CN111899811A - Method, system, equipment and storage medium for establishing catalytic reforming device product prediction model - Google Patents
Method, system, equipment and storage medium for establishing catalytic reforming device product prediction model Download PDFInfo
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Abstract
The invention relates to a method, a system, equipment and a storage medium for establishing a product prediction model of a catalytic reforming device. The establishing method comprises the following steps: obtaining the raw material molecular composition of a catalytic reforming raw material, and processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition; respectively calculating the reaction rate corresponding to each reaction path; and establishing a product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path. The yield of the target product of the catalytic reforming device under different reaction conditions is predicted through the product prediction model, and the product prediction of the catalytic reforming device is realized on a molecular level, so that the production process can be simulated and optimized, and the production benefit is improved.
Description
Technical Field
The invention relates to the technical field of petroleum processing, in particular to a method, a system, equipment and a storage medium for establishing a product prediction model of a catalytic reforming device.
Background
Catalytic reforming is one of petroleum refining processes, which converts light gasoline fraction (or naphtha) obtained by distilling crude oil into high-octane gasoline (reformed gasoline) rich in aromatic hydrocarbons, and by-products of liquefied petroleum gas and hydrogen, under the conditions of heating, hydrogen pressure and the presence of a catalyst.
However, the types of petroleum processing devices are various, and when the types of complex and varied raw materials are faced, the reaction process of the raw materials in each petroleum processing device is generally difficult to determine, and the product information of each petroleum processing device is further impossible to determine, so that the components of the products cannot be determined in advance, and the value of the products is difficult to estimate. For example: catalytic reforming is an important naphtha processing technology in the oil refining industry and is also an important process for improving the octane number of gasoline and realizing the integrated goal of oil refining/chemical industry. The catalytic reforming device produces low-sulfur low-olefin clean gasoline and can also produce high-purity hydrogen as a byproduct. The products produced by the catalytic reforming process can meet the demands of the market for clean fuels and aromatic hydrocarbons to a great extent. However, in the face of complicated and variable raw materials, it is difficult to accurately reflect the reaction mechanism of the catalytic reforming process, and the product after catalytic reforming cannot be determined.
Disclosure of Invention
In order to solve the problems in the prior art, at least one embodiment of the present invention provides a method, a system, a device and a storage medium for building a product prediction model. However, the types of petroleum processing devices are various, and when the types of complex and varied raw materials are faced, the reaction process of the raw materials in each petroleum processing device is generally difficult to determine, and the product information of each petroleum processing device is further impossible to determine, so that the components of the products cannot be determined in advance, and the value of the products is difficult to estimate. For example: catalytic reforming is an important naphtha processing technology in the oil refining industry and is also an important process for improving the octane number of gasoline and realizing the integrated goal of oil refining/chemical industry. The catalytic reforming device produces low-sulfur low-olefin clean gasoline and can also produce high-purity hydrogen as a byproduct. The products produced by the catalytic reforming process can meet the demands of the market for clean fuels and aromatic hydrocarbons to a great extent.
In a first aspect, an embodiment of the present invention provides a method for building a product prediction model of a catalytic reforming apparatus, where the method includes:
obtaining the raw material molecular composition of the catalytic reforming raw material;
processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition;
respectively calculating the reaction rate corresponding to each reaction path;
and establishing the product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
Based on the above technical solutions, the embodiments of the present invention may be further improved as follows.
With reference to the first aspect, in a first embodiment of the first aspect, before the separately calculating the reaction rate corresponding to each reaction path, the establishing method further includes:
obtaining a first molecular composition of a device product according to a reaction path corresponding to each single molecule in the raw material molecular composition of the catalytic reforming raw material; the plant product comprises the catalytic reforming feedstock, an intermediate product, and a predicted product;
acquiring a second molecular composition of an actual product of the catalytic reforming device, and acquiring a first relative deviation according to the second molecular composition and the first molecular composition;
if the first relative deviation meets a preset condition, executing the step of respectively calculating the reaction rate corresponding to each reaction path;
and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, processing the raw material molecular composition according to the adjusted reaction rule set, and obtaining the reaction path corresponding to each single molecule again until the first relative deviation of the first molecular composition and the second molecular composition accords with the preset condition.
With reference to the first embodiment of the first aspect, in the second embodiment of the first aspect, the obtaining a first relative deviation according to the second molecular composition and the first molecular composition comprises:
acquiring the species of single molecules in the second molecular composition to construct a second set;
acquiring the types of single molecules in the first molecular composition to construct a first set;
determining whether the second set is a subset of the first set;
if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value;
if the second set is a subset of the first set, calculating a first relative deviation by: determining the first relative deviation as a ratio of the number of species of the portion of the molecular composition of the predicted product in which a single molecule is not in the second set to the total number of species of a single molecule in the molecular composition of the predicted product;
for example, the first relative deviation is calculated by the following calculation formula:
x1is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the catalytic reforming feedstock, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
With reference to the first aspect, in a third embodiment of the first aspect, the separately calculating the reaction rate corresponding to each reaction path includes:
calculating a reaction path rate constant corresponding to each reaction path according to a transition state theoretical calculation method;
for example, the reaction rate constant corresponding to each reaction path is calculated according to the following calculation formula:
wherein k is the reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where a reaction path is located, exp is an exponential function with a natural constant as a base, Delta S is an entropy change before and after a reaction corresponding to a reaction rule corresponding to the reaction path, Delta E is a reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
the catalyst activity factor P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path;
and obtaining the reaction rate of the corresponding reaction path according to the reaction rate constant.
With reference to the third embodiment of the first aspect, in a fourth embodiment of the first aspect, the establishing method further includes:
obtaining the monomolecular content of each monomolecular in the catalytic reforming raw material;
obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model;
obtaining an actual content of each single molecule in an actual product of the catalytic reformer;
calculating a second relative deviation according to the predicted content of each single molecule in the predicted product and the actual content of each single molecule in the actual product;
if the second relative deviation does not meet the preset condition, adjusting the reaction rate corresponding to each reaction path in the product prediction model, and obtaining a new prediction product according to the product prediction model; until the second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a preset condition.
With reference to the first aspect or the first, second, third, and fourth embodiments of the first aspect, in a fifth embodiment of the first aspect, the obtaining a feedstock molecular composition of a catalytic reforming feedstock comprises:
determining the molecular composition of the feedstock by one or more of comprehensive two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometry detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry, and ion mobility mass spectrometry.
In a second aspect, an embodiment of the present invention provides a product prediction model building system for a catalytic reforming unit, where the product prediction model building system includes:
a first obtaining unit for obtaining a feedstock molecular composition of a catalytic reforming feedstock;
the reaction path generation unit is used for processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition;
the first calculating unit is used for calculating the reaction rate corresponding to each reaction path;
and the establishing unit is used for establishing the product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
With reference to the second aspect, in a first embodiment of the second aspect, the product prediction model building system further includes:
the product prediction unit is used for obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the catalytic reforming raw material; the plant product comprises the catalytic reforming feedstock, an intermediate product, and a predicted product;
a second obtaining unit for obtaining a second molecular composition of an actual product of the catalytic reformer;
a second calculating unit, configured to obtain a first relative deviation according to the second molecular composition and the first molecular composition;
the first judgment unit is used for judging whether the first relative deviation meets a preset condition or not;
the reaction path generating unit is further configured to adjust a reaction rule in the reaction rule set if the first relative deviation does not meet a preset condition, process the raw material molecular composition according to the adjusted reaction rule set, and obtain a reaction path corresponding to each kind of single molecule again until the first relative deviation between the first molecular composition and the second molecular composition meets the preset condition.
With reference to the first embodiment of the second aspect, in a second embodiment of the second aspect, the product prediction model building system further includes:
a third acquiring unit, configured to acquire a kind of a single molecule in the second molecular component, and construct a second set; acquiring the types of single molecules in the first molecular composition to construct a first set;
a second judging unit, configured to judge whether the second set is a subset of the first set;
a fourth obtaining unit, configured to, if the second set is not a subset of the first set, obtain a pre-stored relative deviation value that does not meet a preset condition as the first relative deviation value;
the second calculating unit is configured to calculate a first relative deviation by: determining the first relative deviation as a ratio of the number of species of the portion of the molecular composition of the predicted product in which a single molecule is not in the second set to the total number of species of a single molecule in the molecular composition of the predicted product;
for example, the first relative deviation is calculated by the following calculation formula:
x1is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the catalytic reforming feedstock, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
With reference to the second aspect, in a third embodiment of the second aspect, the first calculating unit is specifically configured to calculate a reaction path rate constant corresponding to each reaction path according to a transition state theoretical calculation method;
for example, the method is specifically used for calculating the reaction rate constant corresponding to each reaction path according to the following calculation formula:
wherein k is the reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where a reaction path is located, exp is an exponential function with a natural constant as a base, Delta S is an entropy change before and after a reaction corresponding to a reaction rule corresponding to the reaction path, Delta E is a reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
the catalyst activity factor P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path;
and the first calculating unit is used for obtaining the reaction rate of the corresponding reaction path according to the reaction rate constant.
With reference to the third embodiment of the second aspect, in a fourth embodiment of the second aspect, the establishing system includes:
a first obtaining unit, which is also used for obtaining the single-molecule content of each single molecule in the catalytic reforming raw material;
the product content prediction unit is used for obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model;
a fifth obtaining unit for obtaining an actual content of each single molecule in an actual product of the catalytic reformer;
a third calculation unit for calculating a second relative deviation based on the predicted content of each monomolecular in the predicted product and the actual content of each monomolecular in the actual product;
a third judging unit for judging whether the second relative deviation meets a preset condition,
the first calculating unit is further configured to adjust a reaction rate corresponding to each reaction path in the product prediction model if the second relative deviation does not meet a preset condition, and obtain a new predicted product according to the product prediction model; until the second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a preset condition.
In a fifth embodiment of the second aspect in combination with the second aspect or the first, second, third or fourth embodiment of the second aspect, the first acquisition unit is configured to determine the molecular composition of the feedstock by one or more of two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometer detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry and ion mobility mass spectrometry.
In a third aspect, an embodiment of the present invention provides a device for building a product prediction model of a catalytic reforming apparatus, including a processor, a communication interface, a memory, and a communication bus, where the processor and the communication interface are used, and the memory completes communication with each other through the communication bus;
a memory for storing a computer program;
a processor configured to implement the method for building a product prediction model according to any one of the embodiments of the first aspect when executing a program stored in a memory.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the method for building a product prediction model according to any one of the first aspect.
Compared with the prior art, the technical scheme of the invention has the following advantages: the embodiment of the invention obtains the raw material molecule composition of the catalytic reforming raw material, matches the single molecules according to the reaction rules in the reaction rule set to obtain the reaction path of each single molecule, respectively calculates the reaction rate of each reaction path, constructs a product prediction model based on the reaction paths and the reaction rates, predicts the yield of the target product of the catalytic reforming device under different reaction conditions through the product prediction model, and realizes the product prediction of the catalytic reforming device on a molecular level, so that the production process can be simulated and optimized, and the production benefit is improved.
Drawings
Fig. 1 is a schematic flow chart of a method for building a product prediction model of a catalytic reforming unit according to an embodiment of the present invention.
Fig. 2 is a schematic flow chart of a method for building a product prediction model of a catalytic reforming unit according to another embodiment of the present invention.
Fig. 3 is a schematic flow chart of a method for building a product prediction model of a catalytic reforming unit according to another embodiment of the present invention.
Fig. 4 is a block diagram of a system for modeling a product prediction for a catalytic reformer according to yet another embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a product prediction modeling apparatus of a catalytic reforming unit according to another embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a product prediction modeling apparatus of a catalytic reforming unit according to yet another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for building a product prediction model of a catalytic reforming apparatus.
Referring to fig. 1, the setup method includes:
and S11, obtaining the molecular composition of the raw material of the catalytic reforming raw material.
In this example, the catalytic reforming raw material is an oil product obtained by distilling and cutting crude oil in the crude oil treatment process, and the catalytic reforming is a process of rearranging the molecular structure of hydrocarbons in the gasoline fraction into a new molecular structure under the action of a catalyst, which is called catalytic reforming. One of petroleum refining processes is a process of converting a light gasoline fraction (or naphtha) obtained by distilling crude oil into a gasoline (reformed gasoline) rich in aromatic hydrocarbons and having a high octane number, and by-producing liquefied petroleum gas and hydrogen, under the conditions of heating, hydrogen pressure and the presence of a catalyst. The reformed gasoline can be directly used as a blending component of gasoline, and can also be extracted by aromatic hydrocarbon to prepare benzene, toluene and xylene. The byproduct hydrogen is an important source of hydrogen for hydrogenation devices (such as hydrofining and hydrocracking) in petroleum refineries. Although the number of molecular species in the catalytic reforming raw material is not as large as that of crude oil molecules, in order to ensure the accuracy of product prediction, the accuracy of the obtained molecular composition needs to be ensured, in this embodiment, the molecular composition of the catalytic reforming raw material may be determined by one or more of a full-two-dimensional gas chromatography, a quadrupole gas chromatography-mass spectrometer detection method, a gas chromatography/field ionization-time-of-flight mass spectrometry detection method, a gas chromatography, a near-infrared spectroscopy, a nuclear magnetic resonance spectroscopy, a raman spectroscopy, a fourier transform ion cyclotron resonance mass spectrometry, an electrostatic field orbitrap mass spectrometry, and an ion mobility mass spectrometry. Of course, the molecular composition of the mixture can also be determined in other ways, for example: the molecular composition of the mixture is determined by means of ASTM D2425, SH/T0606 and/or ASTM D8144-18.
In this embodiment, the composition of molecules in the raw material is complex, and in order to improve the data processing efficiency, a single molecule may be constructed based on a structure-oriented lumped molecular characterization method, that is, an SOL molecular characterization method, after the molecules in the raw material are detected by the above method, where the method uses 24 structure increment segments to characterize the basic structure of the complex hydrocarbon molecules. Any one petroleum molecule can be represented by a set of specific structural increment segments. The SOL method belongs to the lumped on the molecular scale, reduces the number of molecules in a practical system from millions to thousands, and greatly reduces the complexity of simulation. The characterization method can not only represent alkanes, cycloalkanes, up to complex aromatic structures containing 50 to 60 carbon atoms, but also alkenes or cycloalkenes as intermediate products or secondary reaction products, in addition to heteroatom compounds containing sulfur, nitrogen, oxygen, etc., being considered.
And S12, processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition.
In this embodiment, each raw material molecule in the catalytic reforming raw material is reacted according to a reaction rule in the reaction rule set to obtain a reaction path corresponding to each molecule, wherein after each molecule is reacted for the first time to generate an intermediate product, a molecular structure of the intermediate product may satisfy another reaction rule, and then the intermediate product will continue to undergo subsequent reactions until the molecule does not conform to any reaction rule in the reaction rule set, and then the final product of the reaction of the molecule is obtained, and the summary of the reactions is the reaction path of the molecule.
And S13, respectively calculating the reaction rate corresponding to each reaction path.
Specifically, the reaction rate of each reaction path is calculated according to a reaction rate constant in a reaction rate algorithm.
Calculating a reaction rate constant corresponding to each reaction path according to the following calculation formula:
wherein k is a reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where a reaction path is located, exp is an exponential function with a natural constant as a base, Delta S is an entropy change before and after a reaction corresponding to a reaction rule corresponding to the reaction path, Delta E is a reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
In this embodiment, k in the above formula is called reaction rate constant, which is also called rate constant k or λ, is a quantitative representation of chemical reaction rate, and its physical meaning is that its value is equivalent to the reaction rate when all the substances participating in the reaction are in unit concentration (1mol/L), so it is also called reaction specific rate, different reactions have different rate constants, and the rate constants are related to reaction temperature, reaction medium (solvent), catalyst, etc., and even vary with the shape and properties of the reactor. Regardless of concentration, but is influenced by factors such as temperature, catalyst, surface properties of the solid, and the like. In this embodiment, after the reaction rate constant is calculated, the real-time reaction rate of the molecule can be obtained from the concentration of the molecule, for example, if the reaction rate of the molecule per unit concentration is k, and after the concentration V is confirmed, the reaction rate of the molecule corresponding to the reaction path is Vk, and thus the reaction rate is calculated.
And S14, establishing a product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
In this embodiment, a product prediction model of the catalytic reforming apparatus may be established by combining the reaction paths obtained in the above steps and the reaction rate corresponding to each reaction path, and the molecular composition and the corresponding concentration of the product may be obtained by inputting the molecular composition of the raw material product through the product prediction model.
As shown in fig. 2, in a specific embodiment, before the reaction rate corresponding to each reaction path is calculated, the method for establishing the model further includes the following steps:
s21, obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the catalytic reforming raw material; the plant product comprises catalytic reforming feedstock, intermediate products, and predicted products.
And S22, acquiring a second molecular composition of the actual product of the catalytic reforming device, and obtaining a first relative deviation according to the second molecular composition and the first molecular composition.
Specifically, acquiring the types of single molecules in the second molecular composition, and constructing a second set; acquiring the species of single molecules in the first molecular composition to construct a first set; determining whether the second set is a subset of the first set; if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as a first relative deviation value; if the second set is a subset of the first set, calculating a first relative deviation by:
wherein x is1Is a first relative deviation, M is a first set, M1M is a collection of species constituents of a single molecule in the molecular composition of the catalytic reforming feedstock2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
The preset conditions comprise: relative deviation range. The two endpoints of the relative deviation range are empirical values or experimentally obtained values.
S23a, if the first relative deviation meets the preset condition, executing the step of calculating the reaction rate corresponding to each reaction path respectively.
When the first relative deviation value meets the preset condition, that is, the reaction rule set is established, the correspondingly generated reaction path meets the preset condition, and the reaction rule set does not need to be adjusted.
And S23b, if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, processing the raw material molecule composition according to the adjusted reaction rule set, and obtaining the reaction path corresponding to each single molecule again until the first relative deviation of the first molecule composition and the second molecule composition accords with the preset condition.
As shown in fig. 3, in a specific embodiment, before the product prediction model is built according to the reaction rate corresponding to the reaction path and each reaction path, the model building method further includes the following steps:
and S31, obtaining the single-molecule content of each single molecule in the catalytic reforming raw material.
And S32, obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model.
In this embodiment, the reaction rate corresponding to each reaction path is calculated by the reaction rate calculation method in the product prediction model, and in combination with the monomolecular content of each monomolecular in the raw material, namely, the predicted content of each single molecule in the predicted product can be calculated, for example, the single molecule A in the raw material is assumed to correspond to 3 reaction paths, and the reaction rate corresponding to 3 reaction paths is known, as the reaction proceeds, the concentration of the single molecule A decreases, the reaction rate corresponding to 3 reaction paths decreases according to the decreasing proportion of the concentration, therefore, the single molecule A will generate the product with the ratio of the reaction rate of 3 paths, according to the above steps, the product obtained by each molecule reaction can be obtained, the predicted product can be obtained, and the content of each single molecule in the predicted product can be obtained when the content of each single molecule in the catalytic reforming raw material is known.
S33, obtaining the actual content of each single molecule in the actual product of the catalytic reformer.
And S34, calculating a second relative deviation according to the predicted content of each single molecule in the predicted product and the actual content of each single molecule in the actual product.
The second relative deviation is calculated, for example, as:
second relative deviation (actual content-predicted content) ÷ actual content.
S35, if the second relative deviation does not meet the preset condition, adjusting the reaction rate corresponding to each reaction path in the product prediction model, and obtaining a new prediction product according to the product prediction model; until a second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a predetermined condition.
In this embodiment, if the second relative deviation meets the preset condition, a product prediction model is established according to the reaction paths and the reaction rates corresponding to each of the reaction paths.
Adjusting the reaction rate corresponding to each reaction path in the product prediction model specifically comprises: and (3) calculating parameters in a formula by adjusting a reaction rate constant in the reaction rate calculation method corresponding to each reaction path in the product prediction model. The accuracy of the reaction rate calculation method in the product prediction model is ensured through feedback adjustment.
As shown in fig. 4, an embodiment of the present invention provides a product prediction modeling system for a catalytic reforming apparatus, where the product prediction modeling system includes: the device comprises a first acquisition unit, a reaction path generation unit, a first calculation unit and an establishment unit.
In the present embodiment, a first obtaining unit for obtaining a feedstock molecular composition of a catalytic reforming feedstock; the molecular composition of the mixture can be determined by one or more of comprehensive two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometry detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry, and ion mobility mass spectrometry. Of course, the molecular composition of the mixture can also be determined in other ways, for example: the molecular composition of the mixture is determined by means of ASTM D2425, SH/T0606 and/or ASTM D8144-18. In this embodiment, the composition of molecules in the raw material is complex, and in order to improve the data processing efficiency, a single molecule may be constructed based on a structure-oriented lumped molecular characterization method, that is, an SOL molecular characterization method, after the molecules in the raw material are detected by the above method, where the method uses 24 structure increment segments to characterize the basic structure of the complex hydrocarbon molecules. Any one petroleum molecule can be represented by a set of specific structural increment segments. The SOL method belongs to the lumped on the molecular scale, reduces the number of molecules in a practical system from millions to thousands, and greatly reduces the complexity of simulation. The characterization method can not only represent alkanes, cycloalkanes, up to complex aromatic structures containing 50 to 60 carbon atoms, but also alkenes or cycloalkenes as intermediate products or secondary reaction products, in addition to heteroatom compounds containing sulfur, nitrogen, oxygen, etc., being considered.
In this embodiment, the reaction path generating unit is configured to process the raw material molecular composition according to a preset reaction rule set, so as to obtain a reaction path corresponding to each kind of single molecule in the raw material molecular composition; reacting each raw material molecule in the catalytic reforming raw material according to a reaction rule in the reaction rule set to obtain a reaction path corresponding to each molecule, wherein after each molecule is subjected to a first reaction to generate an intermediate product, the molecular structure of the intermediate product possibly meets another reaction rule, the intermediate product continues to perform subsequent reactions until the molecule does not meet any reaction rule in the reaction rule set, the molecule is subjected to a final product of the reactions, and the summary of the reactions is the reaction path of the molecule.
In this embodiment, the first calculating unit is configured to calculate a reaction rate corresponding to each reaction path;
the reaction rate for each reaction path can be calculated from the reaction rate constants in the reaction rate algorithm.
Calculating a reaction rate constant corresponding to each reaction path according to the following calculation formula:
wherein k is a reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where a reaction path is located, exp is an exponential function with a natural constant as a base, Delta S is an entropy change before and after a reaction corresponding to a reaction rule corresponding to the reaction path, Delta E is a reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
In this embodiment, k in the above formula is called reaction rate constant, which is also called rate constant k or λ, is a quantitative representation of chemical reaction rate, and its physical meaning is that its value is equivalent to the reaction rate when all the substances participating in the reaction are in unit concentration (1mol/L), so it is also called reaction specific rate, different reactions have different rate constants, and the rate constants are related to reaction temperature, reaction medium (solvent), catalyst, etc., and even vary with the shape and properties of the reactor. Regardless of concentration, but is influenced by factors such as temperature, catalyst, surface properties of the solid, and the like. In this embodiment, after the reaction rate constant is calculated, the real-time reaction rate of the molecule can be obtained from the concentration of the molecule, for example, if the reaction rate of the molecule per unit concentration is k, and after the concentration V is confirmed, the reaction rate of the molecule corresponding to the reaction path is Vk, and thus the reaction rate is calculated.
In this embodiment, the establishing unit is configured to establish the product prediction model according to the reaction paths and the reaction rates corresponding to each of the reaction paths. And (3) combining the reaction paths obtained in the steps and the reaction rate corresponding to each reaction path to establish a product prediction model of the catalytic reforming device, and inputting the molecular composition of the raw material product through the product prediction model to obtain the molecular composition and the corresponding concentration of the product.
Wherein, the system for establishing the product prediction model further comprises:
the product prediction unit is used for obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the catalytic reforming raw material; the plant product comprises a catalytic reforming feedstock, an intermediate product, and a predicted product;
a second obtaining unit for obtaining a second molecular composition of an actual product of the catalytic reformer;
the second calculation unit is used for obtaining a first relative deviation according to the second component and the first component;
specifically, acquiring the types of single molecules in the second molecular composition, and constructing a second set; acquiring the species of single molecules in the first molecular composition to construct a first set; determining whether the second set is a subset of the first set; if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as a first relative deviation value; if the second set is a subset of the first set, calculating a first relative deviation by:
wherein x is1Is a first relative deviation, M is a first set, M1M is a collection of species constituents of a single molecule in the molecular composition of the catalytic reforming feedstock2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
The preset conditions comprise: relative deviation range. The two endpoints of the relative deviation range are empirical values or experimentally obtained values.
The first judging unit is used for judging whether the first relative deviation meets a preset condition or not;
and the reaction path generation unit is further used for adjusting the reaction rules in the reaction rule set if the first relative deviation does not meet the preset condition, processing the raw material molecule composition according to the adjusted reaction rule set, and obtaining the reaction path corresponding to each single molecule again until the first relative deviation of the first molecule composition and the second molecule composition meets the preset condition.
When the first relative deviation value meets the preset condition, that is, the reaction rule set is established, the correspondingly generated reaction path meets the preset condition, and the reaction rule set does not need to be adjusted.
Wherein, the system for establishing the product prediction model further comprises:
and the first obtaining unit is also used for obtaining the single-molecule content of each single molecule in the catalytic reforming raw material.
And the product content prediction unit is used for obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model.
In this embodiment, the reaction rate corresponding to each reaction path is calculated by the reaction rate calculation method in the product prediction model, and in combination with the monomolecular content of each monomolecular in the raw material, namely, the predicted content of each single molecule in the predicted product can be calculated, for example, the single molecule A in the raw material is assumed to correspond to 3 reaction paths, and the reaction rate corresponding to 3 reaction paths is known, as the reaction proceeds, the concentration of the single molecule A decreases, the reaction rate corresponding to 3 reaction paths decreases according to the decreasing proportion of the concentration, therefore, the single molecule A will generate the product with the ratio of the reaction rate of 3 paths, according to the above steps, the product obtained by each molecule reaction can be obtained, the predicted product can be obtained, and the content of each single molecule in the predicted product can be obtained when the content of each single molecule in the catalytic reforming raw material is known.
And a fifth obtaining unit for obtaining an actual content of each single molecule in an actual product of the catalytic reformer.
And a third calculating unit for calculating a second relative deviation based on the predicted content of each of the single molecules in the predicted product and the actual content of each of the single molecules in the actual product.
The second relative deviation is calculated, for example, as:
second relative deviation (actual content-predicted content) ÷ actual content.
A third judging unit for judging whether the second relative deviation meets a preset condition,
the first calculating unit is further used for adjusting the reaction rate corresponding to each reaction path in the product prediction model if the second relative deviation does not meet the preset condition, and obtaining a new predicted product according to the product prediction model; until a second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a predetermined condition.
In this embodiment, if the second relative deviation meets the preset condition, a product prediction model is established according to the reaction paths and the reaction rates corresponding to each of the reaction paths.
Adjusting the reaction rate corresponding to each reaction path in the product prediction model specifically comprises: and (3) calculating parameters in a formula by adjusting a reaction rate constant in the reaction rate calculation method corresponding to each reaction path in the product prediction model. The accuracy of the reaction rate calculation method in the product prediction model is ensured through feedback adjustment.
As shown in fig. 5, an embodiment of the present invention provides a product prediction model building apparatus for a catalytic reforming unit, which includes a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, wherein the processor 1110, the communication interface 1120, and the memory 1130 complete communication with each other through the communication bus 1140;
a memory 1130 for storing computer programs;
obtaining the raw material molecular composition of the catalytic reforming raw material;
processing the raw material molecule composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecule composition;
respectively calculating the reaction rate corresponding to each reaction path;
and establishing a product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
In the electronic device provided by the embodiment of the present invention, the processor 1110 implements, by executing the program stored in the memory 1130, obtaining the raw material molecular composition of the catalytic reforming raw material, constructing a reaction rule set according to the reaction type occurring in the catalytic reforming apparatus, matching the single molecules according to the reaction rules in the reaction rule set to obtain the reaction path of each single molecule, calculating the reaction rate of each reaction path, constructing a product prediction model based on the reaction path and the reaction rate, and implementing product prediction for the catalytic reforming apparatus at a molecular level, so that a production process can be optimized in a simulation manner, and production benefits are improved.
The communication bus 1140 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices.
The Memory 1130 may include a Random Access Memory 1130 (RAM), and may also include a Non-volatile Memory 1130(Non-volatile Memory), such as at least one disk Memory 1130. Optionally, the memory 1130 may also be at least one memory device located remotely from the processor 1110.
The Processor 1110 may be a general-purpose Processor 1110, and includes a Central Processing Unit (CPU) 1110, a Network Processor (NP) 1110, and the like; the device may also be a Digital Signal processor 1110 (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components.
In a specific embodiment, a schematic block diagram of a system configuration of the product prediction model building apparatus of the catalytic reforming apparatus is shown in fig. 6, the product prediction model building apparatus of the catalytic reforming apparatus further includes an input unit 1150, a display 1160 and a power supply 1170, the processor 1110 uses a central processing unit 1111 (when the central processing unit 1111 is used for executing a program stored in a memory 1130, specific steps for building a product prediction model are realized by referring to the processor 1110 through executing the program stored in the memory 1130, and repeated parts are not described again);
the memory 1130 includes a buffer memory 1131 (sometimes referred to as a buffer). The memory 1130 may include an application/function storage portion 1132, the application/function storage portion 1132 for storing an application program and a function program or a flow for executing the operation of the product prediction model creation means of the catalytic reformer by the central processing unit 1111;
the memory 1130 may also include a data store 1133, the data store 1133 being configured to store data, such as a preset set of reaction rules, reaction paths, reaction rates, numerical data, pictures, and/or any other data used by the product prediction model building apparatus of the catalytic reformer; the driver storage section 1134 of the memory 1130 may include various drivers of the product prediction model establishing apparatus of the catalytic reformer;
a central processor 1111, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, the central processor 1111 receiving inputs and controlling the operation of the various components of the product prediction modeling apparatus of the catalytic reformer;
the input unit 1150 provides input to the central processor 1111; the input unit 1150 is, for example, a key or a touch input device; a power supply 1170 for providing power to a product prediction model building apparatus of the catalytic reformer; the display 1160 is used for displaying display objects such as images and characters; the display may be, for example, an LCD display, but is not limited thereto.
Embodiments of the present invention provide a computer-readable storage medium storing one or more programs, which are executable by one or more processors 1110 to implement the method for building a product prediction model according to any of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the invention are brought about in whole or in part when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (14)
1. A method of building a product prediction model for a catalytic reformer, the method comprising:
obtaining the raw material molecular composition of the catalytic reforming raw material;
processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition;
respectively calculating the reaction rate corresponding to each reaction path;
and establishing the product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
2. The method of claim 1, wherein before the calculating the reaction rate corresponding to each reaction path, the method further comprises:
obtaining a first molecular composition of a device product according to a reaction path corresponding to each single molecule in the raw material molecular composition of the catalytic reforming raw material; the plant product comprises the catalytic reforming feedstock, an intermediate product, and a predicted product;
acquiring a second molecular composition of an actual product of the catalytic reforming device, and acquiring a first relative deviation according to the second molecular composition and the first molecular composition;
if the first relative deviation meets a preset condition, executing the step of respectively calculating the reaction rate corresponding to each reaction path;
and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, processing the raw material molecular composition according to the adjusted reaction rule set, and obtaining a reaction path corresponding to each single molecule in the raw material molecular composition again until the first relative deviation of the first molecular composition and the second molecular composition accords with the preset condition.
3. The method of claim 2, wherein obtaining a first relative deviation from the second molecular composition and the first molecular composition comprises:
acquiring the species of single molecules in the second molecular composition to construct a second set;
acquiring the types of single molecules in the first molecular composition to construct a first set;
determining whether the second set is a subset of the first set;
if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value;
if the second set is a subset of the first set, calculating a first relative deviation by:
x1is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the catalytic reforming feedstock, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
4. The method of claim 1, wherein the calculating the reaction rate corresponding to each reaction path comprises:
calculating a reaction rate constant corresponding to each reaction path according to the following calculation formula:
wherein k is the reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where the reaction path is located, exp is an exponential function with a natural constant as a base, and Delta S is a reaction rule pair corresponding to the reaction pathEntropy change before and after the reaction, Delta E is the reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
the catalyst activity factor P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path;
and obtaining the reaction rate of the corresponding reaction path according to the reaction rate constant.
5. The method of building a product prediction model according to claim 4, further comprising:
obtaining the monomolecular content of each monomolecular in the catalytic reforming raw material;
obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model;
obtaining an actual content of each single molecule in an actual product of the catalytic reformer;
calculating a second relative deviation according to the predicted content of each single molecule in the predicted product and the actual content of each single molecule in the actual product;
if the second relative deviation does not meet the preset condition, adjusting the reaction rate corresponding to each reaction path in the product prediction model, and obtaining a new prediction product according to the product prediction model; until the second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a preset condition.
6. The method of any one of claims 1-5, wherein obtaining the molecular composition of the feedstock of the catalytic reformer feedstock comprises:
determining the molecular composition of the feedstock by one or more of comprehensive two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometry detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry, and ion mobility mass spectrometry.
7. A product prediction modeling system for a catalytic reformer, the product prediction modeling system comprising:
a first obtaining unit for obtaining a feedstock molecular composition of a catalytic reforming feedstock;
the reaction path generation unit is used for processing the raw material molecular composition according to a preset reaction rule set to obtain a reaction path corresponding to each single molecule in the raw material molecular composition;
the first calculating unit is used for calculating the reaction rate corresponding to each reaction path;
and the establishing unit is used for establishing the product prediction model according to the reaction paths and the reaction rate corresponding to each reaction path.
8. The product prediction model creation system of claim 7, further comprising:
the product prediction unit is used for obtaining a first molecular composition of a device product according to a reaction path corresponding to each single molecule in the raw material molecular composition of the catalytic reforming raw material; the plant product comprises the catalytic reforming feedstock, an intermediate product, and a predicted product;
a second obtaining unit for obtaining a second molecular composition of an actual product of the catalytic reformer;
a second calculating unit, configured to obtain a first relative deviation according to the second molecular composition and the first molecular composition;
the first judgment unit is used for judging whether the first relative deviation meets a preset condition or not;
the reaction path generating unit is further configured to adjust a reaction rule in the reaction rule set if the first relative deviation does not meet a preset condition, process the raw material molecular composition according to the adjusted reaction rule set, and obtain a reaction path corresponding to each kind of single molecule again until the first relative deviation between the first molecular composition and the second molecular composition meets the preset condition.
9. The product prediction model creation system of claim 8, further comprising:
a third acquiring unit, configured to acquire a kind of a single molecule in the second molecular component, and construct a second set; acquiring the types of single molecules in the first molecular composition to construct a first set;
a second judging unit, configured to judge whether the second set is a subset of the first set;
a fourth obtaining unit, configured to, if the second set is not a subset of the first set, obtain a pre-stored relative deviation value that does not meet a preset condition as the first relative deviation value;
the second calculating unit is configured to calculate a first relative deviation by:
x1is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the catalytic reforming feedstock, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
10. The product prediction model building system according to claim 7, wherein the first calculating unit is specifically configured to calculate the reaction rate constant corresponding to each reaction path according to the following calculation formula:
wherein k is the reaction rate constant, kBIs a Boltzmann constant, h is a Planck constant, R is an ideal gas constant, E is a temperature value of an environment where a reaction path is located, exp is an exponential function with a natural constant as a base, Delta S is an entropy change before and after a reaction corresponding to a reaction rule corresponding to the reaction path, Delta E is a reaction energy barrier corresponding to the reaction rule corresponding to the reaction path,
the catalyst activity factor P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path;
and the first calculating unit is used for obtaining the reaction rate of the corresponding reaction path according to the reaction rate constant.
11. A product prediction model creation system as claimed in claim 10 wherein the creation system comprises:
a first obtaining unit, which is also used for obtaining the single-molecule content of each single molecule in the catalytic reforming raw material;
the product content prediction unit is used for obtaining the predicted content of each single molecule in the predicted product according to the single molecule content and the product prediction model;
a fifth obtaining unit for obtaining an actual content of each single molecule in an actual product of the catalytic reformer;
a third calculation unit for calculating a second relative deviation based on the predicted content of each monomolecular in the predicted product and the actual content of each monomolecular in the actual product;
a third judging unit for judging whether the second relative deviation meets a preset condition,
the first calculating unit is further configured to adjust a reaction rate corresponding to each reaction path in the product prediction model if the second relative deviation does not meet a preset condition, and obtain a new predicted product according to the product prediction model; until the second relative deviation between the predicted content of each single molecule and the actual content of each single molecule meets a preset condition.
12. A product prediction model creation system as claimed in any one of claims 7-11 wherein said first acquisition unit is configured to determine the molecular composition of said feedstock by one or more of full two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometry detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry and ion mobility mass spectrometry.
13. The product prediction model establishing equipment of the catalytic reforming device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the method of creating a product prediction model according to any one of claims 1 to 6 when executing a program stored in a memory.
14. A computer-readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the method of creating a product prediction model of any of claims 1-6.
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