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Carbon-neutral polygeneration utilizing biogas-reforming and biomass-combustion; life cycle assessment and machine learning assisted optimization

Author

Listed:
  • Yu, Ning
  • Li, Yujie
  • Abed Balla, Hyder H.
  • Abed Abood, Ahmed Sabeeh
  • Rasool, Hussein Ali
  • Dutta, Ashit Kumar
  • Bayhan, Zahra
  • Ali, H. Elhosiny
  • Alansari, Abdulrahman

Abstract

Growing global energy demand, and relying heavily on fossil fuels to meet these energy needs led to serious environmental and economic concerns. Within the gate-to-gate operational boundary, this work introduces a revolutionary polygeneration carbon neutral process that can concurrently produce valuable products (electricity/heating/cooling/syngas) with negligible CO2 emissions. This configuration combines a biomass combustor, with biogas bi-reforming unit, Rankine cycle with orthoxylene organic working-fluid, and absorption chiller, which are simulated using Aspen-HYSYS software. The study applies the evaluation process integrated with life cycle assessment and profitability analysis, while the optimal operating is determined using comparative machine learning-assisted multi-objective optimization approach. With a net electricity of 356 kW, heating and cooling capacities of 282 kW and 325 kW, and a syngas production of 0.7754 kg/s, the system shows exceptional efficiencies of 96.92% and 71.63% for energy and exergy. Furthermore, the system maintains a nearly zero CO2 footprint (0.000858 kg/kWh) along with negative global warming potential (−0.0038 kgCO2-eq/kWh), which highlight its novelty contribution toward low-carbon system. Moreover, the system demonstrated indicates that the energy production and product generation processes operate at a competitive cost level, with the cost of energy of 0.19 $/kWh and the total unit cost of product (TUCP) of 4.21 $/GJ, which results net present value of 8.26 million $, and a payback-period of 6.21 years. The Firefly optimization algorithm find the optimal configuration with efficiency of 73.60% for exergy and TUCP of 4.03 $/GJ. The Monte-Carlo sensitivity evaluation indicates that the mass flow of biogas as the most influential variables affecting system performance.

Suggested Citation

  • Yu, Ning & Li, Yujie & Abed Balla, Hyder H. & Abed Abood, Ahmed Sabeeh & Rasool, Hussein Ali & Dutta, Ashit Kumar & Bayhan, Zahra & Ali, H. Elhosiny & Alansari, Abdulrahman, 2026. "Carbon-neutral polygeneration utilizing biogas-reforming and biomass-combustion; life cycle assessment and machine learning assisted optimization," Renewable Energy, Elsevier, vol. 273(C).
  • Handle: RePEc:eee:renene:v:273:y:2026:i:c:s0960148126008761
    DOI: 10.1016/j.renene.2026.126050
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