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换热器网络设备面积与清洗时序同步优化
引用本文:樊婕,李继龙,刘琳琳,庄钰,都健.换热器网络设备面积与清洗时序同步优化[J].化工学报,2014,65(11):4484-4489.
作者姓名:樊婕  李继龙  刘琳琳  庄钰  都健
作者单位:1. 大连理工大学化工系统工程研究所, 辽宁 大连 116024; 2. 大连理工大学环境学院, 工业生态与环境工程教育部重点实验室, 辽宁 大连 116024
基金项目:中央高校基本科研业务费专项资金(DUT14RC,中国博士后科学基金项目,辽宁省自然科学基金项目(2014020007)。@@@@ supported by the Fundamental Research Funds for the Central Universities of China (DUT14RC,the China Postdoctoral Science Foundation,the Natural Science Foundation of Liaoning Province
摘    要:表面结垢会严重影响换热器的传热效率,定期清洗是解决该问题的主要方式.针对以往换热器网络清洗时序优化方法中用于决策的整型变量较多而难以求解的问题,提出以换热器清洗的最大允许污垢热阻为优化变量,取代表示换热器是否清洗的二进制变量,将混合整数非线性规划问题转化成非线性规划问题,能够有效地减小问题规模,降低求解难度.优化过程中兼顾换热器网络的设计型与操作型问题,采用遗传/模拟退火算法同步优化换热器的面积与清洗时序.将该方法用于一个实例,所得年度总费用与文献基本一致,验证了该方法的有效性.

关 键 词:系统工程  换热网络  优化  结垢  清洗时序  
收稿时间:2014-07-18
修稿时间:2014-07-28

Simultaneous optimization of areas and cleaning schedule for heat exchanger networks
FAN Jie,LI Jilong,LIU Linlin,ZHUANG Yu,DU Jian.Simultaneous optimization of areas and cleaning schedule for heat exchanger networks[J].Journal of Chemical Industry and Engineering(China),2014,65(11):4484-4489.
Authors:FAN Jie  LI Jilong  LIU Linlin  ZHUANG Yu  DU Jian
Affiliation:1. Institute of Chemical Process Systems Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China; 2. Key Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
Abstract:Fouling over the heat transfer surface of equipments always causes reduction to the overall heat transfer coefficient. Regular cleanings become an important means of saving energy. In the existing researches about the optimal cleaning schedule in heat exchanger networks, too many binary variables were involved, which raised the difficulties to solve the problem. This paper took the maximum allowable fouling resistance of the heat unit as the optimization variable, instead of the binary variables to represent requirement of cleaning the heat exchangers. The proposed method converted the mixed integer nonlinear programming (MINLP) problem into a nonlinear programming (NLP) problem, effectively reducing the size of the problem and the difficulty to solve the problem. With consideration of both design and operation problems of the heat exchanger network, genetic/simulated annealing algorithm (GA/SA) was adopted to optimize areas and cleaning schedule of the heat exchangers simultaneously. An example was studied to illustrate the effectiveness of the method.
Keywords:system engineering  heat exchanger network  optimization  fouling  cleaning schedule
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