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Prediction of extreme price occurrences in the German day-ahead electricity market

Author

Listed:
  • Lars Ivar Hagfors
  • Hilde Hørthe Kamperud
  • Florentina Paraschiv
  • Marcel Prokopczuk
  • Alma Sator
  • Sjur Westgaard

Abstract

Understanding the mechanisms that drive extreme negative and positive prices in day-ahead electricity prices is crucial for managing risk and market design. In this paper, we consider the problem of understanding how fundamental drivers impact the probability of extreme price occurrences in the German day-ahead electricity market. We develop models using fundamental variables to predict the probability of extreme prices. The dynamics of negative prices and positive price spikes differ greatly. Positive spikes are related to high demand, low supply and high prices the previous days, and mainly occur during the morning and afternoon peak hours. Negative prices occur mainly during the night and are closely related to low demand combined with high wind production levels. Furthermore, we do a closer analysis of how renewable energy sources, hereby photovoltaic and wind power, impact the probability of negative prices and positive spikes. The models confirm that extremely high and negative prices have different drivers, and that wind power is particularly important in relation to negative price occurrences. The models capture the main drivers of both positive and negative extreme price occurrences and perform well with respect to accurately forecasting the probability with high levels of confidence. Our results suggest that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets.

Suggested Citation

  • Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
  • Handle: RePEc:taf:quantf:v:16:y:2016:i:12:p:1929-1948
    DOI: 10.1080/14697688.2016.1211794
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    2. repec:eee:appene:v:210:y:2018:i:c:p:604-612 is not listed on IDEAS
    3. repec:gam:jeners:v:11:y:2018:i:8:p:2039-:d:162196 is not listed on IDEAS
    4. repec:eee:eneeco:v:70:y:2018:i:c:p:396-420 is not listed on IDEAS
    5. Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
    6. Bartosz Uniejewski & Rafał Weron, 2018. "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models," Energies, MDPI, Open Access Journal, vol. 11(8), pages 1-26, August.

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