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Optimization of Cost and Greenhouse Gas Emissions of a Dedicated Energy Crop Supply System to Biorefineries in Tennessee PowerPoint PPT Presentation


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Optimization of Cost and Greenhouse Gas Emissions of a Dedicated Energy Crop Supply System to Biorefineries in Tennessee. Integrated Biomass Supply Systems. Zidong Wang T. Edward Yu Burton C. English – Presenter James A. Larson. July 30, 2013. Currently.

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Optimization of Cost and Greenhouse Gas Emissions of a Dedicated Energy Crop Supply System to Biorefineries in Tennessee

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Optimization of cost and greenhouse gas emissions of a dedicated energy crop supply system to biorefineries in tennessee

Optimization of Cost and Greenhouse Gas Emissions of a Dedicated Energy Crop Supply System to Biorefineries in Tennessee

Integrated Biomass Supply Systems

ZidongWang

T. Edward Yu

Burton C. English – Presenter

James A. Larson

July 30, 2013


Currently

Currently

  • 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.

  • 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.

  • Considerable amounts of feedstock will be needed to fulfill this goal.

  • 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.

  • 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.


Objectives

Objectives

  • 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.

  • 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.


Methods

Methods

  • A spatial multi-objective mixed integer programming model is developed.

  • The output from the multi-objective optimization is compared with single-objective optimization results.


Methods spatial framework

Methods – Spatial Framework

21,902 five square mile hexagons as the potential feedstock supply area

233 industrial parks eligible to build the biorefinery plant


Methods multiple objective functions minimize

Methods – Multiple Objective Functions -- Minimize


Additional model assumptions

Additional Model Assumptions

  • Production

    • Non-private land excluded

    • 50% Hay land/pasture available

    • Land in Tennessee and within 50 miles state border

  • Storage

    • Field side

    • Tarp

    • Pallet

  • Biorefinery

    • 50 million gallon

    • 76 gallon per ton

    • Power, water, roads and storage area

  • Transportation

    • Semi-truck

    • 75 miles

    • Monthly delivery schedule

  • Harvest

    • Nov. – Feb.

    • Square bale


Methods continued

Methods (Continued)

  • With cost and GHG emissions minimization as objectives, the model will optimize the following variables simultaneously:

    • Location of the biorefinery and associated feedstock draw area,

    • Amount of land converted from previous crops, and

    • Month of delivery and month of harvest

    • Input use including energy consumption, fertilizer herbicide, seed and farm machinery usage.

  • Subject to a set of Constraints


Emission modeling

Emission Modeling

GREET used to model farm and harvest machines, energy consumption, and indirect, DAYCENT used to model land use change.


Model operations

Model Operations

Multiple Potential Locations in Region

Single Plant Location in a Region


Individual solution points for the 233 industrial parks

Individual Solution Points for the 233 Industrial Parks


Results

Results

Min Cost Curve

For Firm A

Min GHG Curve

For Firm B

Tradeoff Curve


Tradeoff curve

Tradeoff Curve

B0

Min Cost Curve

For Firm A

Min GHG Curve

For Firm B

A0

O0

Tradeoff Curve


Costs at the three s elected p oints on the tradeoff curve

Costs at the Three Selected Points on the Tradeoff Curve

B

O

A


Land use change

Land Use Change

79,816 80,819 82,808 acres


Ghg emissions at the three selected points on the tradeoff curve

GHG Emissions at the Three Selected Points on the Tradeoff Curve

LUC Condition

Point


Minimize costs

Minimize Costs


Minimize ghg

Minimize GHG


Somewhere in the middle location changes

Somewhere in the Middle: Location Changes


Discussion

Discussion

  • Land availability, land use, and transportation play an important role in determining the location of biorefinerybased on the economics of the feedstock supply chain.

  • 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.

  • Location site is impacted based on the criteria used

  • Policies that reduce GHG may increase conversion of land traditionally in crop production.

  • Livestock impacts were not incorporated in this analysis

  • Pasture/hay production practices need further study ( Extension recommendations vs actual practice)


Funding for this project was advanced by the following

Funding for this project was advanced by the following:

:

Integrated Biomass Supply Systems


Ghg emissions change converting different crops into switchgrass from daycent

GHG Emissions Change Converting Different Crops into Switchgrass from DAYCENT


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