Abstract
One intriguing option that could displace the current nonrenewable energy systems is hydrogen-enabled integrated energy systems (H-IES), they have not yet been widely adopted, though, and their development is fraught with difficulties. The intricacy of balancing supply and demand, fluctuating consumer demand, and difficulties integrating and using hydrogen are some of these primary obstacles. The real-world operation of H-IES cannot meet the requirements of typical energy management strategies in the energy sector, which mostly rely on precise models created by subject-matter specialists or traditional techniques like simulation and optimization. These obstacles can be addressed by advanced data analytics (ADA), particularly machine learning, or artificial intelligence. Although ADA is widely employed in many different industries, more research is necessary to determine how ADA and hydrogen might be combined to enable H-IES. The benefits, research gaps, and future directions of ADA, as well as the function of hydrogen in H-IES, are examined in this chapter.
| Original language | English |
|---|---|
| Title of host publication | Fuelling the Future |
| Subtitle of host publication | Intelligent Approaches for Harnessing Hydrogen Energy |
| Place of Publication | Netherlands |
| Publisher | Elsevier |
| Chapter | 10 |
| Pages | 201-212 |
| Number of pages | 12 |
| ISBN (Electronic) | 9780443340901 |
| ISBN (Print) | 9780443340918 |
| DOIs | |
| Publication status | Published - 19 Sept 2025 |
Keywords
- Artificial intelligence
- Computing
- Efficiency
- Enhancement
- Hydrogen energy
- Information systems
- Machine learning
- Statistical applications
ASJC Scopus subject areas
- General Energy
