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Forecasting the distributions of hourly electricity spot prices

Author

Listed:
  • Christian Pape
  • Arne Vogler
  • Oliver Woll
  • Christoph Weber

    (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen (Campus Essen))

Abstract

We present a stochastic modelling approach to describe the dynamics of hourly electricity prices. The suggested methodology is a stepwise combination of several mathematical operations to adequately characterize the distribution of electricity spot prices. The basic idea is to analyze day-ahead prices as panel of 24 cross-sectional hours and to identify principal components of hourly prices to account for the cross correlation between hours. Moreover, non-normality of residuals is addressed by performing a normal quantile transformation and specifying appropriate stochastic processes for time series before fit. We highlight the importance of adequate distributional forecasts and present a framework to evaluate the distribution forecast accuracy. The application for German electricity prices 2015 reveal that: (i) An autoregressive specification of the stochastic component delivers the best distribution but not always the best point forecasting results. (ii) Only a complete evaluation of point, interval and density forecast, including formal statistical tests, can ensure a correct model choice.

Suggested Citation

  • Christian Pape & Arne Vogler & Oliver Woll & Christoph Weber, 2017. "Forecasting the distributions of hourly electricity spot prices," EWL Working Papers 1705, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised May 2017.
    • Handle: RePEc:dui:wpaper:1705
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Arne Vogler & Florian Ziel, "undated". "On The Evaluation Of Binary Event Probability Predictions In Electricity Price Forecasting," EWL Working Papers 1911, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    2. 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.
    3. Andreas Dietrich & Christian Furtwängler & Christoph Weber, "undated". "Thesenpapier: Managing combined power and heat portfolios in sequential spot power markets under uncertainty," EWL Working Papers 2003, University of Duisburg-Essen, Chair for Management Science and Energy Economics.

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    More about this item

    Keywords

    Distribution forecasts; Electricity; Price forecasting; Panel data; Statistical tests;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • N74 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Europe: 1913-

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