Electrical Load Demand Forecasting Using Feed-Forward Neural Networks
The higher share of renewable energy sources in the electrical grid and the electrification of significant sectors, such as transport and heating, are imposing a tremendous challenge on the operation of the energy system due to the increase in the complexity, variability and uncertainties associated...
Guardado en:
Autores principales: | Eduardo Machado, Tiago Pinto, Vanessa Guedes, Hugo Morais |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/31156735011d4c48864b9b9d0efbd439 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Comparison of Baseline Load Forecasting Methodologies for Active and Reactive Power Demand
por: Edgar Segovia, et al.
Publicado: (2021) -
Forward Kinematics of Delta Manipulator by Novel Hybrid Neural Network
por: Mahesh A. Makwana, et al.
Publicado: (2021) -
Load forecasting of hybrid deep learning model considering accumulated temperature effect
por: Haihong Bian, et al.
Publicado: (2022) -
Enhanced Short-Term Load Forecasting Using Artificial Neural Networks
por: Athanasios Ioannis Arvanitidis, et al.
Publicado: (2021) -
Load forecasting of electric vehicle charging station based on grey theory and neural network
por: Jiawei Feng, et al.
Publicado: (2021)