化工学报 ›› 2022, Vol. 73 ›› Issue (7): 3145-3155.doi: 10.11949/0438-1157.20220024

• 过程系统工程 • 上一篇    下一篇

精细搜索策略应用于质量交换网络综合

杨岭(),崔国民(),周志强,肖媛   

  1. 上海理工大学能源与动力工程学院，上海市动力工程多相流动与传热重点实验室，上海 200093
  • 收稿日期:2022-01-06 修回日期:2022-03-23 出版日期:2022-07-05 发布日期:2022-08-01
  • 通讯作者: 崔国民 E-mail:969101139@qq.com;cgm@usst.edu.cn
  • 作者简介:杨岭（1997—），男，硕士研究生，969101139@qq.com
  • 基金资助:
    国家自然科学基金项目(21978171);中国博士后科学基金项目(2020M671171)

Fine search strategy applied to mass exchange network synthesis

Ling YANG(),Guomin CUI(),Zhiqiang ZHOU,Yuan XIAO   

  1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, Shanghai 200093, China
  • Received:2022-01-06 Revised:2022-03-23 Published:2022-07-05 Online:2022-08-01
  • Contact: Guomin CUI E-mail:969101139@qq.com;cgm@usst.edu.cn

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摘要：

质量交换网络是化工过程系统的重要组成部分，其优化设计对降低污染排放具有重要意义。采用启发式算法优化质量交换网络时，存在难以兼顾全局搜索和局部搜索的问题。通过分析不同精度优化参数下的优化结果，揭示了该问题的成因，并提出一种精细搜索策略用于基础算法所得结构的深度优化。该策略包含两种方法，方法1采用具有个体回代与分化的高精度强制进化随机游走算法，可保留个体结构变异能力；方法2采用确定性方法依次对多维目标函数中的每个变量进行一维搜索，具有精度高收敛快的优点。将该策略应用于焦炉气脱硫和空气除氨算例，得到的结果分别为407308 USD·a-1和127807 USD·a-1，经济性优于现有文献中的结果，验证了本策略的有效性。

关键词: 质量交换网络, 过程系统, 优化, 强制进化随机游走算法, 确定性方法

Abstract:

Mass exchange network is an important part of chemical process system, and its optimal design is of great significance to reduce pollution emissions. When the heuristic algorithm is used to optimize the mass exchange network, there is a problem that it is difficult to take into account both the global search and the local search. By analyzing the optimization results under different precision optimization parameters, this paper reveals the causes of the problem, and proposes a fine search strategy for the in-depth optimization of the structure obtained by the basic algorithm. The strategy includes two methods. Method 1 adopted a high-precision random walk algorithm with compulsive evolution (RWCE) with individual back substitution and differentiation, which can retain the ability of individual structure variation. Method 2 used the deterministic approach to perform a one-dimensional search for each variable in the multidimensional objective function in turn, which has the advantages of high precision and fast convergence. Applying this strategy to coke oven gas sweetening and ammonia removal problem, the results are 407308 USD·a-1 and 127807 USD·a-1, which are better than the best results in the current literature. The effectiveness of the proposed strategy is verified.

Key words: mass exchange network, process system, optimization, random walk algorithm with compulsive evolution, deterministic method

中图分类号: 

  • TQ 021.8

图1

质量交换网络示意图"

图2

贫富流股的相平衡关系"

图3

有分流节点非结构模型"

图4

参数A得到的结构"

图5

参数B得到的结构"

图6

不同优化参数的TAC迭代曲线"

图7

基于启发式算法的精细搜索策略流程"

表1

算例1的流股数据"

流股最大流量/(kg·s-1)入口浓度/(kg H2S·kg-1)目标浓度/(kg H2S·kg-1)mbC0
R10.90000.070000.00030
R20.10000.051000.00010
S12.30000.000600.031001.450117360
S2∞0.000200.003500.260176040

图8

算例1优化全过程的TAC迭代曲线"

图9

算例1精细搜索前后的网络结构"

表2

算例1的结果对比"

文献单元数总塔板数TAC/(USD·a-1)
[24]4—530471
[25]5—469968
[7]5—431613
[26]425429700
[27]421422293
[28]424420545
[15]420412500
[16]422411166
[13]619410971
[14]619410565
本文421407308

表3

算例2的流股数据"

流股最大流量/(kg·s-1)入口浓度/(kg NH3·kg-1)目标浓度/(kg NH3·kg-1)mbC0
R12.00000.005000.00100
R24.00000.005000.00250
R33.50000.011000.00250
R41.50000.010000.00500
R50.50000.008000.00250
S11.80000.001700.007101.200
S21.00000.002500.00850100
S3∞0.000000.017000.500.001

图10

算例2基础RWCE与精细搜索优化过程的TAC曲线"

图11

算例2精细搜索前后的结构"

表4

算例2的结果对比"

文献单元数操作费用/(USD·a-1)投资费用/(USD·a-1)TAC/(USD·a-1)
[30]88520348797134000
[12]78241050913133323
[25]98130148599129900
[28]87335047367120717
本文97750850299127807
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