Artificial Intelligence (AI) has turned out to be a major facilitator in the development of hydrogen-based green energy technologies by enhancing efficiency, level of sustainability and integration of the system at the hydrogen value chain level. Life cycle analysis reports indicate that other hydrogen routes, such as waste polymer and biomass-based gasification combined with carbon capture have reduced environmental effects as compared to standard steam methane reforming. The AI modeling and optimization complement them by increasing the efficiency of the processes, integration of renewable electricity, transport logistics, and evaluation of the environmental impact. With the help of AI-based forecasting and control, intermittency and market uncertainty can be reduced in renewable-powered electrolysis systems thus hydrogen can be produced at a cost-effective rate. The AI is used to provide intelligent energy management, grid stability, and techno-economic optimization at both centralized and decentralized levels. Moreover, AI increases the hydrogen capacity and application in predictive maintenance, safety, optimum underground storage, and fuel cell. All these developments put AI
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