A method and device for improving prediction accuracy of catalytic cracking model

Abstract

The present invention discloses a method and device for improving the prediction accuracy of a catalytic cracking model, and belongs to the technical field of petrochemical engineering. The method comprises the following steps: correcting the reaction rate in a catalytic cracking lumped kinetic model with a correction function; wherein P is the system pressure; and UOPK is a characteristic factor of the oil product. The above method is applicable to a process in which the reaction system is relatively complex, includes parallel sequential reactions, and gas is the terminal product. The method can solve the problem that the existing model predicts that the change of gas product yield with reaction pressure is inconsistent with the actual situation, and accurately predicts the change of gas product yield with reaction pressure.

Description

Technical Field

[0001] The invention relates to the technical field of petrochemical engineering, and in particular to a method and a device for improving the prediction accuracy of a catalytic cracking model. Background Art

[0002] Catalytic cracking is one of the important processes for lightening heavy oil, and plays an important role in the production of light oil products such as gasoline and diesel. The catalytic cracking reaction process model can be used to guide the design of catalytic cracking units and optimize the operation of the units, which plays an important role in improving the economic benefits of the units.

[0003] The catalytic cracking reaction process is complex, and there are a large number of parallel sequential reactions. The lumped kinetic modeling method is generally used to model its reaction process. Many scholars have conducted a lot of research in this area. At present, the lumped kinetic modeling method of catalytic cracking has become relatively mature and has formed a relatively standard modeling process. Usually, the catalytic cracking kinetic equation is as follows: Where Y = [y1, y2, ... y n ] T is the mass fraction vector of each lumped component, n is the total number of lumps; X = x / H represents the dimensionless relative distance at the x section in the bed, x represents the distance from the riser inlet into the reactor, unit m, H represents the total length of the catalyst bed, unit m; P represents the system pressure, unit Pa; R is the gas constant, 8.314 J·mol -1 ·K -1 ; T represents the system temperature, unit K; S WH Indicates the real weight hourly space velocity, in units of g feed (oil + inerts) / h / g (catalyst); M i Represents the relative molecular mass of the aggregate i, in g·mol -1 ; K is the reaction rate constant matrix, and the subscript i represents the i-th lumped component.

[0004] This formula is established based on the catalytic cracking reaction mechanism and the riser reactor model, and has a relatively strict physical meaning. However, there are certain problems in practical application. The catalytic cracking reaction process is a parallel sequential reaction, with gasoline and diesel as intermediate products, and gas and coke as final products. According to the above formula, as the pressure of the reaction system increases, the yield of gas and coke increases. But in fact, increasing the reaction pressure is beneficial to the condensation reaction. As the reaction pressure increases, the coke yield increases and the gas yield decreases. Usually for the built catalytic cracking unit, the reaction pressure is stable, and the range of pressure adjustment in the operation optimization of the unit is very small, and this problem is often ignored. At present, no scholar has paid attention to this problem.

[0005] However, this problem cannot be ignored in the design stage of catalytic cracking unit. The gas yield is not only related to the design of the unit reaction system, but also to the design of the downstream product separation system. Accurate prediction of gas is of great significance to the optimal design of catalytic cracking unit.

[0006] In view of this, the present invention is proposed. Summary of the invention

[0007] The object of the present invention is to provide a method and device for improving the prediction accuracy of catalytic cracking model to solve the above technical problems.

[0008] This application can be implemented as follows:

[0009] In a first aspect, the present application provides a method for improving the prediction accuracy of a catalytic cracking model, comprising the following steps:

[0010] Correction function Correction of reaction rates in the lumped kinetic model of catalytic cracking;

[0011] Where P is the system pressure and UOPK is the characteristic factor of the oil.

[0012] In an optional embodiment, the catalytic cracking lumped kinetic model is obtained by establishing a reaction network based on the catalytic cracking reaction mechanism and the lumped kinetic model divided from the raw materials and products;

[0013] Among them, the raw material aggregate includes the vacuum residue aggregate and the distillate oil aggregate; the product aggregate includes the gas aggregate, gasoline aggregate, diesel aggregate, slurry oil aggregate and coke aggregate.

[0014] In an optional embodiment, the establishment of the reaction network includes:

[0015] The vacuum residue aggregate is matched with the gas aggregate, gasoline aggregate, diesel aggregate, slurry aggregate and coke aggregate to establish a reaction network.

[0016] The reaction network is established by corresponding the distillate oil aggregate to the gas aggregate, gasoline aggregate, diesel aggregate, slurry aggregate and coke aggregate one by one.

[0017] The diesel lumps are matched with the gas lumps, gasoline lumps and coke lumps one by one to establish a reaction network;

[0018] The reaction network is established by corresponding the oil slurry aggregate to the gas aggregate and the coke aggregate one by one;

[0019] The reaction network is established by corresponding the gasoline lumps to the gas lumps and the coke lumps one by one.

[0020] In an optional embodiment, the catalytic cracking lumped reaction rates before correction are as follows:

[0021]

[0022]

[0023]

[0024]

[0025]

[0026]

[0027]

[0028] Where X = x / H represents the dimensionless relative distance at the x section in the bed; x represents the distance from the riser inlet into the reactor; H represents the total length of the catalyst bed; T represents the system temperature; R is the gas constant; S WH Indicates the true weight-hourly space velocity; M i represents the relative molecular mass of the aggregate i; y i is the mass fraction of the i-th set; k j is the reaction rate constant of reaction j, Among them, A j represents the pre-exponential factor, E j represents the activation energy;

[0029] VR stands for vacuum residue, VGO stands for distillate, GAS stands for gas, G stands for gasoline, D stands for diesel, S stands for slurry oil, and CK stands for coke;

[0030] Reaction 1 is the reaction between the distillate oil aggregate and the diesel aggregate, reaction 2 is the reaction between the distillate oil aggregate and the slurry oil aggregate, reaction 3 is the reaction between the distillate oil aggregate and the gasoline aggregate, reaction 4 is the reaction between the distillate oil aggregate and the gas aggregate, reaction 5 is the reaction between the distillate oil aggregate and the coke aggregate; reaction 6 is the reaction between the vacuum residue oil aggregate and the diesel aggregate, reaction 7 is the reaction between the vacuum residue oil aggregate and the slurry oil aggregate, reaction 8 is the reaction between the vacuum residue oil aggregate and the gasoline aggregate, reaction 9 is the reaction between the vacuum residue oil aggregate and the gasoline aggregate. and gas lumps, reaction 10 is the reaction between the vacuum residue oil lumps and the coke lumps; reaction 11 is the reaction between the diesel lumps and the gasoline lumps, reaction 12 is the reaction between the diesel lumps and the gas lumps, reaction 13 is the reaction between the diesel lumps and the coke lumps; reaction 14 is the reaction between the slurry oil lumps and the gas lumps, reaction 15 is the reaction between the slurry oil lumps and the coke lumps; reaction 16 is the reaction between the gasoline lumps and the gas lumps, reaction 17 is the reaction between the gasoline lumps and the coke lumps.

[0031] In an optional embodiment, the corrected catalytic cracking lumped reaction rates are as follows:

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039] In an optional embodiment, it also includes proposing an objective function to estimate the reaction kinetics model parameters.

[0040] In an optional embodiment, the objective function is

[0041] in, is the sum of squares of the error between the test value and the fitted value; n exp is the number of trials; n c is the number of components, a ij represents the experimental concentration of i in reaction j, represents the trial fit concentration of lumped i in reaction j.

[0042] In a second aspect, the present application provides a modeling device for improving the prediction accuracy of a catalytic cracking model, which includes a modeling module for modeling using the method for improving the prediction accuracy of a catalytic cracking model of any of the aforementioned embodiments.

[0043] In a third aspect, the present application provides an electronic device including a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method for improving the prediction accuracy of the catalytic cracking model of any of the aforementioned embodiments are executed.

[0044] In a fourth aspect, the present application provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the method for improving the prediction accuracy of a catalytic cracking model as described in any of the aforementioned embodiments are performed.

[0045] The beneficial effects of this application include:

[0046] This application can effectively solve the problem that the existing model predicts that the gas product yield changes with the reaction pressure and does not match the actual situation by correcting the reaction rate in the catalytic cracking lumped kinetic model with a specific correction function, and accurately predict the change of gas product yield with reaction pressure. This method is suitable for process processes with complex reaction systems, including parallel sequential reactions and gas as the terminal product, and is of great significance to the optimization design of catalytic cracking units. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 A schematic diagram of a lumped reaction network in a method for improving prediction accuracy of a catalytic cracking model provided in the present application;

[0049] Figure 2 This is a result diagram of predicting the change of product distribution with pressure in Example 1 of the present application;

[0050] Figure 3 This is a result diagram of the predicted product distribution as a function of pressure in Comparative Example 1 of the present application;

[0051] Figure 4 This is a graph showing the predicted product distribution as a function of pressure for comparative example 2 of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be described clearly and completely below. If the specific conditions are not specified in the embodiments, they are carried out according to conventional conditions or conditions recommended by the manufacturer. If the manufacturer of the reagents or instruments used is not specified, they are all conventional products that can be purchased commercially.

[0053] The method for improving the prediction accuracy of the catalytic cracking model provided in the present application is described in detail below.

[0054] The present application proposes a method for improving the prediction accuracy of a catalytic cracking model, comprising the following steps:

[0055] Correction function Correction of reaction rates in the lumped kinetic model of catalytic cracking;

[0056] Where P is the system pressure and UOPK is the characteristic factor of the oil.

[0057] It should be noted that the characteristic factors of oil products can be calculated from their density and boiling point by referring to the relevant formulas in the prior art, and will not be elaborated on here.

[0058] The above catalytic cracking lumped kinetic model is based on the catalytic cracking reaction mechanism, and a reaction network is established according to the lumped reaction network divided by raw materials and products (lumped reaction network is as follows Figure 1 shown).

[0059] The application includes 7 assemblies in total, including 2 raw material assemblies and 5 product assemblies. The raw material assemblies include vacuum residue assemblies and distillate oil assemblies, and the product assemblies include gas assemblies, gasoline assemblies, diesel assemblies, slurry assemblies and coke assemblies.

[0060] In terms of abbreviations, VR stands for vacuum residue oil, VGO stands for distillate oil, GAS stands for gas, G stands for gasoline, D stands for diesel, S stands for slurry oil, CK stands for coke, and the same below.

[0061] For the catalytic cracking reaction process, according to the reaction mechanism, the following assumptions are made:

[0062] A. According to the carbonium ion reaction mechanism, it is assumed that the cracking of hydrocarbons is mainly from large molecules to small molecules step by step;

[0063] B. Gasoline, diesel, and slurry oil are intermediate products;

[0064] C. Gas and coke are the final products.

[0065] On this basis, a catalytic cracking reaction network is established to describe the reaction process.

[0066] Specifically, the establishment of the reaction network includes:

[0067] The vacuum residue aggregate is matched with the gas aggregate, gasoline aggregate, diesel aggregate, slurry aggregate and coke aggregate to establish a reaction network.

[0068] The reaction network is established by corresponding the distillate oil aggregate to the gas aggregate, gasoline aggregate, diesel aggregate, slurry aggregate and coke aggregate one by one.

[0069] The diesel lumps are matched with the gas lumps, gasoline lumps and coke lumps one by one to establish a reaction network;

[0070] The reaction network is established by corresponding the oil slurry aggregate to the gas aggregate and the coke aggregate one by one;

[0071] The reaction network is established by corresponding the gasoline lumps to the gas lumps and the coke lumps one by one.

[0072] Among them, the reaction between the distillate oil aggregate and the diesel aggregate is recorded as reaction 1, the reaction between the distillate oil aggregate and the oil slurry aggregate is recorded as reaction 2, the reaction between the distillate oil aggregate and the gasoline aggregate is recorded as reaction 3, the reaction between the distillate oil aggregate and the gas aggregate is recorded as reaction 4, and the reaction between the distillate oil aggregate and the coke aggregate is recorded as reaction 5; the reaction between the vacuum residue oil aggregate and the diesel aggregate is recorded as reaction 6, the reaction between the vacuum residue oil aggregate and the oil slurry aggregate is recorded as reaction 7, the reaction between the vacuum residue oil aggregate and the gasoline aggregate is recorded as reaction 8, and the reaction between the vacuum residue oil aggregate and the gas aggregate is recorded as reaction 9. The reaction between the lumps is recorded as reaction 9, and the reaction between the vacuum residue oil lumps and the coke lumps is recorded as reaction 10; the reaction between the diesel lumps and the gasoline lumps is recorded as reaction 11, the reaction between the diesel lumps and the gas lumps is recorded as reaction 12, and the reaction between the diesel lumps and the coke lumps is recorded as reaction 13; the reaction between the slurry oil lumps and the gas lumps is recorded as reaction 14, and the reaction between the slurry oil lumps and the coke lumps is recorded as reaction 15; the reaction between the gasoline lumps and the gas lumps is recorded as reaction 16, and the reaction between the gasoline lumps and the coke lumps is recorded as reaction 17.

[0073] For the riser reactor, the lumped kinetic model before correction can be derived, where the lumped reaction rates are given by:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081] Wherein, X = x / H represents the dimensionless relative distance at the x section in the bed; x represents the distance from the riser inlet into the reactor (in meters); H represents the total length of the catalyst bed (in meters); T represents the system temperature (in K); R is the gas constant (8.314 J / (mol·K)); S WH Indicates the real weight hourly space velocity, in g feed (oil + inerts) / h / g (catalyst); M i Represents the relative molecular mass of the aggregate i (in g·mol -1 );y i is the mass fraction of the i-th set, with the unit being 1; k j is the reaction rate constant of reaction j (in cm3 / (g·h)), Among them, A j represents the pre-exponential factor (unit: 1 / s), E j represents the activation energy (in kJ / mol).

[0082] according to It is shown that as the pressure increases, the gas generation rate increases.

[0083] Based on the fact that the pressure of the catalytic cracking reaction system is generally 0.2-0.4MPa, the reaction pressure increases from 0.2MPa to 0.4MPa, and the gas yield decreases by 10%-40% depending on the properties of the raw materials. This application specifically proposes a corresponding correction function The gas generation rate decreases as the pressure increases.

[0084] The lumped reaction rates of catalytic cracking corrected by the above correction functions are as follows:

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] Furthermore, an objective function is proposed, and based on the experimental data, an optimization algorithm is applied to solve the model parameters (to estimate the reaction kinetics model parameters).

[0093] For reference, the objective function is

[0094] in, is the sum of squares of the error between the test value and the fitted value; n exp is the number of trials; n c is the number of components, a ij represents the experimental concentration of i in reaction j, represents the trial fit concentration of lumped i in reaction j.

[0095] It should be noted that other modeling processes and other parameters not disclosed in this application can refer to the prior art and will not be elaborated here.

[0096] In addition, the present application also provides a modeling device for improving the prediction accuracy of a catalytic cracking model, which includes a modeling module for modeling according to the above method for improving the prediction accuracy of a catalytic cracking model.

[0097] Furthermore, the present application also provides an electronic device, which includes a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the above-mentioned method for improving the prediction accuracy of the catalytic cracking model are executed.

[0098] Furthermore, the present application provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the above-mentioned method for improving the prediction accuracy of the catalytic cracking model are executed.

[0099] Among them, the electronic device may include a modeling device for improving the prediction accuracy of the catalytic cracking model, a memory, a storage controller, a processor, a peripheral interface, an input and output unit, an audio unit and a display unit.

[0100] The above-mentioned memory, storage controller, processor, peripheral interface, input and output unit, audio unit, and display unit are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these elements can be electrically connected to each other through one or more communication buses or signal lines. The modeling device for improving the prediction accuracy of the catalytic cracking model includes at least one software function module that can be stored in the memory in the form of software or firmware or solidified in the operating system (OS) of the modeling device for improving the prediction accuracy of the catalytic cracking model. The processor is used to execute the executable module stored in the memory, such as the software function module or computer program included in the modeling device for improving the prediction accuracy of the catalytic cracking model.

[0101] The memory may be, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory is used to store programs, and the processor executes the corresponding program after receiving the execution instruction. The method executed by the server defined by the flow process involved in this application can be applied to the processor or implemented by the processor.

[0102] The processor can be an integrated circuit chip with signal processing capabilities. The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0103] The peripheral interface couples various input / output devices to the processor and the memory. For reference, the peripheral interface, the processor, and the memory controller can be implemented in a single chip, or they can be implemented by separate chips.

[0104] The input and output unit is used to provide input data to the user to realize the interaction between the user and the server (or local terminal). The input and output unit can be, but is not limited to, a mouse and a keyboard.

[0105] The audio unit provides an audio interface to the user and may include one or more microphones, one or more speakers, and audio circuitry.

[0106] The display unit provides an interactive interface (e.g., a user operation interface) between the electronic device and the user or is used to display image data for the user's reference. For reference, the display unit may be a liquid crystal display or a touch display. If it is a touch display, it may be a capacitive touch screen or a resistive touch screen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations generated simultaneously from one or more locations on the touch display, and the sensed touch operations are handed over to the processor for calculation and processing.

[0107] The peripheral interface couples various input / output devices to the processor and the memory. For reference, the peripheral interface, the processor and the memory controller can be implemented in a single chip, or they can be implemented by separate chips.

[0108] The input and output unit is used to provide input data to the user to realize the interaction between the user and the processing terminal. The input and output unit can be, but is not limited to, a mouse and a keyboard.

[0109] It is worth noting that the electronic device of the present application may also include more or fewer components than those disclosed above, or have a configuration different from the above. The above components may be implemented by hardware, software or a combination thereof.

[0110] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0111] Example 1

[0112] This embodiment provides a method for improving the prediction accuracy of the catalytic cracking model, which is as follows:

[0113] according to Figure 1 A catalytic cracking reaction kinetic model was established, which divided the raw materials into two lumps, namely vacuum residue and distillate oil, and the products into five lumps, namely gas, gasoline, diesel, slurry oil, and coke. The model contained a total of seven lumps. According to the method provided in this application, 17 reaction networks were established, and a reaction kinetic model was established;

[0114] Introducing the correction function Correction is performed to obtain a corrected catalytic cracking lumped reaction rate;

[0115] The pilot test investigated the catalytic cracking reaction performance of different raw materials under different operating conditions. The pilot test data are shown in Table 1.

[0116] Table 1 Test data

[0117]

[0118]

[0119] According to the objective function Based on the pilot test data, the optimization algorithm is applied to estimate the model parameters and obtain the model parameters.

[0120] Based on the industrial calibration data of a refinery catalytic cracking unit, the model unit factors are calculated and obtained. The model is then used to predict the product distribution. The product distribution changes with the reaction pressure, see Figure 2 .

[0121] Comparative Example 1

[0122] The reaction model was established according to Example 1, except that the pressure correction function θ(P) was not used. The product distribution predicted by the model changes with the reaction pressure. Figure 3 .

[0123] contrast Figure 2 and Figure 3 It can be seen that the gas product yield predicted by Example 1 shows a decreasing trend with increasing reaction pressure, which is consistent with the catalytic cracking reaction mechanism. The gas product yield predicted by Comparative Example 1 shows an increasing trend with increasing reaction pressure, which is inconsistent with the catalytic cracking reaction mechanism. From the data comparison, it can be seen that Example 1 shows a good prediction ability. It shows that the method for improving the prediction accuracy of the catalytic cracking model proposed in this application is effective.

[0124] Comparative Example 2

[0125] The reaction model was established according to Example 1, except that the correction function used was The product distribution predicted by the model changes with reaction pressure. Figure 4 .

[0126] contrast Figure 2 and Figure 4 It can be seen that the gas product yield predicted in Comparative Example 2 shows a decreasing trend with increasing reaction pressure, which is consistent with the catalytic cracking reaction mechanism. However, as the reaction pressure increases from 0.1MPa to 0.2MPa, the gas product yield decreases from 37w% to 24w%, which is inconsistent with the actual gas yield of the catalytic cracking unit. The conventional gas yield of catalytic cracking is 20w%-30w%.

[0127] In summary, this application can effectively solve the problem that the existing model predicts that the gas product yield changes with the reaction pressure and is inconsistent with the actual situation by correcting the reaction rate in the catalytic cracking lumped kinetic model with a specific correction function, and accurately predict the change of the gas product yield with the reaction pressure. This method is suitable for process processes with complex reaction systems, including parallel sequential reactions and gas as the terminal product, and is of great significance to the optimization design of catalytic cracking units.

[0128] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for improving the prediction accuracy of a catalytic cracking model, characterized in that: The following steps are involved: Correction function Correction of reaction rates in the lumped kinetic model of catalytic cracking; In the formula, P is system pressure; is the characteristic factor of the oil; The catalytic cracking lumped kinetic model is based on the catalytic cracking reaction mechanism and is obtained by establishing a reaction network based on the lumps divided by raw materials and products. Among them, the raw material aggregate includes the vacuum residue aggregate and the distillate oil aggregate; the product aggregate includes the gas aggregate, gasoline aggregate, diesel aggregate, slurry aggregate and coke aggregate; The establishment of the reaction network includes: A reaction network is established by corresponding the vacuum residue oil aggregate to the gas aggregate, the gasoline aggregate, the diesel aggregate, the slurry oil aggregate and the coke aggregate in a one-to-one manner; Establish a reaction network by corresponding the distillate oil aggregate to the gas aggregate, the gasoline aggregate, the diesel aggregate, the slurry oil aggregate and the coke aggregate in a one-to-one manner; Establish a reaction network by corresponding the diesel aggregate to the gas aggregate, the gasoline aggregate and the coke aggregate one by one; Establish a reaction network by corresponding the oil slurry aggregate to the gas aggregate and the coke aggregate one by one; Establish a reaction network by corresponding the gasoline aggregate to the gas aggregate and the coke aggregate one by one; The corrected catalytic cracking lumped reaction rates are as follows: ； ； ； ； ； ； ； In the formula, X=x / H , X Indicates the bed x The dimensionless relative distance at the corresponding cross section; x It indicates the distance from the riser inlet into the reactor; H represents the total length of the catalyst bed; T Indicates the system temperature; R is the gas constant; S WH represents the true weight-hourly space velocity; M i Represents lumped i The relative molecular mass; y i for i Aggregate test concentration; For reaction The reaction rate constant, ,in, represents the pre-exponential factor, represents the activation energy; VR stands for vacuum residue, VGO Represents distillate oil, GAS Represents gas, G Represents gasoline, D Represents diesel, S Represents oil slurry, CK represents coke; y VR represents the experimental concentration of vacuum residue lumps, y VGO represents the test concentration of the distillate aggregate, y GAS represents the test concentration of the gas lumps, y G represents the test concentration of gasoline lumps, y D represents the test concentration of diesel lumps, y S represents the test concentration of the lumped slurry, y CK represents the test concentration of the coke aggregate; Reaction 1 is the reaction between the distillate oil aggregate and the diesel aggregate, reaction 2 is the reaction between the distillate oil aggregate and the slurry oil aggregate, reaction 3 is the reaction between the distillate oil aggregate and the gasoline aggregate, reaction 4 is the reaction between the distillate oil aggregate and the gas aggregate, reaction 5 is the reaction between the distillate oil aggregate and the coke aggregate; reaction 6 is the reaction between the vacuum residue oil aggregate and the diesel aggregate, reaction 7 is the reaction between the vacuum residue oil aggregate and the slurry oil aggregate, reaction 8 is the reaction between the vacuum residue oil aggregate and the gasoline aggregate, reaction 9 is the reaction between the vacuum residue oil aggregate and the gasoline aggregate. and gas lumps, reaction 10 is the reaction between the vacuum residue oil lumps and the coke lumps; reaction 11 is the reaction between the diesel lumps and the gasoline lumps, reaction 12 is the reaction between the diesel lumps and the gas lumps, reaction 13 is the reaction between the diesel lumps and the coke lumps; reaction 14 is the reaction between the slurry oil lumps and the gas lumps, reaction 15 is the reaction between the slurry oil lumps and the coke lumps; reaction 16 is the reaction between the gasoline lumps and the gas lumps, reaction 17 is the reaction between the gasoline lumps and the coke lumps.

2. The method according to claim 1, characterized in that The lumped reaction rates of catalytic cracking before correction are as follows: ； ； ； ； ； ； 。 3. The method according to claim 1 or 2, characterized in that: It also includes the proposed objective function to estimate the reaction kinetic model parameters.

4. The method according to claim 3, characterized in that The objective function is ; Where φ is the sum of squares of the error between the test value and the fitted value; is the number of trials; n c is the number of components, a ij express i Lumped in response j The test concentration in express i Lumped in response j The trial fit concentration in .

5. A modeling device for improving the prediction accuracy of a catalytic cracking model, characterized in that: The modeling device comprises a modeling module which performs modeling by using the method for improving the prediction accuracy of the catalytic cracking model as described in any one of claims 1 to 4.

6. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method for improving the prediction accuracy of the catalytic cracking model according to any one of claims 1 to 4 are executed.

7. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for improving the prediction accuracy of a catalytic cracking model as described in any one of claims 1 to 4 are performed.

Images