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The RES-Induced Switching Effect Across Fossil Fuels: An Analysis of Day-Ahead and Balancing Prices

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  • Angelica Gianfreda, Lucia Parisio, and Matteo Pelagatti

Abstract

The empirical literature on electricity markets has highlighted a strong cointegrating relationship governing the dynamics of electricity and fuel prices. More recently the massive introduction of RES in electricity generation, fostered by generous supporting schemes, has influenced the shape and position of the supply function and consequently the equilibrium prices. We believe that the new competitive scenario may have influenced the fuel-electricity nexus with a different impact in day-ahead and balancing markets. Empirical evidence of the evolving fuels-electricity nexus is shown looking at one Italian zone across two samples characterized by a significant change in the level of RES penetration. We conduct the analysis taking into account both day-ahead and, for the first time, balancing market sessions. Results indicate that fuel prices are much less relevant in determining the dynamics of electricity prices in recent years characterized by high RES penetration. On the contrary, taking into account flexible thermal sources, we show that in the second sample balancing and fuel prices (especially gas) are in a long run equilibrium.

Suggested Citation

  • Angelica Gianfreda, Lucia Parisio, and Matteo Pelagatti, 2019. "The RES-Induced Switching Effect Across Fossil Fuels: An Analysis of Day-Ahead and Balancing Prices," The Energy Journal, International Association for Energy Economics, vol. 0(The New E).
    • Handle: RePEc:aen:journl:ej40-si1-gianfreda
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    Cited by:

    1. Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020. "Comparing the forecasting performances of linear models for electricity prices with high RES penetration," International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
    2. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    3. Gianfreda, Angelica & Maranzano, Paolo & Parisio, Lucia & Pelagatti, Matteo, 2023. "Testing for integration and cointegration when time series are observed with noise," Economic Modelling, Elsevier, vol. 125(C).
    4. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
    5. Nazifi, Fatemeh & Trück, Stefan & Zhu, Liangxu, 2021. "Carbon pass-through rates on spot electricity prices in Australia," Energy Economics, Elsevier, vol. 96(C).

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    JEL classification:

    • F0 - International Economics - - General

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