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自复叠制冷系统降温过程组分浓度优化及控制策略
引用本文:潘垚池,刘金平,许雄文,付志明. 自复叠制冷系统降温过程组分浓度优化及控制策略[J]. 化工学报, 2017, 68(8): 3152-3160. DOI: 10.11949/j.issn.0438-1157.20161610
作者姓名:潘垚池  刘金平  许雄文  付志明
作者单位: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
基金项目:国家自然科学基金青年科学基金项目(51506057);华南理工大学亚热带建筑科学国家重点实验室开放基金项目(2015ZC13,2016KA01);中国科学院低温工程学重点实验室开放基金项目(CRYO201616);广东高校优秀青年创新人才培养计划项目(2013LYM_0111)。
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。

关 键 词:自复叠系统  多元混合工质  算法  优化  控制  
收稿时间:2016-11-14
修稿时间:2017-04-13

Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system
PAN Yaochi,LIU Jinping,XU Xiongwen,FU Zhiming. Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system[J]. Journal of Chemical Industry and Engineering(China), 2017, 68(8): 3152-3160. DOI: 10.11949/j.issn.0438-1157.20161610
Authors:PAN Yaochi  LIU Jinping  XU Xiongwen  FU Zhiming
Affiliation:1.School of Electric Power, South China University of Technology, Guangzhou 510640, Guangdong, China;2.State Key Lab of Subtropical Building Science, South China University of Technology, Guangzhou 510640, Guangdong, China;3.Hisense Ronshen(Guangdong) Cold Cabinet Co., Ltd., Foshan 528305, Guangdong, China
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.
Keywords:auto-cascade  mixed refrigerant  algorithm  optimization  control  
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