Optimization of solar and geothermal energy assisted power, heating and hydrogen production using field programmable gate arrays and artificial neural networks
Thermal Science and Engineering Progress, cilt.66, 2025 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 66
- Basım Tarihi: 2025
- Doi Numarası: 10.1016/j.tsep.2025.104048
- Dergi Adı: Thermal Science and Engineering Progress
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
- Anahtar Kelimeler: Artificial neural networks, Field programmable gate arrays, Geothermal energy, Hydrogen production, Optimization, Solar energy, Space heating
- Kırklareli Üniversitesi Adresli: Evet
Özet
This study presents a thermodynamic and economic evaluation of an integrated solar–geothermal energy system designed to produce electricity, hydrogen, and space heating. The motivation of the work is to improve the efficiency and cost-effectiveness of renewable hybrid systems by applying advanced digital optimization. The methodology employs a multilayer artificial neural network implemented on a field programmable gate array, enabling real-time optimization with high computational precision. The novelty of this research lies in the unique combination of solar and geothermal resources with neural network–based hardware optimization, which allows simultaneous production of multiple energy outputs with improved performance. Classical analysis yielded a cycle power output of 1113 kW, heating capacity of 7351 kW, energy efficiency of 32.87 %, exergy efficiency of 34.31 %, electricity cost of 0.09373 $/kWh, and hydrogen production cost of 1.856 $/kg. With the proposed optimization, the system achieved 1913 kW of power, 1340 kW of fuel cell output, 8936 kW of heating capacity, 34.04 % energy efficiency, and 43.66 % exergy efficiency, while reducing the hydrogen cost to 1.707 $/kg, the heating cost to 0.005757 $/kWh, and the electricity cost to 0.08417 $/kWh. These results demonstrate that combining renewable energy with advanced real-time optimization can significantly enhance sustainable energy systems’ technical performance and economic viability.