Thermodynamics and exergoeconomics evaluations of a new solar–biomass–natural gas integrated energy system coupled with a heat recovery system: biofuel yield prediction under two different machine-learning models

Xiaoao Li, Zheqi Chen, Jiangang Gao, Noradin Ghadimi

2025

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DOI 10.1093/ijlct/ctaf128
Data confidence 70 medium
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Abstract

Abstract This study addresses the challenge of developing low-carbon, efficient energy systems by proposing an integrated solar–biomass–natural gas configuration coupled with a heat recovery system and hydrogen production. Thermodynamic and exergoeconomic analyses evaluate performance, while random forest and Kernel Ridge regression models predict biofuel yield with high accuracy. The optimized system achieves energy and exergy efficiencies of 39.5% and 34.5%, producing 11.22 MW electricity and 0.0442 kg/s H2, with CO2 emissions of 106.92 kg/h. This conceptual design reduces natural gas consumption, enhances renewable integration, and demonstrates a scalable pathway toward sustainable, multioutput power generation.