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

doi:10.11949/0438-1157.20210953

摘要/Abstract

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

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

中图分类号:

TQ 021.8

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.

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.

图/表 11

图1 在初始时刻进行输入阶跃后气相的变化

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

图2 四种模型在控制催化剂藏量和压力的情况下进行主风量阶跃后的曲线

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

表1 模型的部分相关参数

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	℃

图3 烧焦罐主风阶跃后一氧化碳含量变化

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

图4 反再系统在不控制温度时的温度曲线

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

表2 基于工艺优先的相对能量增益矩阵

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

表2 基于工艺优先的相对能量增益矩阵

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

表3 变量配对结果

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

表4 相对能量增益矩阵

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

表4 相对能量增益矩阵

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

图5 精细化模型的控制效果曲线

Fig.5 Control effect curves of refined model

表5 原模型的控制器参数

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

表5 原模型的控制器参数

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

表6 精细化模型的控制器参数

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

表6 精细化模型的控制器参数

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

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