Abstract
The inherent intermittent output characteristics of renewable energy sources (RES) have an adverse impact on the demand side, which greatly limits its penetration and utilization. In this context, emerging technologies for hydrogen production by water electrolysis provide the necessary flexibility to complement the uncontrollability of the power supply side for better integration of abundant RES. This paper mainly summarizes modelling, optimal scheduling, application scenarios and their assessment of large-scale water alkaline electrolyzers (WAE) in grid-connected operation modes, and discusses the challenges of WAE systems’ digitalization, optimal scheduling of green hydrogen, and future research directions of wind-hydrogen dominated renewable energy systems (WHDRES) based on artificial intelligence.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2022 International Conference on Artificial Intelligence and Computer Information Technology |
| Number of pages | 6 |
| Publisher | IEEE |
| Publication date | 2022 |
| ISBN (Electronic) | 978-1-6654-5087-4 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 2022 International Conference on Artificial Intelligence and Computer Information Technology - Yichang, China Duration: 16 Sept 2022 → 18 Sept 2022 |
Conference
| Conference | 2022 International Conference on Artificial Intelligence and Computer Information Technology |
|---|---|
| Country/Territory | China |
| City | Yichang |
| Period | 16/09/2022 → 18/09/2022 |
Keywords
- Alkaline electrolyzer
- Dispatched model
- Non-linear model optimization
- Reinforcement learning
