A Flexible Deep Learning Method for Energy Forecasting

A Flexible Deep Learning Method for Energy Forecasting

Load prediction with higher accuracy and less computing power has become an important problem in the smart grids domain in general and especially in demand-side management (DSM), as it can serve to minimize global warming and better integrate renewable energies. To this end, it is interesting to hav...

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Bibliographic Details
Main Authors:	Ihab Taleb, Guillaume Guerard, Frédéric Fauberteau, Nga Nguyen
Format:	Article
Language:	English
Published:	MDPI AG 2022-05-01
Series:	Energies
Subjects:	flexible load forecasting time series hybrid model deep learning machine learning artificial neural networks
Online Access:	https://www.mdpi.com/1996-1073/15/11/3926

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