Optimization of Cost and Greenhouse Gas
Emissions of a Dedicated Energy Crop
Supply System to Biorefineries in
TennesseeZidong WangT. Edward Yu
Burton C. English – PresenterJames A. Larson
Integrated Biomass Supply Systems
July 30, 2013
CurrentlyO Producing biofuels from lignocellulosic biomass (LCB) has been
suggested as a way to mitigate the dependence on fossil fuels and the production of greenhouse gas (GHG) emissions.
O In the U. S., the Renewable Fuel Standard (RFS2) in the Energy Independence and Security Act (EISA) of 2007 mandated 16 billion gallons of LCB-based biofuels per year for transportation use by 2022.
O Considerable amounts of feedstock will be needed to fulfill this goal.
O Configuration of the feedstock supply chain for biofuels should be carefully examined since the quality and quantity of feedstock will influence the cost of biofuels production and environmental performance.
O GHG emissions associated with LCB feedstock supply from changes in land use and LCB feedstock production, storage, and transportation activities can also impact the sustainability of LCB-based biofuel production.
ObjectivesO Determine the optimal energy crop supply
chain including the location of biorefinery, the layout of feedstock draw area, the harvest and storage technologies and monthly inventory management by considering both cost and GHG emissions as the objectives.
O Analyze the potential trade-off between the economic and environmental performance of the energy crop supply chain and the impact factors leading to this tradeoff effect.
MethodsO A spatial multi-objective mixed
integer programming model is developed.
O The output from the multi-objective optimization is compared with single-objective optimization results.
Methods – Spatial Framework
233 industrial parks eligible to build the
biorefinery plant
21,902 five square mile hexagons as the potential
feedstock supply area
Methods – Multiple Objective Functions -- Minimize
Cost (C)
Opportunity Barley, Corn, Cotton, Hay/Pasture, Oats, Rice, Sorghum, Soybeans, Wheat
Production Establishment, Maintenance
Harvest Labor, Fuel, and Machinery
Storage Labor, Fuel, Machinery, and Material
Transportation Labor, Fuel, and Truck
GHG Emission (E)
Direct land use change Land use change
Energy usage in production, harvest and storage
Fuel usage and machinery production
Transportation Truck emissions and truck production
Indirect sources indirect sources of GHG emissions included the production of machinery, fertilizer, herbicide and seed Dry Matter Losses and Cattle Production
Additional Model Assumptions
Transportation•Semi-truck•75 miles•Monthly delivery schedule
Production•Non-private land excluded
•50% Hay land/pasture available
•Land in Tennessee and within 50 miles state border
Harvest•Nov. – Feb.•Square bale
Storage•Field side•Tarp•Pallet
Biorefinery•50 million gallon•76 gallon per ton•Power, water, roads and storage area
Methods (Continued)O With cost and GHG emissions minimization as
objectives, the model will optimize the following variables simultaneously:O Location of the biorefinery and associated
feedstock draw area,O Amount of land converted from previous crops,
andO Month of delivery and month of harvestO Input use including energy consumption,
fertilizer herbicide, seed and farm machinery usage.
O Subject to a set of Constraints
Emission ModelingItems Value Source
Land use change CO2
--
Corn -385.84
DAYCENT
Cotton -377.89Hay 210.46Sorghum -271.39Soybean -98.22Wheat -404.78
Land use change N2O--
Corn 69.19
DAYCENT
Cotton 71.06Hay 117.86Sorghum 78.81Soybean 95.53Wheat 65.96
Farm and harvest machine a
--
Tractor 985.77
GREET
Loader 468.22Square baler 3155.54Round baler 1693.28Mower 2111.25PTO rake 615.54
Energy consume--
Production 33.19GREETHarvest 405.17
Storage 2.32b
Production of fertilizer, seed and herbicide
--
Fertilizer 106.49
GREETSeed 18.16
Herbicide 1.34
GREET used to model farm and harvest machines, energy consumption, and indirect, DAYCENT used to model land use change.
(500.00)
(400.00)
(300.00)
(200.00)
(100.00)
-
100.00
200.00
300.00
400.00 CO2 Emission N2O Emissions
Total GHG E missions
CO2e
kg/
acre
/yea
r
Model OperationsSingle Plant Location in a
Region
Multiple Potential Locations in
Region
Individual Solution Points for the 233 Industrial Parks
20000000 30000000 40000000 50000000 60000000 70000000 80000000 90000000 10000000040000000
45000000
50000000
55000000
60000000
65000000
70000000
75000000
80000000
85000000
90000000
Results
20000000 30000000 40000000 50000000 60000000 70000000 80000000 90000000 10000000040000000
50000000
60000000
70000000
80000000
90000000
100000000
110000000
B0E
Tradeoff Curve
Min GHG CurveFor Firm B
Min Cost CurveFor Firm A
Tradeoff Curve
20000000 30000000 40000000 50000000 60000000 70000000 80000000 90000000 100000000 40,000,000
45,000,000
50,000,000
55,000,000
60,000,000
65,000,000
70,000,000
75,000,000
80,000,000
85,000,000
90,000,000
Tradeoff Curve
Min GHG CurveFor Firm B
Min Cost CurveFor Firm A
A0
B0
O0
Costs at the Three Selected Points on the Tradeoff Curve
0100000002000000030000000400000005000000060000000700000008000000090000000
Opportunity Production
A O
B
20000000 30000000 40000000 50000000 60000000 70000000 80000000 90000000 100000000
40,000,000
45,000,000
50,000,000
55,000,000
60,000,000
65,000,000
70,000,000
75,000,000
80,000,000
85,000,000
90,000,000
Land Use Change
A B O -
30,000
60,000
90,000
Thou
sand
Acr
es
79,816 80,819 82,808 acres
GHG Emissions at the Three Selected Points on the Tradeoff
Curve
In Out In Out In OutA A B B O O
-40000000
-20000000
0
20000000
40000000
60000000
80000000
100000000
IndirectTransportationEnergyLand Use Change
Mill
ion
GH
G C
O2e
Kg
LUC Condition
Point
Minimize Costs
Minimize GHG
Somewhere in the Middle: Location Changes
DiscussionO Land availability, land use, and transportation play an
important role in determining the location of biorefinery based on the economics of the feedstock supply chain.
O Comparing the (O) site with the cost-efficient site, its feedstock supply chain system reduced nearly GHG by nearly half at the expense of a 10% increase in cost.
O Location site is impacted based on the criteria usedO Policies that reduce GHG may increase conversion of
land traditionally in crop production.O Livestock impacts were not incorporated in this analysisO Pasture/hay production practices need further study
( Extension recommendations vs actual practice)
Integrated Biomass Supply Systems
:
Funding for this project was advanced by the following:
GHG Emissions Change Converting Different Crops into
Switchgrass from DAYCENT
Corn Cotton Hay Sorghum Soybean Wheat (500.00)
(400.00)
(300.00)
(200.00)
(100.00)
-
100.00
200.00
300.00
400.00
CO2 Emission N2O Emissions Total GHG Emissions
CO2e
kg/
acre
/yea
r
