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Bewertung und Steuerung von Kraftwerksscheiben

  • Markt, Handel und Risikomanagement
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Zeitschrift für Energiewirtschaft Aims and scope Submit manuscript

Zusammenfassung

In diesem Artikel werden zunächst einleitend das traditionelle Bewertungsverfahren der Discounted Cashflow Methodik sowie die Realoptionsmethodik zur Bewertung und letztlich Steuerung von Kraftwerken bzw. Kraftwerksscheiben skizziert. Hierauf aufbauend wird ein Fall beschrieben, der in den folgenden Abschnitten behandelt wird. Zur Bewertung der Kraftwerksscheibe als Realoption wird daher nach der Fallbeschreibung ein kurzer überblick über die stochastische Modellierung der Marktpreise gegeben. Es wird dabei davon ausgegangen, dass sowohl Brennstoffpreise als auch Strompreise stochastische Variablen sind. Danach wird der in diesem Artikel verwendete Ansatz der Least Squares Monte-Carlo-Methodik skizziert und die Kraftwerksscheibe entsprechend der Fallbeschreibung modelliert. Die Ergebnisse illustrieren den Mehrwert durch die Betrachtung der Kraftwerksscheibe als Realoption und demonstrieren den praktischen Einsatz der Methodik zur Steuerung der Kraftwerke.

Abstract

To start off, in this article the common approaches of the discounted cash flow methodology as well as the real options methodology for the evaluation of power plant dispatch, or the dispatch of power plant stakes, are outlined. For the evaluation of the power plant stake as a real option there is initially a description of the case study, followed by an overview of the stochastic modelling of market prices. It is assumed that fuel prices as well as electricity prices are stochastic variables. Then the Least Squares Monte Carlo methodology used in this article is outlined and the power plant stake modelled according to the case study description. The results illustrate the added value created by regarding the power plant stake as a real option and demonstrate the practical use of the methodology for the dispatch of power plants. for allowances interact with bidding strategies and optimal institutional design.

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Literaturverzeichnis

  1. Bertsekas, D. (2005): Dynamic Programming and Optimal Control, Vol.1, 3.ed, Athena Scientific

  2. Borchert, J., Schemm, R., Korth, S. (2006): Stromhandel — Institutionen, Marktmodelle, Pricing und Risikomanagement

  3. Carmona, R., Durrleman V. (2003): Pricing and Hedging Spread Options, SIAM Review, Vol. 45, No. 4, 627–685

    Article  MATH  MathSciNet  Google Scholar 

  4. Clewlow, L., Strickland, C. (2000): Energy Derivatives: Pricing and Risk Management, Lacima Publications, London

    Google Scholar 

  5. Deng, S., Xia, Z. (2005): Pricing and Hedging Electricity Supply contracts: a Case with Tolling Agreements, Georgia Institute of Technology

  6. Deng, S., Johnson, B., Sogomonian, A. (2001): Exotic electricity options and the valuation of electricity generation and transmission assets, Decision Support Systems 30(2001), 383–392

    Google Scholar 

  7. Deng, S., Xia, Z. (2005): Pricing and Hedging Electricity Supply contracts: a Case with Tolling Agreements, Georgia Institute of Technology

  8. Dias, M.A., Rocha K.M. (1999): Petroleum Concessions With Extendible Options Using Mean Reversion, Paper for 3rd International Conference on Real Options

  9. Dixit, A.K., Pindyck, R.S. (1994): Investment under Uncertainty, Princeton University Press

  10. Gubina A., Ilic M., Skantze P. (2000): Bid-Based Stochastic Model for Electricity Prices: The Impact of Fundamental Drivers on Market Dynamics, MIT Laboratory

  11. Hull, J.C. (2003): Options, Futures, and Other Derivatives, Third ed., Pearson

  12. Kloeden, P.E., Platen, E. (1999): Numerical Solution of Stochastic Differential Equations, Springer

  13. Longstaff, F.A., Schwartz, E.S. (2001): Valuing American Options by Simulation: A Simple Least-Squares Approach, Finance, May 9, 2001, Paper 1-01

  14. Schwartz, E. S., (1997): The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging, The Journal Of Finance, Vol LII, No.3, July 1997

  15. Schwartz, E. S., Smith, J.E. (2000): Short-Term Variations and Long-Term Dynamics in Commodity Prices, Management Science, Vol.46, No. 7, July 2000, 893–911

    Article  Google Scholar 

  16. Skantze, P., Gubina, A., Ilic, M. (2000): Bid-based Stochastic Model for Electricity Prices: The Impact of Fundamental Drivers on Market Dynamics, MIT Energy Laboratory Technical Report EL 00-004, Cambridge, Massachusetts

  17. Tavella, D., Randall C. (2000): Pricing Financial Instruments — The Finite Difference Method, John Wiley & Sons Inc.

  18. Tikhonov, A.N., Goncharsky A.V. et al. (1995): Numerical Methods for the Solution of Ill-Posed Problems, Kluwer Academic Publishers, Dordrecht

    MATH  Google Scholar 

  19. Villaplana, P. (2002): Pricing Power Derivatives: A Two-Factor Jump-Diffusion Approach, Working Paper

  20. Weron, R. (2006): Modeling and forecasting electricity loads and prices, John Wiley & Sons Ltd.

  21. Wilmott, P. (2006): Paul Wilmott on Quantitative Finance, John Wiley & Sons Ltd.

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Correspondence to Jörg Borchert.

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Dr. Jörg Borchert ist Berater bei der BET GmbH in Aachen

Dipl. Vw. Marc Hasenbeck ist Gesellschafter der price it in Halle und Doktorand an der Universität Halle

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Borchert, J., Hasenbeck, M. Bewertung und Steuerung von Kraftwerksscheiben. ZS Energ. Wirtsch. 33, 115–126 (2009). https://doi.org/10.1007/s12398-009-0014-0

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  • DOI: https://doi.org/10.1007/s12398-009-0014-0

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