Multi-aspect analysis and multi-objective optimization of a novel biomass-driven heat and power cogeneration system; utilization of grey wolf optimizer

In the current work, the feasibility of a novel heat and power cogeneration system comprising a biomass gasifier, a supercritical carbon dioxide cycle, a gas turbine cycle, a Stirling engine, and a domestic water heater in a well-organized design is investigated. The whole system's performance...

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Veröffentlicht in:Journal of cleaner production 2022-06, Vol.355, p.131442, Article 131442
Hauptverfasser: Zhang, Guiju, Li, Hao, Xiao, Caiyuan, Sobhani, Behrooz
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Sprache:eng
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Zusammenfassung:In the current work, the feasibility of a novel heat and power cogeneration system comprising a biomass gasifier, a supercritical carbon dioxide cycle, a gas turbine cycle, a Stirling engine, and a domestic water heater in a well-organized design is investigated. The whole system's performance has been appraised, overlooking the role of the Stirling engine. The biomass fuels employed in the gasification process are municipal solid waste (MSW), paper, paddy husk, and wood. Subsequently, the energy, exergy, exergoeconomic, and environmental (4E) investigations are applied to conduct a comparative study and designate the best biomass. Consequently, the MSW was recognized as efficient biomass fuel, and the comprehensive parametric study and multi-criteria optimization for the whole system were implemented utilizing this fuel. The optimization process has been performed using the MOGWO algorithm and the LINMAP decision-making approach. The results revealed that the evaluated variables are more sensitive to vary the gas turbine inlet temperature and Stirling engine features than the other parameters. Also, for the MSW, the optimum exergy efficiency and total coat rate of the setup are found to be 46.48% and 401.4 $/h, respectively. •A novel cogeneration system fueled by different biomasses is suggested.•The system's performance is analyzed, overlooking the role of the Stirling engine.•The energy, exergy, exergoeconomic, and environmental analyses are performed.•The optimization process is conducted using the grey wolf optimization algorithm.•The optimum exergy efficiency and cost rate are found to be 46.48% and 401.4 $/h.
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2022.131442