Deep Learning for Wind and Solar Energy Forecasting in Hydrogen Production

Deep Learning for Wind and Solar Energy Forecasting in Hydrogen Production

This research delineates a pivotal advancement in the domain of sustainable energy systems, with a focused emphasis on the integration of renewable energy sources—predominantly wind and solar power—into the hydrogen production paradigm. At the core of this scientific endeavor is the formulation and...

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Bibliographic Details
Main Authors: Arturs Nikulins, Kaspars Sudars, Edgars Edelmers, Ivars Namatevs, Kaspars Ozols, Vitalijs Komasilovs, Aleksejs Zacepins, Armands Kviesis, Andreas Reinhardt
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
sustainable energy systems
renewable energy sources
hydrogen production
deep learning
weather forecasting
fully connected neural networks
Online Access:https://www.mdpi.com/1996-1073/17/5/1053

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https://www.mdpi.com/1996-1073/17/5/1053

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