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 and Noradin Ghadimi

International Journal of Low-Carbon Technologies, 2025, vol. 20, 1936-1950

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.

Keywords: integrated energy system; biomass-natural gas combustion; parabolic trough solar collector; exergoeconomics; biofuel yield prediction; random forest and kernel ridge regression (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/ijlct/ctaf128 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:1936-1950.

Access Statistics for this article

International Journal of Low-Carbon Technologies is currently edited by Saffa B. Riffat

More articles in International Journal of Low-Carbon Technologies from Oxford University Press
Bibliographic data for series maintained by Oxford University Press ().