Biomass-driven multigeneration with dual-bed adsorption cooling and cryogenic hydrogen liquefaction: 4E analysis and ANN-MOGWO optimization for economic-environmental feasibility
Applied Thermal Engineering, cilt.304, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 304
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.applthermaleng.2026.132591
- Dergi Adı: Applied Thermal Engineering
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, DIALNET, Business Source Ultimate (EBSCO)
- Anahtar Kelimeler: Alkaline water electrolysis, Biomass-based multigeneration, Carbon footprint reduction, Cryogenic hydrogen storage, Dynamic adsorption cooling, Economic-environmental feasibility assessment
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
A novel biomass-driven multigeneration system capable of simultaneously producing electricity, domestic heating, cooling, freshwater, and liquid hydrogen is proposed and comprehensively assessed through thermodynamic, economic, environmental, and sustainability analyses. The integrated configuration combines a biomass gasifier–Brayton cycle, domestic heating unit, dual-bed adsorption chiller, reverse osmosis desalination unit, alkaline water electrolyzer, and Claude-cycle hydrogen liquefaction subsystem. The adsorption cooling unit was analyzed dynamically to capture cyclic adsorption–desorption behavior. To identify the most favorable operating conditions, a feed-forward artificial neural network surrogate model was coupled with multi-objective grey wolf optimization (MOGWO), simultaneously maximizing exergy efficiency and liquid hydrogen production while minimizing total cost rate and carbon emissions. The dual-bed adsorption chiller demonstrated stable cyclic operation, with adsorbate uptake varying periodically between 0.045 and 0.085 kgwv/kgs over five consecutive cycles. The developed artificial neural network (ANN) model achieved excellent predictive capability, with coefficients of determination exceeding 0.999 for all objective functions. The optimal operating condition yielded an exergy efficiency of 19.43%, a total cost rate of 165.77 $/h, a carbon emission rate of 0.0879 ton/GJ, and a liquid hydrogen production rate of 12.41 kg/h. Compared with the base case, optimization reduced total cost rate and carbon emissions by 42.91% and 18.84%, respectively, while decreasing the payback period from 3.87 to 3.11 years. Furthermore, the optimized system can avoid approximately 20.4 kton/year of CO2 emissions, corresponding to nearly 408 kton of cumulative carbon mitigation over a 20-year lifetime. Contour-based net present value (NPV) analysis revealed that the highest profitability occurs at low discount rates and long project lifetimes, with maximum NPVs of 58.31 M$ and 56.12 M$ for the base and optimized cases, respectively. These findings demonstrate the strong potential of the proposed multigeneration system for sustainable and economically viable decentralized energy applications.