CIESC Journal ›› 2019, Vol. 70 ›› Issue (2): 496-507.doi: 10.11949/j.issn.0438-1157.20181082

• Process system engineering • Previous Articles     Next Articles

Hybrid modeling and optimization of acetylene hydrogenation process

Zhencheng YE(),Huanlan ZHOU,Debao RAO   

  1. Key Laboratory of Chemical Process Control and Optimization Technology, Ministry of Education, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
  • Received:2018-09-26 Revised:2018-10-23 Online:2019-02-05 Published:2018-10-29
  • Contact: Zhencheng YE E-mail:yzc@ecust.edu.cn

Abstract:

The mathematical model of the acetylene hydrogenation reactor established by traditional single modeling method does not meet the needs of industrial practical applications in predictive performance. This paper proposes a mechanism and neural network nesting modeling method, which fully utilizes the mechanism model. It makes full use of mass and energy balance information in mechanism model to reduce the degree of constraint violation of the neural network model, which can describe the process characteristics of industrial reactor well. The optimization problem which targets the operational profits as the objective function is studied basing on the hybrid model. The main decision variables include several key parameters, such as the reactor feed hydrogen-alkyne ratio, the feed temperature, and the two-stage reactor operating cycle and many more. For the long-term operation of the reactor, processing capacity of the reactor will decrease due to the decreased catalyst activity, and an improved optimizing strategy is proposed by adjusting the hydrogen-alkyne ratio as well as the reaction temperature simultaneously. The sequence method is used to discretize the operating cycle of the reactor. The two-stage difference algorithm is improved by introducing differential mutation strategy and potential solution alternative strategy. Then the optimization problem is solved by combining the incremental coding method with the improved two-stage difference algorithm. And the results confirm the effectiveness. Furthermore the optimal operating cycle and operating strategy of the reactor are given.

Key words: acetylene hydrogenation, dynamic model, control, algorithm, optimization

CLC Number: 

  • TP 18

Fig.1

Schematic diagram of hydrid model structure"

Fig.2

Schematic diagram of ANN structure"

Table 1

Prediction error of different models/%"

Parameters Hybrid model Mechanism model
acetylene 1.706 7.040
ethylene 0.025 1.119
temperature 0.429 0.985

Table 2

Factors and levels of orthogonal test"

Level Factor
NP β NS δ R
1 70 0.1 4 0.8 0.1
2 80 0.2 5 0.85 0.2
3 90 0.3 6 0.9 0.3
4 100 0.4 7 0.95 0.4

Table 3

Analysis table of standard deviation"

Problem NP β NS δ R
C07 0.150 0.095 0.095 0.095 0.095
C08 3.553 1.474 3.010 1.635 3.354
C13 0.252 0.134 0.140 0.035 0.071
C15 3.688 3.588 3.588 3.688 3.588
C17 0.094 0.133 0.168 0.113 0.062
C18 0.307 0.446 0.240 0.409 0.252

Table 4

Time complexity analysis table"

Dim Algorithm T 1 T 2 (T 2-T 1)/T 1

10

TSDE 0.01240 0.18911 14.25080
RTSDE 0.01269 0.22084 16.40268

30

TSDE 0.02741 0.21881 6.98285
RTSDE 0.02786 0.24745 7.88191

Table 5

Comparison of best values"

Pro TSDE εDEag CO-CLPSO
10 30 10 30 10 30
C01 + + ~ ~ ~ +
C02 + + ~ + ~ ~
C07 ~ + ~ + + +
C08 ~ + ~ + + +
C13 + + ~ + ~ +
C14 ~ + ~ + + +
C15 + + - ~ - -
C16 + + + ~ ~ ~
C17 + + + + + +
C18 + + + + + +

Table 6

Comparison of mean values"

Pro TSDE εDEag ICTLBO CO-CLPSO
10 30 10 30 10 30 10 30
C01 + + - ~ + + + +
C02 + + + + + + + +
C07 ~ ~ + + + + + +
C08 + - + - + + + +
C13 + + ~ + + + + +
C14 + ~ + + + + + +
C15 + - + ~ + ~ + +
C16 + + - ~ + + ~ +
C17 + + + + + + + +
C18 + + + + + + + +

Fig.3

Comparison of convergence for test functions"

Fig.4

Iterative curves of algorithms"

Table 7

Comparison of algorithms results"

R1 cycle R2 cycle DE TSDE RTSDE

300

100 1.038×105 1.104×105 1.146×105
120 1.035×105 1.107×105 1.145×105
140 9.911×104 1.062×105 1.105×105

320

100 1.014×105 1.114×105 1.149×105
120 1.103×105 1.081×105 1.132×105
140 9.646×104 1.103×105 1.105×105

340

100 9.783×104 1.108×105 1.134×105
120 9.460×104 1.075×105 1.115×105
140 9.272×104 1.045×105 1.098×105

Fig.5

Curve of first reactor catalyst’s selectivity"

Fig.6

Curve of first reactor outlet temperature"

Fig.7

Curve of total flow rate increment of ethylene"

"

ai ,aj ——反应ij的失活系数
Ci ——i组分的工厂实测浓度值
Ci sim ——模型对i组分的模拟浓度值
Cpi ——气体的比定压热容,kJ·kg-1·K-1
E ——相对误差
E a ——失活活化能,kJ·kmol-1
Ei ——反应i的活化能,kJ·kmol-1
Fi ——气体i的摩尔流率,kmol·h-1
g(·) ——约束条件
ΔHj ——反应j焓变,kJ·kmol-1
Δ I C 2 H 4 ——两段反应器总乙烯流率增量,kmol·h-1
Ki ——气体i的吸附常数,kPa-1
ka ——失活指前因子,kmol·kg-1·h-1·kPa-3
k 0 ,i ——反应i的指前因子,kmol·kg-1·h-1·kPa-3
M C 2 H 4 ——乙烯的质量通量,kg·kmol-1
ni ——反应i的失活级数
P C 2 H 4 ,P reg ——分别表示乙烯的价格和催化剂再生费用
pi ——气体i的分压,kPa
R ——理想气体常数,kJ·kmol-1·K-1
ri ,rj ——反应ij的速率,kmol·kg-1·h-1
S ——反应器横截面积,m2
T ——反应温度,K

T 1

——CEC2010测试函数求解10000次所需的平均计算时间,s

T 2

——算法对CEC2010测试函数求解10000次所需的总平均计算时间,s
ΔT max ——工厂实际温度的最大温升,K
t first,t second ——分别表示一段、二段反应器总运行时间,d
t 1,t 2 ——分别表示一段、二段反应器当前运行时间,d
z ——反应器长度,m
ρ ——催化剂填充密度,kg·m-3
下角标
in,out ——分别表示反应器进、出口
R1,R2 ——分别代表一、二段反应器
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