Techno-economic optimization of hybrid renewable systems for sustainable energy solutions
Abstract This study is focusing on the techno-economic optimization of hybrid renewable energy systems and the energy. The system integrates geothermal, wind, and solar sources for sustainable hydrogen production its important. The objective is to maximize energy efficiency, reduce operational costs...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-08171-3 |
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| Summary: | Abstract This study is focusing on the techno-economic optimization of hybrid renewable energy systems and the energy. The system integrates geothermal, wind, and solar sources for sustainable hydrogen production its important. The objective is to maximize energy efficiency, reduce operational costs, and ensure stable energy delivering. A simulation-based framework is used for analyse system behaviour under various environmental conditions it helps. The scope includes defining parameter, sensitivity analysis, and optimization using iterative algorithms which are complex. Time-step simulations evaluating energy dynamics help to and performance trade-offs, which is necessary for understanding. The proposed hybrid system achieves 78.5% energy efficiency and 64.3% exergy efficiency, and this is good. It produces 500 kg of hydrogen daily with an LCOE of $0.085 per kWh, which is quite low. Sensitivity results show that a 15% increase in wind speed improves output by 10%, and this is significant. A 20% drop in solar irradiance reduces output by 8%, which is not good. Geothermal contributes 40% of the total energy share, with wind and solar supplying 35% and 25%, respectively, and this shows balance. Optimization improves hydrogen production efficiency by 12% and leads to a six-year payback period, which is reasonable. The system shows resilience under load changes, supporting its robustness that is impressive. The findings validate the system’s scalability and economic potential, which is promising for future. Future work will explore advanced storage and real-time adaptive control. |
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| ISSN: | 2045-2322 |