Literature review on forecasting green hydrogen production using machine learning and deep learning - Rhafes, Mohamed Yassine; Moussaoui, Omar; Raboaca, Maria Simona (Institute of Advanced Engineering and Science, 2025)
Green hydrogen is a sustainable and clean energy source, for this purpose, it conducts the global energy transition. The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL) with the process of green hydrogen production is essential in enhancing its production. This literature review studies in detail the intersection between AI and green hydrogen. Firstly, it concentrates on ML and DL algorithms used in forecasting green hydrogen production. Secondly, it presents an analysis of the studies released from 2021 to March 2024. Finally, the focus is on the results realized by the ML and DL algorithms proposed by the studies reviewed. This study provides a summary that explains the trends and methods used, as well as highlights the gaps and the opportunities in the field of AI and green hydrogen production. This liternature review presents a solid foundation for future research initiatives in this field.