考虑原油性质波动的炼厂氢气网络集成优化

doi:10.11949/0438-1157.20211657

化工学报 ›› 2022, Vol. 73 ›› Issue (4): 1631-1646.doi: 10.11949/0438-1157.20211657

考虑原油性质波动的炼厂氢气网络集成优化

张欣(),周利(),王诗慧,吉旭,毕可鑫

四川大学化学工程学院，四川成都 610065

收稿日期:2021-11-18 修回日期:2022-01-07 出版日期:2022-04-05 发布日期:2022-04-25
通讯作者: 周利 E-mail:xinscu@outlook.com;chezli@scu.edu.cn
作者简介:张欣（1997—），女，硕士研究生，xinscu@outlook.com
基金资助:
国家重点研发计划项目(2021YFB40005);中央高校基本科研业务费专项资金项目(YJ201838);国家自然科学基金项目(22108178)

Integrated optimization of refinery hydrogen networks with crude oil properties fluctuations

Xin ZHANG(),Li ZHOU(),Shihui WANG,Xu JI,Kexin BI

School of Chemical Engineering, Sichuan University, Chengdu 610065, Sichuan, China

Received:2021-11-18 Revised:2022-01-07 Published:2022-04-05 Online:2022-04-25
Contact: Li ZHOU E-mail:xinscu@outlook.com;chezli@scu.edu.cn

摘要/Abstract

摘要：

针对原油性质的不确定性，提出了一种基于质量传递机理的随机规划建模框架，以实现炼厂氢气网络在经济效益和抗扰能力上的同步优化。该框架耦合了常减压蒸馏、加氢精制以及闪蒸分离等过程单元，从微观上解析原油性质波动对网络运行的影响；采用了代理模型技术增设脱硫模块，并利用了二阶段随机规划方法改造管网，从宏观上优化氢气网络以满足生产要求。为验证所提方法的有效性和适用性，对某一现有的炼厂氢网络进行了改造设计研究。结果表明，集成过程单元的多场景优化策略能够有效提升网络的经济性能，并且能使其灵活应对因原油性质波动引起的操作场景的改变。

关键词: 氢气网络, 优化设计, 集成, 过程系统, 代理模型技术, 随机规划

Abstract:

A stochastic programming modeling framework based on mass transfer mechanism was proposed, which took the uncertainty of crude oil properties into consideration, to achieve the simultaneous optimization of economic performance and disturbance rejection ability of refinery hydrogen network. The framework integrated process units such as atmospheric and vacuum distillation, hydrofining and flash separation to analyze the impact of crude oil properties fluctuations on network operation microscopically; adopted surrogate-assisted techniques to embed desulfurization unit and used the two-stage stochastic programming approach to retrofit network, so as to optimize hydrogen network macroscopically to meet production requirements. To verify the effectiveness and applicability of the proposed method, studies on the optimization design of an industrial hydrogen system were presented. The results show that the multi-scenario optimization strategy integrated process units can effectively improve the economic performance of hydrogen network. And it can flexibly respond to changes in operating scenarios caused by fluctuations in crude oil properties.

Key words: hydrogen network, optimal design, integration, process systems, surrogate modeling techniques, stochastic programming

中图分类号:

TE 68

张欣, 周利, 王诗慧, 吉旭, 毕可鑫. 考虑原油性质波动的炼厂氢气网络集成优化[J]. 化工学报, 2022, 73(4): 1631-1646.

ZHANG Xin, ZHOU Li, WANG Shihui, JI Xu, BI Kexin. Integrated optimization of refinery hydrogen networks with crude oil properties fluctuations[J]. CIESC Journal, 2022, 73(4): 1631-1646.

图/表 22

图1

图2

图3

图4

表1

表2

表3

表4

表5

表6

脱硫装置的输入变量范围"

项目	输入变量范围/（kmol/h）
项目	$F H 2 i n$	$F C 1 i n$	$F C 2 i n$	$F C 3 i n$	$F C 4 i n$	$F C 5 i n$	$F H 2 S i n$	$F N H 3 i n$	$F M D E A i n$
HP-DS^U	7000	500	100	90	35	10	40	10	65
HP-DS^L	3000	170	45	40	10	1.5	10	2	10
LP-DS^U	150	40	8.4	5	1	0.5	4.0	0.15	10
LP-DS^L	20	5	0.5	0.1	0.1	0.01	0.1	0.01	2

表6

图5

表7

脱硫单元代理模型验证结果"

输出变量	HP-DS单元		LP-DS单元
输出变量	RMSE	R²	RMSE	R²
$F H 2 o u t$	0.00023	0.9999	0.00001	0.9999
$F C 1 o u t$	0.00034	0.9999	0.00007	0.9999
$F C 2 o u t$	0.00429	0.9996	0.00333	0.9997
$F C 3 o u t$	0.01490	0.9948	0.00430	0.9996
$F H 2 S o u t$	0.02499	0.9888	0.01656	0.9940
$F f r a o u t$	0.00485	0.9993	0.00034	0.9999

表7

图6

图7

图8

图9

图10

图11

图12

图13

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场景	硫含量/（mg/kg）	氮含量/（mg/kg）	发生概率
1	0.9097	0.2016	0.0400
2	0.9097	0.2058	0.1000
3	0.9097	0.2100	0.0600
4	0.9493	0.2016	0.1000
5	0.9493	0.2058	0.2500
6	0.9493	0.2100	0.1500
7	0.9888	0.2106	0.0600
8	0.9888	0.2058	0.1500
9	0.9888	0.2100	0.0900

加氢处理装置	油品流量/(t/h)	T/K	P/bar	LHSV/h^-1
DHT-1	150.00	633	67.2	1.92
DHT-2	373.81	648	70.0	2.00
GHT	216.67	513	27.0	3.00
KHT-1	50.00	553	38.3	2.25
KHT-2	70.00	573	54.5	1.79

项目	距离/m
项目	DHT-1	DHT-2	GHT	KHT-1	KHT-2
HP-DS	540	360	350	450	550
LP-DS	480	310	500	750	90

Item	DHT-1	DHT-2	GHT	KHT-1	KHT-2
DHT1-PC1	0.7041	0	0	0	0
DHT1-PC2	0.2959	0	0	0	0
DHT2-PC1	0	0.7935	0	0	0
DHT2-PC2	0	0.2065	0	0	0
GHT-PC	0	0	1.0000	0	0
KHT1-PC	0	0	0	1.0000	0
KHT2-PC	0	0	0	0	1.0000

虚拟组分	相对密度	分子量	馏程/℃
虚拟组分	相对密度	分子量	HK(初馏点)	10%	50%	90%	KK(终馏点)
DHT1-PC1	0.8478	239.567	208	249	300	346	370
DHT1-PC2	0.8647	246.974	225	256	311	354	380
DHT2-PC1	0.8439	233.709	211	248	291	347	370
DHT2-PC2	0.8396	227.525	180	233	288	348	376
GHT-PC	0.7441	95.420	36.9	49.9	105	172	202
KHT1-PC	0.7832	155.505	151	172	189	230	—
KHT2-PC	0.8122	180.524	—	124	257	363	373

考虑原油性质波动的炼厂氢气网络集成优化

Integrated optimization of refinery hydrogen networks with crude oil properties fluctuations

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项目	原氢气网络模型	确定性模型	随机规划模型
变量数量	62	97	97
方程个数	68	132	132
CPU计算时间	0.016 s	2.578 s	44.875 s
计算机配置	64位操作系统，16 GB RAM 1.10 GHz Intel Core i7-10710U
求解器	GAMS-DICOPT

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