An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture

An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture

This paper describes the development of a deep neural network architecture based on transformer encoder blocks and Time2Vec layers for the prediction of electricity prices several steps ahead (8 h), from a probabilistic approach, to feed future decision-making tools in the context of the widespread...

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Bibliographic Details
Main Authors: Sergio Cantillo-Luna, Ricardo Moreno-Chuquen, Jesus Lopez-Sotelo, David Celeita
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Energies
Subjects:
decision making
deep learning
electricity price forecasting (EPF)
probabilistic forecasting
time series forecasting
Online Access:https://www.mdpi.com/1996-1073/16/19/6767

Internet

https://www.mdpi.com/1996-1073/16/19/6767

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