CN110066682B - Optimization method of temperature gradient of reforming reactor - Google Patents
Optimization method of temperature gradient of reforming reactor Download PDFInfo
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- CN110066682B CN110066682B CN201810065435.2A CN201810065435A CN110066682B CN 110066682 B CN110066682 B CN 110066682B CN 201810065435 A CN201810065435 A CN 201810065435A CN 110066682 B CN110066682 B CN 110066682B
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- 238000005457 optimization Methods 0.000 title claims abstract description 56
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- 238000004422 calculation algorithm Methods 0.000 claims abstract description 13
- 238000006243 chemical reaction Methods 0.000 claims description 66
- 238000006057 reforming reaction Methods 0.000 claims description 47
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- 238000005265 energy consumption Methods 0.000 claims description 5
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Classifications
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- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G35/00—Reforming naphtha
- C10G35/24—Controlling or regulating of reforming operations
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/20—Characteristics of the feedstock or the products
- C10G2300/30—Physical properties of feedstocks or products
- C10G2300/305—Octane number, e.g. motor octane number [MON], research octane number [RON]
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/40—Characteristics of the process deviating from typical ways of processing
- C10G2300/4006—Temperature
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/40—Characteristics of the process deviating from typical ways of processing
- C10G2300/4025—Yield
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2400/00—Products obtained by processes covered by groups C10G9/00 - C10G69/14
- C10G2400/30—Aromatics
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- Chemical & Material Sciences (AREA)
- Oil, Petroleum & Natural Gas (AREA)
- Engineering & Computer Science (AREA)
- Chemical Kinetics & Catalysis (AREA)
- General Chemical & Material Sciences (AREA)
- Organic Chemistry (AREA)
- Production Of Liquid Hydrocarbon Mixture For Refining Petroleum (AREA)
Abstract
The invention relates to the field of catalytic reforming, and discloses an optimization method of a reforming reactor temperature gradient, wherein the optimization method comprises the following steps: (1) establishingA model; (2) correcting the model; (3) determining a weight Q1、Q2、Q3And Q4A value of (d); (4) calculating the optimized value of the average bed temperature and the yield of the aromatic hydrocarbon; (5) and calculating an optimized value. The optimization method of the reforming reactor temperature gradient is based on a thirty-three lumped dynamic model, and the model is corrected by adopting a differential evolution algorithm, so that the optimization method has the characteristics of rapidness and global optimum, and the corrected model can accurately reflect the actual working condition. The optimization method adopts a two-step control strategy, firstly, the average bed layer temperature is increased to an optimized suggested value, then, the specific gravity of the inlet temperature of each reactor section is adjusted, the inlet temperature of a reforming reactor is controlled, and the yield of aromatic hydrocarbon is increased.
Description
Technical Field
The invention relates to the field of catalytic reforming, in particular to a method for optimizing the temperature gradient of a reforming reactor, which can be used for simulation and operation optimization of an industrial catalytic reforming process.
Background
The catalytic reforming device is one of important secondary processing devices in the petroleum processing process, and not only can be used for producing high-octane gasoline, but also can be used for providing a large amount of aromatic chemical raw materials, such as benzene, toluene, xylene and the like; but also can produce hydrogen in the catalytic reforming process, and provide a cheap hydrogen source for other devices such as isomerization, disproportionation and the like. Therefore, the catalytic reforming unit is an indispensable important production unit for modern refinery enterprises and also one of important sources of economic benefits of petrochemical enterprises.
The reforming reaction feed is a normally depressurized reforming monolith and a hydrocracked heavy naphtha, consisting mainly of paraffins and naphthenes with lesser amounts of aromatics. Under the action of the catalyst, the main reaction is the conversion of paraffin and naphthene into aromatic hydrocarbon. The aromatic hydrocarbon content of the oil refining device is increased in the catalytic reforming reaction process, and the comprehensive benefit is improved.
FIG. 1 is a schematic flow diagram of a typical prior art catalytic reformer, in which a feedstock is mixed with recycle hydrogen, heated by a reaction feed/discharge heat exchanger and a reaction furnace, introduced into a first-stage reactor, subjected to a first-stage reaction, and then heated to a reaction temperature, introduced into a second-stage reactor, and repeatedly passed through four-stage reactors. The reaction product enters a product separation part through a gas-liquid separation tank. The gas phase mainly comprises a mixture of hydrogen and low-carbon hydrocarbons, part of the gas phase is used as circulating hydrogen to enter a reaction system, and part of the gas phase is used as hydrogen production to enter a three-stage compression purification system; and the liquid phase enters a stabilizing tower to be separated to obtain a product.
In the actual operation of a catalytic reformer, the skilled worker is mainly concerned with how to determine appropriate operating conditions according to the properties of the feedstock and the production requirements, and to improve the economic benefits on the premise of smooth operation of the apparatus. However, the catalytic reforming reaction process has a complex mechanism, a large number of operating variables and strong coupling, and is difficult to perform systematic analysis, so that an effective method for determining the raw material configuration and the operating conditions for the actual working conditions is not available all the time.
Currently, many scholars have conducted partial modeling and operation optimization studies on reaction units in the oil refining process, such as catalytic cracking, delayed coking, hydrocracking and the like, based on the lumped theory. Catalytic reforming has also been studied with a lumped correlation theory. Because the traditional model is not fine enough in raw material division, simulation and optimization of the whole reforming production process are lacked in practical industrial application, and guidance of important operation variables in practical production cannot be provided for technical personnel.
Disclosure of Invention
The invention aims to overcome the problems in the prior art and provides an optimization method for reforming reactor temperature gradient, which is based on a reforming reaction thirty-three lumped dynamic model which is independently developed, combines an advanced process simulation technology and a differential evolution algorithm to realize the simulation and correction of the model, applies the model to the reforming reactor temperature gradient optimization, and has very important significance for guiding the operation of actual working conditions, improving the yield of aromatic hydrocarbon and improving the economic benefit.
In order to achieve the above object, in a first aspect, the present invention provides a method for optimizing a temperature gradient of a reforming reactor, wherein the method comprises the steps of:
(1) establishing a thirty-three lumped reaction kinetic model of the reforming reaction;
(2) correcting a thirty-three lumped reaction kinetic model of the reforming reaction by adopting a differential evolution algorithm, and establishing a mechanism model of the thirty-three lumped reaction kinetic of the reforming reaction;
(3) according to the mechanism model in the step (2), carrying out operation variable sensitivity analysis on the inlet temperature of the reforming reactor to obtain the most sensitive inlet temperature of the aromatic hydrocarbon yield; determining the weight value of the inlet temperature of the reforming reactor in temperature distribution according to the sensitivity result of the inlet temperature of the reforming reactor to the yield of the aromatic hydrocarbon;
(4) optimizing by using the mechanism model in the step (2) by taking the average bed temperature as a variable and taking the aromatic hydrocarbon yield maximization as a target function, and calculating an optimized value of the average bed temperature and the aromatic hydrocarbon yield;
(5) and (4) calculating the optimized value of the inlet temperature of the reforming reactor according to the weighted value of the inlet temperature of the reforming reactor in the temperature distribution in the step (3) and the optimized value of the average bed temperature in the step (4).
Preferably, in step (1), the thirty-three lumped reaction kinetic model of reforming reaction separates feedstock into paraffins, naphthenes, aromatics and hydrogen;
wherein the feedstock is naphtha, the naphtha containing paraffins, naphthenes, and aromatics;
preferably, the paraffins include normal paraffins and isoparaffins;
preferably, the normal alkane is a C1-C10 normal alkane; the isoparaffin is C5-C10 isoparaffin; the cycloalkane is C6-C10 cycloalkane; the aromatic hydrocarbon is C6-C10 aromatic hydrocarbon.
Preferably, in step (1), the thirty-three lumped reaction kinetic model of the reforming reaction comprises 41 reactions, and the reaction types of the reactions comprise dehydrocyclization reaction, dehydrogenation reaction, isomerization reaction and hydrocracking reaction.
Preferably, in the step (2), the reforming reaction kinetic parameters in the thirty-three lumped reaction kinetic model of the reforming reaction are corrected with the yield maximization of the aromatic hydrocarbon as an optimization target; the reforming reaction kinetic parameters comprise the pre-factor and the activation energy of each reaction, and the reforming reaction kinetic parameters are 82.
Preferably, the number of reforming reactors is 4.
Preferably, the inlet temperature of the reforming reactor is 515-544 deg.C, more preferably 518-530 deg.C.
Preferably, in step (3), the sensitivity analysis comprises: and analyzing the influence of the inlet temperature of the reforming reactor on the yield of the aromatic hydrocarbon, the yield of the reformate, the octane number, the yield of the hydrogen and the energy consumption on the basis of a thirty-three lumped reaction kinetic mechanism model of the reforming reaction.
Preferably, in step (3), the manipulated variable sensitivity calculation includes: influence of the inlet temperature of the reforming reactor on the yield of aromatics; the effect of the inlet temperature of the reforming reactor on the reformate yield; the influence of the inlet temperature of the reforming reactor on the octane number; the effect of the inlet temperature of the reforming reactor on the hydrogen yield, and the effect of the inlet temperature of the reforming reactor on the energy consumption.
Preferably, the reforming reactor comprises a reforming first reactor, a reforming second reactor and a reforming third reactorAnd a reforming fourth reactor, and inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor are represented as T1、T2、T3And T4；
The optimized values of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor of the reforming reactors are expressed as T'1、T′2、T′3And T'4(ii) a And
the weight value of the inlet temperature of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor in the temperature distribution of the reforming reactors is represented as Q1、Q2、Q3And Q4；
The conditions satisfied by the inlet temperature of the reforming reactor, the optimized value of the inlet temperature of the reforming reactor, and the weighted value of the inlet temperature of the reforming reactor in the temperature distribution are as follows:
Q1：Q2：Q3：Q4＝(T′1-T1)：(T′2-T2)：(T′3-T3)：(T′4-T4)。
preferably, in step (4), the optimized value of the average bed temperature is an average of the sum of optimized values of the inlet temperature of the reforming reactor;
further preferably, the optimized value T of the average bed temperature is 518-527 ℃.
Preferably, the optimized value T 'of the inlet temperature of the reforming first reactor of the reforming reactor'1Of the reforming reactor, and an optimum value T 'of the inlet temperature of the reforming fourth reactor of the reforming reactor'4The reaction temperature of (2) is highest; preferably, the optimized values T 'of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor of the reforming reactor'1、T′2、T′3And T'4The conditions are satisfied as follows: t'1＜T′2＜T′3＜T′4。
Preferably, the optimized values of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor are 518-530 ℃, preferably 518-527 ℃.
In a second aspect, the present invention provides a reforming reactor temperature gradient calculated by the optimization method described above.
According to the technical scheme, the method for optimizing the temperature gradient of the reforming reactor is based on the lumped theory, the model is optimized and corrected by combining a differential evolution algorithm aiming at the modeling of an industrial catalytic reforming device, the influence of the reaction temperatures of four reactors on the comprehensive benefits is intensively researched, a two-step optimization scheme is provided, and the optimal optimization is performed on the temperature of the four-stage reforming reaction reactor for guiding the actual industrial operation and improving the comprehensive benefits.
Drawings
FIG. 1 is a schematic flow diagram of a typical prior art catalytic reformer;
FIG. 2 is a schematic network diagram of a thirty-three lumped kinetic model of reforming reaction established by the present invention;
FIG. 3 is a schematic flow diagram of an optimization method using the reforming reactor temperature gradient of the present invention;
FIG. 4 is an inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Influence on the yield of the product aromatic hydrocarbon at different temperatures;
FIG. 5 is an inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Influence on the yield of hydrogen gas at different temperatures;
FIG. 6 is the inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Influence on the yield of the product reformate at different temperatures;
FIG. 7 is an inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Effect on product octane number at different temperatures.
Detailed Description
The endpoints of the ranges and any values disclosed herein are not limited to the precise range or value, and such ranges or values should be understood to encompass values close to those ranges or values. For ranges of values, between the endpoints of each of the ranges and the individual points, and between the individual points may be combined with each other to give one or more new ranges of values, and these ranges of values should be considered as specifically disclosed herein.
In a first aspect, the present invention provides a method for optimizing a temperature gradient of a reforming reactor, wherein the method may comprise the steps of:
(1) establishing a thirty-three lumped reaction kinetic model of the reforming reaction;
(2) correcting a thirty-three lumped reaction kinetic model of the reforming reaction by adopting a differential evolution algorithm, and establishing a mechanism model of the thirty-three lumped reaction kinetic of the reforming reaction;
(3) according to the mechanism model in the step (2), carrying out operation variable sensitivity analysis on the inlet temperature of the reforming reactor to obtain the most sensitive inlet temperature of the aromatic hydrocarbon yield; determining the weight value of the inlet temperature of the reforming reactor in temperature distribution according to the sensitivity result of the inlet temperature of the reforming reactor to the yield of the aromatic hydrocarbon;
(4) optimizing by using the mechanism model in the step (2) by taking the average bed temperature as a variable and taking the aromatic hydrocarbon yield maximization as a target function, and calculating an optimized value of the average bed temperature and the aromatic hydrocarbon yield;
(5) according to the inlet temperature of the reforming reactor in the step (3); and (4) calculating the optimized value of the inlet temperature of the reforming reactor according to the weighted value of the inlet temperature of the reforming reactor in the temperature distribution and the optimized value of the average bed temperature in the step (4).
According to the optimization method, in the step (1), according to the actual operation data of the reforming device, a reforming lumped theory is combined, a reforming reaction thirty-three lumped reaction kinetic model is established, and a model basis is provided for the optimization of the inlet temperature of the reforming reactor; in the present invention, the "actual operation data according to the reformer" is not particularly limited, and may be selected conventionally by those skilled in the art, and for example, the actual operation data of the reformer may include: one or more of reaction temperature, raw material condition, reaction pressure and hydrogen-oil ratio.
Wherein, in step (1), the reforming reaction thirty-three lumped reaction kinetic models established by the present invention, such as the network schematic diagram of the reforming reaction thirty-three lumped reaction kinetic models shown in fig. 2, are used, in the present invention, the raw material is subdivided according to the industrial practical data of the reforming device, and specifically, the raw material can be divided into paraffin, naphthene, aromatic hydrocarbon and hydrogen; the feedstock may be naphtha, which contains paraffins, naphthenes, and aromatics.
Preferably, the paraffins include normal paraffins and isoparaffins;
further preferably, the normal alkane is C1-C10, and as shown in the network schematic diagram of thirty-three lumped reaction kinetics model of reforming reaction in fig. 2, the C1-C10 normal alkane may include: methane (P)1) Ethane (P)2) Propane (P)3) N-butane (P)4) N-pentane (P)5) N-hexane (P)6) N-heptane (P)7) N-octane (P)8) N-nonane (P)9) And C10+N-alkanes (P)10+)；
The isoparaffin can be C5-C10 isoparaffin, and the C5-C10 isoparaffin can comprise: isomeric pentanes (P)5) Isomeric Hexane (P)6) Isomeric heptanes (P)7) Iso-octane (P)8) Isomeric nonanes (P)9) And C10+Isoparaffins (P)10+)；
The cycloalkane may be a C6-C10 ringAlkanes, the C6-C10 cycloalkanes may include: methylcyclopentane (6N)5) C7 cyclopentane (7N)5) C8 cyclopentane (8N)5) Cyclohexane (6N)6) Methylcyclohexane (7N)6) C8 cyclohexane (8N)6) C9 cyclohexane (9N)6) And C10+ (10+ N)6)；
The aromatic hydrocarbon may be a C6-C10 aromatic hydrocarbon, and the C6-C10 aromatic hydrocarbon may include: benzene (A)6) Toluene (A)7) Ethylbenzene (EB), p-methylbenzene (OX), Trimethylbenzene (TMB), 1-methyl-2-ethylbenzene (MEB), Propylbenzene (PB) and C10+Aromatic hydrocarbons (A)10+)。
Wherein the thirty-three lumped reaction kinetic models of the reforming reaction comprise 33 lumped hydrocarbons, in particular, the thirty-three lumped reaction kinetic models of the reforming reaction comprise normal paraffin (10 lumped hydrocarbons), isoparaffin (6 lumped hydrocarbons), cycloparaffin (8 lumped hydrocarbons), arene (8 lumped hydrocarbons) and hydrogen (1 lumped hydrocarbon).
In addition, the thirty-three lumped reaction kinetic models of the reforming reactions comprise forty-one reactions, the types of the reactions comprise dehydrocyclization reactions, dehydrogenation reactions, isomerization reactions and hydrocracking reactions, and the reforming reaction kinetic parameters comprise reaction activation energy and pre-factors of each reaction, the total number of the reforming reaction kinetic parameters is 82, and the main parameters of the thirty-three lumped reaction kinetics of the reforming reactions are shown in table 1.
TABLE 1
According to the optimization method of the invention, in the step (2), according to the manual analysis data of the plant reforming unit on the production materials, with the important components of the reaction products, such as aromatic hydrocarbon yield, as optimization targets, an intelligent optimization algorithm, namely a differential evolution algorithm, is adopted to correct the reforming reaction kinetic parameters in the thirty-three lumped reaction kinetic model of the reforming reaction, so as to further improve the accuracy of the model.
Specifically, in the invention, a differential evolution algorithm is adopted to respectively carry out parameter correction on the reforming reaction kinetic model. Wherein, the optimization variable is a kinetic factor, and the total number of the optimization variables is 82. The optimized objective function is:
wherein, yi,simuAnd yi,plant(i ═ 1,2, …,4) are the contents of the 4 major components, C6 aromatics, C7 aromatics, C8 aromatics and C9 aromatics, respectively, in the reactor outlet product. The subscript simula represents model calculations and the subscript plant represents field data. And selecting partial data from the screened data to fit the kinetic parameters, and using the rest data to verify the accuracy of the model.
The optimization method according to the present invention, wherein, in step (3), the number of reforming reactors is 3 to 8, preferably 3 to 5, and more preferably 4.
In step (3), the inlet temperature of the reforming reactor is 515-.
Wherein, in step (3), the sensitivity analysis may include: and analyzing the influence of the reaction temperature on the yield of aromatic hydrocarbon, the yield of reformate, the octane number, the yield of hydrogen and the energy consumption on the basis of a thirty-three lumped reaction kinetics mechanism model of the reforming reaction.
Wherein, in the step (3), the analyzing of the influencing factors may include: influence of the inlet temperature of the reforming reactor on the yield of aromatics; the effect of the inlet temperature of the reforming reactor on the reformate yield; the influence of the inlet temperature of the reforming reactor on the octane number; the effect of the inlet temperature of the reforming reactor on the hydrogen yield; and the influence of the inlet temperature of the reforming reactor on the energy consumption.
Wherein, in the step (3), preferably, the inlet temperature of the reforming reactor including the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor is represented by T1、T2、T3And T4；
The above-mentionedThe optimized values for the inlet temperatures of the reforming first, second, third and fourth reactors of the reforming reactor are denoted as T'1、T′2、T′3And T'4(ii) a And
the weight value of the inlet temperature of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor in the temperature distribution of the reforming reactors is represented as Q1、Q2、Q3And Q4；
The conditions satisfied by the inlet temperature of the reforming reactor, the optimized value of the inlet temperature of the reforming reactor, and the weighted value of the inlet temperature of the reforming reactor in the temperature distribution are as follows:
Q1：Q2：Q3：Q4＝(T′1-T1)：(T′2-T2)：(T′3-T3)：(T′4-T4)。
the optimization method provided by the invention is characterized in that in the step (4), the bed average temperature is taken as a variable, and the aromatic hydrocarbon yield is maximized as an objective function, wherein the objective function is as follows:
max J＝AY
s.t.WAITmin<WAIT<WAITmax
wherein AY represents the Aromatic Yield (Aromatic Yield).
Wherein the optimized value of the average bed temperature is denoted as T, and the optimized value of the average bed temperature T may be an average of a sum of optimized values of the inlet temperature of the reforming reactor. That is, in the present invention, if the number of reforming reactors is 4, T ═ T'1+T′2+T′3+T′4)/4。
Preferably, the optimized value T of the average bed temperature is 518-527 ℃.
In the present invention, taking the number of reforming reactors as 4 as an example, sensitivity analysis was performed by singly adjusting the influence of the inlet temperature of one of the reactors on the product characteristics. I.e. to change a certain reactor separatelyThe inlet temperature and other temperature values are kept unchanged. As shown in fig. 4 to 7, which are obtained by simulation, fig. 4 is an inlet temperature T of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor1、T2、T3And T4Influence on the yield of the product aromatic hydrocarbon at different temperatures; FIG. 5 is an inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Influence on the yield of hydrogen gas at different temperatures; FIG. 6 is the inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Influence on the yield of the product reformate at different temperatures; FIG. 7 is an inlet temperature T for the reforming first reactor, the reforming second reactor, the reforming third reactor, and the reforming fourth reactor1、T2、T3And T4Effect on product octane number at different temperatures. From the simulation results, it can be seen that the inlet temperature variation of the fourth reactor has the greatest influence on various indexes of the product, as shown by the maximum slope of the curve. The third reactor is next to the first, the smallest. Therefore, the magnitude of the increase in the inlet temperature to the fourth reactor during tuning should be maximized, provided that the overall average bed temperature is determined.
Therefore, the optimization process according to the invention, wherein the optimized value T 'of the inlet temperature of the reforming first reactor of the reforming reactor'1Of the reforming reactor, and an optimum value T 'of the inlet temperature of the reforming fourth reactor of the reforming reactor'4The reaction temperature of (2) is highest; preferably, the optimized values T 'of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor of the reforming reactor'1、T′2、T′3And T'4The conditions are satisfied as follows: t'1＜T′2＜T′3＜T′4。
The reforming reactor temperature gradient according to the present invention, wherein the optimized values of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor may be distributed between 518-530 ℃, preferably 518-527 ℃.
In a second aspect, the present invention provides a reforming reactor temperature gradient calculated by the optimization method described above.
The optimization method has the beneficial effects that: (1) the catalytic reforming device is simulated by adopting a lumped theory, a thirty-three lumped dynamic model not only can accurately predict the yield of important components of a reforming product, but also can accurately describe the change of the yield of the components of the important product along with the axial direction of a reactor, and the input conditions of the model can be completely obtained from an industrial field; (2) the model correction adopts a differential evolution algorithm, so that a global optimum point can be quickly and accurately obtained, and the corrected model accurately reflects the actual working condition; (3) and (3) carrying out optimization control on the inlet temperature of the four-section reactor of the reforming unit by adopting a two-step optimization scheme, optimally distributing the temperature of the four-section reactor, obtaining the optimal reactor operating temperature, guiding the actual working condition to select the optimal operating point, and maximizing the yield of the aromatic hydrocarbon.
The present invention will be described in detail below by way of examples.
Example 1
This example is a schematic flow diagram illustrating the optimization method of the reforming reactor temperature gradient according to the present invention as shown in fig. 3, and the temperature gradient of the reforming reactor is determined using the optimization method of the present invention.
The number of reforming reactors in this example was 4.
(1) Establishing a thirty-three lumped kinetic model of reforming reaction:
according to the reformer industry practice, the feedstock is subdivided, with paraffins further subdivided into normal paraffins and isoparaffins, to build a thirty-three lumped kinetic mechanism model of the reforming reaction.
(2) And (3) correcting the model:
and respectively carrying out parameter correction on the reforming reaction kinetic model by adopting a differential evolution algorithm. Wherein, the optimization variable is a kinetic factor, and the total number of the optimization variables is 82. The optimized objective function is:
wherein, yi,simuAnd yi,plant(i ═ 1,2, …,4) are the contents of the 4 major components, C6 aromatics, C7 aromatics, C8 aromatics and C9 aromatics, respectively, in the reactor outlet product. The subscript simula represents model calculations and the subscript plant represents field data. And selecting partial data from the screened data to fit the kinetic parameters, and using the rest data to verify the accuracy of the model.
The comparison between the calculation result of the corrected model and the field data is shown in table 2.
As can be seen from table 2, the model predicted deviations for C6 aromatics, C7 aromatics, C8 aromatics, C9 aromatics were 0.588%, 1.246%, 0.782% and 0.342%, respectively.
The result shows that the corrected thirty-three lumped catalytic reforming reaction kinetic model can accurately describe the actual catalytic reforming industrial process.
(3) And (3) sensitivity analysis is carried out to obtain the weight value of the temperature of the four-section reactor to the aromatic hydrocarbon yield slope:
according to the mechanism model in the step (2), sensitivity analysis is respectively carried out on the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor to obtain the most sensitive reaction condition which is the reaction temperature; and inlet temperatures T to the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor1、T2、T3And T4Performing sensitivity calculation of operation variables to obtain the most sensitive operation variables as the inlet temperatures T of the first reforming reactor, the second reforming reactor, the third reforming reactor and the fourth reforming reactor1、T2、T3And T4Influence on the yield of aromatics; further determining the inlet temperature T of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor1、T2、T3And T4Yield of aromatic hydrocarbons at different temperaturesWeight Q of influence of1、Q2、Q3And Q4Are 0.034, 0.217, 0.335, 0.414, respectively.
(4) Optimizing the integral average bed layer to obtain the optimal integral average bed layer temperature:
taking the average temperature of the bed layer as a variable and taking the yield maximization of the aromatic hydrocarbon as an objective function, such as:
max J＝AY
s.t.WAITmin<WAIT<WAITmax
wherein AY represents the Yield of Aromatic hydrocarbon (Aromatic Yield), and is optimized by utilizing a mechanism model of thirty-three lumped reaction kinetics of reforming reaction, and the optimized value T of the average bed temperature is calculated to be 524.5 ℃, and the Yield of Aromatic hydrocarbon is 62.538 weight percent.
(5) Optimum four-stage reactor temperature:
T1、T2、T3and T4Inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor before temperature gradient distribution are indicated as 522 ℃, 519.1 ℃, 518.2 ℃ and 518.4 ℃ respectively; and the weight of the inlet temperature of each stage reactor in the temperature distribution is equal to the ratio of the change values of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor; the calculation procedure according to the temperature distribution is as follows:
(T′1+T′2+T′3+T′4)/4＝524.5 (I)
(T′1-T1)：(T′2-T2)＝0.034：0.217 (II)
(T′1-T1)：(T′3-T3)＝0.034：0.335 (III)
(T′1-T1)：(T′4-T4)＝0.034：0.414 (IV)
wherein, T'1、T′2、T′3And T'4Showing the temperature gradient distribution, the first reforming reactor, the second reforming reactor and the third reforming reactorInlet temperatures of the reactor and the reforming fourth reactor are required to be variable; solving a system of equations consisting of formula (I) through formula (IV):
calculating the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor according to the temperature weights of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor, and optimizing the inlet temperatures T 'of the distributed reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor'1、T′2、T′3And T'4522.7 ℃, 523.5 ℃, 525 ℃ and 526.8 ℃ respectively.
As can be seen from Table 3, the inlet temperatures T of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor at the time of initiation1、T2、T3And T4The aromatic yield was 61.063 wt% at 522 deg.C, 519.1 deg.C, 518.2 deg.C and 518.4 deg.C, respectively; after the optimization method of the present invention is adopted, the inlet temperatures T 'of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor after the temperature adjustment, namely, the optimized distribution'1、T′2、T′3And T'4The yield of the aromatic hydrocarbon was 62.538 wt% at 522.7 deg.C, 523.5 deg.C, 525 deg.C and 526.8 deg.C, respectively, and the yield of the aromatic hydrocarbon was calculated to be improved by 1.475 wt%.
TABLE 2
TABLE 3
From the above results, it can be seen that an optimization method of the temperature gradient of the reforming reactor is provided based on the actual conditions of catalytic reforming. The optimization method of the reforming reactor temperature gradient is based on thirty-three lumped dynamic models, and the thirty-three lumped dynamic models are corrected by adopting a differential evolution algorithm, so that the optimization method has the characteristics of rapidness and global optimum, and the corrected models can accurately reflect the actual working conditions. The optimization method of the reforming reactor temperature gradient adopts a two-step control strategy, firstly, the average bed layer temperature is increased to an optimized suggested value, then, the specific gravity of the inlet temperature of each reactor section is adjusted, the inlet temperature of the reforming reactor is controlled, and the yield of aromatic hydrocarbon is increased.
The preferred embodiments of the present invention have been described above in detail, but the present invention is not limited thereto. Within the scope of the technical idea of the invention, many simple modifications can be made to the technical solution of the invention, including combinations of various technical features in any other suitable way, and these simple modifications and combinations should also be regarded as the disclosure of the invention, and all fall within the scope of the invention.
Claims (14)
1. A method of optimizing a reforming reactor temperature gradient, the method comprising the steps of:
(1) establishing a thirty-three lumped reaction kinetic model of reforming reaction, wherein the thirty-three lumped reaction kinetic model of reforming reaction comprises 41 reactions, and the reaction types of the reactions comprise dehydrocyclization reaction, dehydrogenation reaction, isomerization reaction and hydrocracking reaction; the thirty-three lumped reaction kinetic model of the reforming reaction comprises 10 lumped normal alkanes, 6 lumped isoparaffins, 8 lumped cycloalkanes, 8 lumped aromatics and 1 lumped hydrogen;
(2) according to the manual analysis data of a factory reforming unit on production materials, the yield of important reaction product aromatic hydrocarbon is taken as an optimization target, a difference evolution algorithm is adopted to correct a thirty-three lumped reaction kinetic model of the reforming reaction, and a mechanism model of the thirty-three lumped reaction kinetic of the reforming reaction is established;
the differential evolution algorithm is adopted to carry out parameter correction on the reforming reaction kinetic model, the optimization variables are kinetic factors, 82 variables are counted, and the optimized objective function is as follows:
wherein,
and
the contents of 4 main components of C6 aromatic hydrocarbon, C7 aromatic hydrocarbon, C8 aromatic hydrocarbon and C9 aromatic hydrocarbon in the reactor outlet product are respectively; i =1, 2, 3, 4, subscript
Denotes model calculated values, subscripts
Representing field data; selecting partial data from the screened data to fit kinetic parameters, and using the remaining data to verify the accuracy of the model;
(3) according to the mechanism model in the step (2), carrying out operation variable sensitivity analysis on the inlet temperature of the reforming reactor to obtain the most sensitive inlet temperature of the aromatic hydrocarbon yield; determining the weight value of the inlet temperature of the reforming reactor in temperature distribution according to the sensitivity result of the inlet temperature of the reforming reactor to the yield of the aromatic hydrocarbon;
wherein the sensitivity analysis comprises: analyzing the influence of the inlet temperature of the reforming reactor on the yield of aromatic hydrocarbon, the yield of reformate, the octane number, the yield of hydrogen and the energy consumption on the basis of a thirty-three lumped reaction kinetic mechanism model of the reforming reaction;
(4) optimizing by using the mechanism model in the step (2) by taking the average bed temperature as a variable and taking the aromatic hydrocarbon yield maximization as a target function, and calculating an optimized value of the average bed temperature and the aromatic hydrocarbon yield;
the specific formula of the objective function is as follows:
wherein,
represents the yield of aromatic hydrocarbons;
(5) calculating the optimized value of the inlet temperature of the reforming reactor according to the weighted value of the inlet temperature of the reforming reactor in the step (3) in the temperature distribution and the optimized value of the average bed layer temperature in the step (4);
wherein the reforming reactor comprises a reforming first reactor, a reforming second reactor, a reforming third reactor and a reforming fourth reactor, and the inlet temperature of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor is represented as T1、T2、T3And T4；
The optimized values of the inlet temperatures of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor of the reforming reactors are expressed as T'1、T′2、T′3And T'4(ii) a And
the weight value of the inlet temperature of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor in the temperature distribution of the reforming reactors is represented as Q1、Q2、Q3And Q4；
The conditions satisfied by the inlet temperature of the reforming reactor, the optimized value of the inlet temperature of the reforming reactor, and the weighted value of the inlet temperature of the reforming reactor in the temperature distribution are as follows:
Q1：Q2 ：Q3：Q4 =（T′1-T1）：（T′2-T2）：（T′3-T3）：（T′4-T4）。
2. the optimization method according to claim 1, wherein in step (1), the thirty-three lumped reaction kinetic model of the reforming reaction separates the feedstock into paraffins, naphthenes, aromatics and hydrogen.
3. The optimization method according to claim 2, wherein the feedstock is naphtha, said naphtha containing paraffins, naphthenes and aromatics.
4. The optimization method of claim 3, wherein the paraffins comprise normal paraffins and isoparaffins; the cycloalkane is C6-C10 cycloalkane; the aromatic hydrocarbon is C6-C10 aromatic hydrocarbon.
5. The optimization method of claim 4, wherein the normal alkane is a C1-C10 normal alkane; the isoparaffin is C5-C10 isoparaffin.
6. The optimization method according to claim 1, wherein in step (2), reforming reaction kinetic parameters in the thirty-three lumped reaction kinetic model of the reforming reaction are corrected with the aromatic hydrocarbon yield maximization as an optimization target; the reforming reaction kinetic parameters comprise pre-factors and reaction activation energy of each reaction, and the reforming reaction kinetic parameters are 82.
7. The optimization method according to claim 1, wherein, in the step (3), the number of reforming reactors is 4; the inlet temperature of the reforming reactor was 515-.
8. The optimization method of claim 7, wherein the inlet temperature of the reforming reactor is 518-530 ℃.
9. The optimization method according to claim 1, wherein in step (4), the optimized value of the average bed temperature is an average of a sum of optimized values of the inlet temperature of the reforming reactor.
10. Optimization method according to claim 1 or 9, wherein the optimized value of the average bed temperature is 518-527 ℃.
11. The optimization method according to claim 1, wherein the optimized value T 'of the inlet temperature of the reforming first reactor of the reforming reactor'1Of the reforming reactor, and an optimum value T 'of the inlet temperature of the reforming fourth reactor of the reforming reactor'4The reaction temperature of (2) is highest.
12. The optimization method of claim 11, wherein the optimized values of inlet temperatures T 'of the reforming first, second, third and fourth reactors of the reforming reactor'1、T′2、T′3And T'4The conditions are satisfied as follows: t'1＜T′2＜T′3＜T′4。
13. The optimization method according to claim 12, wherein the optimized values of the inlet temperatures T 'of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor'1、T′2、T′3And T'4Each at 518 ℃ and 530 ℃.
14. The optimization method according to claim 13, wherein the optimized values of the inlet temperatures T 'of the reforming first reactor, the reforming second reactor, the reforming third reactor and the reforming fourth reactor'1、T′2、T′3And T'4Each 518-527 ℃.
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