Abstract
The solar-driven high-temperature steam electrolysis is promising for efficient large-scale H2 production. In this study, a comprehensive component-to-system model and optimization framework is developed to investigate the performance of a zero-emission H2 production system based on solar power plant and protonic ceramic electrolysis cell. Compared to previous system studies, the detailed description of cell internal operating characteristics is realized by integrating multi-physics simulation and artificial neural network. After parametric analyses, it is found that the system energy/exergy efficiency and co-generation performance are complicated by each subsystem. And the optimal system performance (ηth = 50.63 %, Z = 179.63 $·h−1 and ηex = 33.03 %, Z = 178.94 $·h−1, with LCOE = 0.172 $·kWh−1 and ZH2 = 6.497 $·kg−1) is obtained considering cell operating features and system energy-exergy-economic factors through multi-objective optimizations. Besides, the tradeoff between system maximum H2 production capacity and cell internal thermal conditions is revealed. This study can facilitate the development of zero-emission green H2 production driven by renewable energy.
| Original language | English |
|---|---|
| Pages (from-to) | 1415-1428 |
| Number of pages | 14 |
| Journal | International Journal of Hydrogen Energy |
| Volume | 83 |
| DOIs | |
| Publication status | Published - 19 Sept 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Artificial neural network
- Green H production
- Protonic ceramic electrolysis cell
- Solar power tower
- Supercritical CO Brayton cycle
- Thermodynamic and economic analysis
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Condensed Matter Physics
- Energy Engineering and Power Technology
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