 100 150 200 250 300
conventional
uniform format
billion $
Number of new cellulosic biorefineries (2010-2030)uniform format design: 203conventional design: 260
The tradeoff between transportation costs and capital costs does not provide justificationto adopt uniform format design for biomass feedstocks
Net present valueof costs associatedto production of grainand cellulosic ethanol(2010-2030)
20102011
20122013
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20202021
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20300
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15% stock-to-use ratiounconstrained
mill
ion
dry
tons
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DRY MILLBCHEMBCHEMFLEXTCHEMFLEX
mill
ion
dry
tons
Flexible biorefineries help minimize total system costs over the planning periodeven though they are 20% more expensive to build
Supply availability for multiple feedstocks changes over time anda flexible biorefinery can adjust to those changes
BASECASE RESULTS: STOCKS AND BIOREFINERY TYPES
On the other hand, the model only chooses to keep speculative stocks.Working stock costs do not meet a counterbalancing benefit under perfect foresight conditions
BIOREFINERY CAPITAL STOCK
CELLULOSIC BIOMASS INVENTORIES
Cost of E85 retail infrastructure is heavily dependent on load factor
10-15 c/gallon for utilization factorscomparable to those of E10 pumps
Over $1/gallon for low utilization factors
BASECASE RESULTS: E85 RETAIL CAPACITY
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E85 STATION SHARE
E85 RETAIL LOAD FACTOR
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E85 PUMP SHARE
Optimal station and pump share vary significantly from region to region
SCENARIO: FEEDSTOCK PRICE SHOCK Doubling the cost of corn and corn stover in years 2024 and 2025
DRY MILL ACTIVITY LEVEL (Census Division 3)
FB1SU1_shock FB0SU0_shock
Census Division 3 0.16 0.58
Census Division 4 1.09 1.08
Rest of the country 1.05 0.99
Total 0.96 0.96
2024 BIOFUEL PRODUCTION RELATIVE TO BASELINE2010
20122014
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FB1SU1 FB1SU1_shock
mill
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ns
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FB0SU0 FB0SU0_shock
FB1: flexible biochemical availableFB0: flexible biochemical not availableSU1: stock-to-use ratio >=15%SU0: unconstrained stocks
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$/gg
e
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$/ga
llon
ETHANOL PRICE AT BIOREFINERY GATE_ROC
E10 PRICE AT THE PUMP_ROC
Feedstock price shock propagates to ethanol but not to the pump
SCENARIO: FEEDSTOCK PRICE SHOCK
A 100% increase in supply costsfor corn and stover leads to:
51% increase in Pethanol (FB1SU1)58% increase in Pethanol (FB0SU0)
2.8% increase in PE10 (FB1SU1)3.1% increase in PE10 (FB0SU0)
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11.21.41.61.8
22.22.42.62.8
3
FB0SU0FB0SU0_shock
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FB0SU0FB0SU0_shock
SCENARIO: FEEDSTOCK PRICE SHOCK
Total NPV of costs and savings from flexible biochemical biorefineries (FB)and 15% stock-to-use ratio (SU) (2010-2030)
Cost of adding FB and SU to the system: $14.2 billion
Cost of coping with disruption with FB and SU: $7.1 billionCost of coping with disruption without FB or SU: $13.4 billion
Net savings from FB and SU: $6.3 billion
We would need 2.2 shocks of this magnitude over a 20-year periodto make the flexibility investment worthwhile
Even though the system as a whole experiences savings, some supply chain participants(dry mill owners) are actually made worse off by the extra flexibility
FINAL REMARKS
Biofuels are an important piece of the puzzle in the quest for alternative fuels that would reduce U.S. dependence on petroleum
However, we should think more rigorously about how energy security is obtained, and how the biofuel supply chain itself can improve resilience.
Demand flexibility is currently limited by the “blend wall”: E10 blends cannot absorb ethanol volumes much beyond current production levels
With diverse feedstocks and technologies, a major supply/price shock for a single feedstock may have only a modest effect on retail prices of fuel blends, but could have pronounced effects on the profitability of biorefineries
Flexibility elements (inventories, FFVs, flexible biorefineries, biomass preprocessing)reduce price variance but increase average price
SUPPLEMENTARY SLIDES
Approach Effectively Aggregating and Disaggregating Across Different Scales (E.g. for Feedstock Supply Data)
Corn CD4 2010
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3.2
3.4
3.6
3.8
4
4.2
4.4
0 2000 4000 6000 8000
million bushels
$/bu
shel
Fitted POLYSYS
POLYSYS DATA, e.g. Census Division 4
Aggregated to fitted continuous supply curve
FITTED CURVE FOR D4SB MODEL
Model Equilibrium on Fitted Curve
• Identify price level corresponding to cumulative production in the original data
• Identify counties producing under at model equilibrium for results display and sustainability analysis
Disaggregated model solution
Progress: State of development of LR model• V0.9 Implementation
– Complete analytical specification of LR Model, Multi-stage pathways, field to gas-tank
– Long-run, nonlinear dynamic model, 2010-2030– Depicts 7 stages in the feedstock’s path from farm to biorefinery– Census Division based (testing with regions 3 and 4, Rest-of-Country)– Four feedstocks (corn, stover, perennial grasses; forest), twenty annual
periods (2010-2030) and five conversion processes– “Working” stocks representation– Biorefinery technology choice
• Biochemical vs. thermochemical pathways• Initial representation flexible biorefineries (flex thermo, flex or ded
biochem)• Co-products
– Allows tracking economic sustainability (based on ethanol price, and co-products and key input prices) and environmental sustainability (e.g., GHG and water footprint) issues.
– Coupled to basic model of demand markets, vehicle and fuel choice
Data: IMF/IFS database, Commodity Prices & Indices, Monthly, 1970 to Dec 2008.
Issue: Reliability - Variability of Biofuels Supply and Price
0
50
100
150
200
250
300
350
400
1970
M1
1971
M6
1972
M1
1974
M4
1975
M9
1977
M2
1978
M7
1979
M1
1981
M5
1982
M1
1984
M3
1985
M8
1987
M1
1988
M6
1989
M1
1991
M4
1992
M9
1994
M2
1995
M7
1996
M1
1998
M5
1999
M1
2001
M3
2002
M8
2004
M1
2005
M6
2006
M1
2008
M4
Pric
e In
dex
(Nom
inal
, 198
0-M
1 =
100)
OIL 3 SPOT PRICE INDEXMAIZE US(GULF PORTS)SUGAR CARIBBEAN (N.Y.)WHEAT U.S.GULF PORTSSOFTWOOD LOGS INDEX (UNITED STATES )
Cross-Correlations of Monthly Commodity Price Changes, 1990-Jan to 2008-Dec
1990+Crude
Oil Sugar Wheat MaizeSoftwoo
d
Crude Oil 100% 3% 5% -1% 1%
Sugar 100% 20% 10% 2%
Wheat 100% 46% -23%
Maize 100% -10%
Softwood 100%
• Gasoline/diesel and biofuels are subject to different long-run forces, and different supply/demand shocks; but are also linked
• Q: How do gasoline and ethanol prices move in relations to one another, • at different points in supply chain (plant-gate to retail)?• over the long run and short run?
• Q: What does this imply for diversification benefits of alternative fuels?
U.S. Census Regions and Divisions
Source: http://www.eia.doe.gov/emeu/reps/maps/us_census.html
1
9 8 4 3 2
5 6 7
ECONOMIC SUSTAINABILITYECONOMIC SUSTAINABILITY
0.1 0.2 0.3 0.4 0.5
0.600000000000001
0.700000000000001 0.8 0.9 10
0.20.40.60.8
11.21.4
utilization factor
$/ga
llon
number of retail stationsnumber of pumps per stationestimated maximum throughput per pump
Options to increase E85 throughput
increase number of E85 pumps in stations offering E85
increase number of retail stations offering E85
increase utilization factor of existing E85 pumps
Fixed parameters
for 100% load factor
for pump share=0.12
Costs:
$102,000/underground storage tank
$15,000/dispenser
E85 Retail Capacity Evolution
0.1 0.2 0.3 0.40.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
pump share
$/ga
llon
Annualized cost of new E85 retail infrastructure
Annualized cost of new E85 retail infrastructure
INITIAL ILLUSTRATIVE D4SB MODEL RESULTS: Biorefinery Flexibility Reduces Response Cost To Supply Shocks
Scenario: Doubling in the cost of stover in 2020 and 2021
FLEXIBLE BIOCHEMICAL AND THERMOCHEMICAL CONVERSION PROCESSES:
2010
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01000200030004000500060007000
Cellulosic Ethanol Production,Baseline
biochemical-stover biochemical-perennials
mill
ion
gallo
ns
STOVER-DEDICATED BIOCHEMICAL CONVERSION PROCESSES:
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01000200030004000500060007000
Cellulosic Ethanol Production, Baseline
biochemical-stover thermochemical-perennials
mill
ion
gallo
ns
2010
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0
1000
2000
3000
4000
5000
6000
7000Cellulosic Ethanol Production, Shock
biochemical-stover thermochemical-perennialsm
illio
n ga
llons
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2011
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2013
2014
2015
2016
2017
2018
2019
2020
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0
1000
2000
3000
4000
5000
6000
7000Cellulosic Ethanol Production, Shock
biochemical-stoverbiochemical-perennials
mill
ion
gallo
ns
INITIAL ILLUSTRATIVE MODEL RESULTS: Biorefinery Flexibility Reduces Response Cost To Supply Shocks
Scenario: Doubling in the cost of stover in 2020 and 2021
2010
2011
2012
2013
2014
2015
2016
2017
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1
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1.8
1.9
Price Path for Cellulosic Ethanol
baseline-flexible biochemical
shock-flexible biochemical
baseline-inflexible biochemical
shock-inflexible biochemical
$/ga
llon
Scenario: Doubling in the cost of stover in 2020 and 2021 Census Division 4.
Production from Biochemical and Therrmochemical pathways, stover & perennial grass
No feedstock flexibility for Biochemical Complete feedstock
flexibility for Biochemical
Q biomass,field,r,t Q biomass,collection,r,t
Q biomass,transport,r,t QIN biomass,storage,r,t
QOUT biomass,storage,r,t Q biomass,storage,r,t
Q biomass,preprocessing,r,t Q biomass,other,r,t
Q formatted,preprocessing,r,t
Q formatted,refining,r,t
Q biofuel,refining,r,t
X biofuel,transport,r,tQ biofuel,transport,r,tM biofuel,transport,r,t
QIN biofuel,storage,r,t
Q biofuel,storage,r,tQOUTbiofuel,storage,r,tQ gasoline,refined,r,t Q biofuel,blending,r,t
Q blend,blending,r,t Q blend,distribution,r,t
Q blend,retail,r,tQ blend,consumption,r,t
formattedcropY
blendbiofuelY
MATERIAL BALANCE IN REGION R, PERIOD TFA
RMDE
POT
BIO
REFI
NER
YST
ORA
GE/B
LEN
DIN
GTE
RMIN
ALPU
MP
≥
=
=
=
=
Q – quantity QIN – flows into storageQOUT – flows out of storage X – exports M – imports YA
B - yield of A per unit of B
=From regions R’
From petroleum sector
biofuelformattedY
Q co-product,refining,r,tproductcoformattedY
Q formatted,transport,r,t
BASECASE RESULTS: FEEDSTOCK SUPPLY
0
20
40
60
80
100
120
140
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
$/dr
y ton
Marginal costs_corn
D3
D4
ROC
0
20
40
60
80
100
120
140
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
$/dr
y ton
Marginal costs_perennials
D3
D4
ROC
0
20
40
60
80
100
120
140
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
$/dr
y ton
Marginal costs_stover
D3
D4
ROC
0
20
40
60
80
100
120
140
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
$/dr
y ton
Marginal costs_forest residues
D3
D4
ROC
UNIFORM LOGISTIC DESIGN as a way of reducing risk for biorefineries:a) by broadening feedstock base so that a given biorefinery will not be captive of local supply b) by offering a more homogeneous quality that minimizes process adjustment costs
LOGISTIC DESIGN
20092011
20132015
20172019
20212023
20252027
20290
50
100
150
200
250
SWITCHGRASS.TCHMFLX.ROC_CONVENTIONAL
vintage
mile
s
20092011
20132015
20172019
20212023
20252027
20290
50
100
150
200
250
SWITCHGRASS.TCHMFLX.ROC_PIONEER
vintage
mile
s
Optimal biorefinery size(Thermochemical. Rest of the country. 2020)
Conventional logistic design 2.25 million dry tons Pioneer logistic design 20 million dry tons