Structural Diversity Analysis and Improved Optimization Strategy of Heat Exchanger Networks Based on NW-NSM Model

doi:10.19596/j.cnki.1001-246x.8276

Abstract

Abstract:

In optimizing heat exchanger networks by random walk algorithm with compulsive evolution (RWCE), individual structures become similar, which leads to a decline in population diversity and algorithmic global search capability. It becames difficult to optimize the structure of heat exchanger networks further. To explore similarity of individual structures, two evaluation indexes were established to measure similarity level of individual structures.It was found that the number of similar heat units in individual structure increases gradually and the difference of heat load between similar heat units decreases during the optimization process which resulting the evolution of individual structures in the same direction. Therefore, taking the improvement of population diversity as guiding direction, a repulsive-evolution strategy for heat units was proposed. It changes the direction of structure evolution and reduces the scale of similar structure through increasing the heat load gap of similar heat exchange units and promoting differential evolution of similar heat exchange units.Finally, 20SP and 15SP were used to verify effectiveness of the strategy. Total annual cost of the structure saved 12 105 ＄·a^-1 and 52 535 ＄·a^-1, respectively, compared with the optimal result in literature, which indicating that the strategy enhances the algorithmic global search capability effectively.

Key words: heat exchanger networks, population diversity, repulsive evolution, random walk algorithm with compulsive evolution

CLC Number:

TK124

Zhengheng HAN, Guomin CUI, Weijie ZHANG, Qianqian ZHAO, Yuan XIAO, Guanhua ZHANG. Structural Diversity Analysis and Improved Optimization Strategy of Heat Exchanger Networks Based on NW-NSM Model[J]. Chinese Journal of Computational Physics, 2021, 38(4): 479-488.

Figures/Tables 10

References 27

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	Unit	Utility cost/(＄·a^-1)	Equipment cost/(＄·a^-1)	TAC/(＄·a^-1)
Ref.[20]	22	457 768	961 213	1 418 981
Ref.[21]	20	456 775	957 032	1 413 807
Ref.[22]	22	457 125	955 861	1 412 986
Ref.[23]	21	458 615	954 186	1 412 801
Ref.[24]	20	457 750	949 453	1 407 203
Fig. 7	21	457 750	937 348	1 395 098

	Unit	Utility cost/(＄·a^-1)	Equipment cost/(＄·a^-1)	TAC/(＄·a^-1)
Ref.[20]	22	457 768	961 213	1 418 981
Ref.[21]	20	456 775	957 032	1 413 807
Ref.[22]	22	457 125	955 861	1 412 986
Ref.[23]	21	458 615	954 186	1 412 801
Ref.[24]	20	457 750	949 453	1 407 203
Fig. 7	21	457 750	937 348	1 395 098

	Unit	Utility cost/(＄·a^-1)	Equipment cost/(＄·a^-1)	TAC/(＄·a^-1)
Ref.[25]	26	3 464 312	1 768 975	5 233 287
Ref.[26]	26	3 437 670	1 740 115	5 177 785
Ref.[27]	24	3 445 170	1 724 713	5 169 883
Fig. 8	25	3 358 112	1 759 236	5 117 348

	Unit	Utility cost/(＄·a^-1)	Equipment cost/(＄·a^-1)	TAC/(＄·a^-1)
Ref.[25]	26	3 464 312	1 768 975	5 233 287
Ref.[26]	26	3 437 670	1 740 115	5 177 785
Ref.[27]	24	3 445 170	1 724 713	5 169 883
Fig. 8	25	3 358 112	1 759 236	5 117 348

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