Janke, Tim ; Steinke, Florian (2023)
Forecasting the Price Distribution of Continuous Intraday Electricity Trading.
In: Energies, 2019, 12 (22)
doi: 10.26083/tuprints-00015734
Artikel, Zweitveröffentlichung, Verlagsversion
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
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: | 2023 |
| Autor(en): | Janke, Tim ; Steinke, Florian |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Forecasting the Price Distribution of Continuous Intraday Electricity Trading |
| Sprache: | Englisch |
| Publikationsjahr: | 4 Dezember 2023 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2019 |
| Ort der Erstveröffentlichung: | Basel |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Energies |
| Jahrgang/Volume einer Zeitschrift: | 12 |
| (Heft-)Nummer: | 22 |
| Kollation: | 14 Seiten |
| DOI: | 10.26083/tuprints-00015734 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/15734 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| 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 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-157345 |
| Zusätzliche Informationen: | This article belongs to the Special Issue Modeling and Forecasting Intraday Electricity Markets |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 621.3 Elektrotechnik, Elektronik |
| 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: | 04 Dez 2023 10:23 |
| Letzte Änderung: | 12 Mär 2024 10:16 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Forecasting the Price Distribution of Continuous Intraday Electricity Trading. (deposited 04 Dez 2023 10:23) [Gegenwärtig angezeigt]
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