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Forecasting the Price Distribution of Continuous Intraday Electricity Trading

Janke, Tim ; Steinke, Florian (2023)
Forecasting the Price Distribution of Continuous Intraday Electricity Trading.
In: Energies, 2019, 12 (22)
doi: 10.26083/tuprints-00015734
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: Forecasting the Price Distribution of Continuous Intraday Electricity Trading
Language: English
Date: 4 December 2023
Place of Publication: Darmstadt
Year of primary publication: 2019
Place of primary publication: Basel
Publisher: MDPI
Journal or Publication Title: Energies
Volume of the journal: 12
Issue Number: 22
Collation: 14 Seiten
DOI: 10.26083/tuprints-00015734
Corresponding Links:
Origin: Secondary publication DeepGreen

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.

Uncontrolled Keywords: electricity price forecasting, intraday markets, lasso regression, neural networks
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-157345
Additional Information:

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

Classification DDC: 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Energy Information Networks and Systems Lab (EINS)
Date Deposited: 04 Dec 2023 10:23
Last Modified: 08 Dec 2023 08:01
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/15734
PPN: 513780327
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