This study presents a biomass-driven hybrid energy system designed to enhance efficiency while reducing environmental impacts through a comprehensive thermodynamic, economic, and environmental assessment framework. The proposed system integrates an air-fed eucalyptus gasifier with a supercritical carbon dioxide Brayton cycle, an organic Rankine cycle, and heat recovery units to simultaneously produce syngas, electricity, heated water, and heated air. The system is modeled and simulated using Engineering Equation Solver, and the results are validated against available literature data. In addition to conventional energy analysis, detailed exergy, exergo-economic, and environmental analyses are conducted to identify thermodynamic irreversibility, cost formation mechanisms, and CO2 emission characteristics using power-based, heat-based, and outputs-based indicators. Second-order regression-based machine learning models are developed to enable an accurate and computationally efficient six-objective optimization, targeting electrical efficiency, thermal efficiency, cold gas efficiency, total power output, heated water, and heated air. The optimization results indicate an optimal gasification temperature of 864.6 ◦C and a supercritical carbon dioxide Brayton cycle compression ratio of 2.86, yielding a maximum total power output of 163.6 kW, an electrical efficiency of 7.7%, a thermal efficiency of 4.0%, a cold gas efficiency of 80.6%, a heated water of 345 L/s, and a heated air of 112 m3/s. The combined integration of advanced thermodynamic analyses with AI-assisted optimization provides a novel and holistic framework for the design and sustainability-oriented optimization of biomass-based hybrid energy systems.
