Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system

PAN Yaochi; LIU Jinping; XU Xiongwen; FU Zhiming

doi:10.11949/j.issn.0438-1157.20161610

您当前的位置：

首页 >

文章列表页 >

Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system

更新时间：2025-12-10

- Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system
- CIESC Journal Issue 8, Pages: 3152-3160(2017)
- 作者机构：
  
  1. 华南理工大学电力学院,广东,广州,510640
  2. 广东省能源高效清洁利用重点实验室,广东,广州,510640
  3. 海信容声(广东)冷柜有限公司,广东,佛山,528305
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20161610
  CLC： K123
- Online First：05 August 2017，
  
  Published：05 August 2017
- 稿件说明：
移动端阅览
PAN Yaochi, LIU Jinping, XU Xiongwen, et al. Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system[J]. CIESC Journal, 2017, (8): 3152-3160.
DOI：

PAN Yaochi, LIU Jinping, XU Xiongwen, et al. Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system[J]. CIESC Journal, 2017, (8): 3152-3160. DOI： 10.11949/j.issn.0438-1157.20161610.

摘要

混合工质低温制冷系统存在能效比较低、降温速度慢的问题。为提高混合工质自复叠制冷系统的降温性能，减小系统工作能耗，采用遗传算法集成Aspen Plus进行混合工质组分浓度优化，给出了不同工况下最优循环组分的需求规律。模拟结果表明，随着温度的降低，高沸点组分的需求逐渐降低，低沸点组分的需求逐渐增加。据此提出了一种有效的组分浓度控制策略并进行实验验证，实验结果表明，以膨胀储气罐和控制阀联合作用的方法可以增加系统降温速度，减小压缩机总功耗，控制系统的开机压力。

Abstract

The energy efficiency ratio of mixed refrigerant cryogenic system is low. For the sake of improving cryogenic performance and reducing energy consumption in the auto-cascade refrigeration system

genetic algorithm and Aspen Plus were adopted to optimize the ACR system in this paper. The optimal cycle mixed refrigerant compositions under different working condition were got. The simulation results showed that with the reduction of evaporation temperature

the demand of high boiling components reduced gradually. Based on the analysis result

an effective solution was proposed to control the working fluid composition and a corresponding experiment was done. The results showed that the control solution can increase temperature reducing rate of system and reduce the total power consumption of the compressor. Moreover

pressure of system was controlled.

关键词

Keywords

references

Views

202

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Hybrid modeling and optimization of acetylene hydrogenation process

Deep reinforcement learning-based intelligent production scheduling for a heterogeneous production line plants

Water quality prediction in wastewater treatment based on data decomposition and dung beetle optimized TCN-BiGRU/BiLSTM

Prediction of COD concentration in wastewater treatment plant effluent based on secondary decomposition and BiLSTM

A prediction method for effluent ammonia nitrogen concentration based on convolutional layer and attention mechanism long short-term memory network

Related Author

Zhencheng YE

Huanlan ZHOU

Debao RAO

WANG Dantong

GAO Xiaoyong

ZHANG Li

FENG Xugang

TANG Lei

Related Institution

Key Laboratory of Chemical Process Control and Optimization Technology, Ministry of Education, School of Information Science and Engineering, East China University of Science and Technology

Department of Automation, China University of Petroleum

Hainan Institute of China University of Petroleum

School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan

Anhui Province Key Laboratory of Special Heavy Load Robot, Ma’anshan

⁰