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Gas-fired power plants: Investment timing, operating flexibility and CO2 capture

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  • Fleten, Stein-Erik
  • Näsäkkälä, Erkka

Abstract

We analyze investments in gas-fired power plants based on stochastic electricity and natural gas prices. A simple but realistic two-factor model is used for price processes, enabling analysis of the value of operating flexibility, the opportunity to abandon the capital equipment, as well as finding thresholds for energy prices for which it is optimal to enter into the investment. We develop a method to compute upper and lower bounds on plant values and investment threshold levels. Our case study uses representative power plant investment and operations data, and historical forward prices from well-functioning energy markets. We find that when the decision to build is considered, the abandonment option does not have significant value, whereas the operating flexibility and time-to-build option have significant effect on the building threshold. Furthermore, the joint value of the operating flexibility and the abandonment option is much smaller than the sum of their separate values, because both are options to shut down. The effects of emission costs on the value of installing CO2 capture technology are also analyzed.

Suggested Citation

  • Fleten, Stein-Erik & Näsäkkälä, Erkka, 2010. "Gas-fired power plants: Investment timing, operating flexibility and CO2 capture," Energy Economics, Elsevier, vol. 32(4), pages 805-816, July.
  • Handle: RePEc:eee:eneeco:v:32:y:2010:i:4:p:805-816
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    References listed on IDEAS

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    1. Siddiqui, Afzal S. & Maribu, Karl, 2009. "Investment and upgrade in distributed generation under uncertainty," Energy Economics, Elsevier, vol. 31(1), pages 25-37, January.
    2. Majd, Saman & Pindyck, Robert S., 1987. "Time to build, option value, and investment decisions," Journal of Financial Economics, Elsevier, vol. 18(1), pages 7-27, March.
    3. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    4. Abadie, Luis M. & Chamorro, José M., 2008. "Valuing flexibility: The case of an Integrated Gasification Combined Cycle power plant," Energy Economics, Elsevier, vol. 30(4), pages 1850-1881, July.
    5. David Heath & Robert Jarrow & Andrew Morton, 2008. "Bond Pricing And The Term Structure Of Interest Rates: A New Methodology For Contingent Claims Valuation," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 13, pages 277-305, World Scientific Publishing Co. Pte. Ltd..
    6. Erkka Näsäkkälä & Stein‐Erik Fleten, 2005. "Flexibility and technology choice in gas fired power plant investments," Review of Financial Economics, John Wiley & Sons, vol. 14(3-4), pages 371-393.
    7. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    8. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    9. Denny Ellerman, 1998. "Note on The Seemingly Indefinite Extension of Power Plant Lives, A Panel Contribution," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    10. Robert McDonald & Daniel Siegel, 1986. "The Value of Waiting to Invest," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(4), pages 707-727.
    11. Chung-Li Tseng & Kyle Y. Lin, 2007. "A Framework Using Two-Factor Price Lattices for Generation Asset Valuation," Operations Research, INFORMS, vol. 55(2), pages 234-251, April.
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