计算物理 ›› 2020, Vol. 37 ›› Issue (3): 341-351.DOI: 10.19596/j.cnki.1001-246x.8060

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一种内部公用工程进化的换热网络优化策略

姜逸文, 崔国民, 鲍中凯, 刘火林, 周金佳   

  1. 上海理工大学新能源科学与工程研究所, 上海 200093
  • 收稿日期:2019-03-11 修回日期:2019-05-30 出版日期:2020-05-25 发布日期:2020-05-25
  • 通讯作者: 崔国民,E-mail:cgm1226@163.com
  • 作者简介:姜逸文(1995-),男,硕士研究生,E-mail:jiangyiwen1995@163.com
  • 基金资助:
    国家自然科学基金(51176125)及沪江基金研究基地专项(D14001)资助项目

A Heat Exchanger Network Optimization Strategy for Internal Utility Evolution

JIANG Yiwen, CUI Guomin, BAO Zhongkai, LIU Huolin, ZHOU Jinjia   

  1. Institute of New Energy Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2019-03-11 Revised:2019-05-30 Online:2020-05-25 Published:2020-05-25

摘要: 在换热网络优化问题中,采用内部公用工程代替换热温度交叉的不可行匹配能使优化得以继续,同时扩大求解空间,但可能因增加额外的固定投资费用而使其作为差解在进化过程中被接受下来,导致优化效率下降.鉴于此,首先分析内部公用工程对优化进程可能造成的负面影响,提出一种内部公用工程的进化策略,对于具有一对内部公用工程的结构,首先通过扩大其年综合费用以进行惩罚,从而降低其接受的概率,继之,针对仍被接受的内部公用工程结构,在每次迭代时均强制内部公用工程进行随机游走,合理调整其大小,从而改善结构性能.采用两个算例验证策略提升了算法优化效率.

关键词: 换热网络, 优化, 内部公用工程, 强制进化随机游走算法

Abstract: There is an infeasible structure in heat exchanger network optimization in which matching temperatures of cold and hot streams are crossed. Replacing matching by internal utilities is a way to deal with infeasible structure and its solution domain can be expanded. This approach introduces additional fixed investment costs in total annual cost which may be accepted in weaker solutions, which may cause a decrease of optimization efficiency. Therefore, we analyze firstly probable bad influence caused by internal utilities and propose an evolutionary strategy for internal utilities. Total annual cost of the solution which has internal utilities are punished to reduce the accepting probability. If the solution with internal utilities still exist, then heat loads of internal utility exchangers are forced to evolve to optimize the heat load and improve its structure. Effectiveness of the strategy is verified with two examples.

Key words: heat exchanger network, optimization, internal utilities, random walk algorithm with compulsive evolution

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