Multi-objective optimization and performance analyses of an endoreversible rectangular cycle

被引:5
|
作者
Liu, Xiaohong [1 ]
Gong, Qirui [2 ]
Chen, Lingen [3 ,4 ,5 ]
Ge, Yanlin [3 ,4 ,5 ]
机构
[1] Southwest Jiaotong Univ, Engn Res Ctr Adv Drive Energy Saving Technol, Minist Educ, Chengdu 610031, Peoples R China
[2] Wuhan Marine Machinery Plant Co Ltd, Wuhan 430084, Peoples R China
[3] Wuhan Inst Technol, Inst Thermal Sci & Power Engn, Wuhan 430205, Peoples R China
[4] Hubei Prov Engn Technol Res Ctr Green Chem Equipme, Wuhan 430205, Peoples R China
[5] Wuhan Inst Technol, Sch Mech & Elect Engn, Wuhan 430205, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-objective optimization; Rectangular cycle; Power density; Efficient power; Finite-time thermodynamics; GENERATION RATE MINIMIZATION; ENTROPY GENERATION; ECOLOGICAL OPTIMIZATION; HEAT-ENGINE; THERMODYNAMIC OPTIMIZATION; EFFICIENT POWER; BRAYTON CYCLE; CRITERION; CONFIGURATION; WORKING;
D O I
10.1016/j.egyr.2022.09.107
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
Based on the endoreversible rectangular cycle model founded in the previous literature, the rectangular cycle performance characteristics with nonlinear variable specific heats are analyzed by applying finite time thermodynamic theory when the objective functions are efficient power and power density, respectively. The different four-objective, three-objective and two-objective combinations are optimized based on the four objectives of the power density, efficient power, power output and efficiency by using the NSGA-II, then the results of the multi-objective optimizations are compared with those of the single-objective optimizations. The results show that, compared with the maximum power output point, although the heat engine efficiency at the maximum power density working point reduces by 10.97%, the heat engine size reduces by 30.84%; compared with the maximum power output point, although the heat engine power output at the maximum efficient power working point reduces by 0.067%, the heat engine efficiency increases by 0.21%. In the MO optimization results, the smallest deviation index is 0.2371; in the single-objective optimization results, the smallest deviation index is 0.2380; so the optimization result of the MO is better than those of the single-objectives.(c) 2022 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:12712 / 12726
页数:15
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