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A survey of stochastic modelling approaches for liberalised electricity markets

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  • Möst, Dominik
  • Keles, Dogan

Abstract

Liberalisation of energy markets, climate policy and the promotion of renewable energy have changed the framework conditions of the formerly strictly regulated energy markets. Generating companies are mainly affected by these changing framework conditions as they are exposed to the different risks from liberalised energy markets in combination with huge and largely irreversible investments. Uncertainties facing generating companies include: the development of product prices for electricity as well as for primary energy carriers; technological developments; availability of power plants; the development of regulation and political context, as well as the behaviour of competitors. The need for decision support tools in the energy business, mainly based on operation research models, has therefore significantly increased. Especially to cope with different uncertain parameters, several stochastic modelling approaches have been developed in the last few years for liberalised energy markets. In this context, the present paper aims to give an overview and classification of stochastic models dealing with price risks in electricity markets. The focus is thereby placed on various stochastic methods developed in operation research with practical relevance and applicability, including the concepts of: - stochastic processes for commodity prices (especially for electricity); - scenario generation and reduction, which is important due to the need for a structured handling of large data amounts; as well as - stochastic optimising models for investment decisions, short- and mid-term power production planning and long-term system optimisation. The approaches within the energy business are classified according to the above structure. The practical relevance of the different methods and their applicability to real markets is thereby of crucial importance. Shortcomings of existing approaches and open issues that should be addressed by operation research are also discussed.

Suggested Citation

  • Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    • Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:543-556
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    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    2. Christoph Weber, 2005. "Uncertainty in the Electric Power Industry," International Series in Operations Research and Management Science, Springer, number 978-0-387-23048-1, December.
    3. Bowden, Nicholas & Payne, James E., 2008. "Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models," Energy Economics, Elsevier, vol. 30(6), pages 3186-3197, November.
    4. Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
    5. Hahn, Heiko & Meyer-Nieberg, Silja & Pickl, Stefan, 2009. "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, Elsevier, vol. 199(3), pages 902-907, December.
    6. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    7. Troncoso, Alicia & Riquelme, Jose C. & Aguilar-Ruiz, Jesus S. & Riquelme Santos, Jesus M., 2008. "Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1114-1127, March.
    8. SMEERS, Yves, 1997. "Computable equilibrium models and the restructuring of the European electricity and gas markets," LIDAM Discussion Papers CORE 1997061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Yves Smeers, 1997. "Computable Equilibrium Models and the Restructuring of the European Electricity and Gas Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-31.
    10. Gibson, Rajna & Schwartz, Eduardo S, 1990. "Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
    11. Krey, Volker & Martinsen, Dag & Wagner, Hermann-Josef, 2007. "Effects of stochastic energy prices on long-term energy-economic scenarios," Energy, Elsevier, vol. 32(12), pages 2340-2349.
    12. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    13. Patrick Jaillet & Ehud I. Ronn & Stathis Tompaidis, 2004. "Valuation of Commodity-Based Swing Options," Management Science, INFORMS, vol. 50(7), pages 909-921, July.
    14. Finon, Dominique, 1974. "Optimisation model for the French energy sector," Energy Policy, Elsevier, vol. 2(2), pages 136-151, June.
    15. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    16. Olsina, Fernando & Roscher, Mark & Larisson, Carlos & Garces, Francisco, 2007. "Short-term optimal wind power generation capacity in liberalized electricity markets," Energy Policy, Elsevier, vol. 35(2), pages 1257-1273, February.
    17. Barreto, Leonardo & Kypreos, Socrates, 2004. "Emissions trading and technology deployment in an energy-systems "bottom-up" model with technology learning," European Journal of Operational Research, Elsevier, vol. 158(1), pages 243-261, October.
    18. Stein W. Wallace & Stein-Erik Fleten, 2002. "Stochastic programming in energy," GE, Growth, Math methods 0201001, University Library of Munich, Germany, revised 13 Nov 2003.
    19. Loren W. Tauer, 1983. "Target MOTAD," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(3), pages 606-610.
    20. Smeers, Y., 1997. "Computable equilibrium models and the restructuring of the European electricity and gas markets," LIDAM Reprints CORE 1280, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. Blyth, William & Bradley, Richard & Bunn, Derek & Clarke, Charlie & Wilson, Tom & Yang, Ming, 2007. "Investment risks under uncertain climate change policy," Energy Policy, Elsevier, vol. 35(11), pages 5766-5773, November.
    22. Chung-Li Tseng & Graydon Barz, 2002. "Short-Term Generation Asset Valuation: A Real Options Approach," Operations Research, INFORMS, vol. 50(2), pages 297-310, April.
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