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Using Artificial Intelligence to Improve Hydrogen Production Systems
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Author(s): Ayoub Ghailane (Mohammed V University in Rabat, Morocco), Jamal Mabrouki (Mohammed V University in Rabat, Morocco), Anass Ariss (Mohammed V University in Rabat, Morocco), Driss Azdem (Mohammed V University in Rabat, Morocco)and Younes Abrouki (Mohammed V University in Rabat, Morocco)
Copyright: 2025
Pages: 12
Source title:
Obstacles Facing Hydrogen Green Systems and Green Energy
Source Author(s)/Editor(s): Jamal Mabrouki (Faculty of Science, Mohammed V University in Rabat, Morocco)
DOI: 10.4018/979-8-3693-8980-5.ch032
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Abstract
Integrating artificial intelligence (AI) into hydrogen production systems represents an innovative approach to improving efficiency, optimizing resource management and reducing operating costs. This chapter explores the main applications of AI in green hydrogen production, focusing on intelligent energy resource management, process optimization and predictive maintenance. Machine learning algorithms and neural networks (ANN) can be used to adjust production parameters. Guaranteeing maximum efficiency and better adaptation to fluctuations in renewable energy sources. What's more, AI-based predictive maintenance reduces equipment failures, extends system lifetimes and improves reliability. The synergy between AI and hydrogen production not only promotes a more sustainable energy transition, but also the more efficient integration of hydrogen into smart energy grids, The adoption of these technologies represents a significant breakthrough in optimizing the efficiency and competitiveness of hydrogen production, paving the way for a more resilient, low-carbon energy system.
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