Transcript Slide 1

Modeling Energy Security and
Economic Sustainability Issues of
the U.S. Biofuel Industry
Rocío Uría-Martínez
Paul N. Leiby
Gbadebo Oladosu
30th USAEE Conference
Washington, DC. October 10, 2011
Research sponsored by the Laboratory Directed Research and Development Program
of Oak Ridge National Laboratory, managed by UT-Battelle, for the U.S. Department of Energy
OBJECTIVES
Abiding national objective
Central motivation for 2007
EISA legislation
How could future boom and bust
cycles in biofuel infrastructure
be avoided/mitigated?
Exploring energy security and economic sustainability implications of U.S.
biofuel industry configurations and policies using system analysis tools
Combinations of
-feedstocks
-logistics designs
-conversion technologies
-biofuel types
-…
Where in the supply chain is
support most needed?
Should it be taxes, subsidies,
mandates, loan guarantees?
Long-run optimization
&
Short-run simulations
ENERGY SECURITY
It is not just about displacing gasoline but also about creating reliable supply chains that are
resilient to market shocks
How correlated are ethanol and gasoline
prices?
For parity pricing on a gge basis,
Pethanol = 0.67* Pgasoline
WHOLESALE GASOLINE AND ETHANOL PRICES
4.00
CHARLOTTE (NC)
3.50
$/gallon
3.00
Crude Oil
Sugar
Wheat
Maize
Softwood
100%
Sugar
Wheat
1.50
Correlation coefficient = 71%
0.50
unleaded 87 octane gasoline
ethanol
Maize
Softwood
3%
5%
-1%
1%
100%
20%
10%
2%
100%
46%
-23%
100%
-10%
100%
Data: IMF/IFS database, Commodity Prices & Indices,
5/2/2011
4/2/2011
2/2/2011
3/2/2011
1/2/2011
12/2/2010
11/2/2010
9/2/2010
10/2/2010
8/2/2010
7/2/2010
6/2/2010
5/2/2010
4/2/2010
2/2/2010
3/2/2010
1/2/2010
12/2/2009
11/2/2009
0.00
Cross-Correlations of Monthly Commodity Price Changes,
1990-Jan to 2008-Dec
Crude Oil
2.00
1.00
Biofuels link agricultural and energy
commodities
1990+
2.50
U.S. Grain Ethanol Capacity vs. Gasoline Price
Sources: Renewable Fuels
Association, Official
Nebraska Government
Website
Capacity
Installed
ECONOMIC SUSTAINABILITY
Market volatility has been very challenging
for the developing biofuels industry
Gasoline
Price
Capacity
Under
Construction
Capacity
Idled
Ethanol Plant Operating Margins Volatile, and
Collapsed to Near Minimum Sustainable
Ethanol price
Line indicates minimum
sustainable returns
(“margin”) to Ethanol
Production Plant. Actual
returns highly variable.
Other Operating
Costs
Net corn
cost
Plant
“margin”
SYSTEM CONFIGURATION MATTERS FOR
ENERGY SECURITY AND ECONOMIC SUSTAINABILITY
Long Run
Vehicle
Choice
Conventional
Vehicles
E10
Diesel,
middle &
heavy cuts,
chemicals
Imported
Gasoline
FFVs
Short Run
FFV Fuel
Choice
Co-products
Gasoline
Blending
& Retail
Petroleum
Refineries
Light Heavy
Domestic Crude Oil
Ethanol
Imported
Ethanol
Biorefineries
Inventories
Imported
Crude Oil
E85
bales
uniform
format
Corn
Cellulosic
feedstocks
Inventories
INVENTORIES
BioTrans model accounts for two types of inventories:
Speculative inventoriesheld only when the market signals
arbitrage opportunities
Et ( P t 1 )  k  Pt  0 , S t  0
Working inventoriesheld for operational reasons
(typical stock-to-use ratio is 15%)
May/July futures carrying
charge in percent as of May
Et ( P t 1 )  k  Pt  0 , S t  0
End-of-cropyear US stocks of wheat as a function of
CBOT futures spreads
10
5
0
-5
0
50
100
150
200
250
300
350
-10
-15
-20
-25
million bushels
Net marginal cost of storage = marginal cost – convenience yield
Convenience 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?
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)
These 5-year
peak levels set
in 2006 & 2007
1,800,000
5-year Ave.
5-year Min.
1,500,000
Source: IAF Advisors, Feb. 4, 2009
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
Corn Stocks, Production and Consumption (quarterly/seasonal)
14,000
Beginning stocks
12,000
Production
Consumption
Million Bushels
10,000
8,000
6,000
4,000
2,000
0
2001
2002
2003
2004
2005
Source: USDA, ERS, Feedgrains database
2006
2007
2008
BIOMASS FEEDSTOCK LOGISTICS SYSTEM DESIGN
Uniform format Design
Conventional Design
Baled switchgrass
Baled switchgrass
FARM
Average
distance =
71 miles
Long Term Storage
Bales stacked along
edge of field
$5.36/dry ton
Transport
Bales on flatbed truck
$4.61/dry ton;
$0.12/dry ton-mile
Short Term Queue
Bales on asphalt pad
BIOREFINERY
(optimal size =
0.69 M dry tons)
FARM
Long Term Storage
Bales stacked along
edge of field
$4.7/dry ton
Average
distance =
10 miles
Transport
Bales on flatbed truck
$4.61/dry ton;
$0.12/dry ton-mile
Preprocessing
Single grind
$13.03/dry ton
DEPOT
Short Term Queue
Pellets in bins
Preprocessing
Single grind
$13.03/dry ton
Handling
Conveyors, dust control
$2.38/dry ton
Densification
Pelleting
$22.37/dry ton
Average
distance =
205 miles
BIOREFINERY
(optimal size =
6.38 M dry tons)
Transport
Pellets in train
$5.23/dry ton,
$0.027/dry ton-mile
Short Term Queue
Pellets in bins
Handling
Conveyors, dust control
$0.21/dry ton
Uniform format biomass
as a way of reducing risk
for biorefineries:
• by broadening
feedstock base
• by offering
homogeneous quality
FLEXIBLE BIOREFINERIES
Feedstocks
Ethanol conversion
processes
Co-products
corn
dry milling
DDGs
biochemical
carbon
fiber
stover
electricity
multifeedstock
biochemical
switchgrass
forest
residues
Biorefinery feedstock costs
Biorefinery revenue
multifeedstock
thermochemical
C
R
higher
alcohols
 ci * i * Z
P * *Q
i
j
j
j
i= feasible feedstock set
J=feasible output set
=feedstock i fraction
=output j fraction
Z= total input (dry tons)
Q=total output (gallons)
FLEXIBLE BIOREFINERIES
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0.7
0.6
50%
40%
30%
20%
10%
200905
200901
200809
200805
200801
200709
200705
200701
200609
200605
0%
Ethanol/Sugar Relative Value
60%
200601
Ethanol/Sugar Export Quantity
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 FUEL VEHICLES
Needed to increase consumption of ethanol beyond what can be absorbed in E10 blend
RFS2 Volumetric Requirements and Ethanol Demand Potential
50
45
Billion Gallons
40
RFS2 Conventional Biofuels
35
30
25
RFS2 Conventional Plus
Advanced Cellulosic Biofuel
20
RFS2 Conventional Plus Total
Advanced Biofuel
15
E10 Blendwall
10
FFV Max E100 use
5
0
 How much retail capacity is needed if RFS-2 advanced cellulosic biofuel objective
Is attained entirely/partially with ethanol?
How much would it cost to build that capacity?
APPROACH: BioTrans System Design is Novel, While
Building on Existing Capabilities
BLM
POLYSYS
Simulate bioenergy
crop production given
changes in policy,
economic, or resource
conditions
Modeling framework
developed at INL to simulate
bioenergy feedstock supply
logistics from the field to
biorefinery
BILT
TAFV, HyTrans
Biofuel supply chain
transportation and
optimization model
developed at ORNL
ORNL Dynamic market
optimization to balance
motor fuel supply to
demand
BioTrans-Long-Run Model
Petroleum Sector
Simple supply,
Refineries (ORNL-RYM,
NEMS runs)
Integrates 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)
BioTrans Stochastic Short-Run Simulations
Simulate monthly over 1 year (Python)
-Shocks from oil producer behavior, disruptions and accidents
-Shocks to yields from weather events: droughts, floods, pests
-Infrastructure reliability
Oil Security Metrics Model
Provide framework for quantifying and measuring energy and
economic security impacts
Other Measures of Sustainability
- Long run economic costs
- GHG Emission Coefficients (GREET)
- Water Use Coefficients
Electric Sector
External runs for
demand (NEMS,
ORCED)
BASECASE RESULTS: FEEDSTOCK SUPPLY MIX & COST
300
FEEDSTOCK VOLUMES USED IN
ETHANOL PRODUCTION
Balanced set of cellulosic feedstocks
is optimal at the national level although
there is regional specialization
200
perennials
corn stover
150
forest residue
corn
100
50
2.5
0
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
Cellulosic ethanol
cost is expected to be below
that of grain ethanol
for most pathways
COST PER GALLON OF ETHANOL
2
$/gallon
million dry tons
250
1.5
Conversion cost
1
Logistics cost
Feedstock cost
0.5
0
2015
2025
2015
2025
2015
2025
CRN.DRYMILL.D4 STV.BCHEM.D4 PER.TCHEM.ROC
BASECASE RESULTS: FEEDSTOCK LOGISTICS DESIGN
COSTS
The tradeoff between transportation costs and capital costs does not provide justification
to adopt uniform format design for biomass feedstocks
Number of new cellulosic biorefineries (2010-2030)
uniform format design:
203
conventional design:
260
Net present value
of costs associated
to production of grain
and cellulosic ethanol
(2010-2030)
Biorefinery conversion
cost
conventional
Biorefinery capital cost
uniform format
Storage cost
Transportation cost
Preprocessing cost
Feedstock cost
0
50
100
150
billion $
200
250
300
BASECASE RESULTS: STOCKS AND BIOREFINERY TYPES
Flexible biorefineries help minimize total system costs over the planning period
even though they are 20% more expensive to build
180
BIOREFINERY CAPITAL STOCK
160
million dry tons
140
120
DRY MILL
100
BCHEM
80
BCHEMFLEX
60
TCHEMFLEX
40
Supply availability for
multiple feedstocks
changes over time and
a flexible biorefinery
can adjust to those changes
20
0
30
20
CELLULOSIC BIOMASS INVENTORIES
15% stock-to-use ratio
unconstrained
15
10
5
0
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
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
million dry tons
25
BASECASE RESULTS: E85 RETAIL CAPACITY
Optimal station and pump share vary significantly from region to region
1.2
1
E85 STATION SHARE
0.9
1
E85 PUMP SHARE
0.8
0.7
0.8
0.6
D3
0.6
D4
0.4
ROC
D3
0.5
D4
0.4
ROC
0.3
0.2
0.2
0.1
0
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
0
1.2
E85 RETAIL LOAD FACTOR
Cost of E85 retail infrastructure is
heavily dependent on load factor
1
0.8
D3
0.6
D4
0.4
ROC
10-15 c/gallon for utilization factors
comparable to those of E10 pumps
0.2
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
0
Over $1/gallon for low utilization factors
SCENARIO: FEEDSTOCK PRICE SHOCK
Doubling the cost of corn and corn stover in years 2024 and 2025
million gallons
DRY MILL ACTIVITY LEVEL (Census Division 3)
7000
7000
6000
6000
5000
5000
4000
4000
3000
3000
2000
1000
FB1: flexible biochemical
available
FB0: flexible biochemical
not available
SU1: stock-to-use ratio >=15%
SU0: unconstrained stocks
2000
FB1SU1
FB1SU1_shock
FB0SU0
1000
FB0SU0_shock
0
0
2024 BIOFUEL PRODUCTION RELATIVE TO BASELINE
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
SCENARIO: FEEDSTOCK PRICE SHOCK
Feedstock price shock propagates to ethanol but not to the pump
3
ETHANOL PRICE AT BIOREFINERY GATE_ROC
2.6
2.8
2.4
2.6
2.2
2.4
2.2
2
2
1.8
1.8
2014
2012
2010
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2026
FB0SU0_shock
1
2010
1
FB0SU0
2024
1.2
2022
FB1SU1_shock
2020
1.2
2018
1.4
2016
FB1SU1
2030
51% increase in Pethanol (FB1SU1)
58% increase in Pethanol (FB0SU0)
1.6
1.4
2028
1.6
E10 PRICE AT
THE PUMP_ROC
4
4
3.8
3.8
3.6
3.6
3.4
3.4
3.2
3.2
3
3
2.8
2.8
2.6
2.6
2.8% increase in PE10 (FB1SU1)
3.1% increase in PE10 (FB0SU0)
2.4
FB1SU1
2.4
FB0SU0
2.2
FB1SU1_shock
2.2
FB0SU0_shock
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2030
2028
2026
2024
2022
2020
2018
2016
2014
2
2012
2
2010
$/gge
A 100% increase in supply costs
for corn and stover leads to:
3
2010
$/gallon
2.8
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:
Cost of coping with disruption without FB or SU:
$7.1 billion
$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 period
to 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)
FITTED CURVE FOR D4SB MODEL
Aggregated
to fitted
continuous
supply curve
Corn CD4 2010
4.4
Model Equilibrium
on Fitted Curve
4.2
$/bushel
POLYSYS DATA, e.g.
Census Division 4
4
3.8
3.6
Fitted
3.4
POLYSYS
3.2
3
0
2000
4000
6000
8000
million bushels
• Identify price level corresponding
to cumulative production in the
original data
Disaggregated
model solution
• Identify counties producing under
at model equilibrium for results
display and sustainability analysis
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 coproducts 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
Issue: Reliability - Variability of Biofuels Supply and Price
• 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?
OIL 3 SPOT PRICE INDEX
MAIZE US(GULF PORTS)
SUGAR CARIBBEAN (N.Y.)
WHEAT U.S.GULF PORTS
SOFTWOOD LOGS INDEX (UNITED STATES )
350
Cross-Correlations of Monthly Commodity Price Changes,
1990-Jan to 2008-Dec
300
2008M4
2006M1
2005M6
2004M1
2002M8
2001M3
1999M1
1998M5
1996M1
1995M7
1994M2
1992M9
1991M4
1989M1
1988M6
1987M1
1985M8
0
1984M3
Maize
1982M1
50
1981M5
Wheat
1979M1
100
1978M7
Sugar
1977M2
150
1975M9
Crude Oil
1974M4
200
1972M1
1990+
1971M6
250
1970M1
Price Index (Nominal, 1980-M1 = 100)
400
Softwood
Crude Oil
100%
Sugar
Wheat
Maize
Softwoo
d
3%
5%
-1%
1%
100%
20%
10%
2%
100%
46%
-23%
100%
-10%
100%
Data: IMF/IFS database, Commodity Prices & Indices, Monthly, 1970 to Dec 2008.
U.S. Census Regions and Divisions
1
9
8
4
3
2
ECONOMIC SUSTAINABILITY
5
6
7
Source: http://www.eia.doe.gov/emeu/reps/maps/us_census.html
E85 Retail Capacity Evolution
number of retail stations
number of pumps per station
estimated maximum throughput per pump
Fixed parameters
Options to increase E85 throughput
increase number of retail
stations offering E85
increase number of E85 pumps
in stations offering E85
Annualized cost of new E85
retail infrastructure
0.14
1.2
0.10
1
0.08
0.06
0.04
$15,000/dispenser
1.4
0.12
$/gallon
$102,000/underground
storage tank
$/gallon
Costs:
increase utilization factor
of existing E85 pumps
Annualized cost of new E85
retail infrastructure
0.8
for pump share=0.12
0.6
0.4
for 100% load factor
0.02
0.2
0.00
0
0
0.1
0.2
pump share
0.3
0.4
0.1
0.3
0.5
0.7
utilization factor
0.9
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:
Cellulosic Ethanol Production, Shock
7000
7000
6000
5000
4000
3000
2000
1000
0
biochemical-stover
biochemical-perennials
6000
biochemical-perennials
million gallons
biochemical-stover
5000
4000
3000
2000
2030
2028
2026
2024
2022
2020
2018
2016
2014
2010
2012
0
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
1000
2010
million gallons
Cellulosic Ethanol Production,Baseline
STOVER-DEDICATED BIOCHEMICAL CONVERSION PROCESSES:
7000
6000
5000
4000
3000
2000
1000
0
7000
6000
thermochemical-perennials
million gallons
biochemical-stover
Cellulosic Ethanol Production, Shock
biochemical-stover
thermochemical-perennials
5000
4000
3000
2000
0
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
1000
2010
million gallons
Cellulosic Ethanol Production, Baseline
INITIAL ILLUSTRATIVE MODEL RESULTS:
Biorefinery Flexibility Reduces Response Cost To Supply Shocks
Scenario:
Doubling in the cost of stover in 2020 and 2021
Scenario: Doubling in the cost of stover in 2020 and 2021
Production from
Price Path for Cellulosic Ethanol
Biochemical and
Therrmochemical
pathways, stover &
No feedstock
perennial grass
flexibility for
Complete feedstock
Biochemical
flexibility for
Biochemical
1.9
1.8
1.7
1.6
1.5
1.4
baseline-flexible biochemical
1.3
shock-flexible biochemical
1.2
baseline-inflexible biochemical
1.1
shock-inflexible biochemical
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
1
2010
$/gallon
Census Division 4.
FARM
MATERIAL BALANCE IN REGION R, PERIOD T
Q biomass,field,r,t
≥
Q biomass,collection,r,t
=
DEPOT
Q biomass,transport,r,t
QIN biomass,storage,r,t
QOUT biomass,storage,r,t
STORAGE/BLENDING
TERMINAL
BIOREFINERY
Q biomass,preprocessing,r,t
Q biomass,storage,r,t
Q biomass,other,r,t
formatted
Ycrop
Q formatted,preprocessing,r,t
Q formatted,transport,r,t
Q co-product,refining,r,t
co product
Y formatted
=
Q formatted,refining,r,t
biofuel
Yformatted
Q biofuel,refining,r,t
From
regions R’
M biofuel,transport,r,t
From petroleum
sector
Q biofuel,transport,r,t
X biofuel,transport,r,t
QIN biofuel,storage,r,t
Q gasoline,refined,r,t
Q biofuel,blending,r,t
=
QOUTbiofuel,storage,r,t
blend
Ybiofuel
PUMP
Q – quantity
QIN – flows into storage
QOUT – flows out of storage
X – exports
M – imports
YAB - yield of A per unit of B
Q blend,blending,r,t
Q blend,consumption,r,t
=
=
Q blend,distribution,r,t
Q blend,retail,r,t
Q biofuel,storage,r,t
BASECASE RESULTS: FEEDSTOCK SUPPLY
Marginal costs_stover
140
140
120
120
100
100
80
D3
60
D4
$/dry ton
$/dry ton
Marginal costs_corn
ROC
40
80
D3
60
D4
20
20
0
0
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
Marginal costs_perennials
Marginal costs_forest residues
140
140
120
120
100
100
80
D3
60
D4
ROC
40
20
$/dry ton
$/dry ton
ROC
40
80
D3
60
D4
ROC
40
20
0
0
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
LOGISTIC DESIGN
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
Optimal biorefinery size
(Thermochemical. Rest of the country. 2020)
Conventional logistic design  2.25 million dry tons
Pioneer logistic design  20 million dry tons
SWITCHGRASS.TCHMFLX.ROC_PIONEER
250
200
200
150
150
miles
250
100
100
50
0
0
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
50
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
miles
SWITCHGRASS.TCHMFLX.ROC_CONVENTIONAL
vintage
vintage