基于节点配置策略的有分流换热网络优化性能探析

doi:10.16085/j.issn.1000-6613.2020-1539

摘要/Abstract

摘要：

应用节点非结构模型（nodes-based non-structural model，NNM）优化换热网络时，合理地配置节点参数（分流组数和分支数）可辅助算法以更高的效率获得更优的结果。然而，NNM模型的设置中，所有热流股共用一组节点参数，所有冷流股共用一组节点参数，因此无法定制化地满足每一个流股对分流的需求。为提高网络中节点的利用率，本文提出了节点配置策略。该策略可根据流股热容流率对流股上的分支数及其组数进行调整，减少无效结构对优化的阻碍，使算法在优化初期快速获得潜在优势结构，提升优化质量。通过10SP和15SP算例验证策略的有效性，所获结果比文献最优结果分别低340USD/a和2285USD/a，且低于同参数下无该节点配置策略的NNM模型所获结果，从算例分析可知该策略可有效辅助提升算法的优化性能，以获取更优的优化结果。

关键词: 换热网络优化, 节点非结构模型, 节点参数, 模型, 优化

Abstract:

When applying the nodes-based non-structural model (NNM) in optimizing heat exchanger networks, the reasonable adjusting the nodes' parameters (number of stream splitting and the number of groups of stream splitting) can assist the algorithm in obtaining better results within higher efficiency. However, in the setting of NNM model, all hot streams share a set of nodes' parameters and all cold streams share a set of nodes' parameters, thus it cannot customizedly satisfy the requirement of splitting of each stream. To promote the ratio of nodes' utilization in the network, an adjustment strategy was proposed in this paper. This strategy can adjust the number of stream splitting and the number of their splitting groups according to the heat capacities flowrate of streams, which decreases the obstacles resulting from the invalid splitting structures, and obtain the potential superior structures in early optimization period, then improve the optimization quality. 10SP and 15SP were used for proving the validity of strategy in this paper, the results were 340USD/a and 2285USD/a lower than the best ones in literature, respectively. Besides, they are also lower than the ones obtained by the single NNM. The data analysis indicated that this strategy is an effective assistance for improving the performance of the algorithm and contributes to yielding better optimization results.

Key words: heat exchanger network synthesis, nodes-based non-structural model, nodes' parameter, model, optimization

中图分类号:

TK124

徐玥, 崔国民. 基于节点配置策略的有分流换热网络优化性能探析[J]. 化工进展, 2021, 40(7): 3608-3616.

XU Yue, CUI Guomin. Analyzing optimization performance of heat exchanger network synthesis based on nodes' adjustment strategy[J]. Chemical Industry and Engineering Progress, 2021, 40(7): 3608-3616.

图/表 13

参考文献 31

1	Fu YEE T, GROSSMANN I E. Simultaneous optimization models for heat integration (Ⅱ): Heat exchanger network synthesis [J]. Computers & Chemical Engineering， 1990, 14(10): 1165-1184.
2	CHEN Shang, CUI Guomin. Uniformity factor of temperature difference in heat exchanger networks [J]. Applied Thermal Engineering， 2016, 102: 1366-1373.
3	PAVÃO L V, COSTA C, RAVAGNANI M. A new stage-wise superstructure for heat exchanger network synthesis considering substages, sub-splits and cross flows [J]. Applied Thermal Engineering， 2018, 143: 719-735.
4	PAVÃO L V, COSTA C, RAVAGNANI M. An enhanced stage-wise superstructure for heat exchanger networks synthesis with new options for heaters and coolers placement [J]. Industrial & Engineering Chemistry Research, 2018, 57(7): 2560-2573.
5	鲍中凯, 崔国民, 曹冲, 等. 基于公用工程内置策略的换热网络优化[J]. 计算物理, 2019, 36(6): 707-718.
	BAO Zhongkai, CUI Guomin, CAO Chong, et al. Heat exchanger network optimization based on inner utility placement strategy [J]. Chinese Journal of Computational Physics, 2019, 36(6): 707-718.
6	PONCE-ORTEGA J M, SERNA-GONZÁLEZ M, JIMÉNEZ-GUTIÉRREZ A. Synthesis of heat exchanger networks with optimal placement of multiple utilities [J]. Industrial Engineering Chemical Research, 2010, 49: 2849-2856.
7	NA Jonggeol, JUNG Jaeheum, PARK Chansaem, et al. Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages [J]. Computers and Chemical Engineering, 2015, 79: 70-79.
8	HONG Xiaodong, LIAO Zuwei, SUN Jingyuan, et al. Trasshipment type heat exchanger network model for intra- and inter-plant heat integration using process streams [J]. Energy, 2019(178): 853-866.
9	HONG Xiaodong, LIAO Zuwei, JIANG Binbo, et al. New transshipment type MINLP model for heat exchanger network synthesis [J]. Chemical Engineering Science. 2017, 173: 537-559.
10	HONG Xiaodong, LIAO Zuwei, SUN Jingyuan, et al. Indirect heat integration across plants: novel representation of intermediate fluid circles [J]. I&EC Research, 2019, 58: 7233-7246.
11	刘璞, 崔国民, 肖媛, 等. 具有步长调整策略的强制进化随机游走算法优化换热网络[J]. 化工进展, 2017, 36(2): 442-450.
	LIU Pu, CUI Guomin, XIAO Yuan, et al. Optimizing heat exchanger network by random walking algorithm with compulsive evolution combined with step length adjustment strategy [J]. Chemical Industry and Engineering Progress, 2017, 36(2): 442-450.
12	苏戈曼, 崔国民, 鲍中凯, 等. RWCE优化换热网络的不可行解影响分析及强化策略[J]. 化工进展, 2020, 39(1): 14-25.
	SU Geman, CUI Guomin, BAO Zhongkai, et al. Influence analysis and enhancement strategy of infeasible solutions for heat exchanger network optimization with RWCE [J]. Chemical Industry and Engineering Progress, 2020, 39(1): 14-25.
13	邓炜栋, 崔国民, 陈家星, 等. 带惩罚的逆梯度进化算法应用于换热网络[J]. 化工进展, 2018, 37(7): 2500-2509.
	DENG Weidong, CUI Guomin, CHEN Jiaxing, et al. Heat exchange network optimization by inverse gradient evolution strategy with penalty [J]. Chemical Industry and Engineering Progress, 2018, 37(7): 2500-2509.
14	肖媛. 换热网络热集成的全局优化方法及超结构模型研究[D]. 上海: 上海理工大学， 2019.
	XIAO Yuan. Global optimization methods and superstructure model for heat integration of heat exchanger networks [D]. Shanghai: University of Shanghai for Science & Technology, 2019.
15	XU Yue, KAYANGE H A, CUI Guomin. A nodes-based non-structural model considering a series structure for heat exchanger network synthesis [J]. Processes, 2020, 8(695): 1-16.
16	XIAO Yuan, CUI Guomin. A novel random walk algorithm with compulsive evolution for heat exchanger network synthesis [J]. Applied Thermal Engineering, 2017, 115: 1118-1127.
17	AHMAD S. Heat exchanger networks: cost tradeoffs in energy and capital [D]. Manchester: University of Manchester Institute of Science and Technology, 1985.
18	BAO Zhongkai, CUI Guomin, CHEN Jiaxing, et al. A novel random walk algorithm with compulsive evolution combined with an optimum-protection strategy for heat exchanger network synthesis [J]. Energy, 2018, 152: 694-708.
19	孙涛, 崔国民, 陈家星, 等. 采用分流比差异优化策略RWCE算法优化换热网络[J]. 工程热物理学报, 2019, 40(1): 183-190.
	SUN Tao, CUI Guomin, CHEN Jiaxing, et al. Split ratio difference optimization strategy of RWCE algorithm for heat exchanger network synthesis [J]. Journal of Engineering Thermophysics, 2019, 40(1): 183-190.
20	陈子禾, 崔国民, 徐玥, 等. 基于控制参数动态协调策略的换热网络优化研究[J]. 工程热物理学报, 2020, 41(4): 957-965.
	CHEN Zihe, CUI Guomin, XU Yue, et al. Study on heat exchanger network optimization based on dynamic coordination strategy of control parameters [J]. Journal of Engineering Thermophysics, 2020, 41(4): 957-965.
21	RAVAGNANI M, SILVA A P, ARROYO P A, et al. Heat exchanger network synthesis and optimization using genetic algorithm [J]. Applied Thermal Engineering, 2005, 25(7): 1003-1017.
22	彭富裕, 崔国民, 陈家星. 基于模拟退火算法的换热网络双层优化方法[J]. 石油化工, 2014, 43(5): 536-544.
	PENG Fuyu, CUI Guomin, CHEN Jiaxing. Bilevel optimization method for heat exchanger network synthesis based on simulated annealing algorithm [J]. Petrochemical Technology, 2014, 43(5): 536-544.
23	PENG Fuyu, CUI Guomin. Efficient simultaneous synthesis for heat exchanger network with simulated annealing algorithm[J]. Applied Thermal Engineering, 2015, 32(6): 693-700.
24	BJÖRK K M, PETTERSSON F. Optimization of large-scale heat exchanger network synthesis problems [C]// Proceeding of the ISATED International Conference on Modelling and Simulation. Palm Springs. USA, 2003: 313-318.
25	BJÖRK K M, NORDMAN R. Solving large-scale retrofit heat exchanger network synthesis problems with mathematical optimization methods [J]. Chemical Engineering and Process, 2005, 44: 869-876.
26	PAVÃO L V, COSTA C B B, RAVAGNANI M A S S. Heat exchanger network synthesis without stream splits using parallel and simplified simulated annealing and particle swarm optimization [J]. Chemical Engineering Science, 2017, 158: 96-107.
27	FIEG G, LUO Xing, JEZOWSKI J. A monogenetic algorithm for optimal design of large-scale heat exchanger networks [J]. Chemical Engineering and Process, 2009, 48: 1506-1516.
28	PAVÃO L V, COSTA C B B, RAVAGNANI M A S S. Large-scale heat exchanger networks synthesis using simulated annealing and the novel rocket fireworks optimization [J]. AIChE Journal, 2007, 63: 1582-1601.
29	MATTHIAS R, GEORG F. A novel hybrid strategy for cost-optimal heat exchanger network synthesis suited for large-scale problems [J]. Applied Thermal Engineering, 2020, 167: 114771.
30	PAVÃO L V, COSTA C B B, RAVAGNANI M A S S, et al. Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach [J]. Applied Energy, 2017, 203: 304-320.
31	徐玥, 崔国民. 应用结构摄动策略的有分流换热网络优化[J]. 计算物理, 2020(1): 1-12.
	XU Yue, CUI Guomin. The heat exchanger network optimization using structural perturbation strategy [J]. Chinese Journal of Computational Physics, 2020(1): 1-12.

编辑推荐 0

Metrics

阅读次数

全文

612

HTML			PDF

最新录用	在线预览	正式出版	最新录用	在线预览	正式出版
0	0	4	0	0	608

来源	本网站	其他网站

次数	67	545
比例	11%	89%

摘要

313

最新录用	在线预览	正式出版

9	0	304

来源	本网站	其他网站

次数	211	102
比例	67%	33%

流股	Tⁱⁿ/℃	T^out/℃	CF/kW·℃^-1	h/kW·m^-2·℃^-1
H1	85	45	156.3	0.05
H2	120	40	50	0.05
H3	125	35	23.9	0.05
H4	56	46	1250	0.05
H5	90	86	1500	0.05
H6	225	75	50	0.05
C1	40	55	466.7	0.05
C2	55	65	600	0.05
C3	65	165	180	0.05
C4	10	170	81.3	0.05
HU	200	180		0.05
CU	15	20		0.05
热交换器成本=60A USD·a^-1 （A in m²）
热公用工程成本= 100USD·kW^-1·a^-1
冷公用工程成本=15USD·kW^-1·a^-1

流股	Tⁱⁿ/℃	T^out/℃	CF/kW·℃^-1	h/kW·m^-2·℃^-1
H1	85	45	156.3	0.05
H2	120	40	50	0.05
H3	125	35	23.9	0.05
H4	56	46	1250	0.05
H5	90	86	1500	0.05
H6	225	75	50	0.05
C1	40	55	466.7	0.05
C2	55	65	600	0.05
C3	65	165	180	0.05
C4	10	170	81.3	0.05
HU	200	180		0.05
CU	15	20		0.05
热交换器成本=60A USD·a^-1 （A in m²）
热公用工程成本= 100USD·kW^-1·a^-1
冷公用工程成本=15USD·kW^-1·a^-1

节点	Nd_H	Nd_C	Nf_H	Nf_C	Mb_H	Mb_C	TAC/USD·a^-1	R-Nf_C	分流所在流股
A1	10	10	3	3	1	1	5586361	4	C1
A2	6	6	5	5	1	1	5588318	8	C1、C2、C4
B1	8	8	3	3	1	1	5586578	6	C1、C4
B2	6	6	4	4	1	1	5587797	6	C1、C2、C4
B3	12	12	2	2	1	1	5587211	4	C1、C2

节点	Nd_H	Nd_C	Nf_H	Nf_C	Mb_H	Mb_C	TAC/USD·a^-1	R-Nf_C	分流所在流股
A1	10	10	3	3	1	1	5586361	4	C1
A2	6	6	5	5	1	1	5588318	8	C1、C2、C4
B1	8	8	3	3	1	1	5586578	6	C1、C4
B2	6	6	4	4	1	1	5587797	6	C1、C2、C4
B3	12	12	2	2	1	1	5587211	4	C1、C2

文献	TAC/ USD·a^-1	单元	热公用工程/MW	冷公用工程/MW
［17］	7074000	—	—	—
［21］	5672821	13	20529.3	14923.8
［22］	5636048	15	20297	14691
［23］	5596079	18	20339	14733.5
［18］	5587883^①	19	20315.5	14711.9
［19］	5585632^①	17	19442.1	14837.3
本文图4	5585292^①	25	20216.2	14601.8