THERMODYNAMIC ANALYSIS AND OPTIMIZATION OF A SUPERCRITICAL CO2 POWER CYCLE DRIVEN BY A SOFC-GT HYBRID SYSTEM

被引:0
作者
Cao, Runqing [1 ]
Wang, Youna [1 ]
Wu, Zhongliang [1 ]
Liu, Wenhe [1 ]
Cao, Yue [1 ]
机构
[1] Southeast Univ, Sch Energy & Environm, Nanjing, Peoples R China
来源
PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 11 | 2024年
基金
中国国家自然科学基金;
关键词
Solid oxide fuel cell; gas turbine; supercritical carbon dioxide; multiobjective optimization; OXIDE FUEL-CELL; GAS-TURBINE; WASTE-HEAT; PERFORMANCE; DESIGN;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Solid oxide fuel cell-gas turbine (SOFC-GT) hybrid systems are an advanced technology for power generation because of their high efficiency, stability and environmental friendliness. Because the exhaust from the gas turbine in the SOFC-GT system is still of high grade, a bottoming cycle is usually used to recover the exhaust's waste heat. The supercritical CO2 power cycle is selected as the bottoming cycle for the SOFC-GT hybrid system to achieve cascaded utilization of this thermal energy. Here, a thermodynamic model is built for such a supercritical CO2 power cycle driven by an SOFC-GT hybrid system. Six key parameters, including the fuel flow rate, fuel utilization factor, SOFC operating temperature, combustion engine pressure ratio, CO2 turbine inlet pressure and cycle split ratio, are analysed to determine the effects on the thermodynamic performance of the system in terms of the output power, exergy loss and exergy efficiency of the system. Moreover, particle swarm optimization (PSO) is employed to perform multiobjective optimization of the hybrid system. The optimization results for the output power and efficiency of the system are presented at the Pareto front of the system. Further analyses are conducted for the distribution of the values of the key parameters corresponding to the Pareto solution. The optimal operating point of the hybrid system is finally determined by the linear programming decision method of multidimensional preference analysis.
引用
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页数:12
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