Optimization of operation parameters of refrigeration cycle using particle swarm and NLP techniques

被引：27

作者：

Ghorbani, Bahram ^{[1
]}

Mafi, Mostafa ^{[2
]}

Shirmohammadi, Reza ^{[3
]}

Hamedi, Mohammad-Hossein ^{[1
]}

Amidpour, Majid ^{[1
]}

机构：

[1] KNToosi Univ Technol, Fac Mech Engn, Energy Convers Grp, Tehran, Iran

[2] Imam Khomeini Int Univ, Fac Mech Engn, Energy Convers Grp, Qazvin, Iran

[3] Islamic Azad Univ, Fac Engn, Dept Energy Syst Engn, South Tehran Branch, Tehran, Iran

来源：

JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING | 2014年 / 21卷

关键词：

Refrigeration system; Mixed refrigerant; Particle swarm optimization; Non-linear programming; NATURAL-GAS; LIQUEFACTION PROCESS; PROPANE; DESIGN;

D O I：

10.1016/j.jngse.2014.10.007

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：

In this paper, the two mixed refrigerant refrigeration cycles were proposed to be replaced by pure ethylene cycle in the olefin plant of the Tabriz petrochemical complex. Both these components composition of refrigerant and the compressor operations pressures are the key design parameters in the mixed refrigerant refrigeration systems. The purpose of the paper is to present a systematic method based on a combination of mathematical methods and thermodynamic viewpoint to optimize mixed refrigerant cycles parameters. Particle swarm optimization and non-linear programming techniques were employed to optimize the parameters of cycles. Results show that the particle swarm optimization is superior to the NLP optimization techniques in finding the values of optimizing variables. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：779 / 790

页数：12

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