roger hill technical director of geopowering the west l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Roger Hill Technical Director of GeoPowering the West PowerPoint Presentation
Download Presentation
Roger Hill Technical Director of GeoPowering the West

Loading in 2 Seconds...

play fullscreen
1 / 30

Roger Hill Technical Director of GeoPowering the West - PowerPoint PPT Presentation


  • 115 Views
  • Uploaded on

The Role of Geothermal in Enhancing Energy Diversity and Security in the Western US (DRAFT). Roger Hill Technical Director of GeoPowering the West. Wednesday, May 11 2005 Salem, Oregon.

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 'Roger Hill Technical Director of GeoPowering the West' - manny


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
roger hill technical director of geopowering the west

The Role of Geothermal in Enhancing Energy Diversity and Security in the Western US (DRAFT)

Roger Hill

Technical Director of GeoPowering the West

Wednesday, May 11 2005

Salem, Oregon

Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company,for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

the role of geothermal in enhancing energy diversity and security in the western us

The Role of Geothermal in Enhancing Energy Diversity and Security in the Western US

A Mean-Variance Portfolio Optimization of the Region’s Generating Mix to 2013

Prepared for Sandia National Labs

Roger Hill

Contract Officer

By

Shimon Awerbuch, Ph.D.

Tyndall Centre Visiting Fellow - SPRU-University of Sussex

s.awerbuch@sussex.ac.uk

Jaap C. Jansen & Luuk Beurskens

ECN - Energy Research Centre of the Netherlands

Thomas Drennen, Ph.D.

Hobart College and Sandia National Labs

February 28, 2005

a mean variance portfolio optimization of the western region s generating mix to 2013
A Mean-Variance Portfolio Optimization of the Western Region’s Generating Mix to 2013
  • Portfolio optimization locates generating mixes with lowest-expected cost at every level of risk
    • Risk is the year-to-year variability of technology generating costs
  • EIA (NEMS) projected generating mixes serve as a benchmark or starting point;
    • Detailed decommissioning date assumptions using World Electricity Power Plant Database age of existing plants
  • The optimal results generally indicate that compared to EIA target mixes, there exist generating mixes with larger geothermal shares at no greater expected cost or risk
    • There exist mixes with larger geothermal shares that exhibit lower expected cost and risk

© Shimon Awerbuch Feb-05

optimization defines four bands for new geothermal based on resource accessibility
Optimization Defines Four Bands for New Geothermal Based on Resource Accessibility

© Shimon Awerbuch Feb-05

eia 2003 and 2013 generating mixes
EIA 2003 and 2013 Generating Mixes

Geothermal Shares

2003: 2% 2013: 4%

© Shimon Awerbuch Feb-05

electricity generation
Electricity Generation

Source:

Renewable

Energy Atlas

western us load growth
Western US: Load Growth

Source:

Renewable

Energy Atlas

generating cost inputs nominal kwh
Generating Cost Inputs: Nominal $/kWh

© Shimon Awerbuch Feb-05

understanding risk
Understanding Risk
  • Portfolio optimization locates generating mixes with minimum expected cost and risk
  • For each technology, risk is the year-to-year variability (standard deviation) of the three generating cost inputs: fuel, O&M and capital (construction period risk)
    • Fossil fuel standard deviations are estimated from historic US data
      • e.g. standard deviation for natural gas over the last 10 years is 0.30
    • Standard deviations for capital and O&M are estimated using proxy procedures (see Awerbuch and Berger, IEA, 2003)
  • The construction period risk for embedded technologies is 0.0
  • ‘New’ technologies are therefore riskier than embedded ones
    • e.g. new coal is riskier than ‘old’ coal

© Shimon Awerbuch Feb-05

regional power plant emissions
Regional Power Plant Emissions

Source:

Renewable Energy Atlas

slide12

Total Risk for each generating technology is a weighted statistical summation of the component risks

© Shimon Awerbuch Feb-05

2003 eia technology generating costs and estimated technology risk
2003 EIA Technology Generating Costs and Estimated Technology Risk

© Shimon Awerbuch Feb-05

2013 eia technology generating costs and estimated technology risk
2013 EIA Technology Generating Costs and Estimated Technology Risk

© Shimon Awerbuch Feb-05

western region generating cost risk trends
Western Region Generating Cost-Risk Trends
  • 2013 EIA Mix has higher cost and risk relative to 2003
    • Driven by 32% demand increase, decommissioning existing plant, resource shortages and limitations on available options
  • Move to larger gas/coal shares adds to portfolio cost and risk
    • Increases year-to-year expected generating cost volatility
  • Reduces Energy Diversity/ Security
  • Geothermal and wind are ideally positioned to diversify the generating mix and reduce cost/risk

© Shimon Awerbuch Feb-05

portfolio optimization
Portfolio Optimization
  • Portfolio Optimization locates lowest cost portfolio at every level of risk
  • These optimal or efficient portfolios lie along the Efficient Frontier (EF)
  • Portfolio cost is the weighted average cost of the generating mix components
  • For a two-technology generating mix:
    • Expected portfolio cost is the weighted average of the individual expected costs of the two technologies:

Expected Portfolio Cost = E(Cp) = X1•E(C1) + X2•E(C2)

    • Where: X1, X2 are the proportional shares of the two technologies in themix and E(C1) and E(C2) are the expected generating costs for those technologies

© Shimon Awerbuch Feb-05

portfolio optimization continued

Expected Portfolio Risk =

Portfolio Optimization (Continued)
  • Expected Portfolio risk, p, is a weighted average of the individual technology cost variances, as tempered by their co-variances:
    • σ1and σ2 are the standard deviations of the annual costs of technologies 1 and 2
    • ρ12 is their correlation coefficient
  • The correlation coefficient is a measure of diversity. Lower correlation among portfolio cost components increases diversity, which reduces portfolio risk
  • Adding a fixed-cost technology to a risky generating mix, even if it costs more than other alternatives, has the remarkable effect of lowering expected portfolio cost at any level of risk
    • A pure fixed-cost technology, has σi= 0. This reduces portfolio risk since two terms in the above equation reduce to zero

© Shimon Awerbuch Feb-05

eia has consistently underestimated gas prices
EIA has consistently underestimated gas prices

Wellhead Natural Gas Prices (2002$/Mcf)

Source: Union of Concerned Scientists

© Shimon Awerbuch Feb-05

2013 baseline portfolio optimization
2013 Baseline Portfolio Optimization

Mix P: Costs $.003/KWh more than EIA Mix: 9x as much Geo

Mix N costs the same as EIA Mix: 5x as much Geo

Mix S costs less than EIA Mix: 75% more Geo

© Shimon Awerbuch Feb-05

steps to determine sites suitable for development
Steps to Determine Sites Suitable for Development

1. Need a good resource

2. Must have access to loads or grid

3. The land must be developable

But the most important need is to have a buyer

slide26

Geologic Assurance and

Economic Feasibility

  • National R&D
  • helps to expand
  • the geothermal
  • resource base:
  • Geophysics and
  • geoscience to
  • locate and define
  • reservoirs
  • Drilling research
  • to reduce costs
  • Improving
  • capabilities and
  • efficiencies of
  • power plants.

Decreasing information about resource

Undiscovered Resources

Reserves

Undiscovered Resources

Possible

Decreasing quality of resource

Proven

Probable

Sub-Economic Resources

“The McKelvey Diagram”

Sub-Economic Resources

expected trends in future energy system evolution
Expected Trends in Future Energy System Evolution
  • Energy safety, security, reliability, and sustainability have become important energy system design parameters
  • This will change how energy systems are optimized and upgraded
  • This will impact future decisions on energy policy, supply, and use
  • How do we efficiently and cost-effectively transition to this new future infrastructure?
a mean variance portfolio optimization of the western region s generating mix to 201329
A Mean-Variance Portfolio Optimization of the Western Region’s Generating Mix to 2013
  • Portfolio optimization locates generating mixes with lowest-expected cost at every level of risk
    • Risk is the year-to-year variability of technology generating costs
  • EIA (NEMS) projected generating mixes serve as a benchmark or starting point;
    • Detailed decommissioning date assumptions using World Electricity Power Plant Database age of existing plants
  • The optimal results generally indicate that compared to EIA target mixes, there exist generating mixes with larger geothermal shares at no greater expected cost or risk
    • There exist mixes with larger geothermal shares that exhibit lower expected cost and risk

© Shimon Awerbuch Feb-05

a vision for the future
A Vision for the Future
  • Ready Access to Land
  • Thoroughly Mapped and Developed Resources
  • Cost Competitive Technology