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Overview

Analysis Collaborative Topics
Collaboration Topic Matrix
Topic A.
Topic B.
Topic C.
Topic D.
Topic E.
Topic F.
Topic G.
Topic H.

Collaborators

Analysis Activities by Organization

Inaugural Workshop

Contact

Analysis Collaboration Topics

(C) Better Representation of Energy Technologies and Demand Response in Energy Models

Improve representation of energy technologies and demand response in energy models, including the next version of NEMS.

Topic collaborators are currently working on implementation plans, based on the workshop discussions — please watch these pages for updates. You can also find out more about the initiative participants on the collaborators page.

Activity No. 1 – Better Understand the Evolution of Technologies and Markets

  • Goal: Learn from history to help with modeling the future
  • Current related activities:
    • DOE Technology characterization of energy efficient and renewable energy technologies
    • NETL has Technology Characterizations (TC) for fossil energy efficiency and electricity generating technologies
    • Federal government GPRA analyses
    • Market assessments being done by lots of organizations
    • States are heavily involved in deployment within their borders
  • Next steps:
    • Gather actual, empirical examples of historical:
      • Rates of technology change (cost, performance)
      • Identify the underlying dynamics and drivers
      • For all stages of tech. development – emerging, precommercial, and commercial
      • How has the global market impacted technology evolution?
    • Share existing technology characterization methods and results and develop common approaches for maintaining current market assessment information.
    • Incorporate findings into technology maturation and saturation curves in models
    • Perform more complete technology characterizations; more than a catalog – look at historical changes over time and look to the future; how and why things change
      • Separate out improvements due to R&D and improvements due to learning.
  • Lead: NREL (Walter Short: TC for energy efficiency and renewables), NETL (TC for fossil), NREL (market assessment)
  • Participants: DOE-EIA

Activity No. 2 – Quantify the Potential for New/Emerging Technologies

Activity Update (January 2007) -

Walter Short reported that NREL and NETL had met regarding this activity. NETL currently runs NEMS while NREL uses both NEMS (through a contractor) and WinDS. Both models could be improved relative to their treatment of renewable and fossil energy.

Activity Update (December 2006) -

Market Penetration Modeling
This was the focus of the discussions. NETL currently runs NEMS while NREL uses both NEMS (through a contractor) and WinDS. While the scopes of these two models are different – NEMS is a general equilibrium model, while WinDS is only an electric capacity expansion model – they both could be improved relative to their treatment of renewable and fossil energy. The focus of the discussions and this proposal are improvements in the modeling of coal-fired power plants. Currently neither model addresses the following issues for coal-fired power plants:

  • Economies of scale in power plant cost/performance
  • Geospatial techno/economic impacts on potential coal plant siting, such as:
    • Transmission requirements for new plants
    • Water requirements for plant operation
    • Access to and carrying capacity of existing rail lines
    • Environmental exclusion zones
    • Carbon sequestration CO2 transport, injection and reservoir capacity issues
    • Coal resource proximity
    • NIMBYism

There may be ways to use the two models to improve one another and the modeling of these issues. With its 136 power control areas, WinDS can more finely locate power plants within the grid and thereby begin to get a handle on many of the above issues, including the economic optimization for carbon capture and storage. Ideally, this effort would enable the enhancement of WinDS with a coal supply capability, address the above issues in WinDS, and use a reduced form to transfer the WinDS findings back to NEMS.

For example, even though economies of scale cannot be explicitly modeled in a linear program (LP) like WinDS (the electricity capacity expansion model of NEMS also uses an LP), WinDS can be utilized to gain insights into the economies of scale via an algorithm that takes advantage of the fine regional structure of WinDS to send excess generation from a new, large, mine-mouth power plant out to surrounding regions. This addresses both economies of scale and new plant transmission requirements (see Marnay 2006 for a description of how new transmission requirements are overlooked by NEMS). Similarly, with its fine regional structure, WinDS can begin to endogenously address the piping of CO2 for sequestration, rail constraints, and the possibility that entire regions/states in WinDS may be excluded from new coal plant builds for environmental reasons.

NREL has been experimenting with and working with Princeton Energy Resources Inc. to translate its wind findings from WinDS and GIS back to NEMS and other more aggregated models. Similar findings for coal could be translated back to NEMS using supply curves and other reduced form models.

At the same time, the natural gas and coal supply modules and other features of NEMS could be adapted to WinDS. For significant energy market shifts like a climate change scenario, such endogenous feedback would be particularly valuable to the insights provided to NREL, NETL and DOE by WinDS as it would provide a partial equilibrium WinDS capability.

Activity Overview

  • Goal: Identify clear parameters for when new/emerging technologies should be included in modeling
  • Current related activities:
    • EERE's VISION model is specifically designed to answer "what if" questions in the transportation sector;
    • Stanford Modeling Forum is active in this area
  • Next steps:
    • For collaboration potential, ask two questions:
      • Who else does modeling (e.g., states, utilities, US and international groups for climate change)
      • Who is a current (or potential) source of technology data
    • Clarify/define the terminology to get everyone on the same page;
    • Develop a screening criteria in order to Identify a way to consider substitute energy technologies and other competitors in energy modeling, before they are fully commercial, so future scenarios can be modeled; and
    • Also, scan the horizon and identify potential new technologies early (outside US too)
  • Lead: DOE-EERE-PAE, DOE-EIA – Chris Namovicz
  • Participants: TBD

Activity No. 3 – New Empirical Work on Elasticities

  • Goals: Update outdated work on price elasticities, because it is very important and impacts model results substantially. In doing so, need to distinguish between short-term and long-term elasticities, because they are very different
  • Current related activities:
    • ORNL/David Greene is doing a lot on transportation market elasticities
    • Goldman et al. for demand response
    • California pilot projects attempted to define consumer demand
    • Workshop breakout session on behavioral response (H)
  • Next steps:
    • Create a process to improve information on price elasticities for all energy technologies and demand response technologies in energy models (not specificity in the model)
    • Incorporate the new data into the models (be sure to consider model incorporation from the start, to consider best form of information; ease of incorporation)
    • Hold a call to discuss next steps
  • Lead: DOE-EERE-PAE
  • Participants: EPRI?, DOE-EIA, NETL?

Activity No. 4 – Improve link between data-producers and model developers

  • Goal: Address the disconnect between data-producers and model-developers (and potentially model-users as well)
    • Some producers of data may make an effort to get the model [restructured to] to include their data.
    • But generally, there is far too little linkage between the two, and no effective way for data-users (esp. modelers) to "express their latent demand" for better data.
    • So instead of trying to come up with prescriptive solutions, maybe we should focus more on process reforms and rethinking relationships?
  • Current related activities: EPA is having a forum next month on reflecting technology changes in modeling (Pete Wilcox, Alan Sanstad, others...)
  • Next steps:
    • Attend EPA workshop
    • Identify missing participants (either data-producers or model developers)
    • Create a communication mechanism to begin to link the parties.
  • Lead: TBD
  • Participant: TBD

 

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