Author Identifier
Barun Kumar Das: https://orcid.org/0000-0001-5687-4768
Document Type
Journal Article
Publication Title
Scientific Reports
Volume
15
Issue
1
PubMed ID
40216871
Publisher
Nature
School
School of Engineering
RAS ID
81919
Funders
King Saud University (RSP2025R351)
Abstract
This study presents a comprehensive economic and technological evaluation of renewable hybrid power systems for hydrogen refueling stations (HRS) in Nizwa, Oman, leveraging cutting-edge optimization algorithms to determine the most cost-effective and efficient hybrid energy system configurations. Three hybrid energy systems of photovoltaic-wind turbine-battery (PV-WT-B), photovoltaic-wind-fuel cell-battery (PV-WT-FC-B), and wind turbine-battery (WT-B) were evaluated based on net present cost (NPC), levelized cost of energy (LCOE), and levelized cost of hydrogen (LCOH). The study employs advanced optimization techniques, including the Mayfly Algorithm, Genetic Algorithm, CUKO Search, Gray Wolf Optimizer (GWO), Constrained Particle Swarm Optimization (CPSO), Harmony Search (HS), and Flower Pollination Algorithm to determine the most viable hybrid energy system for the HRS in Nizwa. The results indicate that CPSO consistently achieves the lowest NPC, LCOE, and LCOH, whereas HS and GWO yield higher costs due to convergence inefficiencies. Sensitivity analysis reveals a strong inverse correlation between PV capacity and cost metrics, highlighting the economic advantage of increased solar generation. Additionally, hybrid configurations integrating PV and wind turbine (PV-WT-B, PV-WT-FC-B) significantly reduce NPC compared to WT-B, reinforcing the role of solar energy in optimizing economic costs. Furthermore, fuel cell integration (PV-WT-FC-B) imposes additional economic burdens, making PV-WT-B the most viable solution for HRS deployment in Oman. More so, the annual worth and return-on-investment analysis demonstrated that the PV-WT-B is the preferred energy system to meet the needs of the HRS in terms of investment. The findings underscore the importance of renewable energy fraction and capacity factor in energy economics, demonstrating that higher PV integration enhances sustainability and cost-efficiency. This study provides a transformative framework for decarbonizing Oman’s transportation sector, offering insights into optimal hydrogen production strategies to advance the global clean energy transition.
DOI
10.1038/s41598-025-97088-y
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Comments
Okonkwo, P. C., Nwokolo, S. C., Alarifi, S. S., Ekwok, S. E., Orji, R., Udo, S. O., ... & Akpan, A. E. (2025). Bio-inspired computational intelligence metaheuristic-based optimization and sensitivity analysis approach to determine techno-economic feasibility of hydrogen refueling stations for fuel cell vehicles. Scientific Reports, 15, 12451. https://doi.org/10.1038/s41598-025-97088-y