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 Alejandro
Moreno Chuquen, Ricardo
López Sotelo, Jesús
Celeita, David
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/15886
Acceso en línea:
https://hdl.handle.net/10614/15886
https://doi.org/10.3390/en16196767
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