Biogas–geothermal heat integration with post-combustion CO2 capture for power generation, multi-level cooling, and desalination: Exergoeconomic–environmental assessment and optimization


Chaudhry I. A., Basem A., Soliman N. F., Kumar Singh P., Khaliq A., Dahari M., ...Daha Fazla

Thermal Science and Engineering Progress, cilt.75, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 75
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.tsep.2026.104757
  • Dergi Adı: Thermal Science and Engineering Progress
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Anahtar Kelimeler: Biogas–geothermal system, Monoethanolamine (MEA), Multi-effect desalination (MED), Particle swarm optimization, Supercritical CO2 cycle
  • İstanbul Gelişim Üniversitesi Adresli: Evet

Özet

Addressing the interconnected challenges of energy supply, freshwater scarcity, and greenhouse gas emissions requires efficient multigeneration systems. This study proposes a biogas–geothermal energy system with post-combustion CO2 capture for the simultaneous production of electricity, multi-level cooling, and desalinated water. The configuration integrates a biogas-fired combustion unit, an organic Rankine cycle, a supercritical CO2 combined cooling and power cycle, a multi-effect desalination unit, and an amine-based CO2 capture process. A comprehensive thermodynamic, exergoeconomic, and environmental assessment is conducted. The results show that the combustion and organic Rankine subsystems account for more than 67.35% of total exergy destruction, whereas the desalination unit contributes only 1.1%. Increasing the sCO2 turbine inlet pressure from 18 to 22 MPa enhances power output by approximately 8.47%, while increasing the extraction ratio substantially reduces electrical generation with minimal effect on cooling capacity. In the CO2 capture subsystem, reducing the lean/rich heat exchanger temperature difference lowers the reboiler heat duty from 3.38 to 2.77 MJ/kg-CO2, confirming the importance of effective internal heat recovery. To balance exergy efficiency, LCOE, and cooling production, artificial neural network surrogate models are coupled with a multi-objective particle swarm optimization algorithm. The optimal case achieves an exergy efficiency of 28.06%, an LCOE of 10.96 cents/kWh, and a cooling production rate of 1178.02 kW. Economic analysis indicates payback periods as short as 3.16 years and an NPV of up to $42.35 million under favorable market conditions. Overall, the proposed configuration represents a promising and economically viable pathway for advancing low-carbon multigeneration systems integrating energy, cooling, water production, and carbon management.