Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm

Danlei Chen; Yiqing Luo; Xigang Yuan

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Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm

Process Systems Engineering and Process Safety | Updated：2026-01-06

- Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm
- Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm
- 中国化学工程学报（英文版） 2022年50卷第10期页码：412-422
- Affiliations：
  
  1. School of Chemical Engineering and Technology, Tianjin University,Tianjin,China,300072
  2. State Key Laboratory of Chemical Engineering, Tianjin University,Tianjin,China,300072
- Author bio：
- Funds：
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- 纸质出版：2022
- Accepted：
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Danlei Chen, Yiqing Luo, Xigang Yuan. Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm[J]. 中国化学工程学报（英文版）, 2022,50(10):412-422.

Danlei Chen, Yiqing Luo, Xigang Yuan. Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm[J]. Chinese Journal of Chemical Engineering, 2022, 50(10): 412-422.
Danlei Chen, Yiqing Luo, Xigang Yuan. Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm[J]. 中国化学工程学报（英文版）, 2022,50(10):412-422. DOI：

Danlei Chen, Yiqing Luo, Xigang Yuan. Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm[J]. Chinese Journal of Chemical Engineering, 2022, 50(10): 412-422. DOI：

摘要

Abstract

Simultaneous optimization of refrigeration system (RS) and its heat exchanger network (HEN) leads to a large-scale non-convex mixed-integer non-linear programming (MINLP) problem. Conventionally

researchers usually adopted simplifications to confine problem scale from being too large at the cost of reducing solution space. This study established an optimization framework for the simultaneous optimization of RS and HEN. Firstly

A more comprehensive and compact model was developed to guarantee a relatively complete solution space while reducing model scale as well as its solving difficulty. In this model

a tandem arrangement of connecting sub-coolers and expansion valves was considered in the superstructure; and the pressure/temperature levels were optimized as continuous variables. On this basis

we proposed a “two-step transformation method” to equivalently transform the cross-level structure into a non-cross-level structure

and the de-redundant superstructure was established with ensuring comprehensiveness and rigor. Furthermore

the MINLP model was developed and solved by Particle Swarm Optimization algorithm. Finally

our methodology was validated to get better optimal results with less CPU time in two case studies

an ethylene RS in an existing plant and a reported propylene RS.

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