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Modelling German electricity wholesale spot prices with a parsimonious fundamental model – Validation & application

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  • Beran, Philip
  • Pape, Christian
  • Weber, Christoph

Abstract

In this paper, we introduce a parsimonious fundamental model for the German day-ahead market. The methodology approximates the supply stack by a piecewise linear function and considers fundamental information, e.g. power plant availabilities, must-run production and cross-border exchange. We reduce complexity by considering technology classes, uncoupled time periods and only one market area. The model accurately reproduces the hourly historical prices and electricity production volumes for most thermal production units in Germany. In a case study, we investigate the effects of the German nuclear phase-out decision. We find an additional price decrease and reduced electricity imports in the counterfactual scenario.

Suggested Citation

  • Beran, Philip & Pape, Christian & Weber, Christoph, 2019. "Modelling German electricity wholesale spot prices with a parsimonious fundamental model – Validation & application," Utilities Policy, Elsevier, vol. 58(C), pages 27-39.
    • Handle: RePEc:eee:juipol:v:58:y:2019:i:c:p:27-39
    DOI: 10.1016/j.jup.2019.01.008
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    Citations

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    Cited by:

    1. Xiong, Bobby & Predel, Johannes & Crespo del Granado, Pedro & Egging-Bratseth, Ruud, 2021. "Spatial flexibility in redispatch: Supporting low carbon energy systems with Power-to-Gas," Applied Energy, Elsevier, vol. 283(C).
    2. Georg Wolff & Stefan Feuerriegel, 2019. "Emissions Trading System of the European Union: Emission Allowances and EPEX Electricity Prices in Phase III," Energies, MDPI, vol. 12(15), pages 1-15, July.
    3. Felten, Björn, 2020. "An integrated model of coupled heat and power sectors for large-scale energy system analyses," Applied Energy, Elsevier, vol. 266(C).
    4. Croonenbroeck, Carsten & Palm, Marcel, 2020. "A spatio-temporal Durbin fixed effects IV-Model for ENTSO-E electricity flows analysis," Renewable Energy, Elsevier, vol. 148(C), pages 205-213.
    5. Valentin Mahler & Robin Girard & Georges Kariniotakis, 2021. "Data-driven Structural Modeling of Electricity Price Dynamics," Working Papers hal-03445396, HAL.
    6. Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
    7. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2020. "The impact of the integration of renewable energy sources in the electricity price formation: is the Merit-Order Effect occurring in Portugal?," Utilities Policy, Elsevier, vol. 66(C).
    8. Ozan Korkmaz & Bihrat Önöz, 2022. "Modelling the Potential Impacts of Nuclear Energy and Renewables in the Turkish Energy System," Energies, MDPI, vol. 15(4), pages 1-25, February.
    9. Germeshausen, Robert & Wölfing, Nikolas, 2020. "How marginal is lignite? Two simple approaches to determine price-setting technologies in power markets," Energy Policy, Elsevier, vol. 142(C).
    10. Philip Beran & Arne Vogler, 2021. "Multi-Day-Ahead Electricity Price Forecasting: A Comparison of fundamental, econometric and hybrid Models," EWL Working Papers 2102, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2021.

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