Cargando…
A Machine Learning Model Ensemble for Mixed Power Load Forecasting across Multiple Time Horizons
The increasing penetration of renewable energy sources tends to redirect the power systems community’s interest from the traditional power grid model towards the smart grid framework. During this transition, load forecasting for various time horizons constitutes an essential electric utility task in...
Autores principales: | Giamarelos, Nikolaos, Papadimitrakis, Myron, Stogiannos, Marios, Zois, Elias N., Livanos, Nikolaos-Antonios I., Alexandridis, Alex |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304500/ https://www.ncbi.nlm.nih.gov/pubmed/37420606 http://dx.doi.org/10.3390/s23125436 |
Ejemplares similares
-
Multi-Ship Control and Collision Avoidance Using MPC and RBF-Based Trajectory Predictions
por: Papadimitrakis, Myron, et al.
Publicado: (2021) -
An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models
por: Alexandridis, Alex, et al.
Publicado: (2018) -
A novel Bayesian ensembling model for wind power forecasting
por: Tang, Jingwei, et al.
Publicado: (2022) -
A Comprehensive Review on Ensemble Solar Power Forecasting Algorithms
por: Rahimi, Negar, et al.
Publicado: (2023) -
Multi-horizon short-term load forecasting using hybrid of LSTM and modified split convolution
por: Ullah, Irshad, et al.
Publicado: (2023)