A Mini Review on Smart Hydrogen: The Role of AI in Revolutionizing Green Hydrogen Systems
Ria Ghosh, Sonali Kesarwani, Meetu Malhotra
Abstract
High Resolution Image Download MS PowerPoint Slide The shift to sustainable energy demands creative solutions that combine cutting-edge computational tools with clean energy technologies. Green hydrogen has become a viable substitute for fossil fuels thanks to electrolysis fueled by renewable energy. However, obstacles like exorbitant manufacturing costs, constraints on efficiency, and intricate supply chains prevent it from being widely used. The entire green hydrogen value chain, from production and storage to transport and use, may be optimized with artificial intelligence (AI). This paper examines the ways in which AI and green hydrogen may work together, describing how data-driven analytics, machine learning, and deep learning can increase the efficiency of hydrogen generation while lowering operating costs and boosting reliability. A more economical and scalable hydrogen economy is facilitated by AI-powered predictive maintenance, real-time electrolysis optimization, and smart energy grid interconnection. Furthermore, supply and demand are balanced with the use of AI-driven forecasting tools, guaranteeing the best possible use of available resources. The paper also demonstrates how AI is transforming the hydrogen industry and opening the door for a decarbonized energy ecosystem through case studies and practical applications. Current issues are also covered, such as the necessity for interdisciplinary cooperation, regulatory obstacles, and data restrictions. The study concludes with predictions for the future, highlighting how AI-driven innovation will hasten the adoption of green hydrogen worldwide.