Solar photovoltaic generation and electrical demand forecasting using multi-objective deep learning model for smart grid systems

Solar photovoltaic generation and electrical demand forecasting using multi-objective deep learning model for smart grid systems

AbstractThe growing of the photovoltaic (PV) panel’s installation in the world and the intermittent nature of the climate conditions highlights the importance of power forecasting for smart grid integration. This work aims to study and implement existing Deep Learning (DL) methods used for PV power...

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Bibliographic Details
Main Authors: Camille Franklin Mbey, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum, Felix Ghislain Yem Souhe
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Cogent Engineering
Subjects:
Electrical demand prediction
photovoltaic power forecasting
deep learning models
smart grid
long short term memory
multi-objective particle swarm optimization
Online Access:https://www.tandfonline.com/doi/10.1080/23311916.2024.2340302

Internet

https://www.tandfonline.com/doi/10.1080/23311916.2024.2340302

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