化工学报 ›› 2022, Vol. 73 ›› Issue (5): 2060-2072.doi: 10.11949/0438-1157.20211681

• 过程系统工程 • 上一篇    下一篇

一种应用于换热网络综合的阻尼优化方法

刘薇薇(),崔国民(),张璐,肖媛,杨其国,张冠华   

  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:2021-11-24 修回日期:2022-01-18 出版日期:2022-05-05 发布日期:2022-05-24
  • 通讯作者: 崔国民 E-mail:lww_1126@163.com;cgm@usst.edu.cn
  • 作者简介:刘薇薇(1997—),女,硕士研究生,lww_1126@163.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)

Damping optimization method for heat exchange network synthesis

Weiwei LIU(),Guomin CUI(),Lu ZHANG,Yuan XIAO,Qiguo YANG,Guanhua ZHANG   

  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:2021-11-24 Revised:2022-01-18 Published:2022-05-05 Online:2022-05-24
  • Contact: Guomin CUI E-mail:lww_1126@163.com;cgm@usst.edu.cn

摘要:

针对启发式方法优化换热网络在优化后期易陷入局部极值的问题,提出一种阻尼优化方法,即通过引入延缓概率的概念,以一定的概率不接受费用下降的结构,延缓该结构形成固定匹配,避免因连续变量优化过快导致整型变量优化不充分而陷入局部最优。通过探讨不同阶段的优化特点及优化陷入局部极值的成因,进而提出分阶段延缓策略,合理调控延缓条件以及延缓概率的取值,从而提高算法的全局搜索能力。最后采用四个不同规模的算例进行验证,结果表明该方法可有效地跳出局部最优解,促进结构的进一步优化。

关键词: 换热网络, 优化, 局部极值, 延缓, 结构进化, 模型, 计算机模拟

Abstract:

Aiming at the problem that the heat exchange network optimized by the heuristic method is easy to fall into the local extreme value in the later stage of optimization, a damping optimization method is proposed, that is, by introducing the concept of delay probability, the structure with a certain probability will not accept the cost reduction, the structure will be delayed from forming a fixed structure match, and will avoid falling into local optimum due to insufficient optimization of integer variables due to too fast optimization of continuous variables. By discussing the optimization characteristics of different stages and the causes of optimization falling into local extreme, a phased delay strategy is proposed to reasonably adjust the delay conditions and the value of delay probability, to improve the global search ability of the algorithm. Finally, four different scale examples are used to verify the results. The results show that the method can effectively jump out of the local optimal solution and promote the further optimization of the structure.

Key words: heat exchanger network, optimization, local extreme, delay, structural variation, model, computer simulation

中图分类号: 

  • TK 124

图1

有分流节点非结构模型示意图"

图2

RWCE算法优化流程"

图3

当前解及历史最优解的费用变化曲线"

图4

TAC优化过程中的延缓机理"

图5

阻尼RWCE算法优化流程"

图6

不同延缓概率下的费用变化曲线"

表1

分阶段延缓策略在不同优化阶段延缓概率的取值"

Caseit∈[0, 5×107]it∈(5×107, 2×108]it∈(2×108, 8×108]TAC/(USD/a)
DS2-1η=0.6η=0.2η=01497798
DS2-2η=0.6η=0.2η=0.21504171
DS2-3η=0.4η=0.2η=0.21511764
DS2-4η=0.4η=0.2η=01495453
DS2-5η=0.2η=0.2η=0.21509360
DS2-6η=0.2η=0.2η=01496393

表2

9SP在不同优化阶段延缓概率的取值"

Caseit∈[0, 5×107]it∈(5×107, 2×108]it∈(2×108, 8×108]TAC/(USD/a)
RWCE2898422
DS1η=0.2η=0.2η=0.22893376
DS2η=0.5η=0.2η=02892210

图7

9SP算例RWCE算法优化结果(TAC=2898422 USD/a)"

图8

分阶段延缓策略优化9SP最优结果(TAC=2892210 USD/a)"

表3

9SP算例优化结果对比"

ReferencesMethodFormulationUnitsQCU/MWQHU/MWTAC/(USD/a)
Linnhoff等[30]Pinch1333.0225.312.96 × 106
Fieg等[31]GANIM-SWS1431.3423.622922298
霍兆义等[32]GA-PSONIM-SWS1331.9424.222922585
孙涛等[25]RWCENIM-SWS1631.2623.532920246
Pav?o等[4]SA-RFONIM-SWS1432.4824.762909906
鲍中凯等[33]RWCEIU-SWS1832.3124.282906286
图7DS1-RWCENNM-SS2031.5423.872898422
图8DS2-RWCENNM-SS1931.5123.792892210

图9

20SP算例RWCE算法优化结果(TAC=1721621 USD/a)"

表4

20SP在不同优化阶段延缓概率的取值"

Caseit∈[0, 5×107]it∈(5×107, 2×108]it∈(2×108, 8×108]TAC/(USD/a)
RWCE1721621
DS1η=0.15η=0.15η=0.151717208
DS2η=0.5η=0.15η=01714524

图10

分阶段延缓策略优化20SP最优结果(TAC=1714524 USD/a)"

表5

20SP算例优化结果对比"

ReferencesMethodFormulationUnitsQCU/MWQHU/MWTAC/(USD/a)
陈帅等[21]SAA-QPSONS-SWS234.899.041753110
韩正恒等[27]RWCENW-NSS225.019.161727637
Rathjens等[22]HGA-SIRNIM-SWS244.388.531715088
图9DS1-RWCENNM-SS244.498.641721621
图10DS2-RWCENNM-SS224.278.421714524

图11

分阶段延缓策略优化16SP最优结果(TAC=6651937 USD/a)"

表6

16SP算例优化结果对比"

ReferencesMethodFormulationUnitsQCU/MWQHU/MWTAC/(USD/a)
Huo等[34]GA-PSOMixed NS and NIM-SWS16442.3738.807361190
Feyli等[23]GAMQLP17437.7734.217128522
Bao等[35]OP-RWCENW-RWCE19413.6110.046869610
Pav?o等[5]SA-RFONIM-SWS18413.079.506712551
Rathjens等[22]HGA-SIRNIM-SWS18413.029.706657080
图11DS2-RWCENNM-SS18413.089.526651937

图12

分阶段延缓策略优化39SP最优结果(TAC=1877898 USD/a)"

表7

39SP算例优化结果对比"

ReferencesMethodFormulationUnitsQCU/MWQHU/MWTAC/(USD/a)
Zhang等[36]PPSONS-SWS4711.458.151939149
孙涛等[25]RWCENIM-SWS4411.878.561933752
Nemet等[37]GUROBI-DICOPTTransHEN4410.657.351.9288×106①
Pav?o等[17]SA-RFONIM-SWS421900614
图12DS2-RWCENNM-SS4011.027.721877898
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