Heat Re-process approach and thermally integrated renewable energy system for power, compressed hydrogen, and freshwater production; ANN boosted optimization and techno-enviro-economic analysis
This comprehensive investigation undertakes a holistic examination of the design, simulation, and optimization of a hybrid thermal energy system (HTES) that synergistically integrates wind and solar energy sources for the simultaneous production of electricity, compressed hydrogen, and freshwater. T...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25000085 |
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| Summary: | This comprehensive investigation undertakes a holistic examination of the design, simulation, and optimization of a hybrid thermal energy system (HTES) that synergistically integrates wind and solar energy sources for the simultaneous production of electricity, compressed hydrogen, and freshwater. This study introduces an innovative energy system design that integrates a supercritical CO2 Brayton cycle (SCO2-BC) with parabolic trough solar collectors (PTSCs) to increase efficiency and reliability. A key innovation is using waste heat from the SCO2-BC to power an organic Rankine cycle (ORC), which improves the performance and power generation capacity of the proposed system. Additionally, the machine learning optimization technique is employed to optimize the system, significantly reducing computational costs and runtime for the optimization process. The thermal energy input of HTES is supplied by PTSCs, which drive the SCO2-BC, while an ORC unit is employed to recuperate waste heat at the compressor inlet, thereby augmenting electricity generation. Furthermore, the HTES is augmented by a wind turbine to supplement power production. A multidisciplinary techno-economic and environmental framework was applied to analyze the performance of the proposed system. The preliminary simulation results indicate that the solar unit significantly contributes to both exergy destruction and the total cost rate, accounting for 53.8 % of the total exergy losses and 64.9 % of the total costs, respectively. Ultimately, the optimized simulation utilizing a hybrid machine learning approach achieved a peak exergy efficiency of 27.37 % and a minimized total cost rate of 96.2 $/h. Under the optimal operating conditions derived from the multi-objective optimization, the levelized costs of the HTES's products were determined to be 12.63 cents/kWh for electricity, 4.75 $/kg for compressed hydrogen, and 20.59 cents/m3 for freshwater. Furthermore, the environmental assessment indicated that the cost of reducing CO2 emissions is 3.69 $/h under optimal conditions. |
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| ISSN: | 2214-157X |