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LCOE models: A comparison of the theoretical frameworks and key assumptions

Listed author(s):
  • John Foster

    ()

    (School of Economics, University of Queensland)

  • Liam Wagner

    ()

    (School of Economics, University of Queensland)

  • Alexandra Bratanova

    (School of Economics, University of Queensland)

LCOE models are widely applied at national and regional levels for the energy systems design, energy generation projections and technology assessment. Although LCOE is a well developed and standard technique in the energy sector economics, authors approach model construction in different ways to ensure the model matches research tasks and data availability. The LCOE model is interdependent with the data availability – data determines the construction of LCOE model and vice-versa – LCOE model defines what data is required for calculations. However, adjustments made to the standard LCOE comes at a price of limited comparability of the outcomes from the different models. The following section introduces few well known LCOE models developed for national governments with further comparison of basic assumptions in order to determine theoretical framework and datasets to be allied in the project. The next section then will provide the results of comparative analysis of the LCOE models key assumptions, concentrating on capital costs, discount rates and technology learning curves.

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File URL: http://www.uq.edu.au/eemg/docs/workingpapers/2014-4.pdf
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Paper provided by School of Economics, University of Queensland, Australia in its series Energy Economics and Management Group Working Papers with number 4-2014.

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Date of creation: Jul 2014
Handle: RePEc:qld:uqeemg:4-2014
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  1. Liam Wagner & John Foster, 2011. "Is There an Optimal Entry Time for Carbon Capture and Storage? A Case Study for Australia's National Electricity Market," Energy Economics and Management Group Working Papers 07, School of Economics, University of Queensland, Australia.
  2. Andreas Schröder & Friedrich Kunz & Jan Meiss & Roman Mendelevitch & Christian von Hirschhausen, 2013. "Current and Prospective Costs of Electricity Generation until 2050," Data Documentation 68, DIW Berlin, German Institute for Economic Research.
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