LAPSE:2023.6781
Published Article

LAPSE:2023.6781
Predicting Power and Hydrogen Generation of a Renewable Energy Converter Utilizing Data-Driven Methods: A Sustainable Smart Grid Case Study
February 24, 2023
Abstract
This study proposes a data-driven methodology for modeling power and hydrogen generation of a sustainable energy converter. The wave and hydrogen production at different wave heights and wind speeds are predicted. Furthermore, this research emphasizes and encourages the possibility of extracting hydrogen from ocean waves. By using the extracted data from the FLOW-3D software simulation and the experimental data from the special test in the ocean, the comparison analysis of two data-driven learning methods is conducted. The results show that the amount of hydrogen production is proportional to the amount of generated electrical power. The reliability of the proposed renewable energy converter is further discussed as a sustainable smart grid application.
This study proposes a data-driven methodology for modeling power and hydrogen generation of a sustainable energy converter. The wave and hydrogen production at different wave heights and wind speeds are predicted. Furthermore, this research emphasizes and encourages the possibility of extracting hydrogen from ocean waves. By using the extracted data from the FLOW-3D software simulation and the experimental data from the special test in the ocean, the comparison analysis of two data-driven learning methods is conducted. The results show that the amount of hydrogen production is proportional to the amount of generated electrical power. The reliability of the proposed renewable energy converter is further discussed as a sustainable smart grid application.
Record ID
Keywords
electrical power, FLOW-3D, green energy, hydrogen production, Renewable and Sustainable Energy, Simulation
Subject
Suggested Citation
Mirshafiee F, Shahbazi E, Safi M, Rituraj R. Predicting Power and Hydrogen Generation of a Renewable Energy Converter Utilizing Data-Driven Methods: A Sustainable Smart Grid Case Study. (2023). LAPSE:2023.6781
Author Affiliations
Mirshafiee F: Department of Electrical and Computer Engineering, K.N. Toosi University of Technology, Tehran 1999143344, Iran
Shahbazi E: Department of Mechatronic, Amirkabir University of Technology, Tehran 158754413, Iran
Safi M: Department of Mechatronic, Electrical and Computer Engineering, University of Tehran, Tehran 1416634793, Iran
Rituraj R: Doctoral School of Applied Informatics and Applied Mathematics, Faculty of Informatics, Obuda University, 1023 Budapest, Hungary
Shahbazi E: Department of Mechatronic, Amirkabir University of Technology, Tehran 158754413, Iran
Safi M: Department of Mechatronic, Electrical and Computer Engineering, University of Tehran, Tehran 1416634793, Iran
Rituraj R: Doctoral School of Applied Informatics and Applied Mathematics, Faculty of Informatics, Obuda University, 1023 Budapest, Hungary
Journal Name
Energies
Volume
16
Issue
1
First Page
502
Year
2023
Publication Date
2023-01-02
ISSN
1996-1073
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Original Submission
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PII: en16010502, Publication Type: Journal Article
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LAPSE:2023.6781
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https://doi.org/10.3390/en16010502
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Feb 24, 2023
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