Cascaded heat recovery cycles with biomass gasification integration: Dragonfly algorithm-optimized techno-economic-environmental analysis for sustainable poly-generation
Year: 2025
Type: article
Abstract: This study introduces an advanced poly-generation energy system that innovatively combines biomass gasification, Brayton cycle, supercritical CO 2 (sCO 2 ) cycle, and Rankine cycles for simultaneous production of electricity, green hydrogen, and thermal energy. The proposed system incorporates a sophisticated cascaded heat recovery design that maximizes energy efficiency through optimized heat extraction across high, medium, and low-temperature ranges, effectively utilizing waste heat streams. A comprehensive cost allocation analysis identifies the integrated gasifier-Brayton cycle subsystem as the primary cost driver, representing 34.4 % of total system expenditures. Concurrent exergy analysis demonstrates that the gasification process accounts for 32.2 % of total exergy destruction, with thermodynamic irreversibilities stemming principally from endothermic gasification reactions and high-temperature combustion phenomena during syngas generation. A comprehensive techno-economic-environmental evaluation provides critical insights into system performance and operational flexibility for sustainable energy applications. Through an integrated optimization approach combining artificial neural networks (ANNs) with the innovative Dragonfly algorithm, the hybrid ANN-Dragonfly framework enabled rapid convergence of the optimization process. The tri-objective optimization yields optimal outputs of 59.92 kg/s freshwater production with 31.47 % exergy efficiency at a total cost rate of 160.91 $/h. This research offers a promising framework for integrated sustainable poly-generation, offering a viable model for future high-efficiency, carbon-neutral poly-generation that addresses multiple energy demands through a unified optimized framework.
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,620
OpenAlex ID: W4415223642
