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Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

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Author Info

  • John Foster

    ()
    (Department of Economics, University of Queensland)

  • Liam Wagner

    ()
    (Department of Economics, University of Queensland)

  • Phil Wild

    ()
    (Department of Economics, University of Queensland)

  • Junhua Zhao

    (Department of Economics, University of Queensland)

  • Lucas Skoofa
  • Craig Froome

    ()

Abstract

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.

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File URL: http://www.uq.edu.au/eemg/docs/workingpapers/09.pdf
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Bibliographic Info

Paper provided by School of Economics, University of Queensland, Australia in its series Energy Economics and Management Group Working Papers with number 09.

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Date of creation: Dec 2011
Date of revision:
Handle: RePEc:qld:uqeemg:09

Contact details of provider:
Postal: St. Lucia, Qld. 4072
Phone: +61 7 3365 6570
Fax: +61 7 3365 7299
Email:
Web page: http://www.uq.edu.au/eemg
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Related research

Keywords: Distributed Generation. Energy Economics; Electricity Markets; Renewable Energy;

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