Crude oil industry chain overall optimization scene strategy generation method and device

Abstract

The invention relates to the technical field of crude oil processing, in particular to a scene strategy generation method and device for overall optimization of a crude oil industry chain. The scene strategy generation method for overall optimization of the crude oil industrial chain comprises the following steps: setting a plurality of scene templates according to various preset scenes of production and operation of the crude oil industrial chain, and selecting one of the plurality of scene templates as a target scene template; wherein each scene template comprises one or a combination of more of information of partial parameters and information of partial constraints in a pre-constructed crude oil industry chain overall optimization model; wherein the constraint is an upper limit or a lower limit of a constraint equation; according to the target scene template, updating the crude oil industry chain overall optimization model, and generating a target crude oil industry chain overall optimization model; and solving the target crude oil industry chain overall optimization model to obtain a scene strategy of crude oil industry chain overall optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of crude oil processing, and in particular to a scenario strategy generation method and device for overall optimization of the crude oil industry chain. Background Art

[0002] Due to the large fluctuations in market prices and demand faced by the crude oil industry chain, users need to generate business strategies under various market scenarios through the overall optimization model of the crude oil industry chain. In related technologies, in order to obtain different crude oil industry chain scenario strategies, users need to change the configuration of the crude oil industry chain optimization model item by item according to different scenario assumptions and debug the modified model.

[0003] The crude oil industry chain optimization model is based on a large-scale mathematical programming model, covering all aspects of "production, refining, sales, transportation, storage and trade", including many variables, parameters and constraints, and the input and output data of the model are very large. In addition, the optimization of the crude oil industry chain is highly professional, requiring personnel who are familiar with both the crude oil industry chain business and the mathematical programming model operation to accurately complete the adjustment of the crude oil industry chain optimization model.

[0004] Therefore, how to efficiently and conveniently obtain scenario strategies for overall optimization of the crude oil industry chain under multiple scenarios is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present application provides a scenario strategy generation method and device for overall optimization of the crude oil industry chain, which is used to efficiently and conveniently obtain scenario strategies for overall optimization of the crude oil industry chain under multiple scenarios.

[0006] In a first aspect, the present application provides a method for generating scenario strategies for overall optimization of a crude oil industry chain, the method comprising: setting a number of scenario templates according to various preset scenarios for production and operation of the crude oil industry chain, and selecting one of the scenario templates as a target scenario template; wherein each scenario template contains one or more combinations of information on some parameters and some constraints in a pre-constructed overall optimization model of the crude oil industry chain; wherein the constraint is an upper limit or a lower limit of a constraint equation; according to the target scenario template, updating the overall optimization model of the crude oil industry chain to generate a target overall optimization model of the crude oil industry chain; solving the target overall optimization model of the crude oil industry chain to obtain a scenario strategy for overall optimization of the crude oil industry chain.

[0007] Specifically, according to the background technology, the technical problem to be solved by this application is: how to enable users (non-technical personnel) to efficiently and conveniently obtain scenario strategies for overall optimization of the crude oil industry chain under multiple scenarios. Therefore, the scenario templates should be set by technical personnel, and the templates should be selected by users.

[0008] The user can adjust the set scenario template (for example, modify a certain constraint value), and this situation is not reflected in the claims.

[0009] Furthermore, the multiple scenario templates are generated in the following manner: for multiple preset scenarios in the production and operation of the crude oil industry chain, the following operations are performed: according to the preset scenarios, the parameter information and constraint information contained in the scenario templates are determined.

[0010] Furthermore, updating the overall optimization model of the crude oil industry chain according to the target scenario template includes: determining the parameters to be adjusted in the overall optimization model of the crude oil industry chain according to the information of the parameters contained in the target scenario template; updating the values ​​of the parameters to be adjusted according to the information of the parameters; determining the constraints to be adjusted in the overall optimization model of the crude oil industry chain according to the information of the constraints contained in the target scenario template; and updating the values ​​of the constraints to be adjusted according to the information of the constraints.

[0011] Furthermore, the parameter information includes the encoding of the parameter; wherein the encoding of the parameter is obtained according to the classification rules of the parameter set of the overall optimization model of the crude oil industry chain; determining the parameters to be adjusted in the overall optimization model of the crude oil industry chain based on the parameter information contained in the target scenario template includes: selecting a parameter whose type matches the encoding of the parameter as the parameter to be adjusted from the parameter set of the overall optimization model of the crude oil industry chain.

[0012] Furthermore, the constraint information includes the encoding of the constraint; wherein, the encoding of the constraint is obtained according to the classification rules in the constraint set of the overall optimization model of the crude oil industry chain; determining the constraints to be adjusted in the overall optimization model of the crude oil industry chain based on the constraint information contained in the target scenario template includes: selecting a constraint whose type matches the encoding of the constraint as the constraint to be adjusted from the constraint set of the overall optimization model of the crude oil industry chain.

[0013] Furthermore, the parameter information also includes an adjustment value of the parameter; updating the value of the parameter to be adjusted based on the parameter information includes: using a database operating language to update the value of the parameter to be adjusted in a target database based on the adjustment value of the parameter; wherein the parameter set of the overall optimization model of the crude oil industry chain is stored in the target database.

[0014] Furthermore, the constraint information also includes an adjustment value of the constraint; updating the value of the constraint to be adjusted based on the constraint information includes: using a database operating language to update the value of the constraint to be adjusted in the target database based on the adjustment value of the constraint; wherein the constraint set of the overall optimization model of the crude oil industry chain is stored in the target database.

[0015] In a second aspect, the present application provides a scenario strategy generation device for overall optimization of the crude oil industry chain, the device comprising: a first acquisition module, used to set a number of scenario templates according to various preset scenarios of production and operation of the crude oil industry chain, and select one of the scenario templates as a target scenario template; wherein each scenario template contains one or more combinations of information on some parameters and some constraints in a pre-constructed overall optimization model of the crude oil industry chain; wherein the constraint is an upper limit or a lower limit of a constraint equation; a generation module, used to update the overall optimization model of the crude oil industry chain according to the target scenario template, and generate a target overall optimization model of the crude oil industry chain; a second acquisition module, used to solve the target overall optimization model of the crude oil industry chain, and obtain a scenario strategy for overall optimization of the crude oil industry chain.

[0016] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the method described above when running the program.

[0017] In a fourth aspect, the present application provides a storage medium for storing a computer-readable program, wherein when the computer-readable program is executed, the method described above is executed.

[0018] The above technical solution provided by the embodiment of the present application has at least the following advantages compared with the prior art:

[0019] The present invention sets several scenario templates according to various preset scenarios of production and operation of the crude oil industry chain, and selects one of the scenario templates as the target scenario template; wherein each scenario template contains one or more combinations of information of some parameters and some constraints in the pre-constructed overall optimization model of the crude oil industry chain; according to the target scenario template, the overall optimization model of the crude oil industry chain is updated to generate the overall optimization model of the target crude oil industry chain; the overall optimization model of the target crude oil industry chain is solved to obtain the scenario strategy of the overall optimization of the crude oil industry chain. Thus, the scenario strategy of the overall optimization of the crude oil industry chain under multiple scenarios can be obtained efficiently and conveniently. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present application will be further described in the form of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0021] Figure 1 is an exemplary flow chart of a scenario strategy generation method for overall optimization of the crude oil industry chain according to some embodiments of the present application;

[0022] Figure 2is an exemplary flow chart of a method for updating an overall optimization model of a crude oil industry chain according to a target scenario template as shown in some embodiments of the present application;

[0023] Figure 3 is an exemplary schematic diagram of multiple scenario templates according to some embodiments of the present application;

[0024] Figure 4 is an exemplary schematic diagram of a scenario strategy generation device for overall optimization of the crude oil industry chain according to some embodiments of the present application;

[0025] Figure 5 It is a schematic diagram of an exemplary structure of an electronic device according to some embodiments of the present application. DETAILED DESCRIPTION

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0027] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0028] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprises" and "includes" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0029] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0030] For ease of understanding, the technical solution of the present application is introduced below in conjunction with the accompanying drawings and embodiments.

[0031] Figure 1is an exemplary flow chart of a scenario strategy generation method for overall optimization of the crude oil industry chain according to some embodiments of the present application. Figure 1 As shown in FIG. 1 , the scenario strategy generation method for overall optimization of the crude oil industry chain includes the following steps:

[0032] Step S110, according to various preset scenarios of production and operation of the crude oil industry chain, several scenario templates are set, and one of the scenario templates is selected as a target scenario template; wherein each scenario template contains one or more combinations of information of some parameters and some constraints in the pre-constructed overall optimization model of the crude oil industry chain.

[0033] There are many scenarios in the production and operation optimization plan of the crude oil industry chain, including but not limited to: scenarios of increased or decreased crude oil processing volume, increased or decreased product sales volume, and increased or decreased product exports. For example, an increase in diesel product sales of 100,000 tons is one scenario. Another example is an increase in gasoline product exports of 100,000 tons.

[0034] The preset scenarios are the market environment, operating status, etc. that may occur in the production and operation of the crude oil industry chain. In the specific implementation process, in order to adapt to market changes, it is necessary to generate optimization plans for production and operation for a variety of preset scenarios. For example, when it is predicted that the sales market of a certain oil refining or chemical product will be good, an optimization plan can be generated using the overall optimization model of the crude oil industry chain according to the scenario that the sales volume of the oil refining or chemical product will increase by 10%. For another example, when it is predicted that the sales market of oil refining or chemical crude oil products will decline, another optimization plan can be generated using the overall optimization model of the crude oil industry chain according to the scenario that the sales volume of the crude oil product will decrease by 15%.

[0035] The scenario template is used to represent a specific scenario of the production and operation of the crude oil industry chain. In the specific implementation process, the scenario template can have multiple forms of expression, including but not limited to: document form, block diagram form on a visual interface, etc. Each scenario template contains one or more combinations of information on some parameters and some constraints in the pre-built overall optimization model of the crude oil industry chain.

[0036] In the overall optimization model of the crude oil industry chain, parameters may include but are not limited to: purchase prices of various raw materials, sales prices of various products, etc.

[0037] In the overall optimization model of the crude oil industry chain, the constraint is the upper or lower limit of the constraint equation. For example, the constraint equation for the purchase volume SHZ.m of a certain crude oil SHZ is as follows:

[0038] SHZ.max ≥ SHZ.m ≥ SHZ.min (1)

[0039] Among them, SHZ.max is the upper limit of the purchase volume of crude oil SHZ, and SHZ.min is the lower limit of the purchase volume of crude oil SHZ, both of which are constraints; SHZ.m is a variable, and it is necessary to solve the overall optimization model of the crude oil industry chain to obtain the optimal solution of SHZ.m.

[0040] Just as an example, Figure 3 As shown, the target scenario template includes the following parameter information and constraint information: the price of offshore imported oil (HSJK) = base price + 300 (yuan); the purchase limit of Saudi oil = base limit - 500,000 tons.

[0041] In some embodiments, for various preset scenarios in the production and operation of the crude oil industry chain, parameter information and constraint information included in the scenario template can be determined, thereby generating a scenario template for each preset scenario.

[0042] In a specific implementation process, the user may select or adjust any scenario template from among the multiple scenario templates in multiple ways, and use the scenario template as the target scenario template.

[0043] In some embodiments, Figure 3 As shown, a variety of pre-generated scenario templates can be displayed through a visual interface (e.g., a computer screen), and the user can select one or more scenario templates from the displayed multiple scenario templates as target scenario templates through operations such as dragging and clicking.

[0044] In some embodiments, the user can also adjust the selected scenario template and use the adjusted scenario template as the target scenario template. Figure 3 In the target scenario template shown, the user can adjust "Price of offshore imported oil = base price + 300 (yuan)" to "Price of offshore imported oil = base price + 200 (yuan)".

[0045] Step S120, updating the overall optimization model of the crude oil industry chain according to the target scenario template, and generating the overall optimization model of the target crude oil industry chain.

[0046] In the specific implementation process, the parameters and / or constraints of the overall optimization model of the crude oil industry chain can be updated in a variety of ways according to the information of various parameters and / or constraints contained in the target scenario template, and the overall optimization model of the crude oil industry chain after the updated parameters is used as the target overall optimization model of the crude oil industry chain.

[0047] According to the target scenario template, the specific implementation example of updating the overall optimization model of the crude oil industry chain is shown in Figure 2 The relevant content in will not be repeated here.

[0048] Step S130, solving the overall optimization model of the target crude oil industry chain to obtain a scenario strategy for the overall optimization of the crude oil industry chain.

[0049] The scenario strategy for the overall optimization of the crude oil industry chain is to find the optimal solution of the overall optimization model of the crude oil industry chain corresponding to the target scenario template.

[0050] In the specific implementation process, a variety of methods can be used to solve the overall optimization model of the target crude oil industry chain, such as the distribution recursive method, the interior point method, etc., so as to obtain the scenario strategy for the overall optimization of the crude oil industry chain.

[0051] In the embodiments provided in the present application, by providing the user with pre-generated scenario templates for a variety of scenarios, the user selects a target scenario template from them; according to the target scenario template, the overall optimization model of the crude oil industry chain is updated to generate the overall optimization model of the target crude oil industry chain; the overall optimization model of the target crude oil industry chain is solved to obtain the scenario strategy for the overall optimization of the crude oil industry chain. Thus, the user does not need to manually adjust the parameters and constraints of the overall optimization model of the crude oil industry chain, that is, a variety of optimization schemes can be obtained conveniently and quickly.

[0052] Figure 2 It is an exemplary flow chart of a method for updating the overall optimization model of the crude oil industry chain according to a target scenario template as shown in some embodiments of the present application.

[0053] Step S210, determining the parameters to be adjusted in the overall optimization model of the crude oil industry chain according to the parameter information included in the target scenario template.

[0054] The parameter set of the crude oil industry chain optimization model includes all parameters in the overall optimization model of the crude oil industry chain. The parameter set of the overall optimization model of the crude oil industry chain can be stored in the database according to the preset classification rules. In the specific implementation process, the preset classification rules can be the classification rules specified in the data dictionary and the organizational dictionary of the overall optimization model of the crude oil industry chain. For example, according to the preset classification rules, the purchase price of offshore imported crude oil can constitute a subset of the parameter set of the overall optimization model of the crude oil industry chain, and the subset contains the prices of various types of crude oil in offshore imported crude oil. For another example, according to the preset classification rules, the sales price of retail gasoline can constitute a subset of the parameter set of the overall optimization model of the crude oil industry chain, and the subset contains the sales prices of all grades of gasoline belonging to retail gasoline. For another example, according to the preset classification rules, diesel can be divided into: 0# diesel, -10# diesel, -20# diesel, etc. by model, and accordingly, 0# diesel, -10# diesel, -20# diesel can respectively constitute a subset of the parameter set of the overall optimization model of the crude oil industry chain.

[0055] In some embodiments, the parameter information includes the encoding of the parameter, and the encoding of the parameter is obtained according to the classification rules of the parameter set of the crude oil industry chain overall optimization model. Therefore, a parameter whose type matches the encoding of the parameter can be selected from the parameter set of the crude oil industry chain overall optimization model as the parameter to be adjusted. For example, Figure 3 In the target scenario template shown, the code of offshore imported oil is HSJK (the pinyin abbreviation of offshore imported oil). Then, the prices of all crude oils of the offshore imported oil type can be selected from the parameter set of the overall optimization model of the crude oil industry chain as the parameters to be adjusted.

[0056] Step S220: updating the value of the parameter to be adjusted according to the parameter information in the target scenario template.

[0057] In some embodiments, the parameter information also includes an adjustment value of the parameter. Figure 3 In the scenario template shown, the price of offshore imported oil (HSJK) = base price + 300 (yuan), so the adjustment value of the price of all crude oils of the type of offshore imported oil is: base price + 300 (yuan).

[0058] In some embodiments, the database operation language can be used to update the values ​​of the parameters to be adjusted in the target database according to the adjustment values ​​of the parameters in the scenario template, wherein the parameter set of the overall optimization model of the crude oil industry chain is stored in the target database. Therefore, this step is equivalent to modifying the values ​​of some parameters of the overall optimization model of the crude oil industry chain.

[0059] In the specific implementation process, the database operation language can be used to update the value of the parameter to be adjusted in the target database according to the preset code operation logic. Figure 3 The target scenario template shown can use SQL language to perform the following operations to complete the update operation of the value of the parameter to be adjusted in the target database:

[0060] The code "HSJK" is used as the query keyword to query all entries of crude oil prices of the type "offshore imported oil" from the target database; "base price + 300" is used as the value of the entry obtained by the above query and written into the target database.

[0061] Step S230, determining the constraints to be adjusted in the overall optimization model of the crude oil industry chain according to the constraint information contained in the target scenario template.

[0062] The constraint set of the crude oil industry chain optimization model includes all the constraints in the overall optimization model of the crude oil industry chain. The constraint set of the overall optimization model of the crude oil industry chain can be stored in the database according to the preset classification rules. In the specific implementation process, the preset classification rules can be the classification rules specified in the data dictionary and the organizational dictionary of the overall optimization model of the crude oil industry chain. For example, according to the preset classification rules, the upper and lower limits of the purchase volume of offshore imported crude oil can constitute a subset of the constraint set of the overall optimization model of the crude oil industry chain, and the subset contains the upper and lower limits of the purchase volume of each type of offshore imported crude oil. For another example, according to the preset classification rules, the sales volume of retail gasoline can constitute a subset of the constraint set of the overall optimization model of the crude oil industry chain, and the subset contains the upper and lower limits of the sales volume of all grades of retail gasoline.

[0063] In some embodiments, the constraint information includes the constraint code, and the constraint code is obtained according to the classification rule of the constraint set of the crude oil industry chain overall optimization model. Therefore, from the constraint set of the crude oil industry chain overall optimization model, a constraint whose type matches the constraint code can be selected as the constraint to be adjusted. For example, Figure 3 In the scenario template shown: the purchase limit of Saudi oil = basic limit - 500,000 tons, and the code of Saudi oil is ST (the phonetic abbreviation of Saudi Arabia). Then, from the constraint set of the overall optimization model of the crude oil industry chain, the purchase limit of all crude oils of type Saudi oil can be selected as the constraint to be adjusted.

[0064] Step S240: updating the value of the constraint to be adjusted according to the constraint information in the target scenario template.

[0065] In some embodiments, the constraint information also includes an adjustment value of the constraint. Figure 3 In the target scenario template shown: the purchase limit of Saudi oil = basic limit - 500,000 tons, then the adjustment value of the purchase limit of all crude oil of type Saudi oil is: basic limit - 500,000 tons.

[0066] In some embodiments, the database operation language can be used to update the values ​​of the constraints to be adjusted in the target database according to the adjustment values ​​of the constraints in the scenario template, wherein the constraint set of the overall optimization model of the crude oil industry chain is stored in the target database. Therefore, this step is equivalent to modifying the values ​​of some constraints of the overall optimization model of the crude oil industry chain.

[0067] In the specific implementation process, the database operation language can be used to update the value of the constraint to be adjusted in the target database according to the preset code operation logic. Figure 3 The target scenario template shown can use SQL language to perform the following operations to complete the update operation of the value of the constraint to be adjusted in the target database:

[0068] The code "ST" is used as the query keyword to query all entries of the upper limit of crude oil purchase volume of type "Saudi oil" from the target database; "Basic upper limit - 500,000 tons" is used as the value of the entry obtained by the above query and written into the target database.

[0069] Figure 4 It is an exemplary schematic diagram of a scenario strategy generation device for overall optimization of the crude oil industry chain according to some embodiments of the present application.

[0070] like Figure 4 As shown, the scenario strategy generation device for overall optimization of the crude oil industry chain includes: a first acquisition module 410, a generation module 420 and a second acquisition module 430.

[0071] The first acquisition module 410 is used to respond to the user's selection or adjustment operation on any scenario template among multiple scenario templates and use the scenario template as the target scenario template; wherein each scenario template contains one or more combinations of information on some parameters and some constraints in a pre-constructed overall optimization model of the crude oil industry chain; wherein the constraint is an upper limit or a lower limit of a constraint equation.

[0072] The generation module 420 is used to update the crude oil industry chain overall optimization model according to the target scenario template and generate a target crude oil industry chain overall optimization model.

[0073] The second acquisition module 430 is used to solve the overall optimization model of the target crude oil industry chain and obtain a scenario strategy for the overall optimization of the crude oil industry chain.

[0074] In the above-mentioned embodiment of the scenario strategy generation device for overall optimization of the crude oil industry chain, the specific processing of each module and the technical effects it brings can be referred to the relevant descriptions in the corresponding method embodiment, which will not be repeated here.

[0075] Figure 5 It is a schematic diagram of an exemplary structure of an electronic device according to some embodiments of the present application.

[0076] like Figure 5As shown, the electronic device includes: at least one processor 501, at least one communication interface 502, at least one memory 503 and at least one communication bus 504; optionally, the communication interface 502 can be an interface of a communication module, such as an interface of a GSM module; the processor 501 may be a processor CPU, or an application-specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. The memory 503 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Among them, the memory 503 stores a program, and the processor 501 calls the program stored in the memory 503 to execute part or all of the above-mentioned method embodiments.

[0077] The present application relates to a storage medium for storing a computer-readable program. When the computer-readable program is executed, part or all of the above-mentioned method embodiments are executed.

[0078] Alternatively, the storage medium may be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0079] Based on the same inventive concept, an embodiment of the present application further provides a computer program product, including a computer program, which implements part or all of the above-mentioned method embodiments when executed by a processor.

[0080] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements and amendments to the present application. Such modifications, improvements and amendments are suggested in the present application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of the present application.

[0081] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or multiple times in different positions in the present application does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0082] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0083] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the object of this application are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0084] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0085] Each patent, patent application, patent application disclosure, and other materials, such as articles, books, instructions, publications, documents, etc., cited in this application are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the content of this application, documents that limit the broadest scope of the claims of this application (currently or later attached to this application) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the attached materials of this application are inconsistent or conflicting with the content described in this application, the descriptions, definitions, and / or use of terms in this application shall prevail.

[0086] Finally, it should be understood that the embodiments described in this application are only used to illustrate the principles of the embodiments of the present application. Other variations may also fall within the scope of the present application. Therefore, as an example and not a limitation, the alternative configurations of the embodiments of the present application may be considered to be consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly introduced and described in this application.

Claims

1. A scenario strategy generation method for overall optimization of the crude oil industry chain, characterized in that: The method comprises: According to various preset scenarios of production and operation of the crude oil industry chain, several scenario templates are set, and one of the scenario templates is selected as a target scenario template; wherein each scenario template contains one or more combinations of information of some parameters and some constraints in the pre-constructed overall optimization model of the crude oil industry chain; According to the target scenario template, the crude oil industry chain overall optimization model is updated to generate a target crude oil industry chain overall optimization model; Solve the overall optimization model of the target crude oil industry chain and obtain the scenario strategy for the overall optimization of the crude oil industry chain.

2. The method according to claim 1, characterized in that: Set up several scenario templates in the following ways: For each preset scenario in the production and operation of the crude oil industry chain, perform the following operations: According to the preset scenario, parameter information and constraint information included in the scenario template are determined.

3. The method according to claim 1, characterized in that: The updating of the overall optimization model of the crude oil industry chain according to the target scenario template includes: Determining the parameters to be adjusted in the overall optimization model of the crude oil industry chain according to the parameter information included in the target scenario template; According to the information of the parameter, updating the value of the parameter to be adjusted; Determining the constraints to be adjusted in the overall optimization model of the crude oil industry chain according to the constraint information contained in the target scenario template; According to the constraint information, the value of the constraint to be adjusted is updated.

4. The method according to claim 3, characterized in that The parameter information includes the encoding of the parameter; wherein the encoding of the parameter is obtained according to the classification rule of the parameter set of the overall optimization model of the crude oil industry chain; Determining the parameters to be adjusted in the overall optimization model of the crude oil industry chain according to the information of the parameters included in the target scenario template includes: From the parameter set of the crude oil industry chain overall optimization model, a parameter whose type matches the encoding of the parameter is selected as the parameter to be adjusted.

5. The method according to claim 3, characterized in that: The constraint information includes the constraint code; wherein the constraint code is obtained according to the classification rules in the constraint set of the overall optimization model of the crude oil industry chain; Determining the constraints to be adjusted in the overall optimization model of the crude oil industry chain according to the constraint information contained in the target scenario template includes: From the constraint set of the overall optimization model of the crude oil industry chain, a constraint whose type matches the encoding of the constraint is selected as the constraint to be adjusted.

6. The method according to claim 4, characterized in that The parameter information also includes the adjustment value of the parameter; The updating the value of the parameter to be adjusted according to the information of the parameter includes: Using the database operation language, the value of the parameter to be adjusted in the target database is updated according to the adjustment value of the parameter; wherein the parameter set of the overall optimization model of the crude oil industry chain is stored in the target database.

7. The method according to claim 4, characterized in that The constraint information also includes constraint adjustment values; The updating the value of the constraint to be adjusted according to the constraint information includes: Using the database operation language, the value of the constraint to be adjusted in the target database is updated according to the adjustment value of the constraint; wherein the constraint set of the overall optimization model of the crude oil industry chain is stored in the target database.

8. A scenario strategy generation device for overall optimization of the crude oil industry chain, characterized in that: The device comprises: The first acquisition module is used to set a number of scenario templates according to various preset scenarios of production and operation of the crude oil industry chain, and select one of the scenario templates as a target scenario template; wherein each scenario template contains one or more combinations of information of some parameters and some constraints in the pre-constructed overall optimization model of the crude oil industry chain; A generation module, used to update the crude oil industry chain overall optimization model according to the target scenario template, and generate a target crude oil industry chain overall optimization model; The second acquisition module is used to solve the overall optimization model of the target crude oil industry chain and obtain the scenario strategy for the overall optimization of the crude oil industry chain.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the method according to any one of claims 1 to 7 when running the program.

10. A storage medium for storing a computer-readable program, wherein when the computer-readable program is executed, the method according to any one of claims 1 to 7 is executed.

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