Artificial Intelligence Based Optimal Operation of Green Hydrogen Refueling
This study presents an AI-based optimized energy management model for a hydrogen refueling station with a PV system and fuel cell (FC). Using the Time-series Dense Encoder (TiDE) model for day-ahead PV generation and electricity price forecasting, with real data from Spain, the station efficiently manages hydrogen demand and electricity sales. Despite lower-than-expected PV production (11,559.39 kWh vs. 12,991.71 kWh), real-time revenue rose to 1,144.84 Euros, demonstrating operational flexibility and profit.
Authors
- Alper Çiçek (ORCID: https://orcid.org/0000-0003-4540-2276)
- Oğuz Kırat (ORCID: https://orcid.org/0000-0003-2687-9351)
Institutions
- Trakya University (TR)
Publication Details
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1109/telfor63250.2024.10819143
- Citations
- 3
- Primary Topic
- Spacecraft and Cryogenic Technologies
- Type
- article
- Field-Weighted Citation Impact
- 3.90