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

 
 
	 
  
       
       
      