CN117114781A - Method and device for determining crude oil processing scheme - Google Patents

Method and device for determining crude oil processing scheme Download PDF

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CN117114781A
CN117114781A CN202311373385.1A CN202311373385A CN117114781A CN 117114781 A CN117114781 A CN 117114781A CN 202311373385 A CN202311373385 A CN 202311373385A CN 117114781 A CN117114781 A CN 117114781A
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purchasing
interval
purchased
crude oil
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CN117114781B (en
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董丰莲
孙鑫
徐泽进
玉德俊
魏志伟
殷基明
毛晓阳
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Petrochina Co Ltd
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Abstract

The invention provides a method and a device for determining a crude oil processing scheme, wherein the method comprises the following steps: determining the upper limit and the lower limit of parameters of the to-be-purchased quantity in a constraint equation of the to-be-purchased quantity according to purchase price data of the to-be-processed crude oil and a pre-established optimization model of the refining production plan; determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model; determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased; according to the association relation between the to-be-purchased quantity and the purchasing marginal benefit data of the to-be-processed crude oil, the processing scheme of the to-be-processed crude oil is determined, and the corresponding relation between the purchasing marginal benefit data and the processing quantity of a certain crude oil can be accurately obtained, so that a more scientific and reasonable crude oil processing scheme is determined.

Description

Method and device for determining crude oil processing scheme
Technical Field
The invention relates to the technical field of oil refining, in particular to a method and a device for determining a crude oil processing scheme.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
Crude oil is a main raw material of a refinery, and various crude oils are subjected to a series of complex refining processes such as atmospheric and vacuum, continuous reforming, residual oil hydrogenation, catalytic cracking, gasoline and diesel hydrogenation, alkylation and the like in the refinery to produce products such as gasoline, kerosene, diesel oil, lubricating oil, paraffin and the like. The production operations of refineries are affected by numerous factors such as feedstock supply, product demand, plant capacity, product index, etc. In the prior art, a crude oil processing scheme is obtained by establishing and solving a nonlinear programming model, and for a refinery, purchasing marginal benefit data for processing a certain crude oil is always changed along with the change of processing amount under a certain constraint condition. This is not considered in the prior art, so that the obtained crude oil processing scheme is not scientific and reasonable enough.
Disclosure of Invention
The embodiment of the invention provides a method for determining a crude oil processing scheme, which is used for accurately acquiring the corresponding relation between purchasing marginal benefit data and processing amount of a certain crude oil to determine a more scientific and reasonable crude oil processing scheme, and comprises the following steps:
Determining the upper limit and the lower limit of parameters of the to-be-purchased quantity in a constraint equation of the to-be-purchased quantity according to purchase price data of the to-be-processed crude oil and a pre-established optimization model of the refining production plan; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model;
determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
and determining the processing scheme of the crude oil to be processed according to the association relation between the crude oil to be processed to be purchased and the purchasing marginal benefit data.
The embodiment of the invention also provides a device for determining the crude oil processing scheme, which is used for accurately acquiring the corresponding relation between the purchasing marginal benefit data and the processing amount of a certain crude oil to formulate a scientific and reasonable crude oil processing scheme, and comprises the following steps:
The upper limit and the lower limit of the parameter of the to-be-purchased quantity are determined according to the purchasing price data of the crude oil to be processed and a pre-established refining production plan optimization model, and the upper limit and the lower limit of the parameter of the to-be-purchased quantity are determined in a constraint equation of the to-be-purchased quantity; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
the to-be-purchased quantity interval determining module is used for determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of to-be-purchased quantity parameters and the refining production plan optimizing model;
the incidence relation determining module is used for determining incidence relation between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
the processing scheme determining module is used for determining the processing scheme of the crude oil to be processed according to the association relation between the crude oil to be processed to be purchased and the purchasing marginal benefit data.
In the embodiment of the invention, the upper limit and the lower limit of the parameters of the to-be-purchased quantity in the constraint equation of the to-be-purchased quantity are determined according to the purchase price data of the to-be-processed crude oil and a pre-established refining production plan optimization model; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed; determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model; determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased; according to the correlation between the to-be-purchased quantity of the to-be-processed crude oil and the purchasing marginal benefit data, the processing scheme of the to-be-processed crude oil is determined, and compared with the technical scheme that the processing scheme of the crude oil is unreasonable by establishing and solving the nonlinear programming model in the prior art, the embodiment of the invention considers that the purchasing marginal benefit of processing a certain crude oil can be continuously changed along with the change of the processing quantity under a certain constraint condition when determining the processing scheme of the to-be-processed crude oil, so that the corresponding relation between the purchasing marginal benefit data and the processing quantity of processing a certain crude oil can be accurately obtained, and the scientific and reasonable crude oil processing scheme is determined.
Drawings
In order to more clearly illustrate the embodiments of the invention 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, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow chart of a method for determining a crude oil processing scheme provided by an embodiment of the present invention;
FIG. 2 is a flowchart of a specific example of a method for determining a crude oil processing scheme provided by an embodiment of the present invention;
FIG. 3 is a graph showing the relationship between the amount to be purchased and the purchasing marginal benefit data according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of a determination device for crude oil processing scheme provided by an embodiment of the present invention;
fig. 5 is a schematic diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the technical solution of the embodiments of the present invention, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present invention, and it is apparent to those of ordinary skill in the art that the present invention may be applied to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
It should be appreciated that the terms "system," "apparatus," "unit," and/or "module" as used in connection with embodiments of the present invention are intended to be a means for distinguishing between different components, elements, parts, portions, or assemblies at different levels. However, if other words can achieve the same purpose, the words may be replaced by other expressions.
As used in the specification and in the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
A flowchart is used in the present invention to describe the operations performed by a system according to embodiments of the present invention. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.
In the prior art, a crude oil processing scheme is obtained by establishing and solving a nonlinear programming model, but the corresponding relation between the purchasing marginal benefit data and the processing amount of a certain crude oil is not considered. Therefore, there is no scheme for accurately acquiring the correspondence between the purchasing marginal benefit data and the processing amount of a certain crude oil. How to accurately acquire the corresponding relation between the purchasing marginal benefit data and the processing amount of a certain crude oil, so that a more scientific and reasonable crude oil processing scheme is formulated based on the corresponding relation between the purchasing marginal benefit data and the processing amount, and the method is a technical problem to be solved urgently.
When the processing scheme of the crude oil to be processed is determined, the situation that the purchasing marginal benefit of processing a certain crude oil is continuously changed along with the change of the processing amount under a certain constraint condition is considered, so that the corresponding relation between the purchasing marginal benefit data of processing a certain crude oil and the processing amount can be accurately obtained, and a scientific and reasonable crude oil processing scheme is determined.
For easy understanding, the technical scheme of the present invention is described below with reference to the drawings and the embodiments.
Fig. 1 is a flowchart of a method for determining a crude oil processing scheme according to an embodiment of the present invention. As shown in fig. 1, the method for determining a crude oil processing scheme according to an embodiment of the present invention may include:
Step 101, determining the upper limit and the lower limit of parameters of the to-be-purchased quantity in a constraint equation of the to-be-purchased quantity according to purchase price data of the to-be-processed crude oil and a pre-established refining production plan optimization model; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
step 102, determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model;
step 103, determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
and 104, determining a processing scheme of the crude oil to be processed according to the association relation between the amount of the crude oil to be purchased and the purchasing marginal benefit data.
In one embodiment, prior to step 101, a refinery's optimization model of a refinery's production plan for crude oil to be processed may be pre-established with the goal of maximizing profit data for the refinery, the refinery's optimization model of production plan including constraint equations for the amount of crude oil to be purchased.
In this embodiment, the optimization model of the refining production plan of the crude oil to be processed may be a nonlinear programming model. In a specific implementation process, a refining production plan optimization model for crude oil to be processed can be established in various modes. For example, a refining production plan optimization model may be built using software developed by a third party company. By way of example only, the following description will be given by taking the use of a platform to build a production plan optimization model.
The objective function of the refinery production planning optimization model is that profit data of the refinery is maximum, and the variables may include: the purchase quantity of various resources, the yield of various products, the processing quantity of various devices, the feeding quantity and the discharging quantity of various devices, the physical property value of various materials and the like. Parameters of the refining production plan optimization model may include: purchase price of various raw materials, delivery price of various products, unit consumption of raw materials of the device, yield of the products and the like. Constraint equations for the refining production plan optimization model may include: the whole plant balance equation of each material, the association relation equation of the amount of input materials and output materials of the device, the upper and lower limits of raw material purchase quantity, the upper and lower limits of product yield, the upper and lower limits of processing capacity of the device, the physical property index requirements of blended discharge and the like.
In modeling, the embodiment of the invention records all material sets asMRecord the public engineering set asGThe recording device is assembled intoEBy superscriptIdentification of sub-sets corresponding to different links, e.g. links of purchase, atmospheric and vacuum device processing, secondary device processing, reconciliation, sales, etcM s Indicating the need to go through linkssThe materials to be processed are gathered together,E s representing the set of all devices in link s. The embodiment of the invention records the corresponding consumption relationship between the device and the materials and the public works as a setIRecording the corresponding output relation of the device, the materials and the public works as a setO，I M （O M ) AndI G （O G ) The consumption (output) sets of the device with the materials and utilities, respectively, are identified. The material consumption of the embodiment of the invention is +.>And-> By representing linkssMiddle deviceeInflow of a material (public works), +.>By using
Representation linkssMiddle deviceeOutflow of a material (public works). In the optimization model of the refining production plan, subscripts are used in the embodiment of the inventioninAndoutthe inflow and outflow properties of the material or utility are identified.
The objective function of the refining production plan optimization model may be:
(1)
in formula (1):Pprofit for the refinery; parameters (parameters)p m Representing a productmIs a sales price of (a); parameters (parameters) c m Representing the raw materialsmIs a purchase price of (a); parameters (parameters)c g Representing public worksgIs a purchase price of (a);representing sales of product m; />Representing the raw materialsmIs a purchase amount of (1); />Sign utilitygIs a purchase amount of (a) in the purchase amount.
The refining production plan optimization model may include a variety of constraint equations, some of which are listed below:
raw material purchasing range constraint: the raw material purchasing quantity is limited by internal and external factors and needs to be within a given upper and lower limit interval, the embodiment of the invention records the upper and lower limit of the raw material purchasing quantity m as,i.e. the constraint needs to be satisfied:
（2）
product sales range constraints: the sales of the product is required to be within a given upper limit and a lower limit under the influence of internal and external factors, and the embodiment of the invention records the sales upper limit and the sales lower limit of the product m asI.e. the constraint needs to be satisfied:
（3）
device processing capability range constraints: the processing capacity set of the recording device of the embodiment of the invention isH，H s Representation linkssA set of processing capacities for all devices; recording deviceeWorkability and workability of the workinghThe upper and lower limits of (2) are. In general, the process volume of a device is characterized by the consumption of the main raw materials. The processing capacity required for processing all the main raw materials should not exceed the upper and lower limits for each device, i.e. the constraints need to be satisfied:
（4）
and (3) calculating an equation of the physical properties of the blending pool: the embodiment of the invention records the physical property collection of materials as Record->For link->Chinese material->Physical properties of->Is a value of (2). In the embodiment of the invention, the physical property collection satisfying the weight reconciliation relationship is marked as +.>The physical property set satisfying the volume harmony relationship is denoted +.>The physical property calculation during reconciliation should satisfy the following equality constraints:
（5）
（6）
（7）
（8）
wherein,representing the density of the material, embodiments of the present invention herein incorporate volumetric variablesZInstead of the expression (volume = weight/density); function->Representing the passing linkssPhysical Properties after processingqThe value of +.>And the function of physical properties which do not conform to the linear harmony law is determined by the specific physical law.
In equations (5), (6), (7) and (8), the weight of the materialXVolume ofZPhysical properties and physical propertiesYAre variables and therefore these several equations are nonlinear equations.
And (3) physical property range constraint of blending discharging: according to the factory standard requirements of products or the tolerance requirements of devices on raw materials, the physical properties of the blended materials are required to meet certain upper and lower limit constraints. Warp recording linksMixing out materialsmPhysical properties of (3)qThe upper and lower limits of (2) areThe physical properties of the material should satisfy the following constraints:
（9）
in summary, the nonlinearity of the optimization model of the refining production plan is mainly caused by the fact that the product of the material variable and the physical variable is required to be carried out during the calculation of the reconciliation physical property. The existing marginal benefit tracking method aiming at the linear programming model cannot be suitable for the current situation, and in the embodiment of the invention, the marginal benefit tracking of the nonlinear programming model is realized through the following steps.
In step 101, the upper limit and the lower limit of the parameter of the to-be-purchased quantity in the constraint equation of the to-be-purchased quantity can be obtained by adjusting the purchase price data of the to-be-processed crude oil and utilizing the optimization model of the refining production plan.
In one embodiment, determining the upper limit and the lower limit of the parameters of the to-be-purchased quantity in the constraint equation of the to-be-purchased quantity according to the purchase price data of the to-be-processed crude oil and a pre-established optimization model of the refining production plan may include: adjusting purchase price data of crude oil to be processed into first purchase price data; the first purchase price data is greater than market purchase price data of crude oil to be processed; inputting the first purchase price data into a pre-established refining production plan optimization model, and determining the lower limit of a to-be-purchased quantity parameter of crude oil to be processed; adjusting the purchase price data of the crude oil to be processed into second purchase price data; the second purchase price data is smaller than market purchase price data of the crude oil to be processed; and inputting the second purchase price data into a refining production plan optimization model, and determining the upper limit of the parameters of the to-be-purchased amount of the crude oil to be processed.
In this embodiment, the purchase price data of the crude oil to be processed may be adjusted to the first purchase price data; wherein the first purchase price data is greater than market purchase price data of crude oil to be processed; and solving the refining production plan optimization model to obtain the lower limit of the to-be-purchased quantity parameter of the crude oil to be processed.
By way of example only, the price data of the crude oil to be processed may be set to 10 times the market price data in the refining production plan optimization model, for example, 5000 yuan/ton of the market price data of the crude oil to be processed, the price data may be modified to 50000 yuan/ton, and then the refining production plan optimization model may be solved. Since the price data of the crude oil to be processed is high, the refinery will lose the crude oil to be processed, and the calculation result will obtain a value that makes the refinery as little as possibleA scheme for processing the crude oil, according to which the lower limit of the parameters of the amount of crude oil to be purchased to be processed can be obtainedA 0 。
In one embodiment, the purchase price data of the crude to be processed may be adjusted to the second purchase price data; wherein the second purchase price data is less than market purchase price data of the crude oil to be processed; and solving the refining production plan optimization model to obtain the upper limit of the to-be-purchased quantity parameter of the crude oil to be processed.
By way of example only, the price data of the crude oil to be processed may be set to 0 in the refining production plan optimization model, and then the refining production plan optimization model may be solved. Since the price data of the crude oil to be processed is 0, the crude oil can be processed by the oil refinery, the calculation result can obtain a scheme for processing the crude oil as much as possible by the oil refinery, and the upper limit of the parameters of the amount to be purchased of the crude oil to be processed can be obtained according to the scheme A 1 。
In step 102, a plurality of to-be-purchased quantity intervals may be obtained by iterative division according to the upper limit and the lower limit of the to-be-purchased quantity parameter by using the optimization model of the refining production plan.
In this embodiment, the to-be-purchased quantity interval may be a value interval composed of continuous to-be-purchased quantity values.
Fig. 2 is a flowchart of a specific example of a method for determining a crude oil processing scheme according to an embodiment of the present invention, where, with respect to a detailed description of a plurality of intervals of to-be-purchased obtained by iterative division using a refining production plan optimization model according to an upper limit and a lower limit of parameters of to-be-purchased, referring to relevant contents in fig. 2, as shown in fig. 2, the step of determining a plurality of intervals of to-be-purchased according to the upper limit and the lower limit of parameters of to-be-purchased and the refining production plan optimization model may include:
step 201, determining a purchasing interval to be analyzed according to the upper limit and the lower limit of the parameter of the purchasing quantity to be analyzed;
the following steps are repeatedly executed until all the purchasing intervals to be analyzed do not meet the partition conditions, and a plurality of purchasing intervals are determined:
step 202, according to a purchasing interval to be analyzed and a refining production plan optimization model, determining purchasing marginal benefit data corresponding to boundary values of the purchasing interval to be analyzed and states of associated constraints; the state of the associated constraint is the relation between the value of the constrained variable and the constraint upper limit and the constraint lower limit in other constraint equations except the constraint equation of the quantity to be purchased when the optimization model of the refining production plan is used for determining the purchasing marginal benefit data;
Step 203, determining whether the purchasing interval to be analyzed meets the partition condition according to the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed and the state of the association constraint and the difference between the boundary values of the purchasing interval to be analyzed; the partition conditions include: the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference value between the boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision;
step 204, if the purchasing interval to be analyzed meets the partition condition, dividing the purchasing interval to be analyzed into at least two purchasing amount intervals according to the boundary value of the purchasing interval to be analyzed;
step 205, each of the obtained intervals of the amount to be purchased is used as a purchase interval to be analyzed.
In step 201, a first to-be-purchased amount interval may be determined according to the upper limit and the lower limit of the to-be-purchased amount parameter, and the first to-be-purchased amount interval is used as the to-be-analyzed purchase interval.
In the implementation process, the upper limit and the lower limit of the parameter of the to-be-purchased amount can be respectively used as the boundary value of the first to-be-purchased amount interval to obtain the first to-be-purchased amount interval. By way of example only, the upper and lower limits of the quantity to be purchased parameter are respectively noted as A 1 AndA 0 the first interval of the amount to be purchased can be expressed as。
And repeatedly executing the steps 202-205 until the purchasing interval to be analyzed does not meet the partition conditions, wherein the partition conditions comprise: the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference value between the boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision; and determining a plurality of intervals to be purchased.
In step 202, using the optimization model of the refining production plan, the purchasing marginal benefit data and the associated constraint state corresponding to the boundary value of the purchasing interval to be analyzed are obtained.
In a specific implementation process, the purchase quantity of crude oil to be processed in the refining production plan optimization model can be respectively set to be the maximum value and the minimum value of a purchase interval to be analyzed, the refining production plan optimization model is solved, and the obtained result contains the state that the boundary value of the purchase interval to be analyzed corresponds to the purchase marginal benefit data and the association constraint.
For example, in the optimization model of the refining production plan, the upper limit and the lower limit of the to-be-purchased amount of the crude oil to be processed are set as the maximum value of the to-be-analyzed purchasing interval, and then the model is solved to obtain the purchasing marginal benefit data corresponding to the maximum value of the to-be-analyzed purchasing interval And the status of each associated constraint.
For example, in the optimization model of the refining production plan, the upper limit and the lower limit of the to-be-purchased amount of the crude oil to be processed are set to the minimum value of the to-be-analyzed purchasing interval, and then the model is solved to obtain the purchasing marginal benefit data corresponding to the minimum value of the to-be-analyzed purchasing intervalAnd the status of each associated constraint.
For example only, for a refining production plan optimization model established using RIPO in step 101, a distributed recursive method may be employed to solve for the steps of: first, the initial values of the physical properties of the material are given, which corresponds to the values of the variables Y in the constraints (5), (6), (7), and (8) being fixed, so that the constraints become linear constraints. Then, the LP problem can be solved by a solver, and the obtained solution is recursively and repeatedly calculated and updated until the error of the physical property meets the tolerance.
In step 203, it is determined whether the purchasing interval to be analyzed meets the partition condition according to the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed, the state of the association constraint, and the difference between the boundary values.
In an implementation, the partitioning conditions may include:
The difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference. And meeting the condition, wherein the change amount of the purchasing marginal benefit data of the crude oil to be processed is larger than a preset threshold value in the purchasing interval to be analyzed, the change is larger, and the possibility of mutation exists.
And the states of the association constraints corresponding to the boundary values of the purchase interval to be analyzed are different. And meeting the condition, wherein the condition indicates that the change quantity of the purchasing marginal benefit data of the crude oil to be processed is larger than a preset threshold value due to the change of the state of the association constraint in the purchasing interval to be analyzed, namely the mutation occurs.
The difference value between boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision. The preset analysis precision is inflection point analysis precision, the inflection point is in a purchasing quantity-purchasing marginal benefit curve, when the purchasing quantity change is smaller than a preset purchasing quantity threshold value, the corresponding purchasing marginal benefit change quantity is larger than the preset threshold value, and the point is the inflection point. The condition is met, that the purchasing interval to be analyzed can be further subdivided, and the accuracy of purchasing marginal benefit analysis of crude oil to be processed is ensured.
By way of example only, with the first interval of amounts to be purchased To illustrate the execution of this step.
According to the service requirement, a marginal benefit difference gamma (such as 10 units: yuan/ton) and a preset analysis precision epsilon (such as 0.1 units: ten thousand tons) are set.
1. Comparing the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing intervalRelative to gamma. If->And the change of the purchasing marginal benefit data in the interval is smaller, the continuous partitioning of the purchasing marginal benefit data is not needed, and the analysis of the interval is ended.
2. At the position ofAnd (3) determining whether a difference exists between the states of the association constraint corresponding to the boundary value of the purchase interval to be analyzed. If there is a difference, it is stated that the state of the association constraint is changed in the interval, and specifically includes any one of the following: from "upper card limit" to "lower card limit", from "upper card limit" to "no card edge", from "no card edge" to "upper card limit", from "no card edge" to "lower card limit", from "lower card limit" to "upper card limit", from "lower card limit" to "no card edge".
2.1, if the marginal benefit states of all the association constraints are unchanged, the fact that the mutation of purchasing the marginal benefit does not occur in the interval is indicated, and analysis on the interval is not continued.
2.2 if the state of the associated constraint is changed, continuing to compareRelative size to epsilon.
2.2.1 ifAnd (3) the analysis precision is satisfied, the interval does not need to be continuously divided, the state change condition of the association constraint is output, and the state change condition is used as a bottleneck factor for causing the change quantity of the purchasing marginal benefit data corresponding to the purchasing interval to be analyzed to be larger than a preset threshold value, namely the mutation occurs. For example: yield of 92# gasoline on cardThe limit is changed into a non-clamping limit, the processing amount of the catalytic cracking device is changed from a lower clamping limit to a non-clamping limit, the sulfur content of the 92# gasoline is changed from a non-clamping limit to an upper clamping limit, and the like. The analysis of the section is ended.
2.2.2 ifIt is stated that the interval also needs to be subdivided, and the detailed dividing method is described in the following steps.
In step 204, in the case that the to-be-analyzed purchasing interval meets the partition condition, the to-be-analyzed purchasing interval is divided into at least two to-be-purchased-amount intervals according to the boundary value of the to-be-analyzed purchasing interval.
The execution of this step is continued as described in the above example.
Order theThe reserved decimal numbers are consistent with the precision analysis requirement (e.g. epsilon is 0.1, thenOne decimal place is reserved) so that the interval +. >Split into two intervals->And->。
In step 205, each of the divided to-be-purchased quantity intervals is used as a to-be-analyzed purchase interval, and the optimization model of the refining production plan is re-executed to obtain the purchase marginal benefit data corresponding to the boundary value of the to-be-analyzed purchase interval and the state of the associated constraint.
This step will be described with the above example as an example.
For two intervals obtained by splittingAnd->And respectively taking the data as purchase intervals to be analyzed, and continuing processing again according to the step 201.
For example, for intervalsIn step 203, it is determined that the partition condition (1 or 2.1 or 2.2.1) is not satisfied, and the analysis of the section is ended; if the partition condition is satisfied, go to step 204 to let +.>Thereby making the interval +>Split into two new compartments->And->。
Also for example, for intervalsIf the partition condition is not satisfied, ending the analysis of the interval; if the partition condition is satisfied, go to step 204 to let +.>Thereby making the interval +>Split into two new compartments->And->。
In step 103, according to the purchasing marginal benefit data corresponding to the boundary values of the multiple purchasing quantity intervals, the association relationship between the purchasing quantity of the crude oil to be processed and the purchasing marginal benefit data is obtained.
The purchasing marginal benefit data is the marginal benefit data of a constraint equation of the quantity to be purchased in the optimization model of the refining production plan. By way of example only, in the refining production plan optimization model, both the upper and lower limits of the amount to be purchased of the crude oil to be processed are set as the lower limits of the amount to be purchased parameter in the example of step 102A 0 Then solving the model to obtain the quantity to be purchasedA 0 Corresponding purchasing marginal benefit dataAnd the status of each associated constraint.
The state of the associated constraint is the relation between the value of the constrained variable and the constraint upper limit and the constraint lower limit in constraint equations except for constraint equations of the quantity to be purchased when the purchasing marginal benefit data is calculated by using the optimization model of the refining production plan. Association constraints may include, but are not limited to: raw material purchasing range constraint, product sales range constraint, device processing capacity range constraint, reconciliation discharge physical property range constraint and the like.
In one embodiment, the states of the association constraint may include a card upper limit state, a card lower limit state, and a card off-edge state.
The card upper limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset upper limit;
The card lower limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset lower limit;
the non-edge clamping state is as follows: the value of the constrained variable in the association constraint equation determined according to the refining production plan optimization model is between a preset upper limit and a preset lower limit.
The boundary value of the to-be-purchased quantity interval comprises a maximum to-be-purchased quantity and a minimum to-be-purchased quantity. The purchasing marginal benefit data corresponding to the boundary value of the to-be-purchased quantity interval comprises purchasing marginal benefit corresponding to the maximum to-be-purchased quantity and purchasing marginal benefit data corresponding to the minimum to-be-purchased quantity of the to-be-purchased quantity interval.
In one embodiment, determining the association between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals may include: for each to-be-purchased quantity interval, the following operations are executed: taking the highest to-be-purchased quantity in the to-be-purchased quantity interval, the purchasing marginal benefit data corresponding to the highest to-be-purchased quantity, and at least one group of data in the purchasing marginal benefit data corresponding to the lowest to-be-purchased quantity and the lowest to-be-purchased quantity as a purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval; and determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval.
In the specific implementation process, the association relationship between the to-be-purchased amount of the crude oil to be processed and the purchasing marginal benefit data can be represented by using a curve, or can be fitted by using a piecewise function, and is not limited by the expression of the specification.
Fig. 3 is a graph of an association relationship between a to-be-purchased amount and purchasing marginal benefit data according to an embodiment of the present invention, and as can be seen from fig. 3, the association relationship between the to-be-purchased amount and purchasing marginal benefit data can be obtained more accurately and in detail by using the method provided by the present invention.
In some embodiments, a bottleneck factor causing abrupt change of the purchasing marginal benefit data may be further obtained according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals and the states of the association constraint. The method comprises the following steps:
when the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is determined to have abrupt change;
if the difference value between the boundary values of the purchasing interval to be analyzed is smaller than or equal to the preset analysis precision, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference is used as a bottleneck factor that the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is suddenly changed;
And adjusting the processing scheme of the crude oil to be processed according to the bottleneck factors.
The detailed description of the above is referred to the relevant content in step 203, and will not be repeated here.
By way of example only, according to business requirements, a preset marginal benefit difference is set to be gamma (for example, 10, unit: yuan/ton) and a preset analysis precision epsilon (for example, 0.1, unit: ten thousand tons), purchasing marginal benefit data corresponding to a boundary value of a purchasing interval to be analyzed are respectively 390 Yuan/ton and 325 Yuan/ton, the difference between the two is 65 Yuan/ton, the state of the yield of 92# gasoline corresponding to the two is changed from the upper limit of the card to the non-card side, and determining that the state of the yield of 92# gasoline is changed from the upper limit of the card to the non-card side is a bottleneck factor causing the crude oil purchasing marginal benefit data to be changed from 390 Yuan/ton to 325 Yuan/ton.
Table 1 is a marginal benefit tracking and bottleneck factor analysis table for crude A to be processed in a refinery according to an embodiment of the present invention. And (3) measuring and calculating the result, wherein the lowest purchase amount of the crude oil A is 27.5 ten thousand tons, the highest purchase amount is 47.1 ten thousand tons, and after 9 rounds, the comparison analysis of 31 boundary points in total is carried out, the accurate and detailed marginal benefit turning points of the crude oil A to be processed in the oil refinery and bottleneck factors (limiting factors) causing turning are obtained.
TABLE 1
In step 104, a processing scheme of the crude oil to be processed is determined according to the association relationship between the amount of crude oil to be purchased and the purchasing marginal benefit data.
In some embodiments, the processing scheme of the crude oil to be processed may be adjusted according to bottleneck factors that cause abrupt changes in purchasing marginal benefits. For the above example, the procurement margin dip may be avoided by adjusting the 92# gasoline yield in the refined production plan optimization model (e.g., increasing the upper constraint limit in the associated constraint equation).
Fig. 4 is a schematic diagram of a determination apparatus for crude oil processing scheme according to an embodiment of the present invention. As shown in fig. 4, the determination device of the crude oil processing scheme may include:
the upper and lower limit determining module 401 for parameters of the to-be-purchased quantity is used for determining the upper limit and the lower limit of the parameters of the to-be-purchased quantity in a constraint equation of the to-be-purchased quantity according to the purchase price data of the to-be-processed crude oil and a pre-established optimization model of the refining production plan; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
The to-be-purchased quantity interval determining module 402 is configured to determine a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameter and the optimization model of the refining production plan;
the association relationship determining module 403 is configured to determine an association relationship between a to-be-purchased amount of the crude oil to be processed and the purchasing marginal benefit data according to purchasing marginal benefit data corresponding to boundary values of a plurality of to-be-purchased amount intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
the processing scheme determining module 404 is configured to determine a processing scheme of the crude oil to be processed according to an association relationship between a to-be-purchased amount of the crude oil to be processed and purchasing marginal benefit data.
In one embodiment, the module 401 for determining the upper and lower limits of the quantity to be purchased parameter may specifically be configured to:
adjusting purchase price data of crude oil to be processed into first purchase price data; the first purchase price data is larger than market purchase price data of crude oil to be processed;
inputting the first purchase price data into a pre-established refining production plan optimization model, and determining the lower limit of a to-be-purchased quantity parameter of crude oil to be processed;
adjusting the purchase price data of the crude oil to be processed into second purchase price data; the second purchase price data is smaller than market purchase price data of crude oil to be processed;
And inputting the second purchase price data into a refining production plan optimization model, and determining the upper limit of the parameters of the to-be-purchased amount of the crude oil to be processed.
In one embodiment, the to-be-purchased quantity interval determination module 402 may be specifically configured to:
determining a first to-be-purchased quantity interval according to the upper limit and the lower limit of the to-be-purchased quantity parameter, and taking the first to-be-purchased quantity interval as a to-be-analyzed purchase interval;
according to the purchasing interval to be analyzed and the refining production plan optimization model, determining purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed and the state of the associated constraint; the state of the associated constraint is the relation between the value of the constrained variable and the constraint upper limit and the constraint lower limit in other constraint equations except the constraint equation of the quantity to be purchased when the optimization model of the refining production plan is used for determining the purchasing marginal benefit data;
determining whether the purchasing interval to be analyzed meets the partition condition according to the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed, the state of the association constraint and the difference between the boundary values of the purchasing interval to be analyzed; the partition conditions include: the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference value between the boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision;
If the purchasing interval to be analyzed meets the partition condition, dividing the purchasing interval to be analyzed into at least two purchasing amount intervals according to the boundary value of the purchasing interval to be analyzed; and
and re-executing the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed and the state of the associated constraint according to the purchasing interval to be analyzed and the refining production plan optimization model.
In one embodiment, the association determination module 403 may specifically be configured to:
for each to-be-purchased quantity interval, the following operations are executed:
taking the highest to-be-purchased quantity in the to-be-purchased quantity interval, the purchasing marginal benefit data corresponding to the highest to-be-purchased quantity, and at least one group of data in the purchasing marginal benefit data corresponding to the lowest to-be-purchased quantity and the lowest to-be-purchased quantity as a purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval;
and determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval.
In one embodiment, the apparatus for determining a crude oil processing scheme may further include:
The adjustment module is used for determining that the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is suddenly changed when the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference and the state of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed is different; if the difference value between the boundary values of the purchasing interval to be analyzed is smaller than or equal to the preset analysis precision, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference is used as a bottleneck factor that the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is suddenly changed; and adjusting the processing scheme of the crude oil to be processed according to the bottleneck factors.
In one embodiment, associating the state of the constraint may include: a card upper limit state, a card lower limit state and a card edge-free state;
the card upper limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset upper limit; the card lower limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset lower limit; the non-edge clamping state is as follows: the value of the constrained variable in the association constraint equation determined according to the refining production plan optimization model is between a preset upper limit and a preset lower limit.
In the embodiment of the determination device for crude oil processing scheme, specific processing of each module and technical effects brought by the specific processing may refer to the related description in the corresponding method embodiment respectively, and will not be described herein again.
An embodiment of the present invention further provides a computer device, and fig. 5 is a schematic diagram of the computer device in the embodiment of the present invention, where, as shown in fig. 5, the electronic device includes: a plurality of processors 501, a plurality of communication interfaces 502, a plurality of memories 503 and a plurality of communication buses 504; alternatively, the communication interface 502 may be an interface of a communication module, such as an interface of a GSM module; the processor 501 may be a processor CPU or a specific integrated circuit ASIC (Application Specific Integrated Circuit) or one or more integrated circuits configured to implement embodiments of the present invention. The memory 503 may comprise a high-speed RAM memory or may further comprise a non-volatile memory (non-volatile memory), such as a plurality of disk memories. Wherein the memory 503 stores a program, and the processor 501 invokes the program stored in the memory 503 to perform some or all of the method embodiments described above.
Embodiments of the present invention also provide a computer-readable storage medium storing a computer program for executing the above-described method of determining a crude oil processing scheme.
Embodiments of the present invention also provide a computer program product comprising a computer program which, when executed by a processor, implements a method of determining a crude oil processing scheme.
In summary, according to the embodiment of the invention, the upper limit and the lower limit of the parameter of the to-be-purchased quantity in the constraint equation of the to-be-purchased quantity are determined according to the purchase price data of the to-be-processed crude oil and the pre-established optimization model of the refining production plan; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed; determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model; determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased; according to the association relation between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data, the processing scheme of the crude oil to be processed is determined, and compared with the technical scheme that a nonlinear programming model is established and solved to obtain the crude oil processing scheme in the prior art, the purchasing marginal benefit of processing a certain crude oil can be continuously changed along with the change of the processing quantity under a certain constraint condition, and the corresponding relation between the purchasing marginal benefit data and the processing quantity of processing a certain crude oil can be accurately obtained, so that a scientific and reasonable crude oil processing scheme is determined.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (14)

1. A method of determining a crude oil processing plan, comprising:
determining the upper limit and the lower limit of parameters of the to-be-purchased quantity in a constraint equation of the to-be-purchased quantity according to purchase price data of the to-be-processed crude oil and a pre-established optimization model of the refining production plan; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of the to-be-purchased quantity parameters and the refining production plan optimization model;
determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
and determining the processing scheme of the crude oil to be processed according to the association relation between the crude oil to be processed to be purchased and the purchasing marginal benefit data.
2. The method of claim 1, wherein determining the upper and lower limits of the parameters of the quantity to be purchased in the constraint equation of the quantity to be purchased according to the purchase price data of the crude oil to be processed and the pre-established optimization model of the refining production plan comprises:
Adjusting purchase price data of crude oil to be processed into first purchase price data; the first purchase price data is larger than market purchase price data of crude oil to be processed;
inputting the first purchase price data into a pre-established refining production plan optimization model, and determining the lower limit of a to-be-purchased quantity parameter of crude oil to be processed;
adjusting the purchase price data of the crude oil to be processed into second purchase price data; the second purchase price data is smaller than market purchase price data of crude oil to be processed;
and inputting the second purchase price data into a refining production plan optimization model, and determining the upper limit of the parameters of the to-be-purchased amount of the crude oil to be processed.
3. The method of claim 1, wherein determining a plurality of intervals of amounts to be purchased based on the upper and lower limits of the parameters of amounts to be purchased and the optimization model of the refining production plan comprises:
determining a purchasing interval to be analyzed according to the upper limit and the lower limit of the parameter of the purchasing quantity to be analyzed;
the following steps are repeatedly executed until all the purchasing intervals to be analyzed do not meet the partition conditions, and a plurality of purchasing intervals are determined:
according to the purchasing interval to be analyzed and the refining production plan optimization model, determining purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed and the state of the associated constraint; the state of the associated constraint is the relation between the value of the constrained variable and the constraint upper limit and the constraint lower limit in other constraint equations except the constraint equation of the quantity to be purchased when the optimization model of the refining production plan is used for determining the purchasing marginal benefit data;
Determining whether the purchasing interval to be analyzed meets the partition condition according to the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed, the state of the association constraint and the difference between the boundary values of the purchasing interval to be analyzed; the partition conditions include: the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference value between the boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision;
if the purchasing interval to be analyzed meets the partition condition, dividing the purchasing interval to be analyzed into at least two purchasing amount intervals according to the boundary value of the purchasing interval to be analyzed; and
and taking each divided to-be-purchased quantity interval as a to-be-analyzed purchase interval respectively.
4. The method of claim 3, wherein determining the association between the to-be-purchased quantity of the crude oil to be processed and the purchase marginal benefit data according to the purchase marginal benefit data corresponding to the boundary values of the plurality of to-be-purchased quantity intervals comprises:
for each to-be-purchased quantity interval, the following operations are executed:
Taking the highest to-be-purchased quantity in the to-be-purchased quantity interval, the purchasing marginal benefit data corresponding to the highest to-be-purchased quantity, and at least one group of data in the purchasing marginal benefit data corresponding to the lowest to-be-purchased quantity and the lowest to-be-purchased quantity as a purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval;
and determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval.
5. The method as recited in claim 4, further comprising:
when the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the change quantity of the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is determined to be larger than a preset threshold value;
if the difference value between the boundary values of the purchasing interval to be analyzed is smaller than or equal to the preset analysis precision, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference is used as a bottleneck factor that the variation of the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is larger than a preset threshold value;
And adjusting the processing scheme of the crude oil to be processed according to the bottleneck factors.
6. The method of claim 4, wherein associating the state of the constraint comprises: a card upper limit state, a card lower limit state and a card edge-free state;
the card upper limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset upper limit;
the card lower limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset lower limit;
the non-edge clamping state is as follows: the value of the constrained variable in the association constraint equation determined according to the refining production plan optimization model is between a preset upper limit and a preset lower limit.
7. A crude oil processing scheme determining apparatus, comprising:
the upper limit and the lower limit of the parameter of the to-be-purchased quantity are determined according to the purchasing price data of the crude oil to be processed and a pre-established refining production plan optimization model, and the upper limit and the lower limit of the parameter of the to-be-purchased quantity are determined in a constraint equation of the to-be-purchased quantity; the refining production plan optimization model is a refining production plan optimization model of crude oil to be processed in the oil refinery, which is established with the aim of maximizing profit data of the oil refinery; the refining production plan optimization model comprises a constraint equation of the amount to be purchased of the crude oil to be processed;
The to-be-purchased quantity interval determining module is used for determining a plurality of to-be-purchased quantity intervals according to the upper limit and the lower limit of to-be-purchased quantity parameters and the refining production plan optimizing model;
the incidence relation determining module is used for determining incidence relation between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data corresponding to the boundary values of the multiple to-be-purchased quantity intervals; the purchasing marginal benefit data is marginal benefit data of a constraint equation of the quantity to be purchased;
the processing scheme determining module is used for determining the processing scheme of the crude oil to be processed according to the association relation between the crude oil to be processed to be purchased and the purchasing marginal benefit data.
8. The apparatus of claim 7, wherein the means for determining the upper and lower limits of the quantity to be purchased is specifically configured to:
adjusting purchase price data of crude oil to be processed into first purchase price data; the first purchase price data is larger than market purchase price data of crude oil to be processed;
inputting the first purchase price data into a pre-established refining production plan optimization model, and determining the lower limit of a to-be-purchased quantity parameter of crude oil to be processed;
adjusting the purchase price data of the crude oil to be processed into second purchase price data; the second purchase price data is smaller than market purchase price data of crude oil to be processed;
And inputting the second purchase price data into a refining production plan optimization model, and determining the upper limit of the parameters of the to-be-purchased amount of the crude oil to be processed.
9. The apparatus of claim 7, wherein the to-be-purchased-amount interval determining module is specifically configured to:
determining a purchasing interval to be analyzed according to the upper limit and the lower limit of the parameter of the purchasing quantity to be analyzed;
the following steps are repeatedly executed until all the purchasing intervals to be analyzed do not meet the partition conditions, and a plurality of purchasing intervals are determined:
according to the purchasing interval to be analyzed and the refining production plan optimization model, determining purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed and the state of the associated constraint; the state of the associated constraint is the relation between the value of the constrained variable and the constraint upper limit and the constraint lower limit in other constraint equations except the constraint equation of the quantity to be purchased when the optimization model of the refining production plan is used for determining the purchasing marginal benefit data;
determining whether the purchasing interval to be analyzed meets the partition condition according to the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed, the state of the association constraint and the difference between the boundary values of the purchasing interval to be analyzed; the partition conditions include: the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference value between the boundary values of the purchasing interval to be analyzed is larger than the preset analysis precision;
If the purchasing interval to be analyzed meets the partition condition, dividing the purchasing interval to be analyzed into at least two purchasing amount intervals according to the boundary value of the purchasing interval to be analyzed; and
and taking each divided to-be-purchased quantity interval as a to-be-analyzed purchase interval respectively.
10. The apparatus of claim 9, wherein the association determination module is specifically configured to:
for each to-be-purchased quantity interval, the following operations are executed:
taking the highest to-be-purchased quantity in the to-be-purchased quantity interval, the purchasing marginal benefit data corresponding to the highest to-be-purchased quantity, and at least one group of data in the purchasing marginal benefit data corresponding to the lowest to-be-purchased quantity and the lowest to-be-purchased quantity as a purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval;
and determining the association relationship between the to-be-purchased quantity of the crude oil to be processed and the purchasing marginal benefit data according to the purchasing marginal benefit data pair corresponding to the to-be-purchased quantity interval.
11. The apparatus of claim 10, further comprising an adjustment module to:
when the difference value between the purchasing marginal benefit data corresponding to the boundary value of the purchasing interval to be analyzed is larger than the preset marginal benefit difference, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the change quantity of the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is determined to be larger than a preset threshold value;
If the difference value between the boundary values of the purchasing interval to be analyzed is smaller than or equal to the preset analysis precision, the difference exists between the states of the association constraint corresponding to the boundary value of the purchasing interval to be analyzed, and the difference is used as a bottleneck factor that the variation of the purchasing marginal benefit corresponding to the purchasing interval to be analyzed is larger than a preset threshold value;
and adjusting the processing scheme of the crude oil to be processed according to the bottleneck factors.
12. The apparatus of claim 10, wherein the state of the association constraint comprises: a card upper limit state, a card lower limit state and a card edge-free state;
the card upper limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset upper limit;
the card lower limit state is: the value of a constrained variable in an association constraint equation determined according to the refining production plan optimization model reaches a preset lower limit;
the non-edge clamping state is as follows: the value of the constrained variable in the association constraint equation determined according to the refining production plan optimization model is between a preset upper limit and a preset lower limit.
13. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 6 when executing the computer program.
14. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 6.
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CN111507496A (en) * 2019-01-30 2020-08-07 中国石油化工股份有限公司 Method for determining optimal yield scale of crude oil
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