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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Autores:
Cantillo-Luna, Sergio
Moreno-Chuquen, Ricardo
López Sotelo, Jesús Alfonso
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
spa
OAI Identifier:
oai:red.uao.edu.co:10614/15861
Acceso en línea:
https://hdl.handle.net/10614/15861
https://red.uao.edu.co/
Palabra clave:
Decision making
Deep learning
Electricity price forecasting (EPF)
Probabilistic forecasting
Time series forecasting
Rights
openAccess
License
Derechos reservados -MDPI, 2023