Applications of Artificial Intelligence in environmental and economic life cycle analysis of green hydrogen production: improving efficiency and sustainability

Abstract

This paper aims to explore the role of Artificial Intelligence (AI) in improving the environmental and economic analysis of the life cycle of green hydrogen production. The study includes a presentation of how AI can be used to collect and analyze data, model future scenarios, improve process efficiency, and manage risks. Green hydrogen is one of the most promising solutions to achieve sustainability and clean energy goals, but its production requires advanced technology and high efficiency. The study used a multi-level approach that includes a literature review, experimental data analysis, and the application of predictive models and simulations, with a focus on practical applications of AI in the life cycle stages. The study showed that AI can improve the accuracy and effectiveness of data collection, build advanced predictive models, and experiment with scenarios to determine the best environmental and economic options. AI also has the potential to improve the efficiency of production processes by optimizing resource allocation and reducing waste, which increases the productivity of electrolyzer. In addition, AI has contributed to the effective assessment and management of risks, which helps in making informed decisions. AI tools have provided advanced graphical visualizations and data-driven recommendations, which facilitate the decision-making process and enhance sustainability. The study finds that AI plays a crucial role in enhancing the efficiency and sustainability of green hydrogen production and recommends further research and development in this area to achieve global sustainability goals.