Exergetic sustainability evaluation and optimization of an irreversible Brayton cycle performance

被引:15
作者
Ahmadi, Mohammad H. [1 ]
Ahmadi, Mohammad-Ali [2 ]
Aboukazempour, Esmaeil [3 ]
Grosu, Lavinia [4 ]
Pourfayaz, Fathollah [1 ]
Bidi, Mokhtar [5 ]
机构
[1] Univ Tehran, Fac New Sci & Technol, Dept Renewable Energies, Tehran 1417466191, Iran
[2] PUT, Ahwaz Fac Petr Engn, Dept Petr Engn, Ahvaz 61963165, Iran
[3] Islamic Azad Univ, Sci & Res Branch, Grad Sch Environm & Energy, Tehran 1417466191, Iran
[4] Univ Paris Ouest Nanterre La Def, 50 Rue Sevres, F-92410 Ville Davray, France
[5] Shahid Beheshti Univ, Fac Mech & Energy Engn, Tehran 1417466191, Iran
关键词
entropy generation; exergy; Brayton cycle; ecological function; irreversibility; DISH-STIRLING ENGINE; MULTI OBJECTIVE OPTIMIZATION; MULTIOBJECTIVE OPTIMIZATION; ECOLOGICAL COEFFICIENT; THERMODYNAMIC ANALYSIS; HEAT ENGINE; EVOLUTIONARY ALGORITHMS; THERMAL EFFICIENCY; THERMOECONOMIC ANALYSIS; GENETIC ALGORITHMS;
D O I
10.1007/s11708-017-0445-y
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
Owing to the energy demands and global warming issue, employing more effective power cycles has become a responsibility. This paper presents a thermodynamical study of an irreversible Brayton cycle with the aim of optimizing the performance of the Brayton cycle. Moreover, four different schemes in the process of multi-objective optimization were suggested, and the outcomes of each scheme are assessed separately. The power output, the concepts of entropy generation, the energy, the exergy output, and the exergy efficiencies for the irreversible Brayton cycle are considered in the analysis. In the first scheme, in order to maximize the exergy output, the ecological function and the ecological coefficient of performance, a multi-objective optimization algorithm (MOEA) is used. In the second scheme, three objective functions including the exergetic performance criteria, the ecological coefficient of performance, and the ecological function are maximized at the same time by employing MOEA. In the third scenario, in order to maximize the exergy output, the exergetic performance criteria and the ecological coefficient of performance, a MOEA is performed. In the last scheme, three objective functions containing the exergetic performance criteria, the ecological coefficient of performance, and the exergy-based ecological function are maximized at the same time by employing multi-objective optimization algorithms. All the strategies are implemented via multi-objective evolutionary algorithms based on the NSGAII method. Finally, to govern the final outcome in each scheme, three well-known decision makers were employed.
引用
收藏
页码:399 / 410
页数:12
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