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Forecasting the Price Distribution of Continuous Intraday Electricity Trading

Janke, Tim ; Steinke, Florian (2019)
Forecasting the Price Distribution of Continuous Intraday Electricity Trading.
In: Energies, 12 (22)
doi: 10.3390/en12224262
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

The forecasting literature on intraday electricity markets is scarce and restricted to the analysis of volume-weighted average prices. These only admit a highly aggregated representation of the market. Instead, we propose to forecast the entire volume-weighted price distribution. We approximate this distribution in a non-parametric way using a dense grid of quantiles. We conduct a forecasting study on data from the German intraday market and aim to forecast the quantiles for the last three hours before delivery. We compare the performance of several linear regression models and an ensemble of neural networks to several well designed naive benchmarks. The forecasts only improve marginally over the naive benchmarks for the central quantiles of the distribution which is in line with the latest empirical results in the literature. However, we are able to significantly outperform all benchmarks for the tails of the price distribution.

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Janke, Tim ; Steinke, Florian
Art des Eintrags: Bibliographie
Titel: Forecasting the Price Distribution of Continuous Intraday Electricity Trading
Sprache: Englisch
Publikationsjahr: 8 November 2019
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Energies
Jahrgang/Volume einer Zeitschrift: 12
(Heft-)Nummer: 22
DOI: 10.3390/en12224262
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Kurzbeschreibung (Abstract):

The forecasting literature on intraday electricity markets is scarce and restricted to the analysis of volume-weighted average prices. These only admit a highly aggregated representation of the market. Instead, we propose to forecast the entire volume-weighted price distribution. We approximate this distribution in a non-parametric way using a dense grid of quantiles. We conduct a forecasting study on data from the German intraday market and aim to forecast the quantiles for the last three hours before delivery. We compare the performance of several linear regression models and an ensemble of neural networks to several well designed naive benchmarks. The forecasts only improve marginally over the naive benchmarks for the central quantiles of the distribution which is in line with the latest empirical results in the literature. However, we are able to significantly outperform all benchmarks for the tails of the price distribution.

Freie Schlagworte: electricity price forecasting, intraday markets, lasso regression, neural networks
Zusätzliche Informationen:

This article belongs to the Special Issue Modeling and Forecasting Intraday Electricity Markets

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Energieinformationsnetze und Systeme (EINS)
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik
Hinterlegungsdatum: 13 Nov 2019 14:29
Letzte Änderung: 12 Mär 2024 10:16
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