Issue |
E3S Web Conf.
Volume 589, 2024
The 6th International Conference on Green Environmental Engineering and Technology (IConGEET2024)
|
|
---|---|---|
Article Number | 05001 | |
Number of page(s) | 7 | |
Section | Sustainable Energy | |
DOI | https://doi.org/10.1051/e3sconf/202458905001 | |
Published online | 13 November 2024 |
Artificial Intelligence Prediction Tool for Hydrogen Production from Renewable Energy Aimed at Reducing the Impact on the Environment
1 National Institute for Research and Development in Environmental Protection, 294 Splaiul Independenţei Blv., 060031, Bucharest, Romania
2 S.C. Wing Computer Group S.R.L., 24C Blândeşti Str., 042077, Bucharest, Romania
3 University Politechnica of Bucharest, 313 Splaiul Independenţei Blv., 060042, Bucharest, Romania
4 Sustainable Environment Research Group, Centre of Excellence Geopolymer and Green Technology (CEGeoGTech), Universiti Malaysia Perlis 02600 Arau, Perlis, Malaysia
Hydrogen production from renewable energy sources is a sustainable idea both in the field of energy storage and for environmental protection. Still, the fluctuations of production levels can become an impediment and may attract risks or additional production costs. In order to predict hydrogen production from such sources, an Artificial Intelligence prediction tool was implemented as a measure of control for future forecasts and evolutions. In the reason of resilience for further developments, this tool was made in the LabVIEW programming environment, using the easy but also capable graphical programming language. The results of this work found a periodically fluctuations in the hydrogen production but a general stability of the hydrogen marketplace. Into account of the further development of the clean energy to protect the environment, the use of hydrogen from renewable energy can be found as a good strategy.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.