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Forecasting the Price Distribution of Continuous Intraday Electricity Trading

Energy Information Networks & Systems, TU Darmstadt, 64283 Darmstadt, Germany
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Energies 2019, 12(22), 4262; https://doi.org/10.3390/en12224262
Received: 30 August 2019 / Revised: 4 November 2019 / Accepted: 5 November 2019 / Published: 8 November 2019
(This article belongs to the Special Issue Modeling and Forecasting Intraday Electricity Markets)
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. View Full-Text
Keywords: electricity price forecasting; intraday markets; lasso regression; neural networks electricity price forecasting; intraday markets; lasso regression; neural networks
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Janke, T.; Steinke, F. Forecasting the Price Distribution of Continuous Intraday Electricity Trading. Energies 2019, 12, 4262.

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