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
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