Pretreatment process simulation and multi-objective optimization of C5 by reactive dividing wall column

doi:10.11949/0438-1157.20211308

Abstract

Abstract:

In view of the high energy consumption in the pretreatment section of C5 comprehensive utilization, this paper proposes the reactive dividing wall column (RDWC) pretreatment process based on the reactive distillation (RD) pretreatment process. First of all, the chemical simulation software Aspen Plus was used to build the RDWC four tower equivalent rigorous model, and the degree of freedom and univariate analysis were carried out. On this basis, the response surface Box-Behnken Design (BBD) method is used as the model fitting tool to fit the functional relationship between target variables and decision variables, and the fitting results are analyzed by ANOVA. Finally, multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used to optimize the RDWC pretreatment process, and a series of Pareto optimal solutions are obtained. The solution with the smallest TAC is selected and compared with the RD pretreatment process. The results show that compared with RD pretreatment process, RDWC pretreatment process can save TAC 12.8%, save reboiler load 27.8%, and improve selectivity.

Key words: reactive distillation, reactive dividing wall column, simulation, response surface analysis, multi-objective algorithm, optimal design

摘要：

针对碳五综合利用预处理工段能耗较高的现状，在反应精馏(RD)预处理流程基础上提出了隔壁反应精馏(RDWC)预处理流程。首先，利用化工模拟软件Aspen Plus搭建RDWC四塔等效严格模型，并对其进行自由度和单变量分析。在此基础上，以响应面Box-Behnken Design(BBD)方法作为模型拟合工具，拟合出目标变量与决策变量之间的函数关系，并对拟合结果进行方差分析(ANOVA)。最后采用基于分解的多目标进化算法(MOEA/D)对RDWC预处理流程进行多目标优化，得到一系列Pareto最优解，选出其中年总成本(TAC)最小的一组解与RD预处理流程进行对比。结果显示：与RD预处理流程相比，RDWC预处理流程可以节约TAC 12.8%，节省再沸器负荷27.8%，选择性也有所提高。

关键词: 反应精馏, 隔壁反应精馏塔, 模拟, 响应面分析, 多目标算法, 优化设计

CLC Number:

TQ 028.3

Xiaoqing SHI, Weixuan ZHU, Haotian YE, Zhizhong HAN, Hongguang DONG. Pretreatment process simulation and multi-objective optimization of C5 by reactive dividing wall column[J]. CIESC Journal, 2022, 73(3): 1246-1255.

石晓青, 朱炜玄, 叶昊天, 韩志忠, 董宏光. 碳五隔壁反应精馏预处理工艺模拟及多目标优化[J]. 化工学报, 2022, 73(3): 1246-1255.

Figures/Tables 14

Fig.1 Pretreatment technology of thermal dimerization raw materials

Fig.2 Pretreatment process of reactive distillation(RD)

Fig.3 Pretreatment process of RDWC

Table 1 Composition of C5 raw materials

组分	质量分数/%	组分	质量分数/%	组分	质量分数/%
碳四	5.07	正戊烷	10.01	CPD	17.70
3-甲基-1-丁烯	0.13	IP	20.40	顺-1,3-戊二烯	4.31
异戊烷	5.36	反-2-戊烯	1.78	环戊烯	4.99
1,4-戊二烯	1.44	顺-2-戊烯	1.12	环戊烷	2.01
2-丁烯	0.42	2-甲基-2-丁烯	1.90	2-甲基-戊烷	1.71
1-戊烯	2.68	反式-1,3-戊二烯	7.29	苯	6.89
2-甲基-1-丁烯	3.69	2-甲基-1-丁烯-3炔	0.10	甲苯	1.00

Table 2 Kinetics of dimerization and copolymerization

主要二聚反应	反应方程式	Arrhenius方程
环戊二烯二聚		$k_{1} = 1.2 \times 10^{6} e x p (- 16770 / R T)$ ^[27] $k_{1}^{'} = 2.6 \times 10^{13} e x p (- 34000 / R T)$
异戊二烯二聚		$k_{2} = 7.9 \times 10^{7} e x p (- 24900 / R T)$ ^[28]
间戊二烯二聚		$k_{3} = 3.14 \times 10^{5} e x p (- 21820 / R T)$ ^[29]
环戊二烯与间戊二烯共聚		$k_{4} = 2.2 \times 10^{4} e x p (- 19000 / R T)$ ^[30]
环戊二烯与异戊二烯共聚		$k_{5} = 9.45 \times 10^{4} e x p (- 17313 / R T)$ ^[31]

Table 2 Kinetics of dimerization and copolymerization

主要二聚反应	反应方程式	Arrhenius方程
环戊二烯二聚		$k_{1} = 1.2 \times 10^{6} e x p (- 16770 / R T)$ ^[27] $k_{1}^{'} = 2.6 \times 10^{13} e x p (- 34000 / R T)$
异戊二烯二聚		$k_{2} = 7.9 \times 10^{7} e x p (- 24900 / R T)$ ^[28]
间戊二烯二聚		$k_{3} = 3.14 \times 10^{5} e x p (- 21820 / R T)$ ^[29]
环戊二烯与间戊二烯共聚		$k_{4} = 2.2 \times 10^{4} e x p (- 19000 / R T)$ ^[30]
环戊二烯与异戊二烯共聚		$k_{5} = 9.45 \times 10^{4} e x p (- 17313 / R T)$ ^[31]

Table 3 Simulation results of reactive distillation tower and dealkylation tower

操作参数	反应精馏塔	脱炔塔
理论板数	90	120
进料位置	50	80
反应段	41~90	―
停留时间/s	10	―
回流比	8	25
塔顶馏出量/(kg/h)	500	150
IP质量分数/%	55.03
CPD质量分数/%	0.41
总炔烃质量分数/(mg/kg)	25.34
选择性S/%	97.11

Fig.4 Equivalent model of four towers[34]

Fig.5 Sensitivity analysis of gas/liquid distribution ratio

Table 4 BBD combination design factors， levels and coding values

因素	水平
因素	低（-1）	中（0）	高（1）
N₁	68	70	72
N₂	78	80	82
N₃	18	20	22
N_F	43	45	47
N_S	38	40	42
t/s	4	7	10

Fig.6 RDWC optimization flow chart

Fig.7 Pareto front

Table 5 Some Pareto optimal solutions and their corresponding parameter values

优化解	1		2		3
优化解	预测值	模拟值	预测值	模拟值	预测值	模拟值
公共精馏段塔板数	72		71		69
隔板两侧塔板数	82		82		78
公共提馏段塔板数	22		21		21
进料位置(T2塔段计)	46		44		43
侧线采出位置(T3塔段计)	42		41		38
停留时间t/s	7.9		4.4		4
TAC/(USD/a)	3.91×10⁵	3.99×10⁵(2.0%)	3.90×10⁵	4.05×10⁵(3.8%)	3.88×10⁵	3.86×10⁵(-0.5%)
再沸器负荷Q/kW	521.61	533.39(2.3%)	523.51	539.06(3.0%)	578.02	593.55(2.7%)
选择性S/%	97.51	97.41(-0.1%)	97.28	97.37(0.1%)	97.13	97.19(0.1%)

Fig.8 Pareto front side and top views

Table 6 Comparison of RDWC and RD processes

项目	反应精馏塔	脱炔塔	反应精馏工艺	RDWC	节省率
塔板数	90	120	210	168	—
进料位置	50	80	—	112	—
侧线采出位置	—	—	—	107	—
反应段	41~90	—	—	88~168	—
停留时间t/s	10	—	—	4	—
气相分配比	—	—	—	0.51	—
液相分配比	—	—	—	0.47	—
回流比	8	23	—	37.5	—
再沸器负荷Q/kW	432.20	368.36	800.56	578.02	27.8%
TAC/(USD/a)	2.18×10⁵	2.27×10⁵	4.45×10⁵	3.88×10⁵	12.8%
选择性S	—	—	97.11%	97.13%	—

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