Explainable artificial intelligence-based multi-objective optimization of a novel hybrid solar–biogas multigeneration system


KILIÇ ERİKGENOĞLU D., ERGENEKON ARSLAN A., SELVİ A. O., ARSLAN O.

International Journal of Hydrogen Energy, cilt.242, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 242
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.ijhydene.2026.155619
  • Dergi Adı: International Journal of Hydrogen Energy
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Artic & Antarctic Regions, Chemical Abstracts Core, Chimica, Compendex, Environment Index, INSPEC
  • Anahtar Kelimeler: Biogas, Explanable artificial intelligence, Green hydrogen, Multi-criteria, Multigeneration, Solar energy
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

A novel multigeneration system powered by hybrid solar-biogas energy was investigated to generate electricity via improved Brayton and Rankine cycles, produce hydrogen via a solid oxide electrolyzer, and provide domestic heat. The system was optimized using multi-objective optimization modeling after the parametric thermodynamic and economic evaluation. Explainable artificial intelligence and the Analytic Hierarchy Process were applied to an efficiency analysis technique for multi-objective optimization. According to the parametric analysis, energy and exergy efficiencies, power, hydrogen production, stored heat, and the net present value range between 17.55 and 42.75%, 17.41–39.78%, 570.04–733.58 kW, 0.053–0.239 kmol/s, and 9808.72–10140.16 MJ/day, 0.17–2.42 million US$, respectively. At the optimal solution, the overall energy and exergy efficiencies of the system were determined to be 41.96% and 39.08%, with 0.233 kmol/s of hydrogen and 697.91 kW of net power, and the net present value analysis was determined to be 2.35 million US$.