CN116434854A - Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium - Google Patents

Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium Download PDF

Info

Publication number
CN116434854A
CN116434854A CN202111678844.8A CN202111678844A CN116434854A CN 116434854 A CN116434854 A CN 116434854A CN 202111678844 A CN202111678844 A CN 202111678844A CN 116434854 A CN116434854 A CN 116434854A
Authority
CN
China
Prior art keywords
molecular
product
crude oil
preset
physical properties
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202111678844.8A
Other languages
Chinese (zh)
Inventor
王杭州
纪晔
杨诗棋
王弘历
关敬军
毕治国
刘一心
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Petrochina Co Ltd
Original Assignee
Petrochina Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Petrochina Co Ltd filed Critical Petrochina Co Ltd
Priority to CN202111678844.8A priority Critical patent/CN116434854A/en
Publication of CN116434854A publication Critical patent/CN116434854A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/10—Analysis or design of chemical reactions, syntheses or processes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Theoretical Computer Science (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Tourism & Hospitality (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Quality & Reliability (AREA)
  • Computing Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Operations Research (AREA)
  • Analytical Chemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Production Of Liquid Hydrocarbon Mixture For Refining Petroleum (AREA)

Abstract

The invention relates to the technical field of petroleum processing, in particular to a molecular-level oil refining processing whole-flow optimization method, a device, equipment and a storage medium. The method comprises the following steps: according to the preset crude oil proportion, performing simulated mixing on various crude oil raw materials to obtain mixed crude oil; inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products; calculating the physical properties of each product according to the molecular composition of each product and judging whether the physical properties meet the preset physical property index requirements or not: if yes, calculating optimization targets of all products, and judging whether the optimization targets reach an optimal value or not: if yes, the current molecular level processing full-flow model is applied to the actual oil refining processing full-flow. The invention can utilize the molecular level processing full-flow model to develop optimization of crude oil processing and processing scheme of enterprises, fully combine the existing device capacity of the enterprises, excavate the resource advantage of crude oil, and realize maximization of production benefit of the enterprises.

Description

Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium
Technical Field
The invention relates to the technical field of petroleum processing, in particular to a molecular-level oil refining processing full-flow optimization method, a device, equipment and a storage medium.
Background
Along with the economic development, the demand for light fuel oil is continuously increased, and the light fuel oil such as gasoline, diesel oil and the like is used in industries such as glass, ceramics, aluminum processing and the like except the transportation industry. As the demand for light fuel oil increases, the price of the light fuel oil increases, and various kinds of gasoline with different prices can be produced in the refining of crude oil by refineries, but the refineries cannot control the kinds of the produced gasoline.
The refining production process of the oil product is very complex due to the large number of molecular species in the crude oil. To realize the maximum utilization of crude oil resources, the most important point is to realize the optimal configuration of crude oil molecules on the oil refining processing flow so as to optimize the optimization target.
A full-flow optimization method for molecular-level oil refining processing is needed at present, and the problem of low utilization rate of crude oil resources in the oil refining production process in the prior art is solved.
Disclosure of Invention
The method, the device, the equipment and the storage medium for optimizing the whole molecular-level oil refining process are provided, so that the optimization of the whole molecular-level oil refining process is realized, and the utilization rate of crude oil resources is improved.
The specific technical scheme is as follows:
in one aspect, embodiments herein provide a molecular-scale refinery process full-flow optimization method comprising,
according to the preset crude oil proportion, performing simulated mixing on various crude oils to obtain mixed crude oil;
inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule;
calculating the physical properties of each product according to the molecular composition of each product, and judging whether the physical properties of each product meet the requirements of preset physical property indexes;
when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes;
when the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value;
When the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value;
and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
On the other hand, the embodiment also provides a molecular-grade oil refining processing whole-flow optimizing device, which comprises a simulation unit, a processing unit and a processing unit, wherein the simulation unit is used for performing simulation mixing on various crude oils according to a preset crude oil proportion to obtain mixed crude oil;
the input unit is used for inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule;
the processing unit is used for calculating the physical properties of each product according to the molecular composition of each product and judging whether the physical properties of each product meet the requirement of a preset physical property index; when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes; when the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value; when the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value; and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
In another aspect, embodiments herein also provide a computer device including a memory, a processor, and a computer program stored on the memory, the processor implementing the above method when executing the computer program.
Finally, embodiments herein also provide a computer storage medium having stored thereon a computer program which, when executed by a processor of a computer device, performs the above-described method.
Compared with the prior art, the technical scheme of the invention has the following advantages: according to the embodiment of the invention, according to the preset crude oil ratio, multiple crude oil raw materials are subjected to simulated mixing to obtain mixed crude oil; inputting the molecular composition of the mixed crude oil into a preset molecular level processing full-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule; calculating the physical properties of each product according to the molecular composition of each product, and judging whether the physical properties of each product meet the preset physical property index requirements or not: when the physical properties of each product meet the preset physical property index requirements, calculating the optimization targets of all the products, and judging whether the optimization targets reach the optimal values or not: when the optimization target reaches an optimal value, applying material configuration parameters and operation parameters in a current molecular level processing full-flow model to an actual oil refining processing full-flow, wherein the material configuration parameters comprise a current crude oil ratio; when the optimization target does not reach the optimal value, the current crude oil ratio is adjusted, and the step of performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil is performed until the physical properties of each product meet the preset physical property index requirement, and the optimization target of all products reaches the optimal value, so that the molecular level processing full-flow model can be utilized to develop optimization of the processing crude oil of an enterprise and the optimization of the processing scheme, the existing device capacity of the enterprise can be fully combined, the resource advantage of the crude oil is mined, and the maximization of the production benefit of the enterprise is realized.
Drawings
In order to more clearly illustrate the embodiments herein or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments herein and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of an implementation system of a full-flow optimization method for molecular-level refinery processing according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of a full-flow optimization method for molecular-level refinery processing according to an embodiment herein;
FIG. 3 shows the process of the present example of inputting the molecular composition of the blended crude oil into a pre-determined molecular level process full flow model to obtain the molecular composition of a plurality of products;
FIG. 4 illustrates the process of calculating the molecular composition of a blended crude oil in accordance with the embodiments herein;
FIG. 5 illustrates a process for calculating overall economic benefits according to embodiments herein;
FIG. 6 is a schematic flow diagram illustrating a full-flow optimization method for molecular-level refinery processing according to an embodiment herein;
FIG. 7 is a schematic structural diagram of a molecular-level refinery process complete-flow optimizing apparatus according to an embodiment of the present disclosure;
Fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present disclosure.
[ reference numerals description ]:
101. a terminal;
102. a server;
701. a simulation unit;
702. an input unit;
703. a processing unit;
802. a computer device;
804. a processing device;
806. storing the resource;
808. a driving mechanism;
810. an input/output module;
812. an input device;
814. an output device;
816. a presentation device;
818. a graphical user interface;
820. a network interface;
822. a communication link;
824. a communication bus.
Detailed Description
The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the disclosure. All other embodiments, based on the embodiments herein, which a person of ordinary skill in the art would obtain without undue burden, are within the scope of protection herein.
It should be noted that the terms "first," "second," and the like in the description and claims herein and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or device.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
Fig. 1 is a schematic diagram of an implementation system of a full-flow optimization method for molecular-level oil refining processing in this embodiment, which may include a terminal 101 and a server 102, where a communication connection is established between the terminal 101 and the server 102, so as to enable data interaction. The terminal 101 may input the crude oil ratio to the server 102, and the server 102 may perform optimization of the whole molecular-level oil refining process after receiving the input crude oil ratio.
In this embodiment of the present disclosure, the server 102 may be an independent physical server, or may be a server cluster or a distributed system formed by a plurality of physical servers, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN, content Delivery Network), and basic cloud computing services such as big data and artificial intelligence platforms.
In an alternative embodiment, the terminal 101 may construct a library of physical property calculation models in conjunction with the server 102. In particular, the terminal 101 may include, but is not limited to, smart phones, desktop computers, tablet computers, notebook computers, smart speakers, digital assistants, augmented Reality (AR, augmented Reality)/Virtual Reality (VR) devices, smart wearable devices, and other types of electronic devices. Alternatively, the operating system running on the electronic device may include, but is not limited to, an android system, an IOS system, linux, windows, and the like.
In addition, it should be noted that, fig. 1 is only one application environment provided by the present disclosure, and in practical application, other application environments may also be included, which embodiments herein are not limited to.
In particular, embodiments herein provide a molecular-grade refinery process full-flow optimization method that can optimize a molecular-grade refinery process full-flow. FIG. 2 is a flow chart illustrating a method of optimizing a full molecular-scale refinery process in accordance with embodiments herein, wherein the process of optimizing a full molecular-scale refinery process is described, but may include more or fewer operational steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When a system or apparatus product in practice is executed, it may be executed sequentially or in parallel according to the method shown in the embodiments or the drawings. As shown in fig. 2, the method may include:
Step 201: according to the preset crude oil proportion, performing simulated mixing on various crude oils to obtain mixed crude oil;
step 202: inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule;
step 203: calculating the physical properties of each product according to the molecular composition of each product, and judging whether the physical properties of each product meet the requirements of preset physical property indexes;
step 204: when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes;
step 205: when the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value;
Step 206: when the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value;
step 207: and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
According to the method, according to the preset crude oil proportion, multiple crude oil raw materials are subjected to simulated mixing to obtain mixed crude oil; inputting the molecular composition of the mixed crude oil into a preset molecular level processing full-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule; calculating the physical properties of each product according to the molecular composition of each product, and judging whether the physical properties of each product meet the preset physical property index requirements or not: when the physical properties of each product meet the preset physical property index requirements, calculating the optimization targets of all the products, and judging whether the optimization targets reach the optimal values or not: when the optimization target reaches an optimal value, applying material configuration parameters and operation parameters in a current molecular level processing full-flow model to an actual oil refining processing full-flow, wherein the material configuration parameters comprise a current crude oil ratio; when the optimization target does not reach the optimal value, the current crude oil ratio is adjusted, and the step of performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil is performed until the physical properties of each product meet the preset physical property index requirement, and the optimization target of all products reaches the optimal value, so that the molecular level processing full-flow model can be utilized to develop optimization of the processing crude oil of an enterprise and the optimization of the processing scheme, the existing device capacity of the enterprise can be fully combined, the resource advantage of the crude oil is mined, and the maximization of the production benefit of the enterprise is realized.
In this embodiment, whether the optimization target reaches the optimal value may be determined by a global optimization algorithm of multi-start point random search, or the optimization algorithm further includes: optimization algorithms such as gradient descent algorithm, newton method, conjugate gradient method and heuristic optimization method, wherein the gradient descent algorithm comprises the following steps: the random gradient descent algorithm or the batch gradient descent algorithm can determine that the optimization target reaches an optimal value through the method.
According to one embodiment herein, as shown in fig. 3, the molecular composition of the blended crude oil is input into a pre-set molecular level process full flow model, the molecular composition of the resulting multiple products further comprising,
step 301: obtaining molecular compositions of different fractions obtained by distilling the mixed crude oil;
step 302: mixing all fractions according to a preset fraction mixing proportion to obtain mixed fractions, and obtaining the molecular composition of a predicted product according to a product prediction model of the mixed fractions and the petroleum processing device;
step 303: and according to the preset product blending proportion, blending each predicted product serving as a product blending raw material to obtain the molecular composition of the multiple products.
In the examples herein, step 301 comprises the steps of obtaining the molecular composition of the different fractions obtained by distillation of said mixed crude oil:
Taking the mixed crude oil as a feed of a fractionating device to obtain distillation range data and yield data of each fraction;
constructing a fraction cutting model based on the distillation range data and the yield data, wherein the fraction cutting model comprises temperature intervals of a fraction segment and content data corresponding to each temperature interval;
acquiring boiling point data of various single molecules in the crude oil;
and obtaining the molecular composition of the different fractions based on the boiling point data and the single molecule separation coefficient model, wherein the molecular composition of the fractions comprises the content of each single molecule in the fractions.
According to one embodiment herein, the parameters of the molecular level process full flow model include the crude oil blending ratio, the preset fraction blending ratio, the preset product blending ratio, and the operating parameters of a product prediction model of the petroleum processing plant.
In embodiments herein, adjusting the parameters of the molecular level process full flow model in step 204 may include adjusting a combination of one or more of the crude oil blending ratio, the preset fraction blending ratio, the preset product blending ratio, and the operating parameters of the product prediction model of the petroleum processing plant.
According to one embodiment herein, as shown in FIG. 4, the molecular composition of the blended crude oil described in step 202 is obtained by:
step 401: determining the molecular composition of each of said crude oils based on a pre-constructed crude oil molecular database;
step 402: and determining the molecular composition of the mixed crude oil according to the preset crude oil proportion and the molecular composition of each crude oil.
In embodiments herein, the pre-constructed crude oil molecular database includes the molecular composition of crude oil and the macroscopic physical properties of crude oil; further, the molecular composition of crude oil includes: the molecular species of crude oil and the content of each molecule; macroscopic physical properties of crude oil include: density, cloud point, pour point, aniline point, octane number, cetane number, congealing point, cold filtration point, flash point, etc.
According to one embodiment herein, step 203 calculates physical properties of each product based on the molecular composition of each product further comprises,
calculating each single-molecule physical property of each single molecule contained in each product according to a physical property calculation model trained in advance;
and calculating the physical properties of each product according to the physical properties and the content of each single molecule.
In embodiments herein, calculating the individual single molecule physical properties of each single molecule contained in each product according to a pre-trained physical property calculation model further comprises:
obtaining, for each single molecule, the number of groups of each group constituting the single molecule, and obtaining a contribution value of each group to physical properties;
inputting the number of groups of each group constituting the single molecule and the contribution value of each group to physical properties into a physical property calculation model trained in advance, and obtaining the physical properties of the single molecule output by the physical property calculation model.
In some other embodiments, before inputting the number of groups of each group constituting the single molecule and the contribution value of each of the groups to physical properties into the pre-trained physical property calculation model, the method further comprises:
comparing the number of groups constituting each group of the single molecule with the molecular information of template single molecules with known physical properties prestored in a database; the molecular information includes: the number of groups of each group constituting the template single molecule;
judging whether the template single molecule which is the same as the single molecule exists or not;
outputting physical properties of the template single molecule as physical properties of the single molecule if the template single molecule identical to the single molecule exists;
And if the template single molecule which is the same as the single molecule does not exist, performing the steps of inputting the number of groups of each group which form the single molecule and the contribution value of each group to physical properties into a pre-trained physical property calculation model.
In some other embodiments, the physical property calculation model is trained by:
constructing a physical property calculation model of single molecules;
obtaining the number of groups of each group constituting a single molecule of the sample; the physical properties of the sample single molecule are known;
inputting the number of groups of each group contained in the sample single molecule into the physical property calculation model;
obtaining the predicted physical property of the sample single molecule output by the physical property calculation model;
if the deviation value between the predicted physical property and the known physical property is smaller than a preset deviation threshold value, judging that the physical property calculation model converges, acquiring a contribution value corresponding to each group in the converged physical property calculation model, and storing the contribution value as a contribution value of the group to the physical property;
and if the deviation value between the predicted physical property and the known physical property is greater than or equal to the deviation threshold value, adjusting the contribution value corresponding to each group in the physical property calculation model until the physical property calculation model converges.
In some embodiments, the building a physical property calculation model of a single molecule comprises:
establishing a physical property calculation model shown in a formula (1):
Figure BDA0003453339960000091
wherein f is the physical property of the sample single molecule, n i The number of groups, Δf, being the i-th group i The value of the contribution of the i-th group to the physical properties is defined as a correlation constant.
In some embodiments, the obtaining the number of groups of each group comprising a single molecule of the sample comprises:
determining a primary group, the number of groups of the primary group, a multi-stage group and the number of groups of the multi-stage group in all groups of the single molecule of the sample;
all groups constituting a single molecule are taken as primary groups;
a plurality of groups which are simultaneously present and contribute to the same physical property together are used as a multi-stage group, and the number of the plurality of groups is used as a grade of the multi-stage group.
In some embodiments, a physical property calculation model is built as shown in equation (2):
Figure BDA0003453339960000092
wherein f is the physical property of the sample single molecule, m 1i The number of groups, Δf, being the i-th group in the primary groups 1i Is the contribution value of the ith group in the primary groups to physical properties, m 2j The number of groups, Δf, being the j-th group in the secondary groups 2j The contribution value of the j-th group in the secondary groups to physical properties; m is m Nl The number of groups, Δf, being the first group in the N-stage groups Nl The contribution value of the first group in the N-level groups to physical properties; a is a correlation constant; n is a positive integer greater than or equal to 2.
In some embodiments, the obtaining the number of groups of each group comprising the single molecule comprises:
determining a primary group, the number of groups of the primary group, a multi-stage group and the number of groups of the multi-stage group in all groups of the single molecule;
all groups constituting a single molecule are taken as primary groups;
a plurality of groups which are simultaneously present and contribute to the same physical property together are used as a multi-stage group, and the number of the plurality of groups is used as a grade of the multi-stage group.
In some embodiments, the physical properties of the single molecule include: the boiling point of the single molecule;
the method for inputting the number of groups of each group constituting the single molecule and the contribution value of each group to physical properties into a physical property calculation model trained in advance to obtain physical properties of the single molecule output by the physical property calculation model comprises the steps of:
the formula for calculating the boiling point of the single molecule according to the physical property calculation model is (3):
Figure BDA0003453339960000101
wherein T is the boiling point of the single molecule, SOL is a single molecule vector converted according to the number of GROUPs constituting each GROUP of the single molecule, GROUP 11 GROUP is a first contribution vector obtained by converting the contribution value of the primary GROUP to the boiling point 12 GROUP is a second contribution vector obtained by conversion of the contribution value of the secondary GROUP to the boiling point 1N Numh is the number of atoms except hydrogen atoms in single molecules, d is a first preset constant, b is a second preset constant and c is a third preset constant; and N is a positive integer greater than or equal to 2.
In some embodiments, the physical properties of the single molecule include: density of single molecules;
the method for inputting the number of groups of each group constituting the single molecule and the contribution value of each group to physical properties into a physical property calculation model trained in advance to obtain physical properties of the single molecule output by the physical property calculation model comprises the steps of:
the formula for calculating the density of the single molecule according to the physical property calculation model is (4):
Figure BDA0003453339960000102
wherein D is the density of the single molecule, SOL is a single molecule vector converted from the number of GROUPs of each GROUP constituting the single molecule, GROUP 21 GROUP is the n+1-th contribution vector obtained by converting the contribution of the primary GROUP to the density 22 GROUP is an n+2-th contribution vector obtained by converting the contribution of the secondary GROUP to the density 2N The 2N contribution value vector is obtained by converting the contribution value of the N-level group to the density, and e is a fourth preset constant; and N is a positive integer greater than or equal to 2.
In some embodiments, the physical properties of the single molecule include: octane number of single molecule;
the method for inputting the number of groups of each group constituting the single molecule and the contribution value of each group to physical properties into a physical property calculation model trained in advance to obtain physical properties of the single molecule output by the physical property calculation model comprises the steps of:
the formula for calculating the octane number of the single molecule according to the physical property calculation model is (5):
X＝SOL×GROUP 31 +SOL×GROUP 32 +......+SOL×GROUP 3N +h (5)
wherein X is the octane number of the single molecule, SOL is a single molecule vector obtained by conversion according to the number of GROUPs of each GROUP constituting the single molecule 31 GROUP is a 2N+1-th contribution vector obtained by converting the contribution value of the primary GROUP to the octane number 32 GROUP is a 2N+2-th contribution vector obtained by converting the contribution value of the secondary GROUP to the octane number 3N The 3N contribution value vector is obtained by converting the contribution value of the N-level group to the octane value; the N is a positive integer greater than or equal to 2; h is a fifth preset constant.
In some embodiments, the physical properties of the product include: research octane number, motor octane number, rad vapor pressure, enna distillation range, density, benzene volume fraction, aromatic volume fraction, olefin volume fraction, oxygen mass fraction, and sulfur mass fraction.
According to one embodiment herein, determining whether the physical properties of each product meet the requirements of the predetermined physical property index further comprises,
judging whether the physical properties of each product meet any one preset standard in a preset standard set;
if the physical properties of each product meet any one preset standard in the preset standard set, judging that the physical properties of each product meet the requirements of preset physical property indexes;
if the physical properties of each product do not meet any preset standard in the preset standard set, judging that the physical properties of each product do not meet the requirements of preset physical property indexes.
According to one embodiment herein, the set of preset criteria is obtained by:
obtaining standards of oil products of different brands;
and taking the standard of each brand of oil product as a preset standard to form the preset standard set.
According to one embodiment herein, the optimization objective includes at least one of total economic benefit, crude oil remaining stock quantity, or product quality excess value.
According to one embodiment herein, as shown in fig. 5, the total economic benefit is calculated by the following steps:
step 501: acquiring the product price of each product and the yield of each product;
step 502: calculating the product benefit of each product according to the yield of each product and the product price of each product;
step 503: accumulating the product benefits of each product to obtain accumulated benefits;
step 504: acquiring the price of each crude oil and the operation cost of each petroleum processing device;
step 505: and subtracting the prices of all the crude oils and the operation cost of all the petroleum processing devices from the accumulated benefits to obtain the total economic benefit.
According to one embodiment herein, the crude oil remaining stock is calculated by the steps of:
obtaining the processing amount and the current stock amount of each crude oil;
subtracting the processing amount from the current stock amount to obtain the crude oil residual stock amount.
According to one embodiment herein, the product quality excess value is calculated by:
taking the difference between the physical property of the product and the preset physical property index requirement as a product quality excess value, wherein the physical property of the product is calculated by calculating each single molecular physical property of each single molecule contained in the product.
According to one embodiment herein, when the optimization objective is the total economic, step 205 determines whether the optimization objective reaches an optimal value, including:
judging whether the total economic benefit reaches the maximum value:
and when the total economic benefit reaches the maximum value, judging that the optimization target reaches the optimal value.
According to one embodiment herein, when the optimization objective is the crude oil remaining inventory, step 205 determines whether the optimization objective reaches an optimal value, including:
judging whether the residual stock quantity of the crude oil reaches a minimum value:
and when the residual stock quantity of the crude oil reaches the minimum value, judging that the optimization target reaches an optimal value.
According to one embodiment herein, when the optimization objective is the product quality excess value, step 205 determines whether the optimization objective reaches an optimal value, including:
judging whether the product quality excess value reaches a minimum value or not:
and when the product quality excess value reaches the minimum value, judging that the optimization target reaches the optimal value.
In some other embodiments, before the calculating the optimization objectives for all products, the method further comprises:
obtaining the ratio of the yield of the target product in all products;
Judging whether the duty ratio accords with a preset duty ratio interval or not;
if the occupation ratio accords with the preset occupation ratio interval, executing the step of calculating the optimization targets of all the products;
and if the ratio does not accord with the preset ratio interval, adjusting the preset product blending proportion, blending the predicted products serving as product blending raw materials according to the adjusted product blending proportion, and obtaining the molecular composition of a plurality of groups of products again until the ratio accords with the preset ratio interval.
In some other embodiments, before the calculating the optimization objectives for all products, the method further comprises:
obtaining consumption of each group of crude oil raw materials;
confirming the consumption of the target crude oil raw materials according to the consumption of each group of crude oil raw materials;
judging whether the consumption of the target crude oil raw material accords with a preset consumption interval or not;
if the consumption of the target crude oil raw material accords with a preset consumption interval, executing the step of calculating the optimization targets of all products;
if the consumption of the target crude oil raw material does not accord with the preset consumption interval, adjusting the preset crude oil ratio, performing simulated mixing on the crude oil raw materials according to the adjusted crude oil ratio, and obtaining mixed crude oil again until the consumption of the target crude oil raw material accords with the preset consumption interval.
FIG. 6 is a schematic flow chart of the process for optimizing a full flow of a molecular refinery process according to the embodiments herein, wherein the steps of optimizing a full flow of a molecular refinery process are described. It should be noted that, the steps and sequences described in the present figure are not the only steps and sequences for constructing the physical property calculation model library in the embodiment herein, and other steps and sequences for optimizing the whole process of molecular-level oil refining can be obtained by those skilled in the art from the description of the present figure, and the embodiment herein is not limited.
Specifically, the steps of optimizing the whole molecular-level oil refining process flow include:
step 601: according to the preset crude oil proportion, performing simulated mixing on various crude oil raw materials to obtain mixed crude oil;
step 602: inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products;
in this step, the molecular composition includes the molecular species and the content of each molecule, and the product includes, but is not limited to, a final product such as gasoline and diesel. The molecular composition of the mixed crude oil is obtained by the following steps:
determining the molecular composition of each crude oil feedstock based on a pre-constructed crude oil molecular database; wherein the pre-constructed crude oil molecular database comprises the molecular composition of crude oil and the macroscopic physical property of crude oil; further, the molecular composition of crude oil includes: the molecular species of crude oil and the content of each molecule; macroscopic physical properties of crude oil include: density, cloud point, pour point, aniline point, octane number, cetane number, congealing point, cold filtration point, flash point, etc.;
And determining the molecular composition of the mixed crude oil according to the preset crude oil ratio and the molecular composition of each crude oil raw material.
Step 603: calculating physical properties of each product according to the molecular composition of each product;
step 604: judging whether the physical properties of each product meet the preset physical property index requirements or not:
if yes, go to step 605;
if not, go to step 607;
in this step, the calculating physical properties of each product according to the molecular composition of each product includes:
calculating each single-molecule physical property of each single molecule contained in each product based on a physical property calculation model trained in advance;
according to the preset mixing rule of the physical properties of each mixture, calculating the physical properties of each product according to the physical properties and the content of each single molecule.
Step 605: calculating an optimization target of a molecular level processing whole-flow model;
step 606: judging whether the optimization target reaches an optimal value or not:
if yes, go to step 608;
if not, go to step 609;
in this step, the optimization objective includes at least one of total economic benefit, crude oil remaining stock quantity, or product quality excess value.
In this step, it may be determined whether the optimization target reaches an optimal value by a global optimization algorithm of multi-origin random search, or the optimization algorithm further includes: optimization algorithms such as gradient descent algorithm, newton method, conjugate gradient method and heuristic optimization method, wherein the gradient descent algorithm comprises the following steps: the random gradient descent algorithm or the batch gradient descent algorithm can determine that the optimization target reaches an optimal value through the method.
Step 607: adjusting parameters of a current molecular level processing full-flow model, and taking the adjusted molecular level processing full-flow model as a preset molecular level processing full-flow model;
in this step, the molecular level process full flow model parameters include at least one of the crude oil blending ratio, the fraction blending ratio of the petroleum processing plant feed, the operating parameters in the product prediction model, and the product blending ratio. Then, returning to the step 602 until the physical properties of each product meet the preset physical property index requirements
Step 608: the material configuration parameters and the operation parameters in the current molecular level processing full-flow model are applied to the actual oil refining processing full-flow;
in this step, the material configuration parameters include a current crude oil proportioning.
Step 609: adjusting the current crude oil ratio, and taking the adjusted crude oil ratio as a preset crude oil ratio;
after this step, the process returns to step 601 until the physical properties of each product meet the preset physical property index requirements, and the optimization objective reaches the optimal value.
Based on the same inventive concept, the embodiments herein also provide a molecular-level oil refining process full-flow optimizing apparatus, as shown in fig. 7, comprising,
The simulation unit 701 is used for performing simulation mixing on a plurality of crude oils according to a preset crude oil ratio to obtain mixed crude oil;
an input unit 702, configured to input the molecular composition of the mixed crude oil into a preset molecular level processing full-flow model, so as to obtain molecular compositions of multiple products, where the molecular compositions include a molecular type and a content of each molecule;
a processing unit 703, configured to calculate physical properties of each product according to a molecular composition of each product, and determine whether the physical properties of each product meet a requirement of a preset physical property index; when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes; when the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value; when the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value; and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
The beneficial effects obtained by the device are consistent with those obtained by the method, and the embodiments of the present disclosure are not repeated.
It should be noted that this embodiment is only one preferred embodiment of the present invention, and all other forms of modification which can be made by those skilled in the art without the inventive effort should fall within the scope of the present disclosure. According to the calling method of the physical property calculation model library, which is provided by the embodiment of the invention, required physical property calculation models can be conveniently and rapidly obtained from the constructed physical property calculation model library, the physical properties of products are predicted, and the working efficiency of the performance analysis of the petrochemical industry products is improved. In addition, the physical property calculation model library provided by the embodiment of the invention is convenient for various professional petrochemical industry researchers to build, maintain and manage in various stages, and can provide powerful technical support for the scientific and rapid simulation of the petrochemical industry.
Fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present disclosure, where the apparatus may be a computer device according to the present disclosure, and perform the method of the present disclosure. The computer device 802 may include one or more processing devices 804, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 802 may also include any storage resources 806 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage resources 806 may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage resource may store information using any technology. Further, any storage resource may provide volatile or non-volatile retention of information. Further, any storage resources may represent fixed or removable components of computer device 802. In one case, the computer device 802 may perform any of the operations of the associated instructions when the processing device 804 executes the associated instructions stored in any storage resource or combination of storage resources. The computer device 802 also includes one or more drive mechanisms 808, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like, for interacting with any storage resources.
The computer device 802 may also include an input/output module 810 (I/O) for receiving various inputs (via an input device 812) and for providing various outputs (via an output device 814). One particular output mechanism may include a presentation device 816 and an associated Graphical User Interface (GUI) 818. In other embodiments, input/output module 810 (I/O), input device 812, and output device 814 may not be included, but merely as a computer device in a network. The computer device 802 may also include one or more network interfaces 820 for exchanging data with other devices via one or more communication links 822. One or more communications buses 824 couple the above-described components together.
The communication link 822 may be implemented in any manner, such as, for example, through a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. Communication link 822 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.
Corresponding to the method in fig. 2 to 6, embodiments herein also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the above steps.
Embodiments herein also provide a computer readable instruction wherein the program therein causes the processor to perform the method as shown in fig. 2 to 6 when the processor executes the instruction.
It should be understood that, in the various embodiments herein, the sequence number of each process described above does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments herein.
It should also be understood that in embodiments herein, the term "and/or" is merely one relationship that describes an associated object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the elements may be selected according to actual needs to achieve the objectives of the embodiments herein.
In addition, each functional unit in the embodiments herein may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions herein are essentially or portions contributing to the prior art, or all or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments herein. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Specific examples are set forth herein to illustrate the principles and embodiments herein and are merely illustrative of the methods herein and their core ideas; also, as will be apparent to those of ordinary skill in the art in light of the teachings herein, many variations are possible in the specific embodiments and in the scope of use, and nothing in this specification should be construed as a limitation on the invention.

Claims (18)

1. A full-flow optimization method for molecular-level oil refining processing is characterized in that the method comprises the following steps of,
according to the preset crude oil proportion, performing simulated mixing on various crude oils to obtain mixed crude oil;
inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule;
calculating the physical properties of each product according to the molecular composition of each product, and judging whether the physical properties of each product meet the requirements of preset physical property indexes;
when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes;
When the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value;
when the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value;
and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
2. The molecular-grade oil refining process complete-flow optimization method according to claim 1, wherein inputting the molecular composition of the mixed crude oil into a preset molecular-grade process complete-flow model to obtain the molecular composition of a plurality of products further comprises,
obtaining molecular compositions of different fractions obtained by distilling the mixed crude oil;
mixing all fractions according to a preset fraction mixing proportion to obtain mixed fractions, and obtaining the molecular composition of a predicted product according to a product prediction model of the mixed fractions and the petroleum processing device;
And according to the preset product blending proportion, blending each predicted product serving as a product blending raw material to obtain the molecular composition of the multiple products.
3. The method for optimizing a whole process of molecular-grade refining process according to claim 2, wherein obtaining molecular compositions of different fractions obtained by distilling the mixed crude oil further comprises,
taking the mixed crude oil as a feed of a fractionating device to obtain distillation range data and yield data of each fraction;
constructing a fraction cutting model based on the distillation range data and the yield data, wherein the fraction cutting model comprises temperature intervals of a fraction segment and content data corresponding to each temperature interval;
acquiring boiling point data of various single molecules in the crude oil;
and obtaining the molecular composition of the different fractions based on the boiling point data and the single molecule separation coefficient model, wherein the molecular composition of the fractions comprises the content of each single molecule in the fractions.
4. The molecular level refinery process complete process optimization method of claim 2, wherein the parameters of the molecular level process complete process model comprise the crude oil blending ratio, the preset fraction blending ratio, the preset product blending ratio, and the operating parameters of the product prediction model of the petroleum processing plant.
5. The full-flow optimization method for molecular-grade oil refining process according to claim 1, wherein the molecular composition of the mixed crude oil is obtained by the following steps:
determining the molecular composition of each of said crude oils based on a pre-constructed crude oil molecular database;
and determining the molecular composition of the mixed crude oil according to the preset crude oil proportion and the molecular composition of each crude oil.
6. The full-flow optimization method for molecular-scale refinery processing of claim 1, wherein calculating physical properties of each product according to the molecular composition of each product further comprises,
calculating each single-molecule physical property of each single molecule contained in each product according to a physical property calculation model trained in advance;
and calculating the physical properties of each product according to the physical properties and the content of each single molecule.
7. The method of claim 1, wherein determining whether the physical properties of each product meet the predetermined physical property index further comprises,
judging whether the physical properties of each product meet any one preset standard in a preset standard set;
If the physical properties of each product meet any one preset standard in the preset standard set, judging that the physical properties of each product meet the requirements of preset physical property indexes;
if the physical properties of each product do not meet any preset standard in the preset standard set, judging that the physical properties of each product do not meet the requirements of preset physical property indexes.
8. The full-flow optimization method for molecular-level oil refining processing according to claim 7, wherein the preset standard set is obtained by the following steps:
obtaining standards of oil products of different brands;
and taking the standard of each brand of oil product as a preset standard to form the preset standard set.
9. The molecular-grade refinery process complete process optimization method of claim 1, wherein the optimization objectives comprise at least one of total economic benefit, crude residual inventory, or product quality excess values.
10. The full-flow optimization method of molecular-grade oil refining processing according to claim 9, wherein the total economic benefit is calculated by the following steps:
acquiring the product price of each product and the yield of each product;
Calculating the product benefit of each product according to the yield of each product and the product price of each product;
accumulating the product benefits of each product to obtain accumulated benefits;
acquiring the price of each crude oil and the operation cost of each petroleum processing device;
and subtracting the prices of all the crude oils and the operation cost of all the petroleum processing devices from the accumulated benefits to obtain the total economic benefit.
11. The full-flow optimization method for molecular-level oil refining process according to claim 9, wherein the residual stock quantity of crude oil is calculated by the steps of:
obtaining the processing amount and the current stock amount of each crude oil;
subtracting the processing amount from the current stock amount to obtain the crude oil residual stock amount.
12. The full-flow optimization method for molecular-level oil refining processing according to claim 9, wherein the product mass surplus value is calculated by the following steps:
taking the difference between the physical property of the product and the preset physical property index requirement as a product quality excess value, wherein the physical property of the product is calculated by calculating each single molecular physical property of each single molecule contained in the product.
13. The full-flow optimization method for molecular-level oil refining process according to claim 9, wherein when the optimization objective is the total economic benefit, determining whether the optimization objective reaches an optimal value comprises:
judging whether the total economic benefit reaches the maximum value:
and when the total economic benefit reaches the maximum value, judging that the optimization target reaches the optimal value.
14. The molecular-level refinery process complete process optimization method of claim 9, wherein when the optimization objective is the residual inventory of crude oil, determining whether the optimization objective reaches an optimal value comprises:
judging whether the residual stock quantity of the crude oil reaches a minimum value:
and when the residual stock quantity of the crude oil reaches the minimum value, judging that the optimization target reaches an optimal value.
15. The full-flow optimization method for molecular-level oil refining process according to claim 9, wherein when the optimization target is the product mass excess value, determining whether the optimization target reaches an optimal value comprises:
judging whether the product quality excess value reaches a minimum value or not:
and when the product quality excess value reaches the minimum value, judging that the optimization target reaches the optimal value.
16. A molecular-level refinery processing full-process optimization device, characterized in that the device comprises:
the simulation unit is used for performing simulation mixing on various crude oils according to a preset crude oil ratio to obtain mixed crude oil;
the input unit is used for inputting the molecular composition of the mixed crude oil into a preset molecular level processing whole-flow model to obtain the molecular composition of various products, wherein the molecular composition comprises molecular types and the content of each molecule;
the processing unit is used for calculating the physical properties of each product according to the molecular composition of each product and judging whether the physical properties of each product meet the requirement of a preset physical property index; when the physical properties of any one of the products do not meet the requirements of the preset physical property indexes, adjusting the parameters of the molecular level processing full-flow model, and executing the step of inputting the molecular composition of the mixed crude oil into the preset molecular level processing full-flow model according to the adjusted molecular level processing full-flow model to obtain the molecular composition of a plurality of products until the physical properties of each product meet the requirements of the preset physical property indexes; when the physical properties of each product meet the preset physical property index requirements, calculating an optimization target of the molecular level processing whole-flow model, and judging whether the optimization target reaches an optimal value; when the optimization target does not reach the optimal value, adjusting the crude oil ratio, and performing simulated mixing on various crude oil raw materials according to the adjusted crude oil ratio to obtain mixed crude oil until the physical properties of each product meet the preset physical property index requirement, wherein the optimization target reaches the optimal value; and when the optimization target reaches the optimal value, applying the parameters of the crude oil ratio and the molecular level processing full-flow model to the actual oil refining processing full-flow.
17. A computer device comprising a memory, a processor, and a computer program stored on the memory, characterized in that the processor implements the method of any of claims 1 to 15 when executing the computer program.
18. A computer storage medium having stored thereon computer instructions, wherein the computer program, when executed by a processor of a computer device, performs the method of any of claims 1 to 15.
CN202111678844.8A 2021-12-31 2021-12-31 Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium Pending CN116434854A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111678844.8A CN116434854A (en) 2021-12-31 2021-12-31 Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111678844.8A CN116434854A (en) 2021-12-31 2021-12-31 Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN116434854A true CN116434854A (en) 2023-07-14

Family

ID=87083743

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111678844.8A Pending CN116434854A (en) 2021-12-31 2021-12-31 Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN116434854A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117391424A (en) * 2023-12-11 2024-01-12 延安随缘科技发展有限公司 Preparation node combination method and system based on lubricating oil

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117391424A (en) * 2023-12-11 2024-01-12 延安随缘科技发展有限公司 Preparation node combination method and system based on lubricating oil
CN117391424B (en) * 2023-12-11 2024-03-08 延安随缘科技发展有限公司 Preparation node combination method and system based on lubricating oil

Similar Documents

Publication Publication Date Title
CN111899795B (en) Molecular-level oil refining processing full-flow optimization method, device and system and storage medium
CN111899793B (en) Real-time optimization method, device and system for molecular-level device and storage medium
Moro et al. Mixed-integer programming approach for short-term crude oil scheduling
Chen et al. Optimization of short-time gasoline blending scheduling problem with a DNA based hybrid genetic algorithm
Cerdá et al. Optimizing gasoline recipes and blending operations using nonlinear blend models
CN116434854A (en) Molecular-level oil refining processing full-flow optimization method, device, equipment and storage medium
CN111892938B (en) Method, system, device and storage medium for determining molecular composition of crude oil
Zhang et al. Efficient two-level hybrid algorithm for the refinery production scheduling problem involving operational transitions
CN110378532B (en) Scientific research topic state prediction method based on random tree
CN111892960B (en) Gasoline blending method, system, equipment and storage medium
Morisse et al. LRez: a C++ API and toolkit for analyzing and managing Linked-Reads data
CN116410771B (en) Crude oil blending optimization method, device, equipment and storage medium
CN116410772B (en) Crude oil distillation cutting method, device, equipment and storage medium
Ray et al. Feedstock for the petrochemical industry
Gubitoso et al. A planning model for the optimal production of a real-world ethylene plant
CN110413231A (en) The data-optimized storage method of inexpensive high availability under a kind of cloudy environment
Boucheikhchoukh et al. Optimization of a multiperiod refinery planning problem under uncertainty
Al-Shammari et al. Uncertainty analysis for refinery production planning
Pinto-Varela et al. Design and scheduling of periodic multipurpose batch plants under uncertainty
CN116013425B (en) Molecular level refining process model construction method and device and storage medium
CN116417075A (en) Product prediction model optimization method and device of catalytic gasoline hydrogenation device
WO2023193172A1 (en) Automated, configurable, rigorous reversible lumping for chemical separations
Xue et al. Crude oil distillation optimization using surrogate-aided constrained evolutionary optimization
Kumar et al. Transformer-based tool recommendation system in Galaxy
Wen et al. Pattern-based personalized workflow fragment discovery

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination