CN102034000A - Method for optimizing process operation of catalytic hydrogenation reaction of acetylene in industrial device - Google Patents

Method for optimizing process operation of catalytic hydrogenation reaction of acetylene in industrial device Download PDF

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CN102034000A
CN102034000A CN2010105855421A CN201010585542A CN102034000A CN 102034000 A CN102034000 A CN 102034000A CN 2010105855421 A CN2010105855421 A CN 2010105855421A CN 201010585542 A CN201010585542 A CN 201010585542A CN 102034000 A CN102034000 A CN 102034000A
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acetylene
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钱锋
蒋达
杜文莉
叶贞成
田亮
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East China University of Science and Technology
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Abstract

The invention relates to a method for optimizing process operation of catalytic hydrogenation reaction of acetylene in an industrial device. The method has the following beneficial effects: based on a hydrogenation reactor model, the genetic algorithm is used for fitting the parameters of a dynamic model and a deactivation model so as to achieve the aim of precisely describing the chemical reaction process, and on the basis, the genetic algorithm is reused for optimizing the process operation conditions according to the practical industrial production goal, thus the influence of each factor in an industrial reactor on the reaction process can be described; and the models have higher industrial data fitting and predicting precision and good usability, and in addition, the modeling method is suitable for various catalytic hydrogenation reactions in fixed bed reactors and has wide applicability.

Description

A kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method
Technical field
The present invention relates to a kind of process optimization operation method, especially a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method.
Background technology
The course of reaction model investigation is the basis of carrying out technology, engineering development and optimization, and dynamics research is the basis of reaction engineering model investigation.The task of dynamics research is by investigating the chemical characteristic of course of reaction, quantitatively understand the influence of conditions such as temperature of reaction, reactant concentration, catalyzer to course of reaction, being familiar with its rule and mechanism.Catalyst deactivation is a complex phenomena, further study by catalyst activity being changed this complicated phenomenon, express the relation of catalyst inactivation and service time, temperature quantitatively, can explore the various effective measures that prolong the industrial catalyst life-span.Set up kinetic model and deactivation model, thereby for the design of industrial reactor, the optimization of production operation condition and the transformation of production technology etc. provide foundation and means, kinetic model and the deactivation model of therefore setting up energy accurate description course of reaction are significant.
Pyrolysis naphtha or C2-C6 saturated hydrocarbons prepare the essential industry process that polymer grade ethylene is a petrochemical complex, pyrolysis product comprises a large amount of ethene and a spot of acetylene (volume fraction 0.5%-2%), because a little acetylene will make the downstream ethylene polymerization catalysts poison, its content must be lowered to below 5/1000000ths.Modern petrochemical complex can adopt the palladium metal catalyst of load, removes acetylene effectively from ethylene-rich stream thigh by STUDY OF SELECTIVE HYDROGENATION OF ACETYLENE.For the hydrogenation process of the acetylene in the ethylene-rich stream, industrial have two kinds of basic skills available, is called back end hydrogenation and front-end hydrogenation process.Be located at the hydrogenation acetylene removal of carrying out before the demethanizing column and be called front-end hydrogenation, its implication is after pyrolysis gas removes sour gas such as carbon dioxide, sulfuretted hydrogen through alkali cleaning, separates without rectifying, promptly carries out the process of hydrogenation and removing alkynes.In this case, enter in the unstripped gas of hydrogenation reactor, except that containing ethene, propylene, ethane, propane, also contain hydrogen and methane.Relative front-end hydrogenation, back end hydrogenation technology are after light ends such as institute's hydrogen, methane in the pyrolysis gas are separated, and the carbon two of resulting separation are carried out the process of hydrogenation again.The difference of these two kinds of methods is acetylene hydrogenation reactor residing position in whole ethylene unit flow process, and the reactor of back end hydrogenation method is positioned at after the deethanization unit, so inlet stream thigh mainly comprises the C 2 hydrocarbon class.This patent is mainly used in the back end hydrogenation reactor.
Fig. 1 is the technological process of the acetylene catalytic hydrogenation reaction process of back end hydrogenation method, and ethane, ethene, acetylene and hydrogen enter fixed bed reactors in reactor head, flow through to be filled with Pd/Al 2O 3The bed of catalyzer.Acetylene and hydrogen react at catalyst surface, generate ethene or ethane, and ethene also is adsorbed onto catalyst surface and the hydrogen generation ethane that reacts simultaneously.Hydrogenation reaction all is an exothermic process, and reaction bed temperature raises from top to bottom.
By consulting document, obtain hydrogenation reaction mechanism and deactivation mechanism, and kinetic model and deactivation model.But the catalyzer that is loaded in the industrial reactor can be subjected to influences such as temperature, reactant concentration, this given class model parameter of document can not directly apply to commercial plant, therefore be necessary to obtain to be applicable to the catalyzer kinetic model parameter of actual industrial reaction unit, and the dynamic model parameter during catalyst deactivation, thereby course of reaction is deeply understood, and then sought best industrial operation parameter, be applied to production run, optimization production, energy-saving and emission-reduction.
Summary of the invention
The invention provides a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method.The method according to the actual industrial data, is used genetic algorithm parameter in the kinetic model is carried out match on hydrogenation reactor model basis.And on this basis, use genetic algorithm once more, and the parameter in the deactivation model is carried out match, to reach the chemical reaction process in the hydrogenation reactor is carried out accurate description.According to the actual industrial production target, process condition is optimized then, realizes the commercial production energy saving purposes.
A kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method, its feature said method comprising the steps of:
1. historical data is handled.Gather the historical data of whole acetylene hydrogenation reactor life cycle, put in order out and catalyzer every one to one data service time, comprising: the mole flow velocity of the ethane that reactor is imported and exported, ethene, acetylene, hydrogen, the temperature of each bed of reactor;
2. kinetic model parameter fitting.Make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model, select catalyzer and use the comparison other of the data at initial stage as model input and model output, utilize the unknown parameter in the genetic algorithm match dynamics, each variable correspondence each kinetic model parameter value in the genetic algorithm, here adopt four-five rank runge kutta method integrations to find the solution the ordinary differential equation group of band initial-value problem, calculate the ethane of reactor exit, ethene, acetylene, hydrogen mole flow velocity, and the variation of reactor batch temperature, estimate each ideal adaptation degree, colony is carried out repeatedly based on genetic operation, and then search out the optimum individual of optimizing in the colony, promptly obtain the kinetic model parameter;
3. deactivation model parameter fitting.Make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model, select the comparison other of the data in whole service cycle as model input and model output, based on the kinetic model behind the parameter fitting, utilize the unknown parameter in the genetic algorithm match deactivation model, each variable correspondence each deactivation model parameter value in the genetic algorithm, here adopt four-five rank runge kutta method integrations to find the solution the ordinary differential equation group of band initial-value problem, calculate the ethane of reactor exit, ethene, acetylene, hydrogen mole flow velocity, and the variation of reactor batch temperature, estimate each ideal adaptation degree, colony is carried out repeatedly based on genetic operation, and then search out the optimum individual of optimizing in the colony, promptly obtain the deactivation model parameter;
4. operating conditions optimizing.The adiabatic one dimension of two equipressures that makes up series connection is intended homogeneous phase piston flow reactor model, reaction kinetics in the model and the parameter in the deactivation model adopt respectively step 2. with step 3. in data after the match.Last group as first stage reactor, and one group of back is as second stage reactor.Utilize the genetic algorithm optimization operating parameter, each variable correspondence each operational parameter value in the genetic algorithm, use real time data, the input of catalyzer service time and each material mole flow velocity as model, estimate each ideal adaptation degree, colony is carried out repeatedly based on genetic operation, and then search out the optimum individual of optimizing in the colony, find out the various operating conditionss of optimization aim correspondence.
The whole acetylene hydrogenation reactor life cycle of described step in 1. is meant that reactor switches from coming into operation to, the whole process that catalyst performance constantly changes with temperature and time.
The isobaric adiabatic one dimension of described step in 2. intended homogeneous phase piston flow reactor model, be meant and do not consider pressure drop in the reactor, reactor is regarded as adiabatic reactor, and supposition reactor inherence is uniform perpendicular to fluid properties and speed on the cross section of fluid flow direction, radially there are not velocity gradient and thermograde, also do not have concentration gradient, axial heat conduction and mass transfer are only caused by the bulk flow of laminar flow.
Described step 2. medium power is learned the kinetic model that model comprises ethene and hydrogen, acetylene and hydrogen reaction.
The ideal adaptation degree of described step in 2. is meant that each material mole flow velocity calculated value and measured value residual sum of squares (RSS) and temperature computation value and measured value residual sum of squares (RSS) are long-pending, and its formula can be expressed as
Figure BSA00000383883800031
F wherein J, indBe the measured value of j kind component mole flow velocity, F J, simBe the predicted value of the mole flow velocity of j kind component, T K, indBe the measured value of k bed temperature, T K, simIt is the predicted value of k bed temperature.
The deactivation model of described step in 3. is meant with funtcional relationship represents that catalyzer is along with service time and temperature variation and the physicochemical change process of the complexity that changes.
The ideal adaptation degree of described step in 3. is meant that each material mole flow velocity calculated value of finger in all samples and measured value residual sum of squares (RSS) and temperature computation value and measured value residual sum of squares (RSS) are long-pending, and its formula can be expressed as
Figure BSA00000383883800032
F wherein Ij, indBe the j kind component mole flow rate measurements that i gathers sample, F Ij, simBe the j kind component mole flow velocity predicted value that i gathers sample, T Ik, indBe the k bed temperature measured value that i gathers sample, T Ik, simIt is the predicted value that i gathers the k bed temperature of sample.
Described step 4. in operating parameter refer to operating parameters such as temperature in, hydrogen alkynes ratio, pressure, each parameter need be according to reactor assembly and catalyzer instructions variation range given in advance.
The ideal adaptation degree of described step in 4. is meant that the concentration of acetylene that guarantees second stage exit is less than under the 1ppm, through ethene increment behind the hydrogenation reactor of two series connection.The ethene increment is big more, and fitness is big more.
The present invention relates to a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method, the method uses genetic algorithm that kinetic model parameter and deactivation model parameter are carried out match based on the hydrogenation reactor model.According to the actual industrial production target, use this genetic algorithm once more process conditions are optimized then, to reach the purpose of chemical reaction process being carried out accurate description.Improved the precision of model, production technology is transformed, reached energy saving purposes, and the method is applicable to the optimization of all kinds of fixed bed hydrogenation courses of reaction that adaptability is widely arranged to the chemical reaction process prescription.
Description of drawings
Fig. 1 is the process chart that the acetylene gas phase is selected catalytic hydrogenation reaction process formant in the back end hydrogenation technology.In the back end hydrogenation technological process, carbon two materials that go out from deethanizer overhead stream with at first carry out heat exchange after appropriate amount of hydrogen is mixed through turnover material heat interchanger and reactor outlet material, enter then and enter one section acetylene converter after feed preheater is heated to uniform temperature with low-pressure steam with material, most of acetylene in the material is hydroconverted into ethene or ethane in first stage reactor, the one section outlet material with enter two sections acetylene converters through intercooler after appropriate amount of hydrogen is mixed, remaining acetylene is all removed in the material, through taking off the green oil tower, finally send into the ethylene rectification tower separation and obtain polymer grade ethylene then.
Fig. 2 utilizes genetic algorithm to carry out the FB(flow block) of commercial plant acetylene catalytic hydrogenation reaction kinetic parameter match.
Fig. 3 utilizes genetic algorithm to carry out the FB(flow block) of commercial plant acetylene catalytic hydrogenation reaction process catalyst deactivation model parameter match.
Fig. 4 utilizes genetic algorithm to seek the FB(flow block) of commercial plant acetylene catalytic hydrogenation reaction process optimum operating parameter.
Embodiment
The present invention is further described below in conjunction with accompanying drawing and example.
Reaction mechanism and kinetic model
The laboratory study achievement of acetylene catalytic hydrogenation reaction process shows that hydrocarbon covers the palladium metal surface and forms two kinds of different catalytic centers: A center and E center.The A center is made of a series of narrow adsorption sites, and they can adsorb acetylene and hydrogen, but since too narrow and can not ethylene adsorption, thereby can not carry out ethylene hydrogenation; All reactants that comprise ethene can be adsorbed in the E center, because the quantity at E center will be far smaller than the quantity at A center in the steady state catalytic agent, the supercentral acetylene hydrogenation speed of F can be ignored, and mainly ethene is carried out hydrogenation reaction.The reaction that π-C2H2 hydrogenation generates ethane can take place among the A in the heart, and the vinyl hydrogenation (equation (1)) of vertical absorption is passed through in this reaction earlier.In the heart, ethylene hydrogenation generates the reaction of ethane and carries out (equation (2)) by Lang Gemiuer-Hinshelwood mechanism in E.The supercentral selective hydrogenation of acetylene of A generates ethene mainly to be undertaken by two parallel reactors: 1) acetylene and the hydrogen that shifts from carbon deposits react (equation (3)); 2) hydrogen of acetylene and competitive adsorption react (equation (4)).
Figure BSA00000383883800051
Wherein
Figure BSA00000383883800052
(i=1,2,3,4 represents these four reactions of R1, R2, R3 and R4 respectively), E iBe reaction activity, R is an ideal gas constant, and T is a temperature;
Figure BSA00000383883800053
Be the acetylene dividing potential drop; Be ethylene partial pressure;
Figure BSA00000383883800055
Be hydrogen partial pressure;
Figure BSA00000383883800056
Be the adsorption equilibrium costant of acetylene in the agent of A centers catalyse;
Figure BSA00000383883800057
Be the adsorption equilibrium costant of acetylene in the agent of E centers catalyse;
Figure BSA00000383883800058
Be the adsorption equilibrium costant of ethene in the agent of E centers catalyse.When temperature variation is little,
Figure BSA00000383883800059
With
Figure BSA000003838838000511
Can think constant.r 1And r 2Be the subsidiary reaction that generates ethane, r 3And r 4The acetylene hydrogenation that is based on different mechanism respectively generates the main reaction of ethene.
Deactivation mechanism and model
The acetylene that adsorbs on catalyzer can experience a hydrogenation-oligomerization slowly, generates the molecular weight oligomers that comprises even number of carbon atoms.These oligomer meeting blocking catalyst micropores make specific surface area of catalyst descend, thereby cause active decline.Catalyst deactivation is a complex phenomena, and catalyst deactivation mechanisms and mode depend on the real process that each is concrete.Further study by catalyst activity being changed this complicated phenomenon, express the relation in catalyst inactivation and reaction time quantitatively, to exploring catalyst deactivation mechanisms, be very significant thereby explore the various effective measures that prolong the industrial catalyst life-span.Discover the hydrogenation process for different mechanism, its inactivation coefficient is also different.
- d a i dt = k a i exp ( - E a i RT ) a n i , n i > 1 - - - ( 5 )
Wherein i=1,2,3,4 represents these four reactions of R1, R2, R3 and R4 respectively,
Figure BSA00000383883800062
Be the pre-exponential factor of inactivation reaction i, a iBe the inactivation coefficient of reaction i, t is the time,
Figure BSA00000383883800063
Be the inactivation reaction energy of activation of reaction i, R is an ideal gas constant, and T is a temperature, n iBe the inactivation progression of reaction i.
Reactor model
Reactor is done following hypothesis: fluid properties and speed are uniformly on perpendicular to the cross section of fluid flow direction, radially do not have velocity gradient and thermograde, also do not have concentration gradient; Axial heat conduction and mass transfer are only caused by the bulk flow of laminar flow; Volume change and the pressure ignored in the course of reaction change; Reactor is worked under steady state (SS); Be reflected in the adiabatic reactor and take place.Like this, the actual industrial hydrogenation reactor can be reduced to the equipressure shown in the following formula, thermal insulation, plan homogeneous phase, one dimension, laminar flow hydrogenation reactor model, and concrete formula is as follows:
d F i dz = Σ ρ B × r j × S - - - ( 6 )
dT dz = - S × ρ B × Σ ( Δ H i × r i ) Σ ( F i × C p , i ) - - - ( 7 )
Wherein F is the mole flow velocity (kmol/hr) of gas, ρ BBe density of catalyst (kg/m 3), Cp is gas level pressure hot melt (kJ/ (kg*K)), r jBe reaction j speed, Δ H is a reaction enthalpy change (kJ/kmol), and S is that reactor cross section is long-pending, and T is temperature (K), and z is reactor length (m).The form of concrete reaction being introduced reactor model is as follows:
d F C 2 H 6 dz = ρ B × ( r 1 + r 2 ) × S ( 8 ) d F C 2 H 4 dz = ρ B × ( r 3 + r 4 - r 2 ) × S ( 9 ) d F C 2 H 2 dz = - ρ B × ( r 1 + r 3 + r 4 ) × S ( 10 ) d F H 2 dz = - ρ B × ( 2 × r 1 + r 2 + r 3 + r 4 ) × S ( 11 ) dT dz = - S × ρ B × [ r 1 × Δ H 3 + r 2 × Δ H 2 + ( r 3 + r 4 ) × Δ H 1 ] F C 2 H 6 × C p , C 2 H 6 + F C 2 H 4 × C p , C 2 H 4 + F C 2 H 2 × C p , C 2 H 2 + F H 2 × C p , H 2 ( 12 )
F wherein C2H6, F C2H4, F C2H2, F H2Be respectively the mole flow velocity (kmol/hr) of ethane, ethene, acetylene and hydrogen, ρ BBe density of catalyst (kg/m 3), C P, C2H6, C P, C2H4, C P, C2H2, C P, H2Be respectively the level pressure hot melt (kJ/ (kg*K)) of gas ethane, ethene, acetylene, hydrogen, r 1, r 2, r 3, r 4Be respectively the reaction rate (kmol/ (kg*hr)) of reaction R1, R2, R3, R4, Δ H 1Be the enthalpy change (kJ/kmol) of reaction R3 or R4, Δ H2 is the enthalpy change (kJ/kmol) of reaction R2, and Δ H3 is the enthalpy change (kJ/kmol) of reaction R1.
Along with catalyzer increases service time, performance gradually changes, and therefore need be multiplied by corresponding inactivation coefficient in each reaction.The form of the concrete reaction that has the inactivation coefficient being introduced reactor model is as follows:
d F C 2 H 6 dz = ρ B × ( r 1 × a 1 + r 2 × a 2 ) × S ( 13 ) d F C 2 H 4 dz = ρ B × ( r 3 × a 3 + r 4 × a 4 - r 2 × a 2 ) × S ( 14 ) d F C 2 H 2 dz = - ρ B × ( r 1 × a 1 + r 3 × a 3 + r 4 × a 4 ) × S ( 15 ) d F H 2 dz = - ρ B × ( 2 × r 1 × a 1 + r 2 × a 2 + r 3 × a 3 + r 4 × a 4 ) × S ( 16 ) dT dz = - S × ρ B × [ r 1 × a 1 × Δ H 3 + r 2 × a 2 × Δ H 2 + ( r 3 × a 3 + r 4 × a 4 ) × Δ H 1 ] F C 2 H 6 × C p , C 2 H 6 + F C 2 H 4 × C p , C 2 H 4 + F C 2 H 2 × C p , C 2 H 2 + F H 2 × C p , H 2 ( 17 )
A wherein 1, a 2, a 3, a 4It is respectively the inactivation coefficient of reaction R1, R2, R3, R4
Genetic algorithm is simply introduced, is theed contents are as follows:
Genetic algorithm is that the evolution rule (survival of the fittest, survival of the fittest genetic mechanism) that a class is used for reference organic sphere develops and next randomization searching method.Its principal feature is directly structure objects to be operated, and does not have the successional qualification of differentiate and function; Have inherent latent concurrency and better global optimizing ability; Adopt the optimization method of randomization, can obtain and instruct the search volume of optimization automatically, adjust the direction of search adaptively, do not need the rule of determining.Genetic algorithm mainly contains following step:
1) at first forms one group of candidate solution;
2) calculate the fitness of these candidate solutions according to some adaptability condition;
3) keep some candidate solution according to fitness, abandon other candidate solutions;
4) to the candidate solution that keeps intersect, operation such as variation, generate new candidate solution;
5) circulation carries out 2), 3) 4) step reaches given threshold values up to the fitness of optimum individual, when perhaps the fitness of optimum individual and colony's fitness no longer rose, when perhaps iterations reached default algebraically, algorithm stopped.
Genetic algorithm can be expressed as:
SGA＝(C，E，P 0，M，Φ，Γ，Ψ，T) (11)
In the formula: C---individual coded system;
E---ideal adaptation degree evaluation function;
P 0---initial population;
M---population size;
Φ---select operator;
Γ---crossover operator;
ψ---mutation operator;
T---genetic algorithm end condition.
A kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method, use genetic algorithm to acetylene catalytic hydrogenation reaction kinetic model parameter fitting, and use genetic algorithm on this basis, the deactivation model parameter is carried out match, according to the actual industrial production target, reuse genetic algorithm process condition is optimized, its concrete implementation step is as follows:
1. record catalyst performance parameter and reactor parameter (comprising: loaded catalyst, bulk density, loading height, point for measuring temperature position, height for reactor and diameter) gathered industrial reactor in real time and historical data (comprising: alkynes combined feed flow velocity, join hydrogen amount, temperature in, reactor and import and export the content analysis value of each material, each bed temperature value of reactor, catalyzer service time etc.);
2. calculate the reactor corresponding and import and export the mole flow velocity of each material, and find out the bed temperature of corresponding reactor with the time; Pick out one group of catalyzer arbitrarily and use the data at initial stage to be used for follow-up parameter of reaction kinetics model match, every interval was picked out one group of data composition data set (35 groups altogether) in 10 days and is used for follow-up deactivation model parameter fitting;
3. the data of selecting the catalyzer use initial stage are as sample, and according to the mole flow velocity and the temperature that enter each material of reactor, binding kinetics model and reactor model calculate the mole flow velocity of each material in exit, and the variation of reactor batch temperature.Calculate each individual fitness, the kinetic model parameter is carried out match, until reaching the match target, idiographic flow may further comprise the steps as shown in Figure 2:
A. the generation of initial population: produce 100 individualities at random, each individuality comprises 11 variablees, represents 11 parameters in the reaction kinetics (formula (1), (2), (3), (4)) that needs match respectively, and it is as follows that it is provided with scope: k 1∈ [0,40000], k 2∈ [0,40000], k 3∈ [0,40000], k 4∈ [0,40000],
Figure BSA00000383883800081
Figure BSA00000383883800083
Figure BSA00000383883800084
E 1∈ [0,200000], E 2∈ [0,200000], E 3∈ [0,200000], E 4∈ [0,200000];
B. calculate fitness individual in the population;
I. utilize formula (8) to formula (12) to make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model
Ii. with the input of the mole flow velocity and the temperature that enter each material of reactor as reactor model
Iii. reactor model calls kinetic model, adopts four-five rank runge kutta method integrations to find the solution the ordinary differential equation group of band initial-value problem, calculates each material mole flow velocity and temperature along the reactor length changing value
Iv. calculating target function value,
Figure BSA00000383883800091
Wherein ind and sim measure and prediction, and j=1,2,3,4 represents ethane, ethene, acetylene and hydrogen respectively, and k=1,2,3,4 represents first, second, third, fourth bed respectively
V. assess fitness individual in the population, to the desired value ordering of 100 individualities in the population, desired value is more little represents that then 11 parameters in this individuality approach actual value more, and its corresponding individual fitness is big more
C. judge whether the target function value with maximum adaptation degree individuality reaches default optimization target values (＜10), if reach default optimization target values, quits a program, and writes down every kinetic parameter; If do not reach default optimization target values, then carry out next step operation;
D. select, adopting the mode of random ergodic sampling is reproductive probability selection individuality according to the fitness of individuality in current population, and it is 0.7 that generation gap is set, and the part population is selected duplicates, and carries out next step operation;
E. reorganization to the individual discrete recombination mode that adopts of the population of selecting, is returned new population at post-coitum, and crossover probability is 0.7, carries out next step operation;
F. variation, the individuality in given kinetic parameter scope in the variation population carries out next step operation;
G. adopt the ideal adaptation degree after step b method is calculated variation, carry out the c step then.
4. the data of selecting the whole service cycle are as sample, according to the mole flow velocity and the temperature that enter each material of reactor in the sample, and catalyzer service time, binding kinetics model, reactor model and deactivation model calculate ethane, ethene, acetylene, the hydrogen mole flow velocity in exit, and calculate each bed temperature value of reactor simultaneously.Calculate each individual fitness, the deactivation model parameter is carried out match, until reaching the match target, idiographic flow may further comprise the steps as shown in Figure 3:
A. the generation of initial population: produce 100 individualities at random, each individuality comprises 12 variablees, represents 12 deactivation model parameters that need match in the formula (5) respectively, it is as follows that it is provided with scope: n1 ∈ [1,10], n2 ∈ [1,10], n3 ∈ [1,10], n4 ∈ [1,10], ka1 ∈ [0,200000], ka2 ∈ [0,200000], ka3 ∈ [0,200000], ka4 ∈ [0,200000], Ea1 ∈ [1000,400000], Ea2 ∈ [1000,400000], Ea3 ∈ [1000,400000], Ea4 ∈ [1000,400000]
B. calculate fitness individual in the population;
I. utilize formula (13) to formula (17) to make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model
Ii. catalyzer use fate, the mole flow velocity that enters each material of reactor and temperature are as the input of reactor model
Iii. reactor model calls the kinetic model of fitting parameter, call deactivation model more simultaneously, adopt four-five rank runge kutta method integrations to find the solution the ordinary differential equation group of band initial-value problem, calculate each material mole flow velocity and temperature along the reactor length changing value
Iv. calculate desired value, this optimization aim relates to all samples of picking out,
Figure BSA00000383883800101
Wherein ind and sim measure and prediction, and j=1,2,3,4 represents ethane, ethene, acetylene and hydrogen respectively, and k=1,2,3,4 represents first, second, third, fourth bed respectively, and n is a number of samples.
V. assess fitness individual in the population, to the desired value ordering of 100 individualities in the population, desired value is more little represents that then 12 parameters in this individuality approach actual value more, and its corresponding individual fitness is big more
C. judge whether the target function value with maximum adaptation degree individuality reaches optimization target values (＜1000), if reach optimization target values, quits a program, and writes down every deactivation model parameter, if do not reach optimization target values, then carries out next step operation;
D. select, adopting the mode of random ergodic sampling is reproductive probability selection individuality according to the fitness of individuality in current population, and it is 0.7 that generation gap is set, and the part population is selected duplicates, and carries out next step operation;
E. reorganization to the individual discrete recombination mode that adopts of the population of selecting, is returned new population at post-coitum, and crossover probability is 0.7, carries out next step operation;
F. variation, the individuality in given kinetic parameter scope in the variation population carries out next step operation;
G. adopt the ideal adaptation degree after step b method is calculated variation, carry out the c step then.
5. use real time data as the input of model, is calculated each individual fitness to catalyzer service time and each material mole flow velocity, finds out the various operating conditionss of optimization aim correspondence, and idiographic flow may further comprise the steps as shown in Figure 4:
A. the generation of initial population: produce 100 individualities at random, each individuality comprises 4 variablees, representative needs 4 operating parameters of match respectively: than (Ra2), it is as follows that it is provided with scope: T1 ∈ [300,330] than (Ra1), two sections hydrogen alkynes for one section temperature in (T1), two sections temperature ins (T2), one section hydrogen alkynes, T2 ∈ [330,350], Ra1 ∈ [0.8,4], Ra2 ∈ [0.8,10];
B. calculate fitness individual in the population;
I. the adiabatic one dimension of two equipressures that makes up series connection is intended homogeneous phase piston flow reactor model, last group as first stage reactor, one group of back is as second stage reactor, and ethane, ethene, the acetylene of first stage reactor outlet equals ethane, ethene, the acetylene mole flow velocity of second stage reactor inlet respectively
Ii. the catalyzer in a section and the second stage reactor uses fate, and enters the input of the mole flow velocity of each material of first stage reactor as reactor model
Iii. kinetic model after the match of reactor model call parameters (formula (8) is to formula (12)) and deactivation model (formula (13) is to formula (17)) calculate second stage reactor and export each material mole flow velocity
Iv. calculating target function value,
Figure BSA00000383883800111
F wherein Out, C2H4And F In, C2H4Be respectively the output valve of second stage reactor outlet ethene mole flow velocity and the input value of first stage reactor inlet ethene mole flow velocity
V. assess fitness individual in the population, to the desired value ordering of 100 individualities in the population, desired value is more little represents that then 4 parameters in this individuality approach actual value more, and its corresponding individual fitness is big more
C. judge whether the target function value with maximum adaptation degree individuality reaches optimization target values (＜1), if reach optimization target values, quits a program, record operations parameter; If do not reach optimization target values, then carry out next step operation;
D. select, adopting the mode of random ergodic sampling is reproductive probability selection individuality according to the fitness of individuality in current population, and it is 0.7 that generation gap is set, and the part population is selected duplicates, and carries out next step operation;
E. reorganization to the individual discrete recombination mode that adopts of the population of selecting, is returned new population at post-coitum, and crossover probability is 0.7, carries out next step operation;
F. variation, the individuality in given kinetic parameter scope in the variation population carries out next step operation;
G. adopt the ideal adaptation degree after step b method is calculated variation, carry out the c step then.
According to carbon two hydrogenation reaction devices in the sequence flow technology of Lummus, two reactor series connection that hydrogenation catalyst is housed remove acetylene, adopt historical data to simulate the kinetic parameter and the deactivation model parameter of two-stage catalytic agent.The performance of catalyzer and the catalyzer time of coming into operation determines best ethene increment.On the basis that obtains dynamics and deactivation model parameter, further calculate the operating conditions of optimization, below provided the tuning result of four kinds of actual conditions (initial stage, mid-term, later stage, latter stage):
1) use the actual condition (between a section and two sections catalyzer scopes service time 0 to 120 day, the ethane, ethene and the acetylene average content that enter first stage reactor are respectively 15.36%, 83.28%, 1.35%) at initial stage to calculate the optimal operations parameter according to catalyzer.After adjusting operating parameter, one-stage selective 62.10% is increased to 65.20% (the selectivity definition is the ratio between ethene increment and the acetylene decrement, down together) before optimize; Two sections selectivity-12.30% are increased to-0.00% before optimize; The two reactor overall selectivity brings up to 59.80% from 52.50%; The ethene increment significantly improves, and is increased to 1.10% through two groups of ethene increments that add behind the reactor from 0.92%
2) use actual condition in mid-term (between a section and two sections catalyzer scopes service time 120 to 250 days, the ethane, ethene and the acetylene average content that enter first stage reactor are respectively 15.91%, 82.63%, 1.45%) to calculate the optimal operations parameter according to catalyzer.After adjusting operating parameter, one-stage selective 16.96% is increased to 34.76% before optimize; Two sections selectivity-54.80% are increased to-0.15% before optimize; The two reactor overall selectivity brings up to 22.88% from 3.88%; The ethene increment significantly improves, and is increased to 0.38% through two groups of ethene increments that add behind the reactor from 0.07%
3) use later stage actual condition (between a section and two sections catalyzer scopes service time 250 to 360 days, the ethane, ethene and the acetylene average content that enter first stage reactor are respectively 15.87%, 82.67%, 1.46%) to calculate the optimal operations parameter according to catalyzer.After adjusting operating parameter, one-stage selective 21.35% adjusts to 20.47% before optimize; Two sections selectivity-141.39% are increased to-0.25% before optimize; The two reactor overall selectivity brings up to 3.81% from 0.77%; The ethene increment significantly improves, and is increased to 0.067% through two groups of ethene increments that add behind the reactor from 0.013%
4) use actual condition in latter stage (between a section and two sections catalyzer scopes service time 360 to 460 days, the ethane, ethene and the acetylene average content that enter first stage reactor are respectively 15.24%, 83.42%, 1.34%) to calculate the optimal operations parameter according to catalyzer.After adjusting operating parameter, one-stage selective 15.64% adjusts to 5.73% before optimize; Two sections selectivity-217.80% are increased to-0.31% before optimize; The two reactor overall selectivity brings up to-1.86% from-11.37%; Ethylene loss significantly reduces, and reduces to 0.027% through two groups of ethylene losses that add behind the reactor from 0.166%
Only for the preferred embodiment of invention, be not to be used for limiting practical range of the present invention in sum.Be that all equivalences of doing according to the content of the present patent application claim change and modification, all should be technology category of the present invention.

Claims (6)

1. a commercial plant acetylene catalytic hydrogenation reaction process optimization operation method is characterized in that, said method comprising the steps of:
1. gather the historical data of whole acetylene hydrogenation reactor life cycle, put in order out and catalyzer every one to one data service time, comprising: the mole flow velocity of the ethane that reactor is imported and exported, ethene, acetylene, hydrogen, the temperature of each bed of reactor;
2. make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model, select the catalyzer that step obtains in 1. arbitrarily and use the comparison other of every data of time at initial stage correspondence as model input and model output, utilize the unknown parameter in the genetic algorithm match dynamics, each variable correspondence the value of each model parameter, colony is carried out repeatedly based on genetic operation, estimate each ideal adaptation degree,, promptly obtain the kinetic model parameter until searching out the optimum individual of optimizing in the colony;
Described reactor model is:
d F C 2 H 6 dz = ρ B × ( r 1 + r 2 ) × S d F C 2 H 4 dz = ρ B × ( r 3 + r 4 - r 2 ) × S d F C 2 H 2 dz = - ρ B × ( r 1 + r 3 + r 4 ) × S d F H 2 dz = - ρ B × ( 2 × r 1 + r 2 + r 3 + r 4 ) × S dT dz = - S × ρ B × [ r 1 × Δ H 3 + r 2 × Δ H 2 + ( r 3 + r 4 ) × Δ H 1 ] F C 2 H 6 × C p , C 2 H 6 + F C 2 H 4 × C p , C 2 H 4 + F C 2 H 2 × C p , C 2 H 2 + F H 2 × C p , H 2
F wherein C2H6, F C2H4, F C2H2, F H2Be respectively the mole flow velocity of ethane, ethene, acetylene and hydrogen, ρ BBe density of catalyst, C P, C2H6, C P, C2H4, C P, C2H2, C P, H2Be respectively the level pressure hot melt of gas ethane, ethene, acetylene, hydrogen, r 1, r 2, r 3, r 4Be respectively the reaction rate of reaction R1, R2, R3, R4, Δ H 1Be the enthalpy change of reaction R3 or R4, Δ H2 is the enthalpy change of reaction R2, and Δ H3 is the enthalpy change of reaction R1;
Described reaction Kinetics Model is:
R 1 : C 2 H 2 + 2 H 2 → C 2 H 6 r 1 = k 1 p C 2 H 2 p H 2 2 ( 1 + K C 2 H 2 A p C 2 H 2 ) 3 R 2 : C 2 H 4 + H 2 → C 2 H 6 r 2 = k 2 p C 2 H 4 p H 2 ( 1 + K C 2 H 2 E p C 2 H 2 + K C 2 H 4 E p C 2 H 4 ) 3 R 3 : C 2 H 2 + H 2 → C 2 H 4 r 3 = k 3 p C 2 H 2 p H 2 1 + K C 2 H 2 A p C 2 H 2 R 4 : C 2 H 2 + H 2 → C 2 H 4 r 4 = k 4 p C 2 H 2 p H 2 ( 1 + K C 2 H 2 A p C 2 H 2 ) 2
Wherein
Figure FSA00000383883700022
(i=1,2,3,4 represents these four reactions of R1, R2, R3 and R4 respectively), E iBe reaction activity, R is an ideal gas constant, and T is a temperature;
Figure FSA00000383883700023
Be the acetylene dividing potential drop;
Figure FSA00000383883700024
Be ethylene partial pressure;
Figure FSA00000383883700025
Be hydrogen partial pressure;
Figure FSA00000383883700026
Be the adsorption equilibrium costant of acetylene in the agent of A centers catalyse;
Figure FSA00000383883700027
Be the adsorption equilibrium costant of acetylene in the agent of E centers catalyse;
Figure FSA00000383883700028
Be the adsorption equilibrium costant of ethene in the agent of E centers catalyse; r 1And r 2Be the subsidiary reaction that generates ethane, r 3And r 4The acetylene hydrogenation that is based on different mechanism respectively generates the main reaction of ethene;
Wherein, need the unknown parameter of match, promptly described variable is: k 1, k 2, k 3, k 4,
Figure FSA00000383883700029
Figure FSA000003838837000210
Figure FSA000003838837000211
E 1, E 2, E 3And E 4
3. make up isobaric adiabatic one dimension and intend homogeneous phase piston flow reactor model, the data of uniformly-spaced selecting the whole service cycle of obtaining in the step 1 are as sample, based on the kinetic model behind the parameter fitting, utilize the unknown parameter in the genetic algorithm match deactivation model, each variable correspondence the value of each deactivation model parameter, and colony is carried out estimating each ideal adaptation degree based on genetic operation repeatedly, until searching out the optimum individual of optimizing in the colony, promptly obtain the deactivation model parameter;
The reactor model of described introducing inactivation parameter is as follows:
d F C 2 H 6 dz = ρ B × ( r 1 × a 1 + r 2 × a 2 ) × S d F C 2 H 4 dz = ρ B × ( r 3 × a 3 + r 4 × a 4 - r 2 × a 2 ) × S d F C 2 H 2 dz = - ρ B × ( r 1 × a 1 + r 3 × a 3 + r 4 × a 4 ) × S d F H 2 dz = - ρ B × ( 2 × r 1 × a 1 + r 2 × a 2 + r 3 × a 3 + r 4 × a 4 ) × S dT dz = - S × ρ B × [ r 1 × a 1 × Δ H 3 + r 2 × a 2 × Δ H 2 + ( r 3 × a 3 + r 4 × a 4 ) × Δ H 1 ] F C 2 H 6 × C p , C 2 H 6 + F C 2 H 4 × C p , C 2 H 4 + F C 2 H 2 × C p , C 2 H 2 + F H 2 × C p , H 2
A wherein 1, a 2, a 3, a 4It is respectively the inactivation coefficient of reaction R1, R2, R3, R4;
Described deactivation model reaction is as follows:
- d a i dt = k a i exp ( - E a i RT ) a n i , n i > 1
Wherein i=1,2,3,4 represents these four reactions of R1, R2, R3 and R4 respectively,
Figure FSA00000383883700033
Be the pre-exponential factor of inactivation reaction i, a iBe the inactivation coefficient of reaction i, t is the time,
Figure FSA00000383883700034
Be the inactivation reaction energy of activation of reaction i, R is an ideal gas constant, and T is a temperature, n iBe the inactivation progression of reaction i;
Wherein need fitting parameter, promptly described variable is:
Figure FSA00000383883700035
Figure FSA00000383883700036
Figure FSA00000383883700037
n 1, n 2, n 3, n 4,
Figure FSA00000383883700039
Figure FSA000003838837000310
Figure FSA000003838837000311
With
Figure FSA000003838837000312
4. the adiabatic one dimension of two equipressures that makes up series connection is intended homogeneous phase piston flow reactor model, and kinetic parameter in the model and deactivation model parameter are 2. 3. given with step by step respectively; Last group as first stage reactor, and one group of back is as second stage reactor; Utilize the genetic algorithm optimization operating parameter, each variable correspondence each operational parameter value, use real time data, of the input of the mole flow velocity of catalyzer service time and ethane, ethene, acetylene, hydrogen as model, colony is carried out repeatedly based on genetic operation, estimate each ideal adaptation degree, find out the various operating conditionss of optimization aim correspondence;
Wherein, described variable is: one section temperature in T1, two sections temperature in T2, one section hydrogen alkynes compare Ra2 than Ra1, two sections hydrogen alkynes.
2. a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method according to claim 1, it is characterized in that: the whole acetylene hydrogenation reactor life cycle of described step in 1., be meant that reactor switches from coming into operation to, the spent time of whole process that catalyst performance constantly changes with temperature and time.
3. a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method according to claim 1, it is characterized in that: the ideal adaptation degree of described step in 2., be meant that each component mole flow velocity calculated value and measured value residual sum of squares (RSS) and bed temperature calculated value and measured value residual sum of squares (RSS) are long-pending, its formula can be expressed as
Figure FSA00000383883700041
F wherein J, indBe the measured value of j kind component mole flow velocity, F J, simBe the predicted value of the mole flow velocity of j kind component, T K, indBe the measured value of k bed temperature, T K, simIt is the predicted value of k bed temperature.
4. a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method according to claim 1, it is characterized in that: the ideal adaptation degree of described step in 3., be meant that each the material mole flow velocity calculated values of all samples and measured value residual sum of squares (RSS) and bed temperature calculated value and measured value residual sum of squares (RSS) are long-pending, its formula can be expressed as
Figure FSA00000383883700042
F wherein Ij, indBe the j kind component mole flow rate measurements that i gathers sample, F Ij, simBe the j kind component mole flow velocity predicted value that i gathers sample, T Ik, indFor being the k bed temperature measured value that i gathers sample, T Ik, simIt is the predicted value that i gathers the k bed temperature of sample.
5. a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method according to claim 1 is characterized in that: the objective function of the ideal adaptation degree of described step in 4. is: F wherein Out, C2H4And F In, C2H4Be respectively the output valve of second stage reactor outlet ethene mole flow velocity and the input value of first stage reactor inlet ethene mole flow velocity.
6. a kind of commercial plant acetylene catalytic hydrogenation reaction process optimization operation method according to claim 1, it is characterized in that: the concentration of acetylene of this second stage exit is less than 1ppm.
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