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A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies

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  • Hayward, Jennifer A.
  • Graham, Paul W.

Abstract

A global and local learning model (GALLM) has been developed to project the cost and global uptake of different electricity generation technologies to the year 2050. This model features three regions, endogenous technological learning within and across those regions, various government policies to facilitate technological learning and a penalty constraint which is used to mimic the effect market forces play on the capital cost of electricity generation technologies. This constraint has been added as market forces have been a strong factor in technology pricing in recent years. Global, regional and component experience curves have been developed for some technologies. The model, with the inclusion of these features, projects a diverse range of technologies contributing to global electricity generation under a carbon price scenario. The penalty constraint leads to gradual and continual installations of technologies and because the constraint provides a disincentive to install too much of a technology, it reduces the impact of uncertainty in the learning rate. Alternative forms of the penalty constraint were tested for their suitability; it was found that, with a zero and lower-cost version of the constraint, photovoltaics are installed in a boom-and-bust cycle, which is not supported by past experience. When the constraint is set at a high level, there are fewer installations.

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  • Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
    • Handle: RePEc:eee:eneeco:v:40:y:2013:i:c:p:537-548
    DOI: 10.1016/j.eneco.2013.08.010
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    Cited by:

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    8. Graham, Paul W. & Brinsmead, Thomas & Hatfield-Dodds, Steve, 2015. "Australian retail electricity prices: Can we avoid repeating the rising trend of the past?," Energy Policy, Elsevier, vol. 86(C), pages 456-469.
    9. Dali T. Laxton, 2019. "Innovations in the Wind Energy Sector," CERGE-EI Working Papers wp647, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
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    12. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
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    More about this item

    Keywords

    Energy economics; Economic modelling; Learning curves; Experience curves; Capital cost;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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