case simulation and users q&a
TRANSCRIPT
Case Simulation and Users Q&A: Petroleum, Ethanol, Pyrolysis and Plug-in Hybrid
Electric Vehicles
Jeongwoo Han, Amgad Elgowainy
and Jennifer Dunn
Systems Assessment Group
Center for Transportation Research
Argonne National Laboratory
The GREET Training Workshop
Argonne National Laboratory
December 7-8, 2011
Color Scheme for the GREET Model
Clear cells are primarily for calculations and secondary assumptions
Yellow cells are key input assumptions that users can change for their own simulations
Peach cells are key options that users can select for their own simulations from drop-down menu
Green cells are key input assumptions with probability distribution functions built in
Blue cells are GREET forecast cells for running stochastic simulations
Gray cells are placeholder pathways
2
What not to do
Change values in white cells unless you know well enough
Change values in yellow cells of any time series tables and recalculate (pressing F9)
Open GREET with another Excel file
– Especially from one whose calculation setting does not look like …
3
Outline
Petroleum
Pyrolysis
Plug-in Hybrid Electric Vehicles
Ethanol
4
Available at http://pubs.acs.org/doi/abs/10.1021/es201942m
and http://greet.es.anl.gov/publications
Supporting Document: Journal Article and Technical
Memo
System Boundary of Petroleum Pathways
6
Well Drilling
Crude Oil Recovery
Crude Refining
Fuel T&D
Crude Transport
Fuel Combustion
in Vehicle
Energy and emissions calculated in GREET2
Inputs
Fuel_Prod_TS Petroleum
Fuel_Prod_TS Petroleum
Car_TS LDT1_TS LDT2_TS
Oil Sand Recovery (Surface)
Oil Sand Recovery (In-Situ)
Bitumen Upgrading
Bitumen Upgrading
Updated Crude Refining Model
7
1. Combustion emissions (e.g., engines, boilers,
turbines, etc.)
2. Non-combustion emissions (e.g., SMR, GTL, etc.)
3. Other emissions (from internally produced fuels)
Combustion Process Fuel 1
Chemical
Conversion
Process Fuel 2
internally
produced fuel
Main
Product
Oil Sand-based gasoline and diesel generate 15%
more GHG emissions than conv. crude-based ones
8
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Co
nve
nti
on
al C
rud
e
Oil
San
d
U.S
. Ave
rage
Co
nve
nti
on
al C
rud
e
Oil
San
d
U.S
. Ave
rage
Gasoline LSD
g CO
2e/g
gePTW
WTP
Demo
Change efficiencies in the Fuel_Prod_TS tab
– Crude recovery efficiency
– Oil sands recovery and upgrading efficiencies (in-situ and surface mining)
– H2 use for upgrading oil sands (in-situ and surface mining)
– Share of surface mining process in oil sands recovery
– Share of oil sands products in crude oil blend
CO2 emissions for crude recovery in the Petroleum tab
Non-combustion CH4 Emissions are defined in the Petroleum tab
PTW assumptions can be found in the Car_TS, LDT1_TS or LDT2_TS tabs
WTW Results can be found in the Results tab
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Outline
Petroleum
Pyrolysis
Plug-in Hybrid Electric Vehicles
Ethanol
10
Available at http://greet.es.anl.gov/publications
Supporting Document: WTW Analysis Report
Pyrolysis Process Description
12
Pyrolysis
Hydrotreating 1) Integrated Bio-refinery
Bio-char Fuel Gas Steam
Pyrolysis Oil Recovery
Cyclone
Pyrolysis Oil
Pyrolysis Oil Reforming
External NG
External H2
Fuel Gas/NG Reforming
H2 ① ②
③
Transport
2) Distributed Bio-refinery
3) Petroleum Refinery
System Boundary of Pyrolysis-based Fuel Pathways
13
Fertilizer Production
Corn Stover Collection &
Transportation
Gasoline/ Diesel T&D
Vehicle Operation
Forest Residue Collection &
Transportation
Pyrolysis, Hydrotreating & Refining
Bio-char
Steam Fuel Gas
Power Generation
Electricity
Conventional
Electricity
Generation
Conventional LPG
Production
Conventional
Steam Production
Conventional
Fertilizer
Production
Soil Application
Reduced Fertilizer C Sequestration
Ag_Inputs EtOH
EtOH
Pyrolysis
GHG emissions reduce with lower yield, biogenic
H2 and bio-char applied to soil
14
High yield process based on PNNL study with forest residue Low yield process based on ISU study with corn stover
Higher yield increases petroleum savings
15
0
2
4
6
8
10
12
14
Petr
oleu
m S
avin
g (m
mB
tu/t
on ) Low Yield High Yield
Biochar Elec.Generation Biochar Sequestration
Demo
Key input parameters (biomass use, process energy inputs and shares and product slates) for each scenario in Section 10 of the Inputs tab
Methods for dealing with co-products in Section 2 of the Pyrolysis tab
– Steam use
– Effects of biochar applied to soil
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Outline
Petroleum
Pyrolysis
Plug-in Hybrid Electric Vehicles
Ethanol
17
PHEVs WTW Pathway
Upstream
Oil
1%
Gas
20%
Coal
47%
Nuclear
21%
Renewable
11%
18
PHEV
Electricity
Emissions
Crude
Recovery Crude
Transportation Fuel
Transportation
Crude
Refining
Gasoline
19 19 19
Key Issues for WTW of PHEVs
PHEV performance evaluation
Fuel economy by vehicle design (e.g., power-split or series design)
Vehicle electric range (ER) in charge depletion (CD) mode
On-road adjusted fuel economy and electricity consumption for each mode of operation (i.e., Charge Depletion [CD] and Charge Sustaining [CS])
On-road adjusted electric range (ER)
PHEV mileage shares by power source
Determined VMT shares by grid power and on-board power
Electricity generation mix to charge PHEVs
PHEV market penetration projections
Charging level and charging scenarios (starting time, # of charges, etc.)
Generate PHEVs load profiles for corresponding charging scenarios
19
20 20
Fuel and Electricity Consumption of PHEVs and
VMT Share Split Between CD and CS
Adjusted Fuel Economy and Electricity Consumption
(Midsize Vehicle Class)
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*Electricity consumption does not include charging losses; charging efficiency assumed at 85%
PHEV 10 PHEV20 PHEV30 PHEV40
ICEV HEV CD CS CD CS CD CS CD CS
Gasoline Fuel
Economy (mpg) 29.5 44.3 113 47.5 111 47.3 N/A 37.6 N/A 37.2
Electricity
Consumption*
(Wh/mi) N/A N/A 188 N/A 185 N/A 319 N/A 323 N/A
Power-split Series Design
22 22 22
PHEVs with 20-Mile ER Account for 40% of Daily VMT,
PHEVs with 40-Mile for more than 60%
22
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 10 20 30 40 50 60 70 80 90 100
Miles Driven on CD Mode
% o
f D
aily
VM
T o
n C
D M
od
e (
Uti
lity
Fa
cto
r)
fuel consumption for charge depleting and charge sustaining operations were combined
using the utility factor (UF)
(FCCDGrid + FCCDICE )* UF + FCCS * (1-UF)
23 23
Charging Scenarios and Their Impact on
PHEVs Load Profiles
PHEVs Load Profile Can Vary Considerably with Charging
Scenario (Figure Shown for WECC)
24
PHEVs Load is Relatively Small Even at 10% Penetration in
the LDV FLEET (Figure Shown for WECC in 2030)
25
26 26
Electricity Generation Mix
for PHEV Recharging
27
Alternative Charging Scenarios of PHEVs in WECC (including California)
Fuel Technology
Charging Starts at End of
Trip
Charging Ends Before Time
of Departure
Charging Ends Before Time
of Departure + Opportunity
Charge at Work or Home
Coal Utility Boiler /
IGCC
0% 0% 0
Natural Gas Utility Boiler -0.5% 0.2% 0.9%
Combined Cycle 96.5% 97.2% 92.0%
Combustion
Turbine
3.5% 1.8% 6.5%
Residual Oil Utility Boiler 0% 0% 0%
Nuclear Utility Boiler 0% 0% 0%
Biomass Utility Boiler 0% 0% 0%
Renewable Hydro/Wind/Solar 0.5% 0.8% 0.6%
Total 100% 100% 100%
The Marginal Mix for PHEV Recharging is Dominated by NGCC For All Considered
Charging Scenarios
(Table Shown for WECC in 2030)
28 28
WTW Petroleum Use and GHG Emissions
Results
29
WTW Petroleum Use by PHEVs Relative to ICEV and HEVs
(Figure Shown for Unconstrained Charging in WECC)
0
1000
2000
3000
4000
5000
CD CS CD CS CD CS CD CS
ICEV HEV PHEV10 PHEV20 PHEV30 PHEV40
Pe
tro
leu
m U
se [
Btu
/mi]
Power-split Series Design
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WTW GHG Emissions of PHEVs Relative to ICEV and HEVs
(Figure Shown for Unconstrained Charging in WECC)
0
50
100
150
200
250
300
350
400
CD CS CD CS CD CS CD CS
ICEV HEV PHEV10 PHEV20 PHEV30 PHEV40
GH
G E
mis
sio
ns
[g/m
i]
Power-split Series Design
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0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2
GH
G E
mis
sio
ns (
rela
tive to
GV
)
Petroleum Use (relative to GV)
Regular HEV
Baseline Gasoline ICE Vehicle (GV)
Combined CD and CS OperationsCD operation only
PHEV10
PHEV30 PHEV40
PHEV20
Power-Split
Design
Series (EREV)
Design
PHEV30
PHEV40 PHEV10
and
PHEV20
Significant WTW Petroleum Savings for PHEVs Relative to ICEV and HEVs But
WTW GHG Emissions Comparable to HEVs
(Figure Shown for Unconstrained Charging in WECC)
32
Report available at:
http://greet.es.anl.gov/publication-
xkdaqgyk
Acknowledgment
This work has been sponsored by Vehicle
Technologies and Fuel Cell Technologies
programs of EERE, DOE
Outline
Petroleum
Pyrolysis
Plug-in Hybrid Electric Vehicles
Ethanol
33
Life Cycle of Corn Ethanol
34
CCLUB
Inputs
Fuel_Prod_TS
Fuel_Prod_TS
EtOH Inputs Inputs
Ag_Inputs
T&D
Ethanol Life Cycle Supporting Documentation
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Available at: www.greet.es.anl.gov/publications and journal websites
Key factors in corn ethanol life cycle
Nitrogen is a customizable mix of Ammonia, Urea, and Ammonium Nitrate (Ag_Inputs)
Ethanol facility process fuel and co-products (Inputs)
Allocation method (Inputs)
– Displacement
– Energy
– Market value 36
Fertilizer Energy Use (Btu/g) CO2 emissions (g/g)
Nitrogen 47 2.6
P2O5 14 0.97
K2O 8.4 0.65
CaCO3 7.7 0.59
Trend of 35 Studies in the Past 35 Years: Energy
Use in U.S. Corn Ethanol Plants Has Decreased
Significantly
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Fertilizer Use in U.S. Corn Farming Has Reduced
Significantly in the Past 40 Years
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30%
40%
50%
60%
70%
80%
90%
100%
110%
1970 1975 1980 1985 1990 1995 2000 2005 2010
Fer
tili
zer
Use
Per
Bu
shel
of
Co
rn (
rela
tiv
e to
19
70
)
Nitrogen
K2O
P2O5
Wang et al. (2007) from
USDA
Sugarcane Ethanol Life Cycle
39
Fuel_Prod_TS
Inputs
Ag_Inputs
Inputs
Fuel_Prod_TS
T&D
Sugarcane life cycle data updates
In the field (Fuel_Prod_TS):
– Field burning reductions exceeding mandated levels
– Harvest mechanization increasing, resultant increase in harvest energy
At the mill:
– Electricity exports increasing (Inputs)
– Adjusted embodied energy in equipment and buildings (EtOH)
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Cellulosic Ethanol Life Cycle
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Fuel_Prod_TS
Inputs
Ag_Inputs
Inputs
T&D Inputs EtOH
Cellulosic Ethanol Feedstock Supporting
Documents
42
Available at:
www.greet.es.anl.gov/publications
Feedstock Data
(per dry ton) Corn Stover Switchgrass Forest Residue
N application rate (g) 7,700 7,000 0
P application rate (g) 2,000 100 0
K application rate (g) 12,000 200 0
Farming Energy (Btu) 188,500 123,700 230,000
Herbicide application rate (g) 0 28 0
Pesticide application rate (g) 0 0 0
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Life Cycle Results for Ethanol
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Case studies
Feedstock for cellulosic ethanol
– Switchgrass
– Forest Residue
– Corn Stover
Ethanol facility
– Dry mill with only DDGS as co-product and NG as process fuel
– Dry mill with only WDGS as co-product and coal as process fuel
– Dry mill with only WDGS as co-product and biomass as process fuel
Embodied energy
– Derive sugarcane ethanol numbers with and without embedded energy of mill buildings and equipment
– Derive corn ethanol numbers with and without farming equipment
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Backup Slides
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System Boundary of Ethanol Pathways
Six options for feedstock are available
– Corn, Farmed Tree, Switchgrass, Corn Stover, Forest Residue and Sugar Cane
– Selection can be made in the Fuel_Prod_TS tab (Shares of Ethanol Production)
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Fertilizer Production
Biomass Farming, Harvesting & Transport
Ethanol T&D
Ethanol Production
Fuel Combustion in Vehicle
Key Input Parameters for Fertilizer Production and
Biomass Farming Total Energy Inputs and Non-combustion
Emissions for fertilizer and pesticide production can be defined in the Ag_Inputs tab
Farming Energy Use and Fertilizer use
– Farming Energy Use: Corn and Biomass Farming in the Fuel_Prod_TS tab
– Fertilizer Use: Corn and Biomass Farming in the Fuel_Prod_TS tab and 7.2) in the Inputs tab
– Pesticide Use: 7.2) in the Inputs tab and Corn and Biomass Farming in the Fuel_Prod_TS tab
48
Key Input Parameters for Fertilizer Production and
Biomass Farming (Cont’d) CO2 Emissions from Land Use Change
– Defined in Carbon Calculator for Land Use Change from Biofuels (CCLUB) tool
– Linked in the Fuel_Prod_TS tab
N2O Emissions from Fertilizer Applications (7.4 in the Inputs tab)
Other Farming Assumptions
– Corn Stover Removal (7.5 in the Inputs tab)
– Sugar Cane Straw Burning (7.6 in the Inputs tab)
– Inclusion of Production of Farming Equipment (7.7 in the Inputs tab)
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Ethanol Production Processes
50
Corn Ethanol Production
Farmed Tree Switchgrass Corn Stover
Forest Residue Sugar Cane
Fermentation Ethanol
Dry Milling Plant
Wet Milling Plant
Corn NG
Coal Biomass
Electricity
Dry DGS, Wet DGS
CGM, CGF, Corn Meal
DGS: distillers grains with solubles CGM: corn gluten meal CGF : corn gluten feed
Ethanol
Displace animal feed
Electricity
Key Input Parameters for Ethanol Production
Key input parameters (yields, energy use and co-produced electricity) for ethanol production from corn, farmed tree, switchgrass, corn stover and forest residue can be found in the Fuel_Prod_TS tab
The co-product yields of U.S. average corn ethanol production and the details of plant specific assumptions are listed in Section 7.9 of the Inputs tab.
Co-product handling methods for corn ethanol are also presented in Section 7.9
The displacement ratios of corn ethanol co-products to animal feed are calculated in Section 1.3c in the EtOH tab
Sugar cane-based ethanol production is specified in Section 7.12 in the Inputs tab
51
WTW Results for Ethanol Pathways
Share of ethanol in the fuel can be specified in Section 11 of the Inputs tab: Ethanol, Methanol, Biodiesel, FT diesel, Renewable diesel, Renewable gasoline, butanol, E-diesel
WTW Results for selected feedstock can be found in the Results tab
52
Displacement method
– Data intensive: need detailed understanding of the displaced product sector
– Dynamic results: subject to change based on economic and market modifications
– May not be reliable with a large amount of co-product
Backup: Co-Product Methods
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Fuel
Main Product 80%
Co-product 20%
Energy & Emission Burden
80% 20%
Fuel
Main Product
Co-product
Energy & Emission Burden
100% 0%
Production of displaced product
Displacing conv. product
Conventional product
Fuel (Credit)
Allocation methods: based on mass, energy, or market revenue
– Easy to use
– Frequent updates not required for mature industry
– Mass based allocation: not applicable for certain cases such as electricity
– Energy based allocation: results not entirely accurate, when co-products are used in non-fuel applications such as animal feeds
– Market revenue based allocation: subject to price variation
Displacement method
Allocation method