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Impact of Operational Wind Generation in the Australian National Electricity Market over 2007-2012

Author

Listed:
  • Phil Wild

    () (Department of Economics, University of Queensland)

  • William Paul Bell

    () (Department of Economics, University of Queensland)

  • John Foster

    () (Department of Economics, University of Queensland)

Abstract

This paper investigates the effect of wind generation in the states comprising the Australian National Electricity Market (NEM). The methodology utilize an agent based model, which contains many features salient to the NEM including intra-state and inter-state transmission branches, regional location of generators and load centres and accommodation of unit commitment features. The model uses a Direct Current Optimal Power Flow (DC OPF) algorithm to determine optimal dispatch of generation plant, power flows on transmission branches and wholesale prices. We present results of the impact of wind generation on wholesale prices, dispatch patterns, carbon emissions and transmission network adequacy within the NEM.

Suggested Citation

  • Phil Wild & William Paul Bell & John Foster, 2014. "Impact of Operational Wind Generation in the Australian National Electricity Market over 2007-2012," Energy Economics and Management Group Working Papers 1-2014, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uqeemg:1-2014
    as

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    File URL: http://www.uq.edu.au/eemg/docs/workingpapers/2014-1.pdf
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    References listed on IDEAS

    as
    1. Phil Wild & William Paul Bell & John Foster, 2012. "An Assessment of the Impact of the Introduction of Carbon Price Signals on Prices, Production Trends, Carbon Emissions and Power Flows in the NEM for the period 2007-2009," Energy Economics and Management Group Working Papers 4-2012, School of Economics, University of Queensland, Australia.
    2. John Foster & William Paul Bell & Phil Wild & Deepak Sharma & Suwin Sandu & Craig Froome & Liam Wagner & Suchi Misra & Ravindra Bagia, 2013. "Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change," Energy Economics and Management Group Working Papers 6-2013, School of Economics, University of Queensland, Australia.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    carbon emissions; electricity prices; agent-based model; DC OPF Algorithm; wind generation; Australian National Electricity Market.;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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