Forecasting the Price Distribution of Continuous Intraday Electricity Trading

Tim Janke and Florian Steinke
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Tim Janke: Energy Information Networks & Systems, TU Darmstadt, 64283 Darmstadt, Germany
Florian Steinke: Energy Information Networks & Systems, TU Darmstadt, 64283 Darmstadt, Germany

Energies, 2019, vol. 12, issue 22, 1-14

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.

Keywords: electricity price forecasting; intraday markets; lasso regression; neural networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

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