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Multi-aspect assessment and artificial intelligence-based optimization of a sustainable solar-to-power/hydrogen process using three-state numerical simulation and thermal energy storage

Author

Listed:
  • Yang, Xuan
  • Bai, Zhiqing
  • Samad, Sarminah
  • Abed, Azher M.
  • El-Zahar, Essam R.
  • Li, Yujie
  • Al Barakeh, Zaher
  • Ghandour, Raymond
  • Abdullaeva, Barno
  • Ali, H. Elhosiny

Abstract

Solar thermal systems face significant challenges due to daily solar variability, requiring advanced simulation and design methods. This study addresses these issues using a three-state numerical simulation, thermal energy storage, and artificial intelligence-based analysis. The proposed system comprises a solar power tower and an energy storage option designed to support a supercritical CO2 plant. Additionally, this plant is integrated with reverse osmosis desalination and a proton exchange membrane electrolyzer. A three-mode numerical simulation—solar, solar-storage, and storage—is conducted, and an artificial intelligence-driven multi-objective optimization using the NSGA-II algorithm is applied to enhance performance and cost efficiency. Under optimal conditions, the system exhibits a hydrogen production capacity of 54203 m3/day, a net power output of 4415 kW, an exergy round-trip efficiency of 23.01 %, and a unit cost of products (UCOP) of 33.41 $/GJ. The levelized cost of hydrogen is calculated to be 5.06 $/kg, with a net present value of 214.5 M$ and a payback period of 9.4 years. In addition, the entire installation indicates a cost rate of 1436 $/h. Compared to the base case, hydrogen output is improved by 29.7 %, and UCOP is reduced by 12.5 %. These results highlight the system's potential for cost-effective, zero-carbon hydrogen production using solar energy.

Suggested Citation

  • Yang, Xuan & Bai, Zhiqing & Samad, Sarminah & Abed, Azher M. & El-Zahar, Essam R. & Li, Yujie & Al Barakeh, Zaher & Ghandour, Raymond & Abdullaeva, Barno & Ali, H. Elhosiny, 2025. "Multi-aspect assessment and artificial intelligence-based optimization of a sustainable solar-to-power/hydrogen process using three-state numerical simulation and thermal energy storage," Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225043671
    DOI: 10.1016/j.energy.2025.138725
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