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.

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

Aurora Poggi;Luca Di Persio;
2023-01-01

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.
2023
electricity price forecasting
neural network
deep learning
machine learning
autoregressive
univariate model
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1120492
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