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Article

Electricity Price Forecasting via Statistical and Deep Learning Approaches: The German Case

by
Aurora Poggi
1,†,
Luca Di Persio
1,† and
Matthias Ehrhardt
2,*,†
1
Department of Computer Science, College of Mathematics, University of Verona, 37134 Verona, Italy
2
Chair of Applied and Computational Mathematics, University of Wuppertal, 42119 Wuppertal, Germany
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
AppliedMath 2023, 3(2), 316-342; https://doi.org/10.3390/appliedmath3020018
Submission received: 21 February 2023 / Revised: 16 March 2023 / Accepted: 20 March 2023 / Published: 3 April 2023
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Abstract

Our research involves analyzing the latest models used for electricity price forecasting, which include both traditional inferential statistical methods and newer deep learning techniques. Through our analysis of historical data and the use of multiple weekday dummies, we have proposed an innovative solution for forecasting electricity spot prices. This solution involves breaking down the spot price series into two components: a seasonal trend component and a stochastic component. By utilizing this approach, we are able to provide highly accurate predictions for all considered time frames.
Keywords: electricity price forecasting; univariate model; statistical method; autoregressive; machine learning; deep learning; neural network electricity price forecasting; univariate model; statistical method; autoregressive; machine learning; deep learning; neural network

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MDPI and ACS Style

Poggi, A.; Di Persio, L.; Ehrhardt, M. Electricity Price Forecasting via Statistical and Deep Learning Approaches: The German Case. AppliedMath 2023, 3, 316-342. https://doi.org/10.3390/appliedmath3020018

AMA Style

Poggi A, Di Persio L, Ehrhardt M. Electricity Price Forecasting via Statistical and Deep Learning Approaches: The German Case. AppliedMath. 2023; 3(2):316-342. https://doi.org/10.3390/appliedmath3020018

Chicago/Turabian Style

Poggi, Aurora, Luca Di Persio, and Matthias Ehrhardt. 2023. "Electricity Price Forecasting via Statistical and Deep Learning Approaches: The German Case" AppliedMath 3, no. 2: 316-342. https://doi.org/10.3390/appliedmath3020018

APA Style

Poggi, A., Di Persio, L., & Ehrhardt, M. (2023). Electricity Price Forecasting via Statistical and Deep Learning Approaches: The German Case. AppliedMath, 3(2), 316-342. https://doi.org/10.3390/appliedmath3020018

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