epa's energy scenario analysis: national and nine-region u

Office of Research and DevelopmentNational Risk Management Research Laboratory, RTP, NC

Timothy Johnson(CMU/EPP Ph.D., 2002)

U.S. EPA, Office of Research and DevelopmentResearch Triangle Park, NC April 26, 2010

EPA's Energy Scenario Analysis: Technology Assessment and Systems Modeling

2Ref: Lawrence Livermore Laboratory UCRL-51487 Total Energy Consumption ~ 36,000 PJ

3 MARKAL

2050?2050? =104,000 PJ

4

Energy & Environment in the Future?

The energy system andenvironmental quality are closely linked

There are many potential realizationsof the energy system in the future

How the energy system evolves will have profound impacts

on our environment

5

The Big Picture: What Sort of Questions Are We Asking?

• How might the U.S. energy system evolve over the coming decades and what are the impacts on criteria pollutant and GHG emissions?

• How do direct and indirect energy inputs plus environmental impacts vary along the bioenergy supply chain?

• How far can technology take us in meeting GHG mitigation targets? Which technology pathways get us there? How different are these pathways?

• How do assumptions about fossil energy prices, technology development, and environmental and energy policy affect answers to these questions?

6

The Need for an Energy System Perspective• Captures complexity:

–Need to calculate both direct and indirect impacts across the energy economy (e.g., ag. is both an energy producer and consumer; biofuels both displace and use fossil energy)

–Interactions must be considered, but they are not always intuitive

–Trade-offs in technological and economic feasibility often emerge only at the systems level

• Complements life-cycle analysis

7

Coal

Industry

Uranium

Coal

Natural Gas

Oil

Electricity Generation

Agriculture(Future)

Industrial/Commercial

Residential

Transportation

Oil

Refining

EmissionsEmissions

Agricultural biomass

Emissions

Emissions

Emissions

Emissions

EmissionsEmissions

MSW

Forestry biomass

Gasification

Emissions

Livestock waste

Emissions

Emissions

Thermochemical Conversion

BiochemicalConversion

Emissions

Emissions

Emissions

Modeling Energy System Interactions

8

Factors Driving Energy System Evolution

• Population growth and migration• Economic growth and transformation

• Land use change• Technology innovation• Climate change impacts on energy use and production

• Availability and cost of fuel resources

• Consumer and firm behavior

Policy• Climate• Energy security• Environmental• Other

- R&D- Trade- Smart growth

Many uncertainties when projecting to the future

9

Modeling Technology Change with MARKAL

MARKAL Inputs:• Future-year energy service demands• Primary energy resource supplies• Current & future technology

characteristics• Emissions and energy policies

MARKAL Outputs:• Technology penetrations for meeting industrial, residential, commercial, and transportation demands• Fuel use by type and region• Sectoral and system-wide emissions• Marginal fuel and emissions reduction prices

Uranium

Fossil Fuels

OilRefining & Processing

H2 Generation

Clean Energy

Biomass

Combustion

Nuclear Power

Gasification

RenewableResources

Carbon Sequestration

Industry

Industry

Commercial

Residential

Automobiles

Uranium

Fossil Fuels

OilRefining & Processing

H2 Generation

Clean Energy

Biomass

Combustion

Nuclear Power

Gasification

RenewableResources

Carbon Sequestration

Industry

Industry

Commercial

Residential

Automobiles

Through linear optimization MARKAL finds the least cost set of technologies

10

MARKAL - How does it work?

• Selects the optimal mix of technologies and fuels at each time step to minimize the net present value of energy system capital and O&M costs

• Subject to: –Current and projected technology costs & efficiencies–Resource supply costs & competition for fuel across sectors–Resource supply constraints–Trade costs and constraints–Emission limits–Other constraints (e.g., policies)

11

EPA MARKAL Databases

• EPA MARKAL databases allow optimization from 2000- 2050 horizon in 5-yr steps

• National database:– Released to public in 2006– 1-8 minute runtime

• Regional database:– Improves resource supply

characterization– External peer review complete– Current database calibrated to

AEO2008– Runtime: 25 to 45 min on a

desktop computer

12

Mini

Compact

Full-size

Minivan

Pickup

Small SUV

Large SUV

ClassTechnologyConventional ICE

Moderate ICEAdvanced ICE

HybridPlugin-10Plugin-40

E85 Conventional ICEE85 Moderate ICEE85 Advanced ICE

E85 HybridE85 Plugin-10E85 Plugin-40

DieselDiesel Hybrid

CNGElectricity

Hydrogen Fuel Cell

Transportation

Demand

Light Duty

Airplanes

Buses

Ships

Rail

Heavy Duty

U.S. EPA MARKAL 9-Region Database

Technology Detail: Light Duty Vehicles

Fuel

E85

Electricity

Gasoline

Ethanol

13

Electricity

Coal

Natural Gas

Oil

Hydro

Wind

Solar

Geothermal

Class

Nuclear

Biomass

Technology

Conventional

Next Generation

Supercritical

Oxyfuel

IGCC

U.S. EPA MARKAL 9-Region Database

Technology Detail: Electricity Production

NOx: LNB, SCR, SNCRSO2 : FGDCO2 : CCS

Controls

Fuel

14 Coal SupplyRegions

Biomass forCo-firing

14

Technological Detail

Standard• Availability (Year)• Lifetime• Capital Cost• Operating Costs

– Fixed– Variable (non-fuel)

• Efficiency• Fuel Inputs• Emissions Factors

Optional• Capacity Factor• Growth Limit• Learning Rate• Discount Rate• Time of Day Operation• Market Penetration Constraints

• Capacity Increment

15

Constraints / Policy Variables

• System, sectoral and/or regional limits on:– Criteria pollutants (NOx, SO2 , PM10 )– CO2– Fuel supplies– Technology penetration

• Limiting• Forcing

• Incentives– Taxes on fuels or emissions– Subsidies on fuels or technologies

• Other–Renewable portfolio or efficiency standards

16

U.S. EPA MARKAL 9-Region Database: End-use Energy Demands

TransportationLight dutyHeavy dutyBusOff-roadPassenger railFreight railShipping

ResidentialFreezingLightingRefrigerationCoolingHeatingWater HeatingOther

CommercialCookingLightingOffice EquipmentRefrigerationCoolingVentilationWater HeatingOther

IndustrialElectrochemicalFeedstockMachine DriveProcess HeatSteamOtherSectors:RefineriesChemicalFoodPrimary metalsMineralsPulp and paperTransportation equip.Non-manufacturingOther

17

Current Technology Focus

• Electricity generation:–Advanced coal and natural gas plants–Biomass co-firing and gasification–Wind and solar–Advanced nuclear plants–Carbon capture and sequestration

• Transportation:–Biofuels–Conventional and plug-in hybrids–Hydrogen (and other) fuel cells

• Hydrogen infrastructure

18

Role of an Energy System Optimization Model

• Least cost optimization – Identify the least cost technology pathway for meeting energy demands over a time horizon

• Scenario analysis – Develop internally consistent energy system scenarios and calculate the resulting emissions, water use and other metrics

• Parametric and what-if analysis – Learn about the sectoral and cross-sector responses of the energy system to changes in assumptions and application of potential policies

• Decision-making under uncertainty – Develop robust solutions while considering uncertainties in factors such as fuel prices, technologies, energy service demands, and policy

19

Scenario Analysis• Scenarios do not predict the future• Scenarios project internally consistent futures to posited storylines–“What if…” to forecast –“How could…” to backcast

• Scenarios allow visualization and assessment of:–Consequences of varying assumptions–Range of possible futures–Trade-offs and branch points between futures

20

Energy Systems Modeling vs. LCA

• MARKAL is the equivalent of an energy supply chain model–MARKAL maps out the energy system from primary resource

supplies through end-use energy service demands–Energy and materials “flow” through the system–Environmental impacts (air emissions, water consumption,

waste production) are tracked where they occur

• As structured, MARKAL does not account for embodied (indirect) energy and materials use, as well as environmental externalities–But it could

21

Transportation

Electricity Production

Illustrative Results

Industry

Scenario 1: No GHG Policy

22

National Electricity Production by Technology

Existing Coal

New Coal

Natural GasNuclearHydro

Wind

Solar

Scenario 1: No GHG PolicyIllustrative Results

23


Conventional ICE

Advanced ICE

Advanced E85

Hybrid

Diesel

Moderate ICE

E85

Scenario 1: No GHG Policy

24

Scenario 1. No GHG PolicyCO2 Emissions

NOx Emissions

Electricity Technologies

Vehicle Technologies


25

Scenario 2. GHG Policy w/CCSCO2 Emissions

NOx Emissions

CCS

PluginHybrids


Vehicle TechnologiesH2-FCVs


26

Scenario 3. GHG Policy, no CCS

PluginHybrids

Wind

CO2 Emissions

NOx Emissions

Nuclear

H2-FCVs


Vehicle Technologies


27

Power Sector Analysis

Electricity Production by Fuel & Type

-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)


-

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030 2035 2040 2045 2050Year

Qua

ntity

(PJ)

less Wind and Solar more

more C

CS less

Electricity production by technology

For pessimistic nuclear growth

Coal Coal with CCS Natural gas Natural gas with CCS

Nuclear Biomass-to-electricity Hydropower Wind and Solar

ResultsApproach

Nuclear powerbreakthroughoptimisticpessimisticno growth

Wind and solar powerbreakthroughoptimisticpessimisticno growth

CCS growthbreakthroughoptimistic pessimisticnoneCCS start year

202020252030

Model all 160 combination of the Following growth assumptions:

4800 PJ

5300 PJ

6900 PJ

4100 PJ

4600 PJ

5900 PJ

3800 PJ

4300 PJ

5000 PJ

$61/t

$80/t

$180/t

$59/t

$64/t

$95/t

$58/t

$60/t

$70/t

In 2030, electricity from natural gas, CO2 allowance price

28

FeedstockProduction

BiofuelsProduction

BiofuelsDistribution

BiofuelsEnd Use

FeedstockLogistics

Modeling the Full Biofuels Supply Chain

Goals: (1) Examine how broader energy system drivers affect biomass feedstock demand and biofuels production, and (2) evaluate direct and indirect impacts on emissions

29

Motivation for Biofuels/Bioenergy Work• Examine how broader energy system drivers affect biomass feedstock demand and biofuels and bioenergy production–Capture the effects of EISA 2007 –Model entire supply chain and interactions with larger energy system on

a regional scale–Scenario analysis based on fossil energy prices, feedstock prices,

conversion technology development, environmental and energy policy• Evaluate resulting environmental impacts

–Direct emissions changes of criteria pollutants and GHGs from biofuel/bioenergy production and use

– Indirect emissions changes from fossil energy offsets–Ecosystem services, land use changes, natural resource consumption

(collaborations with Ecosystem Services Research Program, EPA R7, Iowa State, Kansas State)

30

Examine Competition for Biomass Within and Between Sectors

Sector Feedstock and Conversion TechnologiesTransportation fuels

Corn-based ethanol (6)Cellulosic ethanol (6)Biodiesel – soybean oil and waste oil

Industrial steam/power

Pulp and paper use of black liquor and biomass

Electric power Co-firing with coal, biomass IGCC, combined heat and power (CHP) units, biomass-steam

Residential heat Wood stoves

31

Biomass Conversion Technologies

Ethanol: BiochemicalDry Mill (corn grain)

(w/ and w/o CHP)Wet Mill (corn grain)Cellulosic (multiple feedstocks)

ThermochemicalPyrolysis to bio-oilGasification to syngas

(to final fuel products)

Power GenerationBiomass gasificationCoal/biomass co-firingBiomass combustionLandfill gas combustionWaste-to-energy

Industrial Heat and PowerPulp and paper (black liquor)Other industrial heat/steam

(lignocellulosic biomass)

BiodieselFAME (virgin soybean oil)FAME (waste oil/grease)Renewable diesel via

thermochemical

Residential Heat/Hot WaterWood stovesOutdoor wood boilers

Liquid Fuels Heat and Power

32

Energy, Emissions and Material Flows: Corn-Based Ethanol

Diesel

Gasoline

LPG

Electricity

Natural gas

Diesel

Gasoline

Transport to refinery

Coal

Electricity

Natural gas

Gasoline

Diesel

Transport to blender

…

Upstream processes

Air Emissions

Air Emissions

Air Emissions

Air Emissions

CO2 uptake

Water

Land

Corn production

corn corn eth

Co-products

Water

Ethanol production

33

All Regions: Biomass Use by Sector (Mt/y)

0

100

200

300

400

500

600

700

800

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Residentialsector

Industrialsector

Electric sector

Transportationbiofuels

All Regions: Biomass Use by Feedstock (Mt/y)

0

100

200

300

400

500

600

700

800

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Urban wood

Mill residues

Forest residues

E-crops: wood

E-crops: grass

Ag residue

Stover

Corn

National Feedstock Utilization by Type (MTonnes/y)

National Feedstock Utilization by Sector (MTonnes/y)

Run including the EISA corn ethanol and cellulosic ethanol volumes (but not the GHG thresholds)

Feedstock Use: National

34

R5: Biomass Use by Sector (Mt/y)

0

10

20

30

40

50

60

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Residentialsector

Industrialsector

Electric sector


R5: Biomass Use by Feedstock (Mt/y)

0

10

20

30

40

50

60

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Urban wood

Mill residues

Forest residues

E-crops: wood

E-crops: grass

Ag residue

Stover

Corn

R4: Biomass Use by Sector (Mt/y)

0

50

100

150

200

250

300

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Residentialsector

Industrialsector

Electric sector


R4: Biomass Use by Feedstock (Mt/y)

0

50

100

150

200

250

300

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Urban wood

Mill residues

Forest residues

E-crops: wood

E-crops: grass

Ag residue

Stover

Corn

Feedstock Use: RegionalMidwest Southeast

With Iowa State and Southern Illinois University, we aredownscaling regional feedstock production and assessing its impacts.

Feedstock Utilization by Type (MTonnes/y) Feedstock Utilization by Type (MTonnes/y)

Feedstock Utilization by Sector (MTonnes/y) Feedstock Utilization by Sector (MTonnes/y)

35

R6: Fossil Fuel Inputs for Ethanol Supply Chain

0

5

10

15

20

25

30

35

40

45

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

TRNDSL

TRGSLC1

INDNGAEA

INDCOAEA

INDELC

TRNDSL

TOHDSLEA

TOHDSLEA

TOHGSLEA

INDNGAEA

INDLPGEA

INDELC

R4: Fossil Fuel Inputs for Ethanol Supply Chain

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

TRNDSL

TRGSLC1

INDNGAEA

INDCOAEA

INDELC

TRNDSL

TOHDSLEA

TOHDSLEA

TOHGSLEA

INDNGAEA

INDLPGEA

INDELC

Biofuels Supply Chain: Fossil Fuel InputsMidwest

Southeast

Diesel

Gasoline

Natural Gas

Coal

Electricity

Diesel

Diesel

Diesel

Gasoline

Natural Gas

LPG

Electricity

Diesel

Gasoline

Natural Gas

Coal

Electricity

Diesel

Diesel

Diesel

Gasoline

Natural Gas

LPG

Electricity

Biofuel Production

Feedstock CollectionFeedstock Transport

Feedstock Production

Biofuel transport

Run including the EISA corn ethanol and cellulosic ethanol volumes (but not the GHG thresholds)

Fossil Energy Input (PJ/y)

Fossil Energy Input (PJ/y)

36

Supply Chain Analysis – Fuel Inputs

ALL REGIONS: Direct Fossil Fuel Inputs for Ethanol Supply Chain vs. Total Ethanol Produced (version: EPAUS9r_v1.0, run: BS_ETH_A)

0

500

1000

1500

2000

2500

3000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 20500

500

1000

1500

2000

2500

3000

TRNDSL

TRGSLC1

INDNGAEA

INDCOAEA

INDELC

TRNDSL

TOHDSLEA

TOHDSLEA

TOHGSLEA

INDNGAEA

INDLPGEA

INDELC

Total ethanolproduced

Diesel

Gasoline

Natural Gas

Coal

Electricity

Diesel

Diesel

Diesel

Gasoline

Natural Gas

LPG

Electricity

Biofuel Transport

Biofuel Production

Feedstock TransportFeedstock Collection

FeedstockProductionBiofuel production is

the primary energy user

The energy balance improveswith additional utilization ofcellulosic ethanol

2.2x2.3x

1.8x

1.4x

1.3x

2.1x

37

Modeling Ag-Energy Feedbacks

With Iowa State, Southern Illinois University, NCA&T, and IFPRI, we are examining how regional crop and energy prices affect farm-level decision making and how the resulting land use choices impact the environment

An integrated perspective is needed to understand:

• the linkages between agricultural and energy markets

• the impacts of those market dynamics on farm-level decision making

• how management of environmental impacts at the field level may constrain development of emerging biomass markets

38

Food, energy

Agricul-ture

Assumptionsor projections:• general economy• ag policies• weather, climate• tech. change

Land cover

Land Cover Change

• Aggregate crop acreages

• Crop prices

Crop data(NASS)

Soils data(SSURGO)

Land cover & management,

runoff, water use, aquatic impact

projections

Assumptionsor projections:•population & GDP•energy demand•emission constraints

•tech. change

Soil productivity

Carbon storage

Services

Water supply

Crop budgets

Energy

Road network impact

GIS plant siting/trans. demand

Crop location

Modeling Ecosystem Service Impacts of Biofuel Production

Land UseChange

Scenario Assumptions

Population & housingprojections

Energy systemprojection

Outputs

Air Quality impacts

Energy & fuel useCriteria & GHG

Emissions

Impacts

epa's energy scenario analysis: national and nine-region u

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