slide1 l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Presentation Outline PowerPoint Presentation
Download Presentation
Presentation Outline

Loading in 2 Seconds...

play fullscreen
1 / 20

Presentation Outline - PowerPoint PPT Presentation


  • 404 Views
  • Uploaded on

Generation and Analysis of Alternative Technology Scenarios Using MARKAL-MGA: Application to the Transportation Sector Dan Loughlin, US EPA Gary Goldstein, IRG, Ltd. International Energy Workshop, Paris, France, June 24 th , 2004 Presentation Outline Context

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Presentation Outline' - erika


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

Generation and Analysis of Alternative Technology Scenarios Using MARKAL-MGA:Application to the Transportation SectorDan Loughlin, US EPAGary Goldstein, IRG, Ltd.International Energy Workshop, Paris, France, June 24th, 2004

presentation outline
Presentation Outline
  • Context
    • US EPA’s Global Change Air Quality Assessment
  • MARKAL and Simulation
    • Simulation versus Optimization
    • Can MARKAL be used for simulation?
  • Modeling to Generate Alternatives (MGA)
    • Theory
    • Initial application to the transportation sector
  • Critique of MGA & MARKAL
  • Next steps
global change air quality assessment
Global Change Air Quality Assessment

Assessment Goal

For 2050, explore the relationships among:

  • Meteorological change
  • Technology change
  • Economic growth
  • Emissions growth
  • Air quality
global change air quality assessment4

Technological change

Economic

Modeling

Productivity

Vehicle

Technologies

Economic growth

By region/sector

Emissions growth

Mobile

Modeling

Emissions

Projection

Emissions growth

By region/sector

Base year

Emissions

Inventories

Projected Mobile

Emissions factors

Regional

Temperatures

Emissions

Processing

Scenario

Assumptions

Regional

Temperatures

Model-ready

emissions

Regional

Meteorology

Global

Circulation

Air Quality

Modeling

Global

Meteorology

Regional

Meteorology

Ambient AQ

Benefits

Assessment

Monetized

benefits

Global Change Air Quality Assessment

Scenario

Assumptions

Economic

Assessment

global change air quality assessment5
Global Change Air Quality Assessment

Scenario

Assumptions

Incorporating

Technological

Change

Energy

Model

Energy Demands

Economic

Modeling

D Energy Prices

Vehicle

Technology

Penetration

Economic growth

By region/sector

Point/Area Source

Emissions Factors

Mobile

Modeling

Emissions

Projection

Emissions growth

By region/sector

Base year

Emissions

Inventories

Projected Mobile

Emissions factors

Regional

Temperatures

Emissions

Processing

Scenario

Assumptions

Regional

Temperatures

Model-ready

emissions

Regional

Meteorology

Global

Circulation

Air Quality

Modeling

Global

Meteorology

Regional

Meteorology

Ambient AQ

Benefits

Assessment

Monetized

benefits

Economic

Assessment

global change air quality assessment6
Global Change Air Quality Assessment

Scenario

Assumptions

Selected

models

MARKAL

Energy Demands

REMI or

EMPAX

D Energy Prices

Vehicle

Technology

Penetration

Economic growth

By region/sector

Point/Area Source

Emissions Factors

Projected VMT

MOBILE6

EGAS

Emissions growth

By region/sector

Base year

Emissions

Inventories

Projected Mobile

Emissions factors

Regional

Temperatures

SMOKE

Scenario

Assumptions

Regional

Temperatures

Model-ready

emissions

MM5

GISS II’

& PCM

CMAQ

Global

Meteorology

Regional

Meteorology

Ambient AQ

BenMAP

Monetized

benefits

REMI or

EMPAX

potential roles of technological modeling
Potential Roles of Technological Modeling

How will things turn out?

Simulation:

  • What set of technologies are expected to be adopted, given various policies and the respective cost-effectiveness of technology options?

Optimization:

  • What set of technologies most cost-effectively meets energy demands and emissions constraints?
  • What policy options most cost-effectively meet energy demands and emissions constraints?

What should I do?

Q: MARKAL is an optimization model. Can it be used for simulation?

A: Yes, but carefully.

what the lc solution does not tell us

One Objective Optimization Problem

Two Objective Optimization Problem

Objective 2

Objective

Objective 1

What the LC Solution Does Not Tell Us
  • The least cost (LC) assumes optimal behavior by individual consumers and companies
  • This outcome likely cannot occur due to unmodeled issues, uncertainties, unpredictability of behavior, etc.
  • The real outcome likely will appear suboptimal
modeling to generate alternatives
Modeling to Generate Alternatives
  • Explore sub-optimal solutions
  • Identify maximally different alternative solutions
  • Analyze, combine, and compare solutions
  • Utilize in:
    • Decision support
    • Exploratory modeling
    • Complementing sensitivity analysis
implementation
Implementation
  • Solve the LC formulation
  • Set total system cost <= (1 + d) * LC
  • Set the objective to maximize some metric of distance from the LC solution
    • For example, minimize the occurrence of all technologies from the LC solution
  • Generate MGA alternative 1
  • Repeat iterative, each time maximizing the difference from the LC & all previous MGA solutions
  • Terminate when a target number of MGA solutions have been reached or where difference is small
least cost optimization

Set of

Feasible

Solutions

Objective:

Minimize Cost

Least Cost

Solution

Constraints

N-dimensional objective space

Least Cost Optimization
modeling to generate alternatives mga

MGA Alternatives

Cost

Constraint

N-dimensional objective space

Modeling to Generate Alternatives (MGA)

Least Cost

Solution

Constraints

illustrative example application
Illustrative Example Application
  • Examining US personal automobile technology penetration through 2030
  • Considering:
    • Conventional vehicles
    • Advanced gasoline-fueled internal combustion engines
    • Advanced diesel engines
    • Hybrid vehicles
    • Advanced hybrid vehicles
    • Hydrogen fuel cell vehicles
least cost solution
Least Cost Solution

Legend

FCV

Hyb3x

Hyb2x

AdvD

AdvG

ConvD

ConvG

Note: These are illustrative results only.

application of mga
Application of MGA
  • Set total system cost <= 1.01 * LC
  • Maximize difference in:
    • Personal vehicle transportation technologies capacity
    • Hydrogen generation infrastructure
  • Generate LC and 25 alternatives
mga alternatives
MGA Alternatives

Legend

FCV

Hyb3x

Hyb2x

AdvD

AdvG

ConvD

ConvG

Note: These are illustrative results only.

mga alternatives17
MGA Alternatives

Fuel Cell Vehicle (FCV) Penetration

  • Fraction of scenarios with FCV penetration: 23%
  • When FCV penetration occurred:

Maximum: 53%

Minimum: 1%

Average: 16%

Std. Dev: 19%

  • Generation of Hydrogen

Primarily centralized generation

Wide range of possible technologies (e.g., SMR, CG)

Typically comes online in 2025 or 2030

Note: These are illustrative results only.

other potential applications
Other Potential Applications
  • Alternative pathways to achieve a target FCV penetration level
  • Alternative emissions outcomes
  • Alternative trading outcomes in an emissions trading program
critique of experience
Critique of Experience

Advantages

  • Easily integrated into MARKAL
  • Readily applied
  • Interesting results

Challenges and Issues

  • What should cost relaxation be?
  • How should results be interpreted?
  • Is ‘expected value’ result meaningful?
  • What are appropriate distance metrics?
  • With overall cost relaxation, small players can behave oddly
next steps
Next Steps
  • Add sector-level cost constraints
  • Application and testing
  • Explore questions on previous slide

For more information, please contact:

Loughlin.Dan@epa.gov

919-541-3928