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Fuel mix diversification incentives in liberalised electricity markets: a Mean-Variance Portfolio Theory Approach

Author

Listed:
  • Fabien A. Roques

    (International Energy Agency, Economic Analysis Division, Judge Business School, University of Cambridge)

  • David M. Newbery

    (Department of Applied Economics, University of Cambridge)

  • William J. Nuttall

    (Judge Business School, University of Cambridge)

Abstract

Monte Carlo simulations of gas, coal and nuclear plant investment returns are used as inputs of a Mean-Variance Portfolio optimization to identify optimal base load generation portfolios for large electricity generators in liberalized electricity markets. We study the impact of fuel, electricity, and CO2 price risks and their degree of correlation on optimal plant portfolios. High degrees of correlation between gas and electricity prices - as observed in most European markets - reduce gas plant risks and make portfolios dominated by gas plant more attractive. Long-term power purchase contracts and/or a lower cost of capital can rebalance optimal portfolios towards more diversified portfolios with larger shares of nuclear and coal plants.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Fabien A. Roques & David M. Newbery & William J. Nuttall, 2006. "Fuel mix diversification incentives in liberalised electricity markets: a Mean-Variance Portfolio Theory Approach," Working Papers EPRG 0626, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg0626
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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