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

doi:10.11949/j.issn.0438-1157.20161610

CIESC Journal ›› 2017, Vol. 68 ›› Issue (8): 3152-3160.DOI: 10.11949/j.issn.0438-1157.20161610

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

PAN Yaochi¹, LIU Jinping^1,2, XU Xiongwen^1,2, FU Zhiming³

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

Received:2016-11-14 Revised:2017-04-13 Online:2017-08-05 Published:2017-08-05
Supported by:
supported by the National Natural Science Foundation of China (51506057), the State Key Lab of Subtropical Building Science (2015ZC13, 2016KA01), the Key Laboratory of Cryogenics, TIPC, CAS (CRYO201616) and the Foundation for Distinguished Young Talents in Higher Education of Guangdong, China (2013LYM_0111).

自复叠制冷系统降温过程组分浓度优化及控制策略

潘垚池¹, 刘金平^1,2, 许雄文^1,2, 付志明³

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

通讯作者: 许雄文
基金资助:
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）。

Abstract

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.

Key words: auto-cascade, mixed refrigerant, algorithm, optimization, control

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

CLC Number:

TK123

PAN Yaochi, LIU Jinping, XU Xiongwen, FU Zhiming. Component concentration optimization analysis of cooling process and control strategy in auto-cascade refrigeration system[J]. CIESC Journal, 2017, 68(8): 3152-3160.

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.

References 26

[1]	朱魁章. 多元混合工质制冷机的应用[J]. 制冷, 1998, 65(4):80-82. ZHU K Z. Application of multi-refrigerant mixtures cryocooler[J]. Refrigeration, 1998, 65(4):80-82.
[2]	YOON W J, SEO K J, CHUNG H J, et al. Performance optimization of a Lorenz-Meutzner cycle charged with hydrocarbon mixtures for a domestic refrigerator-freezer[J]. International Journal of Refrigeration, 2012, 35(1):36-46.
[3]	CHRZ V. Cryogenic mixed refrigerant processes[J]. International Journal of Refrigeration, 2008, 33(3):648-649.
[4]	PODBIELNIAK W. Art of refrigeration:US2041725[P]. 1936-05-26.
[5]	RUHEMANN M. The Separation of Gases[M]. Clarendon Press, 1949:156.
[6]	KLEEMENKO A P. One flow cascade cycle[C]//Proceedings 10th International Congress of Refrigeration. Copenhagen, Denmark:Pergamon Press, 1959:34-39.
[7]	MISSIMER D J. Control system for low temperature refrigeration system:US3698202[P]. 1972-10-17.
[8]	MISSIMER D J. Self-balancing low temperature refrigeration system:US3768273[P]. 1973-10-30.
[9]	LONGSWORTH R C, BOIARSKY M J, KHATRI A. Cryostat refrigeration system using mixed refrigerants in a closed vapor compression cycle having a fixed flow restrictor:US5579654[P]. 1996-12-03.
[10]	LITTLE W A. Self-cleaning low-temperature refrigeration system:US5617739[P]. 1997-04-08.
[11]	LITTLE W A. Method for efficient counter-current heat exchange using optimized mixtures:US5644502[P]. 1997-07-01.
[12]	李文林, 华小龙. 混合工质制冷循环的试验研究[J]. 流体机械, 1987, 53(4):53-55. LI W L, HUA X L. Experimental research on refrigerant mixtures[J]. Fluid Machinery, 1987, 53(4):53-55.
[13]	罗二仓, 公茂琼. 获得低于60 K温区的混合物工质内复叠节流制冷机的研究[J]. 低温工程, 1999, (6):12-16. LUO E C, GONG M Q. Study on a new auto-casade throttle refrigeration cycle with special cryogenic mixture below 60 K[J]. Cryogenics, 1999, (6):12-16.
[14]	刘金平, 朱宇龙. 非共沸混合工质自复叠热泵相积存实验研究[J]. 制冷学报, 2009, 30(6):5-10. LIU J P, ZHU Y L. Experimental study on phase holdup in auto-cascade heat pump with zeotropic mixture[J]. Journal of Refrigeration, 2009, 30(6):5-10.
[15]	刘金平, 吴啸, 郭灵兵. 节流阀开度对自复叠制冷循环冷凝蒸发器换热性能影响的试验研究[J]. 机械工程学报, 2011, 47(8):152-157. LIU J P, WU X, GUO L B. Effects of opening of throttle valves on condenser-evaporator heat transfer performance of auto-cascade refrigeration cycle[J]. Journal of Mechanical Engineering, 2011, 47(8):152-157.
[16]	许雄文, 刘金平, 曹乐, 等. 非共沸混合工质在制冷循环中浓度偏移分析[J]. 化工学报, 2011, 62(11):3066-3072. XU X W, LIU J P, CAO L, et al. Composition shift analysis of zeotropic mixed refrigerant in refrigeration cycle[J]. CIESC Journal, 2011, 62(11):3066-3072.
[17]	吴裕庆, 张华. 混合工质用于单级压缩制冷回热循环的理论研究与分析[J]. 低温与超导, 2010, 38(1):37-40. WU Y Q, ZHANG H. Theoretical study and analysis of mixed for single-stage compression refrigeration regenerative cycles[J]. Cryogenics and Superconductivity, 2010, 38(1):37-40.
[18]	朱军韬, 张华. 单级自动复叠混合工质制冷循环的实验研究[J]. 低温与超导, 2012, 40(8):75-77. ZHU J T, ZHANG H. Experimental research on refrigerant mixtures of a single-stage auto-cascade refrigeration system[J]. Cryogenics and Superconductivity, 2012, 40(8):75-77.
[19]	张书春, 张华, 赵巍. 五级自动复叠制冷循环混合制冷剂特性分析与计算[J]. 低温与超导, 2013, 41(5):48-50. ZHANG S C, ZHANG H, ZHAO W. The analysis of the refrigerator mixtures characters in the five-stage auto-cascade refrigeration cycle[J]. Cryogenics and Superconductivity, 2013, 41(5):48-50.
[20]	许雄文. 非共沸混合工质制冷系统工质浓度变化及其性能优化研究[D]. 广州:华南理工大学, 2012. XU X W. Study of refrigerant composition shift and performance optimization for zeotropic refrigeration system[D]. Guangzhou:South China University of Technology, 2012.
[21]	XU X W, LIU J P, JIANG C S, et al. The correlation between mixed refrigerant composition and ambient conditions in the PRICO LNG process[J]. Applied Energy, 2013, 102(2):1127-1136.
[22]	XU X W, LIU J P, CAO L. Optimization and analysis of mixed refrigerant composition for the PRICO natural gas liquefaction process[J]. Cryogenics, 2013, 59(1):60-69.
[23]	许雄文, 曹乐, 庞伟强, 等. 基于遗传算法一级天然气液化制冷系统优化[C]//2013中国制冷学会学术年会. 武汉, 2013:88. XU X W, CAO L, PANG W Q, et al. The optimization of single-stage natural gas liquefaction refrigeration process based on genetic algorithm[C]//Proceedings of the China Society of Refrigeration in 2013. Wuhan, 2013:88.
[24]	HOLLAND J H. Adaptation in natural and artificial systems:an introductory analysis with applications to biology, control and artificial intelligence[J]. Control & Artificial Intelligence University of Michigan Press, 1975, 6(2):126-137.
[25]	公茂琼, 吴剑锋, 罗二仓. 深冷混合工质节流制冷原理及应用[M]. 北京:中国科学技术出版社, 2014:115-116. GONG M Q, WU J F, LUO E C. Principle and Application of Throttled Refrigeration for Cryogenic Mixture[M]. Beijing:China Science and Technology Press, 2014:115-116.
[26]	王雁. 混合工质R134a/R23物性及其自然复叠循环特性的理论研究[D]. 南京:东南大学, 2005. WANG Y. Study on mixed-refrigerant R134a/R23 and its auto-cascade refrigeration cycle[D]. Nanjing:Southeast University, 2005.

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

自复叠制冷系统降温过程组分浓度优化及控制策略

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