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...
- 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