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Valuing Flexibilities in Power Systems as Optionalities

In: Economics of Power Systems

Author

Listed:
  • Christoph Weber

    (University of Duisburg-Essen)

  • Dominik Möst

    (TU Dresden)

  • Wolf Fichtner

    (Karlsruhe Institute of Technology (KIT))

Abstract

Flexibilities and optionalities in electricity systems are getting increasingly relevant in electricity systems for two reasons: first, the financial trading of electricity products which leads to consider flexibilities in physical assets, like power plants, analogously to financial contracts with flexibilities, namely as “real options”. Second, with the increasing shares of fluctuating renewables, there is a substantial threat of lacking flexibility. More flexibility may be needed when forecast errors increase while the shares of controllable conventional power plants decline in parallel. The chapter starts with the financial perspective on flexibilities. This includes modelling prices as stochastic processes, e.g. as Ornstein-Uhlenbeck process. The concept of the hourly price forward curve to link future and spot prices in electricity markets is then introduced. These elements form the basis for a first simple option valuation approach. A digression to financial options and the seminal Black-Scholes model follows. Assumptions as well as merits and limits of this approach for electricity markets are thereby scrutinised. The modelling of thermal and hydropower plants as options is subsequently developed. An application example shows how the method enables to identify the intrinsic value and the time value of power plants. Finally, the challenge to combine this asset valuation with the system perspective is addressed.

Suggested Citation

  • Christoph Weber & Dominik Möst & Wolf Fichtner, 2022. "Valuing Flexibilities in Power Systems as Optionalities," Springer Texts in Business and Economics, in: Economics of Power Systems, chapter 0, pages 357-386, Springer.
  • Handle: RePEc:spr:sptchp:978-3-030-97770-2_11
    DOI: 10.1007/978-3-030-97770-2_11
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