Artificial Intelligence for Hydrogen-Based Energy Systems

Power-to-hydrogen (P2H) technologies and hybrid energy systems based on green hydrogen are receiving a growing amount of attention, especially in the context of the energy transition. Green hydrogen (GH2) is perceived as a promising solution in replacing traditional, non-renewable energy sources. However, the implementation of GH2 is entailed by a series of challenges and its widespread adoption is yet to be achieved. Besides the techno-economic feasibility issues, the implementation of GH2 is heavily linked with the process of optimal integration in the power system. Typical energy management strategies focus on conventional simulation and optimization methods that are oftentimes unable to fully reap the potential of GH2 hybrid systems. In this context, the application of artificial intelligence (AI) based solutions have the potential to become a stepping stone towards a widespread adoption of GH2. Considering the growing importance of both AI and GH2, the paper analyses the current status and future prospects of AI applications in hydrogen-based energy systems. It also explores different issues and barriers to the wider adoption of GH2 and presents a case-study of a hydrogen-based hybrid energy system.