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Optimal Abandonment of EU Coal-fired Stations

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Author Info

  • Luis M. Abadie
  • José; M. Chamorro
  • Mikel González-Eguino

Abstract

Coal-fired power plants face potential difficulties in a carbon constrained world. The traditional advantage of coal as a cheaper fuel may erode in the future if CO2 allowance prices increase. When would it be optimal to abandon a coal station and obtain its salvage value? We assess this question following the Real Options approach. We consider the case of a coal plant that operates in a deregulated electricity market where natural gas-fired plants are the marginal units. We assume specific stochastic processes for the fundamental uncertainties in our model: coal price, natural gas price, and emission allowance price. The underlying parameters are derived from actual futures markets. They are further used in a three-dimensional binomial lattice to assess the decision to abandon. We draw the optimal exercise boundary. Sensitivity analyses (regarding fuel prices, allowance price, volatilities, useful life, residual value, thermal efficiency, safety valves in carbon prices, time step) are also undertaken.

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Bibliographic Info

Article provided by International Association for Energy Economics in its journal The Energy Journal.

Volume (Year): Volume 32 (2011)
Issue (Month): Number 3 ()
Pages: 175-208

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Handle: RePEc:aen:journl:32-3-a07

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Cited by:
  1. Abdullah Almansour & Margaret Insley, 2013. "The impact of stochastic extraction cost on the value of an exhaustible resource: An application to the Alberta oil sands," Working Papers 1303, University of Waterloo, Department of Economics, revised Jun 2013.
  2. Rohlfs, Wilko & Madlener, Reinhard, 2011. "Multi-Commodity Real Options Analysis of Power Plant Investments: Discounting Endogenous Risk Structures," FCN Working Papers 22/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  3. Luis M. Abadie & Ibon Galarraga & Dirk Rübbelke, 2013. "Evaluation of Two Alternative Carbon Capture and Storage Technologies: A Stochastic Model," Working Papers 2013-07, BC3.

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