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A stochastic fuel switching model for electricity prices

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  • Zachmann, Georg

Abstract

This paper develops and applies a novel electricity price model. We reproduce the merit order of a thermal-dominated electricity system by establishing a non-linear dependency of wholesale electricity prices on the prices of fuels (coal and natural gas) and of CO2 emission allowances. The coefficients are estimated using a Markov Switching Regression.

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  • Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
    • Handle: RePEc:eee:eneeco:v:35:y:2013:i:c:p:5-13
    DOI: 10.1016/j.eneco.2012.06.019
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    3. Alasseur, C. & Féron, O., 2018. "Structural price model for coupled electricity markets," Energy Economics, Elsevier, vol. 75(C), pages 104-119.
    4. Minggang Wang & Chenyu Hua & Hua Xu, 2022. "Dynamic Linkages among Carbon, Energy and Financial Markets: Multiplex Recurrence Network Approach," Mathematics, MDPI, vol. 10(11), pages 1-23, May.
    5. López Prol, Javier & Steininger, Karl W. & Zilberman, David, 2020. "The cannibalization effect of wind and solar in the California wholesale electricity market," Energy Economics, Elsevier, vol. 85(C).
    6. Cyril Martin de Lagarde & Frédéric Lantz, 2017. "Impact of Variable Renewable Production on Electriciy Prices in Germany : A Markov Switching Model," Working Papers hal-03187020, HAL.
    7. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    8. Gerster, Andreas, 2016. "Negative price spikes at power markets: The role of energy policy," Ruhr Economic Papers 636, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    9. Andreas Gerster, 2016. "Negative price spikes at power markets: the role of energy policy," Journal of Regulatory Economics, Springer, vol. 50(3), pages 271-289, December.
    10. Tang, Chun & Liu, Xiaoxing & Chen, Guangkun, 2023. "The spillover effects in the “Energy – Carbon – Stock” system – Evidence from China," Energy, Elsevier, vol. 278(PA).
    11. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    12. Xu, Yingying & Shao, Xuefeng & Tanasescu, Cristina, 2024. "How are artificial intelligence, carbon market, and energy sector connected? A systematic analysis of time-frequency spillovers," Energy Economics, Elsevier, vol. 132(C).
    13. Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
    14. Weiliang Lu & Alexis Arrigoni & Anatoliy Swishchuk & Stéphane Goutte, 2021. "Modelling of Fuel- and Energy-Switching Prices by Mean-Reverting Processes and Their Applications to Alberta Energy Markets," Mathematics, MDPI, vol. 9(7), pages 1-24, March.
    15. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    16. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    17. Martin de Lagarde, Cyril & Lantz, Frédéric, 2018. "How renewable production depresses electricity prices: Evidence from the German market," Energy Policy, Elsevier, vol. 117(C), pages 263-277.
    18. Tang, Chun & Yang, Guangyi & Liu, Xiaoxing, 2024. "Risk spillover within the carbon-energy system – New evidence considering China's national carbon market," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1227-1240.
    19. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    20. Julien Chevallier & Stéphane Goutte, 2017. "Estimation of Lévy-driven Ornstein–Uhlenbeck processes: application to modeling of $$\hbox {CO}_2$$ CO 2 and fuel-switching," Annals of Operations Research, Springer, vol. 255(1), pages 169-197, August.
    21. Antoine Ferré & Guillaume de Certaines & Jérôme Cazelles & Tancrède Cohet & Arash Farnoosh & Frédéric Lantz, 2021. "Short-term electricity price forecastingmodels comparative analysis : Machine Learning vs. Econometrics," Working Papers hal-03262208, HAL.

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    More about this item

    Keywords

    Electricity prices; Markov switching models;

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection

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