Simulation closer to commercial process and prior process analysis based control loop configuration of FCCU reactor-regenerator system

doi:10.11949/0438-1157.20210953

Abstract

Abstract:

Catalytic cracking is the core processing technology in the current refinery. Its reaction-regeneration system is a complex system closely coupled with multiple variables. It is difficult to design dynamic simulation and control systems. At present, a large number of assumptions have been set up in the process of dynamic modeling of FCCU, which is inconsistent with the actual situation. In addition, the current control loop configuration method does not consider the process requirements and is not suitable for open-loop unstable systems such as FCC. For the above reasons, based on the mathematical model of reactor-regenerator system established by the author, this paper establishes a refined dynamic model to approximate the reactor and regenerator models, no longer ignoring the dynamic changes of gas phase, recover the derivative term of gas relative time in the original model, and through the discrete distributed parameter system model, time delay is added to the time-varying variables of each riser and coke can in the discrete model. The simulation results show that the refined dynamic model is closer to the actual chemical commercial process. Based on the above models, a simulation platform is built to design the prior process analysis based control system for the unstable reactor-regenerator system. Firstly, the control loop is configurated according to the chemical process to ensure the system stability, and then design the matching of remaining variables based on relative gain array method, which not only reduces the design complexity of the high-dimensional system, but also ensures the safety of the commercial process. The design results show that for FCCU reactor-regenerator system, after the control loop configuration is completed based on the process characteristics, the remaining variables can ensure the stability and appropriate control performance of the control system without adding additional control loops.

Key words: process systems, process control, FCCU, dynamic simulating, control system design

摘要：

催化裂化是目前炼油厂中的核心加工工艺，其反应-再生系统是一个多变量紧密耦合的复杂系统，动态模拟和控制系统设计难度较大。目前，催化裂化装置在进行动态建模时设置了大量假设条件，与实际状况存在诸多不符，另外当前的控制回路配对方法未考虑工艺要求，也不适用于催化裂化这样的开环不稳定系统。基于以上原因，以已建立的反应-再生系统数学模型为基础，建立精细化动态模型，对反应器和再生器模型进行真实逼近，不再忽略气相动态变化，将原模型中气相对时间的导数项恢复，通过离散化的分布参数系统模型，对离散化模型中每段提升管和烧焦罐的时变变量加入时滞。仿真结果表明，精细化动态模型更加接近实际化工生产过程。根据上述模型搭建仿真平台，通过对不稳定的反再系统进行工艺优先的控制系统设计，首先根据化工工艺设计控制回路保证系统的稳定性，然后基于相对增益阵方法设计剩余变量配对，在降低了高维系统设计复杂度的同时保证了生产过程安全。设计结果表明，对于催化裂化装置反再系统，基于工艺特性完成控制回路配对后，剩余变量无须再添加多余的控制回路就能保证控制系统的稳定性和适当的控制性能。

关键词: 过程系统, 过程控制, 催化裂化装置, 动态模拟, 控制系统设计

CLC Number:

TQ 021.8

Xingshuo ZHANG, Xionglin LUO, Feng XU. Simulation closer to commercial process and prior process analysis based control loop configuration of FCCU reactor-regenerator system[J]. CIESC Journal, 2022, 73(2): 747-758.

张兴硕, 罗雄麟, 许锋. 催化裂化装置反再系统动态模拟精细化与控制系统“工艺优先”配对设计[J]. 化工学报, 2022, 73(2): 747-758.

Figures/Tables 11

Fig.1 Change of gas phase after input step at initial time

Fig.2 The curve for four models with main air volume step under the control of catalyst inventory and pressure

Table 1 Some relevant parameters of the model

参数/变量	数值	单位
新鲜原料进料量	85	t·h^-1
原料预热温度	220	℃
回炼油流量	12.75	t·h^-1
回炼油浆流量	7.25	t·h^-1
烧焦罐主风量	49340	m³·h^-1
二密相床主风量	6658	m³·h^-1
烧焦罐催化剂藏量	24	t
二密相床催化剂藏量	5	t
汽提段催化剂藏量	5	t
一氧化碳助燃剂投放比	0.004	%（质量）
提升管高度	32	m
提升管截面积	0.636	m²
烧焦罐高度	9.810	m
烧焦罐截面积	19.625	m²
烧焦罐温升	~39	℃
烧焦罐底部温度	~656	℃
提升管底部温度	~544	℃
提升管温降	~50	℃

Fig.3 Change of CO content after main air step of regenerator

Fig.4 Temperature curves of reactor-regenerator system without control of temperature

Table 2 Results of REGA based on prior process analysis

变量	REGA各输入对输出的值
变量	V_rg1	V_rg2	T_fresh	X_s
y_a	－3.3962	6.8343	3.3282	－5.7663
y_d	0.1126	－2.4226	0.6199	2.6902
?T_rg1	－0.9462	－0.1789	－2.4691	4.5941
$y O 2$	5.2298	－3.2328	－0.4790	－0.5180

Table 2 Results of REGA based on prior process analysis

变量	REGA各输入对输出的值
变量	V_rg1	V_rg2	T_fresh	X_s
y_a	－3.3962	6.8343	3.3282	－5.7663
y_d	0.1126	－2.4226	0.6199	2.6902
?T_rg1	－0.9462	－0.1789	－2.4691	4.5941
$y O 2$	5.2298	－3.2328	－0.4790	－0.5180

Table 3 Results of variable pairs

操纵变量	被控变量
再生器内循环滑阀开度	二密相床催化剂藏量
待生滑阀开度	汽提段催化剂藏量
富气压缩机转速	沉降器压力
再生烟气双动滑阀开度	两器压差
再生滑阀开度	反应温度

Table 4 Results of REGA

变量	REGA各输入对输出的值
变量	$V r g 1$	$V r g 2$	$X s$	$T f r e s h$	$Z c r g 2$	$F s t e a m$	$Z r g f$	$Z c s t$	$Z c r g 21$
$y a$	16.9541	－8.6770	0.0010	－0.0021	0	－6.8301	－0.4458	0	0.0001
$y d$	1.8916	－0.0314	0.0333	－0.1509	0	－0.7135	－0.0294	0	0.0003
$y o 2$	8.4093	－2.6479	4.0771	－5.4763	0	－3.1971	－0.2143	0	0.0496
$Δ T r g 1$	－12.225	0.0015	－0.0970	6.4739	0.0004	6.4716	0.3743	0	0.0015
$T r a$	－0.0008	0.0028	0	0.0008	0.9968	0	0.0005	0	0
$P r a f$	－0.1253	2.6651	－2.9871	0.1049	0	1.2560	0.0864	0	0.0001
$d P$	－13.863	9.6794	－0.0153	0.0205	0.0028	3.9860	1.1907	0	－0.0001
$W s t$	0	0	0	0	0	0	0	0.9999	0
$W r g 2$	－0.0388	0.0076	－0.0118	0.0294	0	0.0273	0.0379	0	0.9486

Table 4 Results of REGA

变量	REGA各输入对输出的值
变量	$V r g 1$	$V r g 2$	$X s$	$T f r e s h$	$Z c r g 2$	$F s t e a m$	$Z r g f$	$Z c s t$	$Z c r g 21$
$y a$	16.9541	－8.6770	0.0010	－0.0021	0	－6.8301	－0.4458	0	0.0001
$y d$	1.8916	－0.0314	0.0333	－0.1509	0	－0.7135	－0.0294	0	0.0003
$y o 2$	8.4093	－2.6479	4.0771	－5.4763	0	－3.1971	－0.2143	0	0.0496
$Δ T r g 1$	－12.225	0.0015	－0.0970	6.4739	0.0004	6.4716	0.3743	0	0.0015
$T r a$	－0.0008	0.0028	0	0.0008	0.9968	0	0.0005	0	0
$P r a f$	－0.1253	2.6651	－2.9871	0.1049	0	1.2560	0.0864	0	0.0001
$d P$	－13.863	9.6794	－0.0153	0.0205	0.0028	3.9860	1.1907	0	－0.0001
$W s t$	0	0	0	0	0	0	0	0.9999	0
$W r g 2$	－0.0388	0.0076	－0.0118	0.0294	0	0.0273	0.0379	0	0.9486

Fig.5 Control effect curves of refined model

Table 5 Controller parameters of original model

控制回路	$K p$	$K I$
两器压差控制	15	250
反应温度控制	0.5	1

Table 5 Controller parameters of original model

控制回路	$K p$	$K I$
两器压差控制	15	250
反应温度控制	0.5	1

Table 6 Controller parameters of refined model

控制回路	$K p$	$K I$	$K D$
两器压差控制	10	10	25
反应温度控制	0.1	1.5	5

Table 6 Controller parameters of refined model

控制回路	$K p$	$K I$	$K D$
两器压差控制	10	10	25
反应温度控制	0.1	1.5	5

References 33

1	陈俊武, 卢捍卫. 催化裂化在炼油厂中的地位和作用展望: 催化裂化仍将发挥主要作用[J]. 石油学报(石油加工), 2003, 19(1): 1-11.
	Chen J W, Lu H W. Prospects of status and role of FCC in refinery: FCC will continue to play a leading role in petroleum refining industry[J]. Acta Petrolei Sinica (Petroleum Processing Section), 2003, 19(1): 1-11.
2	Weekman V W. A model of catalytic cracking conversion in fixed, moving, and fluid-bed reactors[J]. Industrial & Engineering Chemistry Process Design and Development, 1968, 7(1):90-95.
3	Lee L S, Chen Y W, Huang T N, et al. Four-lump kinetic model for fluid catalytic cracking process[J]. The Canadian Journal of Chemical Engineering, 1989, 67(4): 615-619.
4	Ancheyta-Juárez J, López-Isunza F, Aguilar-Rodrı́guez E. 5-Lump kinetic model for gas oil catalytic cracking[J]. Applied Catalysis A: General, 1999, 177(2): 227-235.
5	Hagelberg P, Eilos I, Hiltunen J, et al. Kinetics of catalytic cracking with short contact times[J]. Applied Catalysis A: General, 2002, 223(1/2): 73-84.
6	Takatsuka T, Sato S, Morimoto Y, et al. Reaction model for fluidized-bed catalytic cracking of residual oil[J]. International Chemical Engineering, 1987, 27(1): 107-116.
7	Jacob S M, Gross B, Voltz S E, et al. A lumping and reaction scheme for catalytic cracking[J]. AIChE Journal, 1976, 22(4): 701-713.
8	Marshall J E, Ward T J. Control of time-delay systems[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1981, 11(7): 515.
9	罗雄麟, 赵晗, 许锋. TE过程闪蒸罐双时间尺度建模与动态特性分析[J]. 化工学报, 2015, 66(1): 186-196.
	Luo X L, Zhao H, Xu F. Two-time scale modeling and dynamic characteristics analysis of flash tank in TE process[J]. CIESC Journal, 2015, 66(1): 186-196.
10	Bristol E. On a new measure of interaction for multivariable process control[J]. IEEE Transactions on Automatic Control, 1966, 11(1): 133-134.
11	He M J, Cai W J, Ni W, et al. RNGA based control system configuration for multivariable processes[J]. Journal of Process Control, 2009, 19(6): 1036-1042.
12	任丽红, 刘雨波, 罗雄麟, 等. 多变量时滞系统的关联分析与变量配对[J]. 化工自动化及仪表, 2012, 39(6): 743-746, 760.
	Ren L H, Liu Y B, Luo X L, et al. Association analysis and variable pairing for multivariable system with time delays[J]. Control and Instruments in Chemical Industry, 2012, 39(6): 743-746, 760.
13	罗雄麟, 任丽红, 周晓龙, 等. 常规控制系统配对设计的动态相对增益阵研究[J]. 化工自动化及仪表, 2012, 39(3): 295-300.
	Luo X L, Ren L H, Zhou X L, et al. Dynamic RGA for control system configuration of multivariable process[J]. Control and Instruments in Chemical Industry, 2012, 39(3): 295-300.
14	Xiong Q, Cai W J, He M J. A practical loop pairing criterion for multivariable processes[J]. Journal of Process Control, 2005, 15(7): 741-747.
15	He M J, Cai W J. New criterion for control-loop configuration of multivariable processes[J]. Industrial & Engineering Chemistry Research, 2004, 43(22): 7057-7064.
16	Witcher M F, McAvoy T J. Interacting control systems: steady state and dynamic measurement of interaction[J]. ISA Transactions, 1977, 16(3): 35-41.
17	Grosdidier P, Morari M, Holt B R. Closed-loop properties from steady-state gain information[J]. Industrial & Engineering Chemistry Fundamentals, 1985, 24(2): 221-235.
18	Mc Avoy T, Arkun Y, Chen R, et al. A new approach to defining a dynamic relative gain[J]. Control Engineering Practice, 2003, 11(8): 907-914.
19	黄从智, 白焰, 刘向杰. 一类网络化串级控制系统的性能分析[J]. 化工自动化及仪表, 2009, 36(5): 34-39.
	Huang C Z, Bai Y, Liu X J. Performance analysis for a class of networked cascade control system[J]. Control and Instruments in Chemical Industry, 2009, 36(5): 34-39.
20	黄从智, 白焰, 李新利. 网络控制系统与网络化串级控制系统的结构分析[J]. 化工自动化及仪表, 2009, 36(2): 1-5.
	Huang C Z, Bai Y, Li X L. Architectural analysis of networked control system and networked cascade control system[J]. Control and Instruments in Chemical Industry, 2009, 36(2): 1-5.
21	龚亦同. 化工工艺设计简介[J]. 安徽化工, 1984, 10(1): 37-40.
	Gong Y T. Introduction to chemical process design[J]. Anhui Chemical Industry, 1984, 10(1): 37-40.
22	吴志泉. 化工过程设计(一):化工工艺计算[J]. 化学世界, 1987, 28(10): 474-476.
	Wu Z Q. Chemical process design (I): Chemical engineering technology calculation[J]. Chemical World, 1987, 28(10): 474-476.
23	朱曾惠. 美国提出化工工艺设计新方向[J]. 化工设计, 2000, 10(3): 50-53.
	Zhu Z H. New direction of chemical process design proposed by the United States[J]. Chemical Engineering Design, 2000, 10(3): 50-53.
24	钱学森, 许国志, 王寿云. 组织管理的技术: 系统工程[J]. 上海理工大学学报, 2011, 33(6): 520-525.
	Qian X S, Xu G Z, Wang S Y. Organizational management technology: system engineering[J]. Journal of University of Shanghai for Science and Technology, 2011, 33(6): 520-525.
25	刘华平, 孙富春, 何克忠, 等. 奇异摄动控制系统: 理论与应用[J]. 控制理论与应用, 2003, 20(1): 1-7.
	Liu H P, Sun F C, He K Z, et al. Survey of singularly perturbed control systems: theory and applications[J]. Control Theory & Applications, 2003, 20(1): 1-7.
26	罗雄麟, 袁璞, 林世雄. 催化裂化装置动态机理模型 (Ⅰ): 反应器部分[J]. 石油学报(石油加工), 1998, 14(1): 34.
	Luo X L,Yuan P, Lin S X. Dynamic model of fluid catalytic cracking unit(Ⅰ): Reactor section[J]. Acta Petrolei Sinica(Petroleum Processing Section), 1998, 14(1): 34.
27	罗雄麟, 袁璞, 林世雄. 催化裂化装置动态机理模型(Ⅱ):再生器部分[J]. 石油学报(石油加工), 1998, 14(2): 34.
	Luo X L,Yuan P, Lin S X. Dynamic modeling of FCC unit(Ⅱ): Regenerator section[J]. Acta Petrolei Sinica(Petroleum Processing Section), 1998, 14(2): 34.
28	罗雄麟, 袁璞, 林世雄. 催化裂化装置动态机理模型(Ⅲ): 催化剂流动和压力系统[J]. 石油学报(石油加工), 1998, 14(3): 34.
	Luo X L,Yuan P, Lin S X. Dynamic modeling of fluid catalytic cracking unit(Ⅲ): Catalyst transport system and pressure system[J]. Acta Petrolei Sinica(Petroleum Processing Section), 1998, 14(3): 34.
29	Wang R, Luo X L, Xu F. Economic and control performance of a fluid catalytic cracking unit: interactions between combustion air and CO promoters[J]. Industrial & Engineering Chemistry Research, 2014, 53(1): 287-304.
30	Berezansky L, Braverman E, Idels L. Nicholson's blowflies differential equations revisited: main results and open problems[J]. Applied Mathematical Modelling, 2010, 34(6): 1405-1417.
31	Wang R, Luo X L, Xu F. Effect of CO combustion promoters on combustion air partition in FCC under nearly complete combustion[J]. Chinese Journal of Chemical Engineering, 2014, 22(5): 531-537.
32	Samad T. A survey on industry impact and challenges thereof [technical activities][J]. IEEE Control Systems Magazine, 2017, 37(1): 17-18.
33	罗雄麟, 许锋. 过程控制与工艺设计一体化: 催化裂化装置动态机理建模与控制分析设计[M]. 北京: 科学出版社, 2008.
	Luo X L, Xu F. Integration of Process Control and Process Design: Dynamic Mechanism Modeling and Control Analysis Design of Catalytic Cracking Unit[M]. Beijing: Science Press, 2008.

[1]	Fei KANG, Weiguang LYU, Feng JU, Zhi SUN. Research on discharge path and evaluation of spent lithium-ion batteries [J]. CIESC Journal, 2023, 74(9): 3903-3911.
[2]	Zhewen CHEN, Junjie WEI, Yuming ZHANG. System integration and energy conversion mechanism of the power technology with integrated supercritical water gasification of coal and SOFC [J]. CIESC Journal, 2023, 74(9): 3888-3902.
[3]	Yue CAO, Chong YU, Zhi LI, Minglei YANG. Industrial data driven transition state detection with multi-mode switching of a hydrocracking unit [J]. CIESC Journal, 2023, 74(9): 3841-3854.
[4]	Yuyuan ZHENG, Zhiwei GE, Xiangyu HAN, Liang WANG, Haisheng CHEN. Progress and prospect of medium and high temperature thermochemical energy storage of calcium-based materials [J]. CIESC Journal, 2023, 74(8): 3171-3192.
[5]	Guixian LI, Abo CAO, Wenliang MENG, Dongliang WANG, Yong YANG, Huairong ZHOU. Process design and evaluation of CO₂ to methanol coupled with SOEC [J]. CIESC Journal, 2023, 74(7): 2999-3009.
[6]	Xiaodan SU, Ganyu ZHU, Huiquan LI, Guangming ZHENG, Ziheng MENG, Fang LI, Yunrui YANG, Benjun XI, Yu CUI. Optimization of wet process phosphoric acid hemihydrate process and crystallization of gypsum [J]. CIESC Journal, 2023, 74(4): 1805-1817.
[7]	Cheng YUN, Qianlin WANG, Feng CHEN, Xin ZHANG, Zhan DOU, Tingjun YAN. Deep-mining risk evolution path of chemical processes based on community structure [J]. CIESC Journal, 2023, 74(4): 1639-1650.
[8]	Zhongqiu ZHANG, Hongguang LI, Yilin SHI. A multi-task learning approach for complex chemical processes based on manual predictive manipulating strategies [J]. CIESC Journal, 2023, 74(3): 1195-1204.
[9]	Jianghuai ZHANG, Zhong ZHAO. Robust minimum covariance constrained control for C₃ hydrogenation process and application [J]. CIESC Journal, 2023, 74(3): 1216-1227.
[10]	Weiyi SU, Jiahui DING, Chunli LI, Honghai WANG, Yanjun JIANG. Research progress of enzymatic reactive crystallization [J]. CIESC Journal, 2023, 74(2): 617-629.
[11]	Yalin WANG, Yuqing PAN, Chenliang LIU. Intermittent process monitoring based on GSA-LSTM dynamic structure feature extraction [J]. CIESC Journal, 2022, 73(9): 3994-4002.
[12]	Le ZHOU, Chengkai SHEN, Chao WU, Beiping HOU, Zhihuan SONG. Deep fusion feature extraction network and its application in chemical process soft sensing [J]. CIESC Journal, 2022, 73(7): 3156-3165.
[13]	Kun WANG, Hongbo SHI, Shuai TAN, Bing SONG, Yang TAO. Local time difference constrained neighborhood preserving embedding algorithm for fault detection [J]. CIESC Journal, 2022, 73(7): 3109-3119.
[14]	Taoyan ZHAO, Jiangtao CAO, Ping LI, Lin FENG, Yu SHANG. Application of interval type-2 fuzzy immune PID controller to temperature control system for uncatalysed oxidation of cyclohexane [J]. CIESC Journal, 2022, 73(7): 3166-3173.
[15]	Xin ZHANG, Li ZHOU, Shihui WANG, Xu JI, Kexin BI. Integrated optimization of refinery hydrogen networks with crude oil properties fluctuations [J]. CIESC Journal, 2022, 73(4): 1631-1646.