CN115938499A - Method and device for optimizing hydrocracking model, electronic equipment and storage medium - Google Patents
Method and device for optimizing hydrocracking model, electronic equipment and storage medium Download PDFInfo
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Abstract
The present disclosure relates to an optimization method and an apparatus for a molecular-scale reaction kinetic model of a hydrocracking unit, wherein the optimization method comprises: obtaining a hydrocracking reaction kinetic model to be optimized; acquiring an initial value of a reaction rate of a reaction path, wherein the reaction rate of the reaction path is a virtual parameter aiming at a reaction rule and is used for expressing the reaction speed under each reaction rule; inputting the value of the reaction rate of the reaction path into a reaction kinetic model for reaction simulation to obtain the molecular composition data of the product; the initial value is taken as the value during the first reaction simulation; calculating a simulation value of a target index of a target product according to the molecular composition data of the product; and optimizing and adjusting the value of the reaction path reaction rate according to the difference between the simulated value and the actual value of the target index until the target reaction path reaction rate corresponding to the difference lower than the set threshold is obtained. The optimization method can improve the accuracy of the model and reduce the calculated amount of the model.
Description
Technical Field
The disclosure relates to the technical field of petrochemical industry, and in particular relates to an optimization method and device of a hydrocracking model, electronic equipment and a storage medium.
Background
The hydrocracking unit is used as a raw material supply of an ethylene unit and a production device of high-added-value products such as-35 # (the reference number-35 # indicates that the lowest allowable working temperature of diesel oil is 35 ℃ below zero) diesel oil and the like, and is an important point for realizing the maximum benefit of petrochemical enterprises. With the deterioration of crude oil properties, the hydrocracking unit plays an important role in the secondary processing of various oils.
At present, various process improvement and optimization work is continuously carried out by various enterprises and research institutions aiming at the hydrocracking unit, wherein some research directions are to model the hydrocracking reaction process so as to simulate the production operation process of the hydrocracking unit. At present, a lumped method is mainly adopted, the method is mature and widely applied, the operation conditions of the process can be effectively optimized, the product yield distribution can be predicted, and the device operation can be guided.
In recent years, with the continuous improvement of the product quality requirement of the market, the management and control of the oil product processing process from the molecular level are urgently needed, and the market demand promotes the development of complex system molecular dynamics models, including developed structure-oriented lumped models, single-event models, monte Carlo analysis models and the like.
In the modeling process based on structure-oriented aggregation, the calculation of the reaction rate is relatively complex, and the accuracy of the model is directly influenced by the accuracy of the value of the reaction rate. Therefore, in the reaction kinetic model, the determination of the reaction rate has always been the focus of research by many researchers.
Disclosure of Invention
To solve, or at least partially solve, the technical problems found in: the existing hydrocracking model has numerous parameters, particularly has very many associated parameters such as carbon number, pressure, temperature, catalyst and device types, so that the model simulation efficiency is low, the difference between the simulation result and actual production data is large, and the parameters of the model are very inconvenient to adjust; in view of this, embodiments of the present disclosure provide a method and an apparatus for optimizing a hydrocracking model, an electronic device, and a storage medium.
In a first aspect, embodiments of the present disclosure provide a method for optimizing a hydrocracking model. The optimization method comprises the following steps: obtaining a reaction kinetic model of hydrocracking to be optimized, wherein the reaction kinetic model comprises: reaction rules and reaction pathway reaction rates; acquiring an initial value of the reaction rate of the reaction path, wherein the reaction rate of the reaction path is a virtual parameter aiming at the reaction rule and is used for expressing the reaction speed under each reaction rule; inputting the value of the reaction rate of the reaction path into the reaction kinetic model for reaction simulation to obtain the molecular composition data of the product; the value is the initial value during the first reaction simulation; calculating a simulation value of a target index of a target product according to the molecular composition data of the product; and optimizing and adjusting the value of the reaction rate of the reaction path according to the difference between the simulated value and the actual value of the target index until the target reaction rate of the reaction path is obtained, wherein the difference is lower than the set threshold value.
In a second aspect, embodiments of the present disclosure provide an apparatus for optimizing a hydrocracking model. The above-mentioned optimizing apparatus includes: the system comprises a model acquisition module, an initial value acquisition module, a reaction simulation module, an index calculation module and an optimization module. The model obtaining module is used for obtaining a hydrocracking reaction kinetic model to be optimized, and the reaction kinetic model comprises: reaction rules and reaction pathway reaction rates. The initial value obtaining module is configured to obtain an initial value of a reaction rate of the reaction path, where the reaction rate of the reaction path is a virtual parameter for the reaction rule, and is used to indicate a reaction speed under each reaction rule. The reaction simulation module is used for inputting the value of the reaction rate of the reaction path into the reaction kinetic model for reaction simulation to obtain the data of the molecular composition of the product; the values are the initial values during the first reaction simulation. The index calculation module is used for calculating the analog value of the target index of the target product according to the product molecule composition data. And the optimization module is used for optimizing and adjusting the value of the reaction path reaction rate according to the difference between the simulated value and the actual value of the target index until the target reaction path reaction rate corresponding to the difference lower than a set threshold is obtained.
According to an embodiment of the present disclosure, in the method provided in the first aspect or the apparatus provided in the second aspect, the target index includes: yield and physical parameters; calculating a simulation value of a target index of the target product according to the molecular composition data of the product, wherein the simulation value comprises the following steps: determining target molecule composition data corresponding to the target product in the product molecule composition data; and calculating the simulated values of the target product for the yield and the physical property parameters according to the yield simulated value, the physical property parameter simulated value and the component content value of the target molecule composition data.
According to an embodiment of the present disclosure, in the method provided in the first aspect or the apparatus provided in the second aspect, the optimizing and adjusting the value of the reaction rate of the reaction path according to a difference between the simulated value and the actual value of the target index includes: calculating a first difference between a simulated value and an actual value of said target product for said yield; calculating a second difference between the simulated value and the actual value of the target product for the physical property parameter; calculating the weighted sum of the first difference and the second difference according to the preset weight of the target index to obtain the difference; determining whether the difference is lower than a set threshold value; and under the condition that the difference is larger than a set threshold, updating the value of the reaction path reaction rate, inputting the updated value into the reaction kinetic model to perform the next reaction simulation until the difference obtained in the Kth reaction simulation is lower than the set threshold, and taking the value of the reaction path reaction rate corresponding to the Kth reaction simulation as the target reaction path reaction rate, wherein K is larger than or equal to 2 and is an integer.
According to an embodiment of the present disclosure, in the method provided by the first aspect or the apparatus provided by the second aspect, calculating a simulated value of the target product with respect to the yield and the physical property parameter according to the yield simulated value, the physical property parameter simulated value, and the component content value of the target molecule composition data includes: carrying out weighted calculation on the yield analog value of the target molecule composition data and the corresponding component content value to obtain an analog value of the target product aiming at the yield; and performing weighted calculation on the physical property parameter simulation value of the target molecule composition data and the corresponding component content value to obtain the simulation value of the target product aiming at the physical property parameter.
According to an embodiment of the present disclosure, in the method provided in the first aspect or the apparatus provided in the second aspect, the reaction kinetic model further includes: feedstock molecular composition data. Inputting the value of the reaction rate of the reaction path into the reaction kinetics model for reaction simulation to obtain the molecular composition data of the product, which comprises the following steps: during the first reaction simulation, according to the initial value, performing reaction kinetic simulation on the raw material molecule composition data based on a corresponding reaction rule to obtain the product molecule composition data; and during the kth reaction simulation, k is more than or equal to 2 and is an integer, and according to the updated value of the reaction rate of the reaction path, performing reaction kinetic simulation on the raw material molecular composition data based on the corresponding reaction rule to obtain the product molecular composition data.
According to an embodiment of the present disclosure, in the method provided in the first aspect or the apparatus provided in the second aspect, a range of the reaction rate of the reaction path r satisfies: r is more than 0 and less than or equal to R, R represents the maximum value of the reaction rate of the reaction path, and R is more than or equal to 1.
According to an embodiment of the present disclosure, in the method provided in the first aspect or the apparatus provided in the second aspect, each of the reaction rules corresponds to 1 or more reaction paths, and the reaction rates of the reaction paths have the same value for 1 or more reaction paths under each reaction rule.
In a third aspect, embodiments of the present disclosure provide an electronic device. The electronic equipment comprises 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; and a processor for implementing the method for optimizing the hydrocracking model when executing the program stored in the memory.
In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of optimizing a hydrocracking model as described above.
The technical scheme provided by the embodiment of the disclosure at least has part or all of the following advantages:
the reaction path reaction rate is constructed in a hydrocracking reaction kinetics model, namely a virtual parameter for reaction rules, the virtual parameter is used for expressing the reaction speed and the reaction speed under each reaction rule, the reaction simulation is carried out on the hydrocracking process from a molecular layer surface, the optimization process of the reaction kinetics model is converted into the process of optimizing the value of the reaction path reaction rate in the reaction simulation process, the complicated correlation parameter is not needed to be considered, the simplification is realized, the value of the optimized reaction path reaction rate enables the hydrocracking reaction kinetics model to be close to actual production data, the accuracy of the model can be improved, meanwhile, the calculated amount of the model is reduced, and the actual production of a hydrocracking device can be better guided according to the optimized reaction kinetics model.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the related art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a method of optimizing a hydrocracking model provided in accordance with an exemplary embodiment of the present disclosure;
fig. 2 is a flowchart illustrating detailed execution of step S140 according to an exemplary embodiment of the disclosure;
fig. 3 is a flowchart illustrating detailed execution of step S150 according to an exemplary embodiment of the disclosure;
FIG. 4 is a block diagram of an optimization apparatus for a hydrocracking model provided in accordance with an exemplary embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all, embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
A first exemplary embodiment of the present disclosure provides a method of optimizing a hydrocracking model. The above optimization method may be performed by an electronic device having computing capabilities. The electronic device may store the reaction kinetics model therein, or may be capable of data communication with an apparatus in which the reaction kinetics model is stored.
FIG. 1 is a flow chart of a method of optimizing a hydrocracking model provided in accordance with an exemplary embodiment of the present disclosure.
Referring to fig. 1, an optimization method of a hydrocracking model provided by an embodiment of the present disclosure includes the following steps: s110, S120, S130, S140 and S150.
In step S110, a reaction kinetic model of hydrocracking to be optimized is obtained, the reaction kinetic model including: reaction rules and reaction pathway reaction rates.
The reaction kinetics model of the embodiments of the present disclosure constructs a virtual parameter of the reaction pathway reaction rate compared to a conventional reaction kinetics model, which has reaction kinetics parameters including various associated parameters, such as: and the conversion rate of the reaction process is constructed according to the relevant parameters, such as carbon number, pressure, temperature, catalyst and device type, and the conversion rate is between 0 and 1 and is the conversion rate of each molecular component. However, in research and development, it is found that a scheme of conversion rate including a large number of complicated correlation parameters is not suitable for the reaction kinetics of hydrocracking, on one hand, the efficiency of model simulation is low due to a large number of reaction kinetics parameters, especially, the correlation parameters are very large, and on the other hand, the difference between the simulation result of the model and actual production data is large, so that the adjustment of the parameters of the model is very inconvenient.
Therefore, the embodiment of the disclosure does not consider the internal action relationship of each associated parameter or kinetic parameter, ignores various detailed associated parameters, but simplifies the process, constructs a virtual parameter for the reaction rule, the virtual parameter can represent the reaction speed under the corresponding reaction rule, and is an integral and virtualized parameter, and the parameter is not limited to a value range of 0 to 1, and the value can be dynamically adjusted according to the actual value and the model simulation value of the hydrocracking reaction.
For example, in some embodiments, the reaction rate of the reaction pathway described above has a range r that satisfies: r is more than 0 and less than or equal to R, R represents the maximum value of the reaction rate of the reaction path, and R is more than or equal to 1. The reaction rate of the reaction path is not limited to a specific value, and in some reaction rules, the reaction rate of the reaction path may be a value greater than 1, and in other reaction rules, the reaction rate of the reaction path may be a value less than 1.
In some embodiments, the reaction rules for hydrocracking share a 8-fold large group, including 30 reaction rules.
The 30 reaction rules are listed below:
(1) Alkane: cracking and isomerization reactions occur mainly (5 reaction rules)
a. Carrying out thermal cracking reaction on the normal paraffin;
b. carrying out thermal cracking reaction on isoparaffin;
c. carrying out catalytic cracking reaction on the normal paraffin;
d. catalytic cracking reaction of isoparaffin;
e. isomerization reaction of alkane;
(2) Olefin (b): mainly undergoes the reactions of hydrosaturation, cracking and isomerization (6 reaction rules)
a. Olefin hydrogenation saturation reaction;
b. carrying out thermal cracking reaction on the normal olefins;
c. carrying out thermal cracking reaction on the isoolefine;
d. carrying out catalytic cracking reaction on normal olefins;
e. carrying out catalytic cracking reaction on isoolefins;
f. olefin isomerization reaction;
(3) Cycloalkane: mainly undergoes side chain cleavage, dealkylation and ring opening reactions (4 reaction rules)
a. Performing side chain cleavage reaction on cyclane;
b. dealkylation of cyclane;
c. ring-opening reaction of cyclane;
d. ring opening reaction of cycloalkyl;
(4) Aromatic hydrocarbons: mainly carry out hydrogenation saturation, side chain breakage and dealkylation (4 reaction rules)
a. Hydrogenation saturation reaction of monocyclic aromatic hydrocarbon;
b. hydrogenation saturation reaction of aromatic ring;
c. aromatic hydrocarbon side chain cleavage reaction;
d. dealkylation of aromatic hydrocarbon;
(5) A sulfur-containing compound: hydrodesulfurization and hydrosaturation reactions occur mainly (6 reaction rules)
a. Hydro-desulfurization reaction of thiols;
b. thioether hydrodesulfurization reaction;
c. hydrogenating and saturating thiophene;
d. carrying out hydrodesulfurization reaction on the thiophenes;
e. hydrogenation saturation reaction of benzothiophenes;
f. carrying out hydrodesulfurization reaction on benzothiophenes;
(6) Nitrogen-containing compound: mainly undergoes hydrogenation saturation and hydrogenation denitrification reaction (2 reaction rules)
a. Hydrogenation saturation reaction;
b. carrying out hydrodenitrogenation reaction;
(7) Oxygen-containing compound: the hydrodeoxygenation reaction mainly takes place (1 reaction rule)
a. Carrying out hydrodeoxygenation reaction;
(8) A metal-containing compound: the hydrodemetallization reaction mainly takes place (2 reaction rules)
a. Hydrogenation and nickel removal reaction;
b. and (4) hydrogenation and vanadium removal reaction.
In step S120, an initial value of the reaction rate of the reaction path is obtained, where the reaction rate of the reaction path is a virtual parameter for the reaction rule, and is used to indicate a reaction speed under each reaction rule.
Each of the reaction rules corresponds to 1 or more reaction paths, and the reaction rates of the reaction paths have the same value for 1 or more reaction paths under each reaction rule. That is, one reaction rule corresponds to a value of a reaction rate of one reaction path.
For a reaction rule, there may be multiple sets of raw materials (i.e., reactants), where each set of raw materials corresponds to the reaction rule to generate a corresponding set of products, and the process of reaction conversion from raw materials to products is represented as a reaction path.
The initial value of the reaction rate of the reaction path may be manually set on the electronic device in advance, or randomly generated by the electronic device.
In step S130, inputting the value of the reaction rate of the reaction path into the reaction kinetic model for reaction simulation, so as to obtain the data of the molecular composition of the product; the values are the initial values during the first reaction simulation.
According to an embodiment of the present disclosure, the reaction kinetic model further includes: feedstock molecular composition data.
In the step S130, the value of the reaction rate of the reaction path is input into the reaction kinetic model for reaction simulation, so as to obtain the data of the molecular composition of the product, including: during the first reaction simulation, according to the initial value, performing reaction kinetic simulation on the raw material molecule composition data based on a corresponding reaction rule to obtain the product molecule composition data; and during the kth reaction simulation, k is not less than 2 and is an integer, and according to the updated value of the reaction rate of the reaction path, performing reaction kinetic simulation on the raw material molecule composition data based on the corresponding reaction rule to obtain the product molecule composition data.
In step S140, a simulation value of the target index of the target product is calculated based on the product molecular composition data.
According to an embodiment of the present disclosure, the target index includes: yield = amount of target product produced/amount of raw material charged × 100%, and physical property parameters. The target product may be a part or all of the product obtained by the reaction simulation. The target product is a product common to a simulated product set obtained by a reaction kinetic model simulation of hydrocracking and an actual product set obtained by production according to an actual hydrocracking unit.
Fig. 2 is a flowchart illustrating detailed execution of step S140 according to an exemplary embodiment of the disclosure.
In some embodiments, referring to fig. 2, in the step S140, calculating a simulated value of the target index of the target product according to the product molecule composition data includes the following sub-steps: s141 and S142.
In substep S141, target molecule composition data corresponding to the target product is determined from the product molecule composition data.
In substep S142, a simulated value of the target product with respect to the yield and the physical property parameter is calculated based on the yield simulated value, the physical property parameter simulated value, and the component content value of the target molecule composition data.
In some embodiments, in the substep S142, calculating the simulated value of the target product for the yield and the physical property parameter according to the yield simulated value, the physical property parameter simulated value and the component content value of the target molecule composition data includes the following substeps:
carrying out weighted calculation on the yield analog value of the target molecule composition data and the corresponding component content value to obtain an analog value of the target product aiming at the yield;
and performing weighted calculation on the physical property parameter simulation value of the target molecule composition data and the corresponding component content value to obtain the simulation value of the target product aiming at the physical property parameter.
In some embodiments, the component content value is a volume component content value or a mass component content value.
In step S150, according to the difference between the simulated value and the actual value of the target index, the value of the reaction rate of the reaction path is optimally adjusted until the target reaction rate corresponding to the difference lower than the set threshold is obtained.
Fig. 3 is a flowchart illustrating detailed execution of step S150 according to an exemplary embodiment of the disclosure. In fig. 3, steps S130 and S140 are also illustrated in dashed boxes for clarity of illustrating the process of cyclically performing multiple reaction simulations.
According to an embodiment of the present disclosure, referring to fig. 3, in the step S150, optimizing and adjusting the value of the reaction rate of the reaction path according to a difference between the simulated value and the actual value of the target index includes the following sub-steps: s151, S152, S153, S154, S155, and S156.
In substep S151, a first difference between the simulated value and the actual value of the target product for the yield is calculated.
In substep S152, calculating a second difference between the simulated value and the actual value of the target product with respect to the physical property parameter;
in the sub-step S153, a weighted sum of the first difference and the second difference is calculated according to the preset weight of the target index, so as to obtain the difference.
In sub-step S154, it is determined whether the difference is below a set threshold.
In the sub-step S155, in the case that the determination is "no", that is, in the case that the difference is greater than the set threshold, the value of the reaction rate of the reaction path is updated.
In sub-step S156, the updated values are input into the reaction kinetics model for the next reaction simulation. The substep S156 is a start step of the loop execution.
In the next reaction simulation, executing S130, S140 and S150 until the obtained difference is lower than the set threshold value in the Kth reaction simulation, and taking the value of the reaction rate of the reaction path corresponding to the Kth reaction simulation as the target reaction rate of the reaction path, wherein K is not less than 2 and is an integer.
Referring to fig. 3, in some embodiments, the step S150 further includes a sub-step S157, and in case that the determination is "yes", i.e. in case that the difference is smaller than the set threshold, the target reaction path reaction rate is outputted. In some embodiments, referring to the dashed line box in fig. 3, while outputting the target reaction path reaction rate, a final product yield value and a product property parameter value may be output, where the final product yield value and the product property parameter value are obtained by performing a reaction simulation on a target reaction kinetic model of hydrocracking corresponding to the target reaction path reaction rate.
In the embodiment including the steps S110 to S150, a virtual parameter for the reaction rule, which is the reaction path reaction rate, is constructed in the hydrocracking reaction kinetics model, the virtual parameter is used for representing the reaction speed and the reaction speed under each reaction rule, the reaction simulation is performed on the hydrocracking process from the molecular layer surface, the optimization process of the reaction kinetics model is converted into a process for optimizing the value of the reaction path reaction rate in the reaction simulation process, no complex associated parameter needs to be considered, the simplification is realized, and the value of the optimized reaction path reaction rate enables the hydrocracking reaction kinetics model to be close to actual production data, so that the accuracy of the model can be improved, the calculated amount of the model is reduced, and the actual production of the hydrocracking device can be better guided according to the optimized reaction kinetics model.
At the same reaction rate, when the molecular composition of the raw material is changed, the corresponding product yield, properties and the like will be changed. Therefore, in actual operation, when the raw materials are changed, the device can adjust the reaction rate according to the change of the raw materials and parameters such as the adjustment of the reaction temperature, and the like, thereby obtaining the expected product yield and properties.
Therefore, in a molecular model of a hydrocracking device, the realization of effective regression of the reaction rate is crucial, and when the composition of the raw material changes, the appropriate reaction rate can be quickly obtained, so that the model is more fit with the actual production.
According to a molecular model established by molecular composition data of hydrocracking raw materials of a petrochemical company, when the model is initially established, an initial value is given to a reaction rate according to experience, and an operation result is as follows:
the number of raw material molecules: 1000 are
Number of reaction rules: 23 are provided with
Reaction quantity: 6636 there are
Reaction product molecule: 3080 there are
Model running time: 7min08s (running time on Server)
The product yield distribution: gas component: 6% (actually 4% or so), naphtha component: 26% (about 24% in practice), 32.8% (about 33% in practice) of aviation kerosene and diesel oil components, and 35.2% (about 40% in practice) of tail oil components.
The main product properties are as follows: the content of aviation kerosene aromatic hydrocarbon is 2.1% (actual 8% -11%), the cetane index of diesel oil is 82 (actual 54% -62%), the content of tail oil aromatic hydrocarbon is 9.9% (actual value is less than 5%), and the tail oil BMCI is 11.9 (actual 9% -13%).
The product yield has larger deviation than an actual value, about 5 percent, the main product property has far deviation than the actual value, and the model does not have application conditions temporarily.
Reaction rules are further screened, and a reaction rate constant regression method is applied to optimize the model (namely, the optimization method of the hydrocracking model provided by the embodiment of the disclosure is adopted to carry out optimization processing). Substituting the optimized reaction rate into the model, and obtaining the following operation results:
the number of raw material molecules is as follows: 1000 are
Number of reaction rules: 22 are provided
Reaction quantity: 2169 are provided
Reaction product molecules: 1580 of
Model runtime: 1min59s (local computer running time)
The product yield distribution: gas component: 4% (actually 4% or so), naphtha component: 23.9% (about 23% in practice), 33% (about 33% in practice) of aviation kerosene and diesel oil components, and 39.1% (about 40% in practice) of tail oil components.
The main product properties are as follows: the content of aviation kerosene aromatic hydrocarbon is 10.6% (actual 8% -11%), the cetane index of diesel oil is 59 (actual 54% -62%), the content of tail oil aromatic hydrocarbon is 0.98% (actual value is less than 5%), and the tail oil BMCI is 11.6 (actual 9% -13%).
The product yield and the product property are both in the normal value range, and the model initially has application conditions.
A second exemplary embodiment of the present disclosure provides an apparatus for optimizing a hydrocracking model.
Fig. 4 is a block diagram of an optimization apparatus for a hydrocracking model provided according to an exemplary embodiment of the present disclosure.
Referring to fig. 4, an optimization apparatus 400 of a hydrocracking model provided by an embodiment of the present disclosure includes: the system comprises a model acquisition module 401, an initial value acquisition module 402, a reaction simulation module 403, an index calculation module 404 and an optimization module 405.
The model obtaining module 401 is configured to obtain a reaction kinetic model of hydrocracking to be optimized, where the reaction kinetic model includes: reaction rules and reaction pathway reaction rates.
The initial value obtaining module 402 is configured to obtain an initial value of the reaction rate of the reaction path, where the reaction rate of the reaction path is a virtual parameter for the reaction rule, and is used to indicate a reaction speed under each reaction rule.
The reaction simulation module 403 is configured to input the value of the reaction rate of the reaction path into the reaction kinetics model to perform reaction simulation, so as to obtain product molecule composition data; the values are the initial values during the first reaction simulation.
The index calculation module 404 is configured to calculate a simulation value of a target index of a target product according to the product molecule composition data.
The optimization module 405 is configured to optimize and adjust the value of the reaction rate of the reaction path according to a difference between the simulated value and the actual value of the target index until a target reaction rate corresponding to the difference lower than a set threshold is obtained.
According to an embodiment of the present disclosure, in the optimization apparatus 400, the target index includes: yield and physical parameters. Calculating a simulation value of a target index of the target product according to the molecular composition data of the product, wherein the simulation value comprises the following steps: determining target molecule composition data corresponding to the target product in the product molecule composition data; and calculating the simulated values of the target product for the yield and the physical property parameters according to the yield simulated value, the physical property parameter simulated value and the component content value of the target molecule composition data.
According to an embodiment of the present disclosure, in the optimization apparatus 400, optimizing and adjusting the value of the reaction rate of the reaction path according to a difference between the simulated value and the actual value of the target index includes: calculating a first difference between a simulated value and an actual value of said target product for said yield; calculating a second difference between the simulated value and the actual value of the target product for the physical property parameter; calculating the weighted sum of the first difference and the second difference according to the preset weight of the target index to obtain the difference; determining whether the difference is lower than a set threshold value; and under the condition that the difference is larger than a set threshold, updating the value of the reaction path reaction rate, inputting the updated value into the reaction kinetic model to perform the next reaction simulation until the difference obtained in the Kth reaction simulation is lower than the set threshold, and taking the value of the reaction path reaction rate corresponding to the Kth reaction simulation as the target reaction path reaction rate, wherein K is larger than or equal to 2 and is an integer.
According to an embodiment of the present disclosure, in the optimization apparatus 400, calculating the simulated value of the target product with respect to the yield and the physical property parameter according to the yield simulated value, the physical property parameter simulated value, and the component content value of the target molecule composition data includes: carrying out weighted calculation on the yield simulation value of the target molecule composition data and the corresponding component content value to obtain a simulation value of the target product for the yield; and performing weighted calculation on the physical property parameter simulated value of the target molecule composition data and the corresponding component content value to obtain a simulated value of the target product for the physical property parameter.
According to an embodiment of the present disclosure, in the optimization apparatus 400, the reaction kinetic model further includes: molecular composition data of the feedstock. Inputting the value of the reaction rate of the reaction path into the reaction kinetics model for reaction simulation to obtain the molecular composition data of the product, which comprises the following steps: during the first reaction simulation, according to the initial value, performing reaction kinetic simulation on the raw material molecular composition data based on the corresponding reaction rule to obtain the product molecular composition data; and during the kth reaction simulation, k is not less than 2 and is an integer, and according to the updated value of the reaction rate of the reaction path, performing reaction kinetic simulation on the raw material molecule composition data based on the corresponding reaction rule to obtain the product molecule composition data.
According to an embodiment of the present disclosure, in the optimization apparatus 400, a range of the reaction rate r of the reaction path satisfies: r is more than 0 and less than or equal to R, R represents the maximum value of the reaction rate of the reaction path, and R is more than or equal to 1.
According to an embodiment of the present disclosure, in the optimization apparatus 400, each of the reaction rules corresponds to 1 or more reaction paths, and the reaction rates of the reaction paths have the same value for 1 or more reaction paths under each reaction rule.
For the details of this embodiment, reference may be made to the description of the first embodiment, which is not described herein again.
Any number of the functional modules included in the optimization apparatus 400 can be combined into one module to be implemented, or any one of the functional modules can be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. At least one of the functional modules included in the optimization apparatus 400 can be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or can be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or can be implemented in any one of three implementations of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the functional modules comprised by the optimization apparatus 400 can be implemented at least partly as a computer program module, which when executed can perform a corresponding function.
A third exemplary embodiment of the present disclosure provides an electronic apparatus.
Fig. 5 is a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.
Referring to fig. 5, an electronic device 500 provided in the embodiment of the present disclosure includes a processor 501, a communication interface 502, a memory 503 and a communication bus 504, where the processor 501, the communication interface 502 and the memory 503 complete communication with each other through the communication bus 504; a memory 503 for storing a computer program; the processor 501 is configured to implement the above-described method for optimizing the hydrocracking model when executing the program stored in the memory.
A fourth exemplary embodiment of the present disclosure also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of optimizing a hydrocracking model as described above.
The computer-readable storage medium may be contained in the apparatus/device described in the above embodiments; or may be present alone without being assembled into the device/apparatus. The computer-readable storage medium carries one or more programs which, when executed, implement a method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present disclosure, which enable those skilled in the art to understand or practice the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (14)
1. A method for optimizing a hydrocracking model, comprising:
obtaining a reaction kinetic model of hydrocracking to be optimized, the reaction kinetic model comprising: the reaction rule comprises reaction rules and reaction path reaction rates, wherein each reaction rule corresponds to 1 or more reaction paths, and the reaction path reaction rates have the same value aiming at 1 or more reaction paths under each reaction rule;
acquiring an initial value of the reaction rate of the reaction path, wherein the reaction rate of the reaction path is a virtual parameter aiming at the reaction rule and is used for expressing the reaction speed under each reaction rule;
inputting the value of the reaction rate of the reaction path into the reaction kinetic model for reaction simulation to obtain the molecular composition data of the product; the value is the initial value during the first reaction simulation;
calculating a simulation value of a target index of a target product according to the product molecule composition data;
and optimizing and adjusting the value of the reaction rate of the reaction path according to the difference between the simulated value and the actual value of the target index until the reaction rate of the target reaction path corresponding to the difference lower than a set threshold is obtained.
2. The optimization method according to claim 1, wherein the target metrics include: yield and physical parameters;
calculating a simulation value of a target index of a target product according to the product molecule composition data, wherein the simulation value comprises the following steps:
determining target molecule composition data corresponding to the target product in the product molecule composition data;
calculating the simulation values of the target product aiming at the yield and the physical property parameters according to the yield simulation value, the physical property parameter simulation value and the component content value of the target molecule composition data;
wherein, yield = production amount of target product/charged raw material amount × 100%.
3. The optimization method according to claim 2, wherein the optimization adjustment of the value of the reaction rate of the reaction path according to the difference between the simulated value and the actual value of the target index comprises:
calculating a first difference between a simulated value and an actual value of the target product for the yield;
calculating a second difference value between the simulated value and the actual value of the target product for the physical property parameter;
calculating the weighted sum of the first difference and the second difference according to the preset weight of the target index to obtain the difference;
determining whether the gap is below a set threshold;
and under the condition that the difference is larger than a set threshold, updating the value of the reaction path reaction rate, inputting the updated value into the reaction kinetic model to perform the next reaction simulation until the difference obtained in the Kth reaction simulation is lower than the set threshold, and taking the value of the reaction path reaction rate corresponding to the Kth reaction simulation as the target reaction path reaction rate, wherein K is more than or equal to 2 and is an integer.
4. The optimization method according to claim 2, wherein calculating the simulated values of the target product for the yield and the physical property parameter based on the yield simulated value, physical property parameter simulated value and component content value of the target molecule composition data comprises:
carrying out weighted calculation on the yield simulation value of the target molecule composition data and the corresponding component content value to obtain a simulation value of the target product aiming at the yield;
and carrying out weighted calculation on the physical property parameter simulation value of the target molecule composition data and the corresponding component content value to obtain the simulation value of the target product aiming at the physical property parameter.
5. The optimization method according to any one of claims 1 to 4, wherein the reaction kinetic model further comprises: raw material molecular composition data;
inputting the value of the reaction path reaction rate into the reaction kinetics model for reaction simulation to obtain product molecule composition data, wherein the data comprises:
during the first reaction simulation, according to the initial value, performing reaction kinetic simulation on the raw material molecule composition data based on a corresponding reaction rule to obtain the product molecule composition data;
and during the kth reaction simulation, according to the updated value of the reaction rate of the reaction path, performing reaction kinetic simulation on the raw material molecule composition data based on a corresponding reaction rule to obtain product molecule composition data, wherein k is more than or equal to 2 and is an integer.
6. The optimization method according to any one of claims 1 to 4, wherein the range of the reaction rate r of the reaction pathway satisfies the following condition: r is more than 0 and less than or equal to R, R represents the maximum value of the reaction rate of the reaction path, and R is more than or equal to 1.
7. An apparatus for optimizing a hydrocracking model, comprising:
a model obtaining module for obtaining a reaction kinetic model of hydrocracking to be optimized, the reaction kinetic model comprising: the reaction rules and the reaction path reaction rates, wherein each reaction rule corresponds to 1 or more reaction paths, and the reaction path reaction rates have the same value for 1 or more reaction paths under each reaction rule;
an initial value obtaining module, configured to obtain an initial value of a reaction rate of the reaction path, where the reaction rate of the reaction path is a virtual parameter for the reaction rule, and is used to indicate a reaction speed under each reaction rule;
the reaction simulation module is used for inputting the value of the reaction speed of the reaction path into the reaction kinetic model for reaction simulation to obtain the molecular composition data of the product; the value is the initial value during the first reaction simulation;
the index calculation module is used for calculating the analog value of the target index of the target product according to the product molecule composition data;
and the optimization module is used for optimizing and adjusting the value of the reaction path reaction rate according to the difference between the simulated value and the actual value of the target index until the target reaction path reaction rate corresponding to the difference lower than a set threshold is obtained.
8. The optimization apparatus of claim 7, wherein the target metrics comprise: yield and physical parameters;
calculating a simulation value of a target index of a target product according to the product molecule composition data, wherein the simulation value comprises the following steps:
determining target molecule composition data corresponding to the target product in the product molecule composition data;
calculating the simulation values of the target product aiming at the yield and the physical property parameters according to the yield simulation value, the physical property parameter simulation value and the component content value of the target molecule composition data;
wherein, yield = production amount of target product/charged raw material amount × 100%.
9. The optimization device according to claim 8, wherein the optimizing and adjusting the value of the reaction rate of the reaction path according to the difference between the simulated value and the actual value of the target index comprises:
calculating a first difference between a simulated value and an actual value of the target product for the yield;
calculating a second difference value between the simulated value and the actual value of the target product for the physical property parameter;
calculating the weighted sum of the first difference and the second difference according to the preset weight of the target index to obtain the difference;
determining whether the gap is below a set threshold;
and under the condition that the difference is larger than a set threshold, updating the value of the reaction path reaction rate, inputting the updated value into the reaction kinetic model to perform the next reaction simulation until the difference obtained in the Kth reaction simulation is lower than the set threshold, and taking the value of the reaction path reaction rate corresponding to the Kth reaction simulation as the target reaction path reaction rate, wherein K is larger than or equal to 2 and is an integer.
10. The optimizing apparatus according to claim 8, wherein calculating the simulated values of the target product for the yield and the physical property parameter based on the yield simulated value, physical property parameter simulated value, and component content value of the target molecule composition data includes:
carrying out weighted calculation on the yield simulation value of the target molecule composition data and the corresponding component content value to obtain a simulation value of the target product for the yield;
and carrying out weighted calculation on the physical property parameter simulation value of the target molecule composition data and the corresponding component content value to obtain the simulation value of the target product aiming at the physical property parameter.
11. The optimization device of any one of claims 7-10, wherein the reaction kinetic model further comprises: raw material molecular composition data;
inputting the value of the reaction rate of the reaction path into the reaction kinetic model for reaction simulation to obtain product molecule composition data, which comprises the following steps:
during the first reaction simulation, according to the initial value, performing reaction kinetic simulation on the raw material molecule composition data based on a corresponding reaction rule to obtain the product molecule composition data;
and during the kth reaction simulation, k is more than or equal to 2 and is an integer, and according to the updated value of the reaction rate of the reaction path, performing reaction kinetic simulation on the raw material molecular composition data based on a corresponding reaction rule to obtain the product molecular composition data.
12. The optimization device according to any one of claims 7 to 10, wherein the reaction path reaction rate has a range r that satisfies: r is more than 0 and less than or equal to R, R represents the maximum value of the reaction rate of the reaction path, and R is more than or equal to 1.
13. An electronic 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 optimization method of any one of claims 1 to 6 when executing a program stored on a memory.
14. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the optimization method of any one of claims 1 to 6.
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