Refining production plan optimization method, device and application

Abstract

The invention discloses a refining production plan optimization method and device and application, and the method comprises the steps: building a constraint equation based on production operation parameters, and the production operation parameters comprise a unit carbon emission parameter of a material and refinery material carbon footprint tracking data; based on the constraint equation and a preset target equation, constructing a refining production plan optimization model; and analyzing the refining production plan optimization model, and determining a refining production optimization plan, a carbon footprint tracking value and an oil product unit carbon emission value. According to the method, a physical property transfer structure of the secondary processing device according to schemes and raw materials is established, and a corresponding physical property calculation equation is established, so that carbon emission transfer from feeding to discharging in the secondary processing device is realized. A double-LP model alternating solving algorithm based on a distributed recursion technology effectively solves a refining production plan optimization model which comprises a whole-plant carbon footprint tracking structure and product unit carbon emission constraint and is provided with circulating materials between devices.

Description

Technical Field

[0001] The present invention relates to the technical field of refining and chemical processing, and particularly to a method, device and application for optimizing a refining and chemical production plan. Background Art

[0002] The petroleum refining and chemical processing process is complex. After multiple crude oils are processed by the atmospheric and vacuum distillation unit, and then processed by secondary processing units such as continuous reforming, residue hydrotreating, fluid catalytic cracking, gasoline and diesel hydrotreating, and alkylation, as well as through steps such as product blending, numerous products such as gasoline, kerosene, diesel, lubricating oil, paraffin wax, and asphalt are produced. Traditionally, when formulating a production plan, refining and chemical enterprises will use professional refining plan optimization software to establish a mathematical programming model, taking into account constraints such as raw material supply, product demand, unit capacity, and product specifications, with the goal of maximizing the economic benefits of the refining and chemical enterprise, and solving to obtain a production plan that meets the constraints.

[0003] Refining and chemical enterprises are major carbon emitters. With the promotion of the country's "dual carbon" goal, it is required that when formulating a production plan, refining and chemical enterprises can simultaneously carry out the carbon footprint tracking of the whole plant. When generating a production plan, the carbon emissions during the production process of the unit can be gradually transferred to the final products to obtain the unit carbon emissions of each product, that is, the "carbon label". In addition, when formulating a production plan, the upper limit of the unit carbon emissions of specific products can be used as a constraint condition, so that the obtained production plan meets the low-carbon requirements of specific products.

[0004] To achieve the above goals, in the refining plan optimization model, it is necessary to establish a carbon emission transfer structure from feed to product for the atmospheric and vacuum distillation unit, secondary processing units, and blending tanks respectively. Among the secondary processing units, since some units have multiple production plans and the raw materials for each production plan may be more than one, it is necessary to establish a carbon emission transfer structure for the unit's sub-plans and sub-raw materials. However, current refining plan optimization software does not have the function of transferring physical properties for sub-plans and sub-raw materials, and cannot model and solve for the business requirements of the whole plant carbon footprint tracking and product unit carbon emissions constraints.

[0005] Since a refining and chemical enterprise usually has multiple production units and multiple materials, and the production process is complex, the number of non-linear equations in a refining plan optimization model that includes the whole plant carbon transfer structure is numerous. If the above model is directly handed over to a non-linear solver (such as baron, etc.), it is difficult to ensure that the solution can be completed within an acceptable time. In the prior art, the principle of the distributed recursive technology for solving the refining plan optimization model is as Figure 1 shown. In step 4, new physical properties are calculated based on the material quantity results, and no specific implementation method is given in the literature. The common practice in the industry currently is to calculate the physical properties of each material sequentially from the front to the back according to the flow sequence of the material in the whole plant. The disadvantage of this method is that it cannot calculate the physical properties of the circulating material flow between units. Summary of the invention

[0006] The present invention aims to provide a method, device and application for optimizing a refinery production plan. To achieve the above-mentioned object, the present invention provides the following technical solutions:

[0007] A first aspect of the present invention provides a method for optimizing a refinery production plan, the method comprising:

[0008] Constructing constraint equations based on production operation parameters, wherein the production operation parameters include material unit carbon emission parameters and refinery material carbon footprint tracking data;

[0009] Based on the constraint equation and the preset target equation, a refinery production plan optimization model is constructed;

[0010] The refinery production plan optimization model is analyzed to determine the refinery production optimization plan, carbon footprint tracking value and unit carbon emission value of oil products.

[0011] Furthermore, the constraint equations include: constraint equations related to carbon emission transfer, plant-wide material balance equations, upper and lower limit constraint equations for device capacity, and utility consumption calculation equations.

[0012] Furthermore, the constraint equations related to the transfer of carbon emissions include a calculation equation for the amount of material in the normal pressure reduction side line, a calculation equation for the physical properties of the material in the normal pressure reduction side line, a calculation equation for the amount of material in the secondary processing device, a calculation equation for the unit carbon emissions of the material output by the secondary processing device, an upper limit constraint equation for the unit carbon emissions of the material output by the secondary processing device, a calculation equation for the amount of material in the blending tank, a calculation equation for the physical properties of the blended product, and an upper limit constraint equation for the carbon emissions of the blended product.

[0013] Furthermore, the preset objective equation is a refinery profit maximization function based on a constraint function constructed based on product sales revenue, raw material procurement cost and utility procurement cost.

[0014] Furthermore, the formula of the preset objective equation is expressed as follows:

[0015] Max profit=Σ ms Price ms ·WM ms -Σ mp Cost mp ·WM mp -∑ ul UCost ul UB ul

[0016] Among them, Max profit means the maximum profit, Pricems is the selling unit price of material ms, Cost mp is the purchase unit price of material mp, UCost ul is the purchase unit price of utility ul, WM ms is the quantity of material ms sold, WM mp is the quantity of material mp purchased, UB ul is the quantity of utility ul purchased.

[0017] Furthermore, analyzing the optimization model of the refining production plan to determine the optimized refining production plan, carbon footprint tracking value, and unit carbon emission value of the oil product, including:

[0018] Extracting the constraint equations related to carbon emission transfer from the constraint equations, based on the non-linear constraint equations in the constraint functions related to carbon emission transfer;

[0019] Constructing a first linear programming model based on the physical property variables in the non-linear constraint equations;

[0020] Constructing a second linear programming model based on the material quantity variables in the non-linear constraint equations;

[0021] Alternately solving the first linear programming model and the second linear programming model using a dual LP model based on distributed recursive technology to obtain the solution of the optimization model of the refining production plan;

[0022] Based on the solution of the optimization model of the refining production plan, determining the optimized refining production plan, carbon footprint tracking value, and unit carbon emission value of the oil product.

[0023] Furthermore, alternately solving the first linear programming model and the second linear programming model using a dual LP model based on distributed recursive technology to obtain the solution of the optimization model of the refining production plan, including:

[0024] Assigning values to the physical property parameters in the production operation parameters;

[0025] Based on the assignment, calculating the first linear programming model to obtain the solution of the first linear programming model; the solution of the first linear programming model is the value of the material quantity variable based on the physical property variables;

[0026] Based on the solution of the first linear programming model, calculating the second linear programming model to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the updated value of the physical property variable;

[0027] Calculating the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model;

[0028] When the relative deviation value < the predetermined convergence accuracy value, the physical property variables assignment in the first linear programming model, the material quantity variable values and the objective function values obtained by solving the first linear programming model are the solutions of the refining production plan optimization model;

[0029] Based on the solutions of the refining production plan optimization model, obtain the optimized refining production plan, carbon footprint tracking value and unit carbon emission value of the oil products.

[0030] Further, the physical property variables include: the unit carbon emission of the atmospheric and vacuum side stream mi, the unit carbon emission of the material mq produced by the secondary unit e in the plan p, the unit carbon emission of the feed mf of the secondary unit e in the plan p, the unit carbon emission of the material mq produced by the secondary unit, the unit carbon emission of the blending product mb, and the unit carbon emission of the blending component mh;

[0031] The material quantity variables include the quantity of the sold material ms, the quantity of the purchased material mp, the quantity of the purchased utility ul, the quantity of the side stream material mi produced by the atmospheric and vacuum unit c, the quantity of the crude oil mc processed in the unit c, the quantity of the material mq produced by the secondary unit e in the plan p, the processing quantity of the secondary unit e in the plan p, the quantity of the material mf consumed by the secondary unit e, the quantity of the material mq produced by the secondary unit e, the quantity of the material mb blended in the blending tank b, and the quantity of the material mh used for blending the material mb in the blending tank b.

[0032] The second aspect of the present invention provides a device for optimizing the refining production plan, and the device includes,

[0033] The first construction module is used to construct a constraint equation based on the production operation parameters, and the production operation parameters include the unit carbon emission parameter of the material and the refinery material carbon footprint tracking data;

[0034] The second construction module is used to construct a refining production plan optimization model based on the constraint equation and the preset objective equation;

[0035] The determination module is used to analyze the refining production plan optimization model to determine the refining production optimization plan, carbon footprint tracking value and unit carbon emission value of the oil products.

[0036] Further, the steps executed by the determination module include:

[0037] Assign values to the physical property parameters in the production operation parameters;

[0038] Based on the assignment, calculate the first linear programming model to obtain the solution of the first linear programming model; the solution of the first linear programming model is the value of the material quantity variable based on the physical property variables;

[0039] Based on the solution of the first linear programming model, calculate the second linear programming model to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the updated value of the physical property variables;

[0040] Calculate the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model;

[0041] When the relative deviation value < the predetermined convergence accuracy value, the assignment of the physical property variables in the first linear programming model, the material quantity variable value and the objective function value obtained by solving the first linear programming model are the solutions of the refining production plan optimization model;

[0042] Based on the solution of the refining production plan optimization model, obtain the optimized refining production plan, carbon footprint tracking value and unit carbon emission value of the oil product.

[0043] The third aspect of the present invention provides an application of the method for optimizing the refining production plan as described above in calculating the unit carbon emissions of each circulating material between computing devices.

[0044] The fourth aspect of the present invention provides a storage medium, on which a program or instruction is stored, and when the program or instruction is run by a processor, the steps of the refining production plan optimization method as described above are implemented.

[0045] The fifth aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps of the above-mentioned refining production plan optimization method are implemented.

[0046] The technical effects and advantages of the present invention:

[0047] 1. A method is proposed for establishing a physical property transfer structure of "dividing schemes and dividing raw materials" for secondary processing units in a refining plan optimization model, and establishing corresponding physical property calculation equations, so as to realize the carbon emission transfer from feedstock to product in secondary processing units.

[0048] 2. A dual LP model alternating solution algorithm based on distributed recursive technology is proposed, which can effectively solve the refining production plan optimization model including the whole plant carbon footprint tracking structure and product unit carbon emission constraints and with circulating materials between units.

[0049] Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures pointed out in the specification and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1Schematic diagram of the distributed recursive technology for optimizing the refining plan in the prior art solution;

[0051] Figure 2 Schematic flow chart of a method for optimizing the refining production plan provided by an embodiment of the present invention;

[0052] Figure 3 Schematic diagram of the recycling of materials in a method for optimizing the refining production plan provided by an embodiment of the present invention;

[0053] Figure 4 Schematic diagram of the distributed recursive technology for optimizing the refining plan in a method for optimizing the refining production plan provided by an embodiment of the present invention;

[0054] Figure 5 Provided by an embodiment of the present invention Figure 4 One of the process schematic diagrams;

[0055] Figure 6 Provided by an embodiment of the present invention Figure 4 Another process schematic diagram;

[0056] Figure 7 Schematic diagram of a refining production plan optimization processing device provided by an embodiment of the present invention;

[0057] Figure 8 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] To solve the deficiencies of the prior art, the present invention discloses a method for optimizing the refining production plan. As Figure 2 shown, the method includes,

[0060] Constructing a constraint equation based on production operation parameters, where the production operation parameters include the unit carbon emission parameter of materials and the refinery material carbon footprint tracking data; constructing a refining production plan optimization model based on the constraint equation and a preset target equation; analyzing the refining production plan optimization model to determine the refining production optimization plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product.

[0061] In a specific embodiment of the present invention, in the refining and chemical production plan optimization model, the "unit carbon emission" of the material is modeled as a kind of "physical property", and the symbol descriptions in the model are shown in Table 1:

[0062] Table 1. Symbol descriptions in the refining and chemical production plan optimization model

[0063]

[0064]

[0065]

[0066] The objective function of the refining and chemical production plan optimization model is to maximize the profit of the whole plant. The preset objective equation is a refinery profit maximization function based on product sales revenue, raw material procurement cost, and utility procurement cost and constructed based on the constraint function.

[0067] Profit = Product sales revenue - Raw material procurement cost - Utility procurement cost.

[0068] The above formula is expressed as follows:

[0069] Max profit = ∑ ms Price ms ·WM ms - Σ mp Cost mp ·WM mp - ∑ ul UCost ul ·UB ul

[0070] Among them, Max profit represents the maximum profit, Price ms is the selling unit price of the material ms, Cost mp is the procurement unit price of the material mp, UCost ul is the procurement unit price of the utility ul, WM ms is the quantity of the material ms sold, WM mp is the quantity of the material mp purchased, UB ul is the quantity of the utility ul purchased.

[0071] The constraint equations include: constraint equations related to carbon emission transfer, the whole plant balance equation of materials, the upper and lower limit constraint equations of device capacity, and the utility consumption calculation equation.

[0072] The constraint equations related to carbon emission transfer include the calculation equation for the amount of side-stream materials in the atmospheric and vacuum distillation units, the physical property calculation equation for the side-stream materials in the atmospheric and vacuum distillation units, the calculation equation for the amount of materials in the secondary processing units, the calculation equation for the unit carbon emission of the materials produced by the secondary processing units, the upper limit constraint equation for the unit carbon emission of the materials produced by the secondary processing units, the calculation equation for the amount of materials in the blending tank, the physical property calculation equation for the blended products, and the upper limit constraint equation for the carbon emission of the blended products. Among them,

[0073] In a specific embodiment of the present invention, the constraint equations related to carbon emission transfer in the atmospheric and vacuum distillation units are as follows:

[0074] (1) Calculation equation for the amount of side-stream materials in the atmospheric and vacuum distillation units:

[0075] WM c,mi = ∑ mc WM c,mc ·CCTU c,mc,mi

[0076] Wherein, WM c,mi is the amount of side-stream material mi produced by the atmospheric and vacuum distillation unit c, WM c,mc is the amount of crude oil mc processed in the unit c, and CCTU c,mc,mi is the cutting yield of side-stream mi of crude oil mc in the atmospheric and vacuum distillation unit c.

[0077] (2) Calculation equation for the carbon emission of side-stream materials in the atmospheric and vacuum distillation units:

[0078] MQ mi,CO2 = ∑ c,mc WM c,mc ·CCTU c,mc,m ·CCTUQ c,mc,mi,CO2 / Σ c WM c,mi

[0079] Equivalent to:

[0080] MQ mi,CO2 * Σ c WM c,mi = Σ c,mc WM c,mc ·CCTU c,mc,m ·CCTUQ c,mc,mi,CO2

[0081] Wherein, MQ mi,CO2 is the unit carbon emission of side-stream mi in the atmospheric and vacuum distillation units, WM c,mc is the amount of crude oil mc processed in the atmospheric and vacuum distillation unit c, CCTU c,mc,mi is the cutting yield of side-stream mi of crude oil mc in the atmospheric and vacuum distillation unit c, and CCTUQ c,mc,mi,CO2is the unit carbon emission of the side stream mi of the crude oil mc in the atmospheric and vacuum distillation unit c, WM c,mi is the amount of the side stream material mi produced by the atmospheric and vacuum distillation unit c.

[0082] The above parameter CCTUQ c,mc,mi,CO2 can be obtained according to the carbon amount emitted per unit of crude oil processed by the unit, combined with principles such as mass distribution, calorific value distribution, or product value distribution.

[0083] In a specific embodiment of the present invention, the constraint equations related to carbon emission transfer in the secondary processing unit are as follows: The carbon transfer in the refining production plan optimization model of the present invention in the secondary processing unit is realized through the physical property transfer structure of "dividing the plan and dividing the raw materials". The refining production plan optimization model of the present invention can calculate the unit carbon emission of each raw material. Taking the wax oil hydrofining unit of a certain refinery as an example, as shown in Table 2:

[0084] Table 2 Wax oil hydrofining unit of a certain refinery

[0085]

[0086]

[0087] As shown in the above table, this unit has two processing plans. The raw materials for Plan 1 are the third side stream and hydrogen, and the raw materials for Plan 2 are coking heavy wax oil and hydrogen. The products produced by both plans are wax oil hydrofining dry gas, wax oil hydrofining naphtha, and hydrotreated wax oil, but the yields are different. In addition, the unit carbon emissions of the two plans are also different.

[0088] For this unit, it is necessary to allocate the carbon emissions in each raw material and the carbon emitted due to the energy consumption of this plan to the products wax oil hydrofining naphtha 2DA and hydrotreated wax oil 2DD through the physical property transfer structure, and then weight-average the unit carbon emissions of a certain product obtained from each plan according to the output to obtain the unit carbon emission of this product.

[0089] Specifically, the constraint equations related to carbon transfer in the secondary processing unit are:

[0090] (1) Material amount calculation equation for the materials produced by the secondary unit:

[0091] WPM e,p,mq = WUP e,p ·UPR e,p,mq

[0092]

[0093] Among them, WPM e,p,mq is the amount of the material mq produced by the secondary unit e in Plan p, and WUP e,pThe processing volume of the process p in the secondary device e, UPR e,p,mq The yield of the material mq produced by the process p of the secondary device e, WM e,mq Is the amount of the material mq produced by the secondary device e.

[0094] Calculation equation for the amount of material consumed by the secondary device:

[0095] WPM e,p,mf = WUP e,p ·UPR e,p,mf

[0096]

[0097] Among them, WPM e，p，mf Is the amount of the material mf consumed by the process p in the secondary device e, WUP e,p Is the processing volume of the process p in the secondary device e, UPR e,p,mf Is the unit consumption of the material mf consumed by the process p of the secondary device e, WM e,mf Is the amount of the material mf consumed by the secondary device e.

[0098] (2) Calculation equation for the unit carbon emission of the material produced by the secondary device:

[0099]

[0100] Is equivalent to:

[0101]

[0102] Among them, MPQ e,p,mq,CO2 Is the unit carbon emission of the material mq produced by the process p in the secondary device e, MQ mf,CO2 Is the unit carbon emission of the feed mf of the process p of the secondary device e; A e,p,mf,mq,CO2 And B e,p,mq,CO2 Are respectively the coefficients for transferring the unit carbon emission of the feed mf and the carbon emitted due to the energy consumption of this process to the product mq in the process p of the device e; UPR e,p,mf Is the unit consumption of the feed mf in the process p of the secondary device e; MQ mq,CO2 Is the unit carbon emission of the material mq produced by the secondary device.

[0103] In the above formula, the transfer coefficient A can be calculated from the unit consumption of raw materials, product yield, etc. of the corresponding process, and the transfer coefficient B can be calculated from the amount of carbon emitted due to energy consumption, product yield, etc. of the corresponding process.

[0104] (3) Upper limit constraint equation for the unit carbon emission of the material produced by the secondary processing device:

[0105]

[0106] In the formula, is the upper limit of the unit carbon emission of material mq set according to business needs.

[0107] 3. Blending tank:

[0108] (1) Equation for calculating the amount of material in the blended product

[0109]

[0110] Where WM b，mb is the amount of material mb blended in blending tank b, and XB b，mb,mh is the amount of blending component mh used for blending material mb in blending tank b.

[0111] (2) Equation for calculating the physical properties of the blended product

[0112] MQ mb,CO2 = Σ b,mh (MQ mh,CO2 * XB b,mb,mh ) / Σ b WM b,mb

[0113] Equivalent to:

[0114] MQ mb,CO2 * ∑ b WM b,mb = ∑ b,mh (MQ mh,CO2 * XB b,mb,mh )

[0115] Where, MQ mb,CO2 is the unit carbon emission of blended product mb, MQ mh,CO2 is the unit carbon emission of blending component mh of blended product mb, XB b,mb,mh is the amount of component mh used for blending material mb in blending tank b, and WM b,mb is the amount of material mb blended in blending tank b.

[0116] (3) Constraint equation for the upper limit of carbon emission of the blended product:

[0117]

[0118] In the formula, is the upper limit of the unit carbon emission of the blended product set according to business needs.

[0119] In addition to the constraint equations related to carbon emission transfer, the refinery production plan optimization model also includes the plant-wide material balance equation, the upper and lower limit constraint equations of device capacity, and the calculation equation of utility consumption, etc.

[0120] Among them,

[0121] For the purchased material mp, its material balance equation for the whole plant is:

[0122]

[0123] Among them, WM mp is the purchase quantity of the material mp, WM c,mc is the quantity of the crude oil mc processed in the atmospheric and vacuum distillation unit c, XB b,mb,mh is the quantity of the blending component mh used for blending the material mb in the blending tank b, WM e,mf is the quantity of the material mf consumed by the secondary processing unit e. For any purchased material mp, the above formula holds when mc, mh, and mf are equal to mp, that is, the purchase quantity of a material is equal to the sum of the quantity of the material entering the atmospheric and vacuum distillation unit, the quantity of the material entering the secondary processing unit, and the quantity of the material entering the blending tank.

[0124] For the sold material ms, its material balance equation for the whole plant is:

[0125]

[0126]

[0127] Among them, WM ms is the sales quantity of the material ms, WM c,mi is the quantity of the side stream material mi produced by the atmospheric and vacuum distillation unit c, WM b,mb is the quantity of the material mb blended in the blending tank b, WM e,mq is the quantity of the material mq produced by the secondary unit e. For any sold material ms, the above formula holds when mi, mb, and mq are equal to mp, that is, the sales quantity of a material is equal to the sum of the quantity of the material produced by the atmospheric and vacuum distillation unit, the secondary processing unit, and the blending tank.

[0128] In a specific embodiment of the present invention, in the above refining production plan optimization model, the variables in the constraint equations can be divided into two categories, one is the material quantity variable, and the other is the physical property value variable, as shown in Table 3:

[0129] Table 3 Variable classification table in the refining production plan optimization model

[0130]

[0131]

[0132] It can be seen that in the carbon emission calculation equation for the atmospheric and vacuum side streams, the unit carbon emission calculation equation for the materials produced by the secondary units, and the physical property calculation equation for the blended products, the material quantity variable and the physical property value variable are multiplied. Therefore, these types of equations are non-linear equations.

[0133] Since a refinery usually has multiple production units and multiple materials, and the production process is complex, there are a large number of non-linear equations in a refinery planning optimization model that includes the carbon transfer structure of the whole plant. If the above model is directly handed over to a non-linear solver (such as baron, etc.), it is difficult to ensure that the solution can be completed within an acceptable time.

[0134] In a specific embodiment of the present invention, for the materials, including recycled materials and non-recycled materials, the recycled materials refer to the feed of a unit, which after being processed by this unit and several subsequent units, is produced again and returned to this unit as the feed. For example Figure 3 the material A shown is a recycled material between units. Figure 3 It is a schematic diagram of the recycling of materials in a refinery production planning optimization method provided by an embodiment of the present invention. As Figure 3 shown, in this embodiment, it is necessary to track the refinery carbon footprint. In the secondary unit 1, the unit carbon emissions of materials C and D need to be calculated from the unit carbon emissions of materials A and B respectively; in the secondary unit 2, the unit carbon emissions of materials F and G need to be calculated from the unit carbon emissions of materials C and E respectively; in the secondary unit 3, the unit carbon emissions of materials A and I need to be calculated from the unit carbon emissions of materials G and H respectively. Since material A is a recycled material and the order of the materials cannot be determined, therefore, the unit carbon emissions of each material cannot be obtained by deduction. Assuming there are no recycled materials in the figure, then Figure 2 the materials in it have a sequence, and thus, the unit carbon emissions of each material can be obtained by sequential deduction.

[0135] If a whole-plant carbon footprint tracking structure is established, then in unit 1, the unit carbon emission of material C needs to be calculated from the unit carbon emissions of materials A and B; in unit 2, the unit carbon emission of material G needs to be calculated from the unit carbon emissions of materials C and E; in unit 3, the unit carbon emission of material A needs to be calculated from the unit carbon emissions of materials G and H. In this case, using the prior art such as Figure 1The technical method shown will be unable to determine the sequence of materials, and thus the unit carbon emissions of each material cannot be obtained through calculation. For this reason, this embodiment proposes an alternating solution algorithm for two linear programming (LP) models based on the distributed recursive technology. By assigning values to the physical property parameters (physical property value variables), the physical property parameters (physical property value variables) are changed into constants, and by assigning values to the material quantity parameters, the material quantity parameters are changed into constants. In this way, in the non-linear function, only material quantity parameters or physical property parameters are included, so that the non-linear function is transformed into a linear function, greatly reducing the amount of computation required for the solution and effectively reducing the solution time.

[0136] For this reason, in a specific embodiment of the present invention, an alternating solution algorithm for a dual LP model based on the distributed recursive technology is proposed, and a model is established. Its constraint equations include: the carbon emissions calculation equation for the atmospheric and vacuum side streams, the unit carbon emissions calculation equation for the materials produced by the secondary units, the unit carbon emissions calculation equation for the material mq produced by the secondary unit e in the scenario p, and the physical property calculation equation for the products. Among them, for the non-linear equations, namely the carbon emissions calculation equation for the atmospheric and vacuum side streams, the unit carbon emissions calculation equation for the materials produced by the secondary units, and the physical property calculation equation for the blended products, the material quantity variables are fixed according to the calculation results of the previous model, so as to transform the non-linear equations into linear equations. Applying an LP solver to solve the above sub-models can obtain the values of the physical property variables. Thus, by analyzing the refinery production plan optimization model, the refinery production optimization plan, the carbon footprint tracking value, and the unit carbon emissions value of the oil products can be determined, and the above problems can be effectively solved.

[0137] In a specific embodiment of the present invention, analyzing the refinery production plan optimization model to determine the refinery production optimization plan, the carbon footprint tracking value, and the unit carbon emissions value of the oil products includes:

[0138] Extracting the constraint equations related to carbon emissions transfer from the constraint equations, based on the non-linear constraint equations in the constraint functions related to carbon emissions transfer;

[0139] Based on the physical property variables in the non-linear constraint equations, constructing a first linear programming model;

[0140] Based on the material quantity variables in the non-linear constraint equations, constructing a second linear programming model;

[0141] Using the dual LP model based on the distributed recursive technology to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refinery production plan optimization model;

[0142] Based on the solution of the refinery production plan optimization model, determining the optimized refinery production plan, the carbon footprint tracking value, and the unit carbon emissions value of the oil products.

[0143] In a specific embodiment of the present invention, the dual LP model based on the distributed recursive technology alternately solves the first linear programming model and the second linear programming model to obtain the solution of the refinery production plan optimization model, including:

[0144] Assign values to the physical property parameters in the production operation parameters; this assignment serves as the initial value of the physical property variables of the first linear programming model;

[0145] Based on the above assignment, calculate the first linear programming model to obtain the solution of the first linear programming model; the solution of the first linear programming model is the value of the material quantity variable based on the physical property variables;

[0146] Based on the solution of the first linear programming model, calculate the second linear programming model to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the updated value of the physical property variables;

[0147] Calculate the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model;

[0148] When the relative deviation value < the predetermined convergence accuracy value, the assignment of the physical property variables in the first linear programming model, the value of the material quantity variable obtained by solving the first linear programming model, and the objective function value are the solutions of the refinery production plan optimization model; the convergence accuracy value is set according to the accuracy requirements of the business for the calculation results. For example, the convergence accuracy value can be set to 1e-4, 1e-5, etc.;

[0149] Based on the solution of the refinery production plan optimization model, obtain the optimized refinery production plan, carbon footprint tracking value, and unit carbon emission value of the oil product.

[0150] In a specific embodiment of the present invention, the method for obtaining the initial value of the physical property variables of the first linear programming model is as follows: Remove the constraints related to physical properties in the refinery plan optimization model, that is, convert the refinery plan optimization non-linear model into a linear model that only contains constraints related to material quantity, and then use a linear programming solver to solve it to obtain a set of values of the material quantity variables. Then, according to this set of values of the material quantity variables, use the P2 model (the second linear programming model) to solve it to obtain a set of values of the physical property variables, which are used as the initial physical property values in the P1 model (the first linear programming model).

[0151] As Figure 4 shown, the dual LP model based on the distributed recursive technology alternately solves the first linear programming model and the second linear programming model to obtain the solution of the refinery production plan optimization model, including:

[0152] Set the physical property variables in the original model as parameters, and with the aid of auxiliary variables, transform the physical property calculation equation into a residual calculation equation for the first linear programming model P1; then give the initial values of the physical property variables in the original model, update the physical property parameters in model P2, and call the LP solver to obtain the solution of the first linear programming model; the solution of the first linear programming model is the solution of the material quantity variable based on the physical property variables.

[0153] Substitute the solution of the first linear programming model into the second linear programming model for calculation to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the solution of the physical property variable based on the material variable.

[0154] Calculate the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model.

[0155] When the relative deviation value < the predetermined convergence accuracy value, terminate the calculation and output the solution of the model. Among them, the assignment of the physical property variables in the first linear programming model is the solution of the refining production plan optimization model.

[0156] When the relative deviation value is greater than or equal to the predetermined convergence accuracy value, then re-assign the initial values of the physical property variables of the first linear programming model, and repeat the alternating solution of the first linear programming model and the second linear programming model based on the distributed recursive technology, until the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model < the predetermined convergence accuracy value.

[0157] In this embodiment, as an optional embodiment, based on the assigned physical property parameters and the refining production plan optimization model, obtaining the material quantity value of the material quantity parameter in the production operation parameters includes:

[0158] Set auxiliary variables, and based on the auxiliary variables, transform the physical property calculation function containing physical property parameters in the refining production plan optimization model into a physical property residual calculation function.

[0159] Based on the assigned physical property parameters, call the linear programming solver to solve the transformed refining production plan optimization model to obtain the material quantity value.

[0160] Based on the material quantity value and the linear programming model, obtain the updated value of the physical property parameters.

[0161] In this embodiment, the material quantity value obtained from the refining production plan optimization model based on the assigned physical property parameters is used as the input of the linear programming model to obtain the updated value of the physical property parameters.

[0162] Based on the updated value, the refinery production plan optimization model, and the linear programming model, obtain the optimized refinery production plan, carbon footprint tracking value, and unit carbon emission value of the oil product.

[0163] Figure 5 This is a schematic flow chart for analyzing the refinery production plan optimization model in a refinery production plan optimization method provided by an embodiment of the present invention. As Figure 5 shown, as an optional embodiment, the material corresponding to the material quantity parameter is a non-recycled material. Based on the updated value, the refinery production plan optimization model, and the linear programming model, obtaining the optimized refinery production plan, carbon footprint tracking value, and unit carbon emission value of the oil product includes:

[0164] S301. Update the assigned physical property parameters using the updated value, and based on the assigned physical property parameters and the refinery production plan optimization model, obtain the material quantity value of the material quantity parameter in the production operation parameters;

[0165] S302. Based on the material quantity value and the transfer sequence of the material in the refinery, perform calculations in sequence from front to back to obtain the updated value of the physical property parameters;

[0166] In this embodiment, according to the sequence of each material (transfer sequence), the updated value of the physical property parameters is obtained by sequential calculation.

[0167] S303. Calculate the physical property relative deviation between the currently obtained updated value and the previously obtained updated value;

[0168] S304. If the physical property relative deviation is less than the preset physical property convergence accuracy threshold, based on the material quantity value of the current material quantity parameter and the updated value corresponding to the physical property parameters, obtain the optimized refinery production plan, carbon footprint tracking value, and unit carbon emission value of the oil product.

[0169] In this embodiment, if the physical property relative deviation is not less than the preset physical property convergence accuracy threshold, execute the step of updating the assigned physical property parameters using the updated value.

[0170] Figure 6 This is another schematic flow chart of step S105 in a refinery production plan optimization method provided by an embodiment of the present invention. As Figure 6 shown, as an optional embodiment, the material corresponding to the material quantity parameter is a recycled material. Based on the updated value, the refinery production plan optimization model, and the linear programming model, obtaining the optimized refinery production plan, carbon footprint tracking value, and unit carbon emission value of the oil product includes:

[0171] S401. Update the assigned physical property parameters using the update value, and obtain the material quantity value of the material quantity parameter in the production operation parameters based on the assigned physical property parameters and the refining production plan optimization model;

[0172] S402. Obtain the updated value of the physical property parameters based on the material quantity value and the linear programming model;

[0173] In this embodiment, after obtaining the material quantity value, the physical property parameters are used as variables to solve for the physical property parameters to obtain the updated value of the physical property parameters.

[0174] S403. Calculate the physical property relative deviation between the currently obtained updated value and the previously obtained updated value;

[0175] S404. If the physical property relative deviation is less than the preset physical property convergence accuracy threshold, obtain the optimized refining production plan, carbon footprint tracking value, and unit carbon emission value of the oil product based on the material quantity value of the current material quantity parameter and the updated value corresponding to the physical property parameters.

[0176] In this embodiment, through the linear programming model and applying linear programming to solve, the physical property variable value is obtained. That is, for the non-linear constraint functions: the unit carbon emission calculation function of the atmospheric and vacuum side lines, the unit carbon emission calculation function of the materials produced by the secondary processing units, and the unit carbon emission calculation function of the blended products, the material quantity variables are fixed according to the calculation results of the previous model, so as to transform the non-linear function into a linear function. Applying the LP solver to solve the current model can obtain the physical property variable value.

[0177] The following gives a specific example to describe the method of this embodiment in detail:

[0178] Applying the method of this embodiment, a refining production plan optimization model including the refinery carbon footprint tracking structure and some unit carbon emission constraints of the oil products is established. The scale of the refining production plan optimization model is shown in Table 4.

[0179] Table 4

[0180]

[0181] Using the method of this embodiment, the refining production plan optimization model constructed based on Table 4 can be solved within 1 minute. In the calculation results of the refining production plan optimization model, in addition to including the optimized refining production plan, it also includes the unit carbon emissions (carbon footprint tracking values) of the incoming and outgoing materials of each secondary unit, as shown in Table 5, which is the carbon balance result of the incoming and outgoing of the wax oil hydrogenation unit; and the unit carbon emissions (unit carbon emission values of the oil products) of each oil product.

[0182] Table 5

[0183]

[0184] Table 6 shows the unit carbon emissions of each oil product.

[0185] Table 6

[0186]

[0187]

[0188] Among them, the unit carbon emissions of 92# National VI gasoline reach the upper limit of 0.56 set by the refining production plan optimization model, that is, the production plan that can make the unit carbon emissions of the product meet the upper limit constraint can be obtained by solving the model.

[0189] In this embodiment, in the refining production plan optimization model, by constructing the physical property transfer structure of the secondary processing unit "by plan and by raw material", and establishing the corresponding physical property calculation function, the method for realizing the carbon emission transfer from the feed to the discharge of the secondary processing unit is realized. The constraint function related to the carbon emission transfer is extracted from the physical property calculation function (constraint function). Based on the non-linear constraint function in the constraint function related to the carbon emission transfer, a linear programming model is constructed. Based on the dual LP model alternating solution algorithm of the distribution recursion technology, the refining production plan optimization model and the linear programming model are alternately solved, and the optimized refining production plan including the refinery carbon footprint tracking structure and the product unit carbon emission constraint and with the circulating materials between the units can be effectively solved. In this way, by comprehensively considering the refinery carbon footprint tracking and the product unit carbon emission constraint, an optimized refining production plan is obtained, so that the optimized refining production plan obtained by solving can meet the low-carbon requirements of specific products, thereby improving the ecological and environmental benefits of the refinery and making the economic benefits and ecological and environmental benefits of the refinery reach the optimal. Further, by using the dual LP model alternating solution algorithm, the resources required for solving can be effectively reduced, the solution efficiency can be greatly improved, and then the generation efficiency of the refining production plan of the refinery is improved.

[0190] Based on the same inventive concept, as Figure 7 shown, the embodiment of the present invention also provides a device for optimizing the refining production plan, and the device includes,

[0191] The first construction module is used to construct a constraint equation based on the production operation parameters, and the production operation parameters include the unit carbon emission parameter of the material and the refinery material carbon footprint tracking data;

[0192] The second construction module is used to construct a refining production plan optimization model based on the constraint equation and the preset target equation;

[0193] A determination module, configured to analyze the refining production plan optimization model to determine a refining production optimization plan, a carbon footprint tracking value, and a unit carbon emission value of the oil product.

[0194] The steps performed by the determination module include:

[0195] Based on the physical property variables in the constraint equation, construct a first linear programming model of the residual calculation equation;

[0196] Based on the material quantity variables in the constraint equation, construct a second linear programming model;

[0197] Alternately solve the first linear programming model and the second linear programming model by a dual LP model based on the distributed recursion technique to obtain the solution of the refining production plan optimization model;

[0198] Based on the solution of the refining production plan optimization model, determine an optimized refining production plan, a carbon footprint tracking value, and a unit carbon emission value of the oil product.

[0199] Based on the same inventive concept, the present invention also provides an application of a method for optimizing a refining production plan in calculating the unit carbon emissions in each recycle material between computing devices.

[0200] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the refining production plan optimization method in any possible implementation manner described above are implemented.

[0201] Optionally, 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, and an optical data storage device, etc.

[0202] Based on the same inventive concept, refer to Figure 8 , an embodiment of the present invention further provides an electronic device, including a memory 101 (such as a non-volatile memory), a processor 102, and a computer program stored on the memory 101 and executable on the processor 102. When the processor 102 executes the program, the steps of the refining production plan optimization method in any possible implementation manner described above are implemented, which is equivalent to the refining production plan optimization device as described above. Of course, the processor can also be used to process other data or operations. The electronic device may be a device such as a PC, a server, or a terminal.

[0203] As Figure 8 shown, the electronic device generally may further include: a memory 103, a network interface 104, and an internal bus 105. In addition to these components, other hardware may also be included, which will not be elaborated herein.

[0204] It should be noted that the above-mentioned refining and chemical production plan optimization device can be implemented by software. As a device in a logical sense, it is formed by the processor 102 of the electronic device where it is located reading the computer program instructions stored in the non-volatile memory into the memory 103 and running them.

[0205] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the refining and chemical production plan, characterized in that, the method includes, constructing a constraint equation based on production operation parameters, where the production operation parameters include the unit carbon emission parameter of materials and the refinery material carbon footprint tracking data; constructing a refining and chemical production plan optimization model based on the constraint equation and a preset target equation; analyzing the refining and chemical production plan optimization model to determine the refining and chemical production optimization plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product.

2. The method for optimizing the refining and chemical production plan according to claim 1, characterized in that, the constraint equation includes: a constraint equation related to carbon emission transfer, a plant-wide balance equation of materials, an upper and lower limit constraint equation of device capacity, and a utility consumption calculation equation.

3. The method for optimizing the refining and chemical production plan according to claim 2, characterized in that, the constraint equation related to carbon emission transfer includes a calculation equation for the amount of atmospheric and vacuum side stream materials, a physical property calculation equation for atmospheric and vacuum side stream materials, a calculation equation for the amount of materials in secondary processing units, a calculation equation for the unit carbon emission of materials produced by secondary processing units, an upper limit constraint equation for the unit carbon emission of materials produced by secondary processing units, a calculation equation for the amount of materials in the blending tank, a physical property calculation equation for the blended product, and an upper limit constraint equation for the carbon emission of the blended product.

4. The method for optimizing the refining and chemical production plan according to claim 1, characterized in that, the preset target equation is a refinery profit maximization function based on product sales revenue, raw material procurement cost, and utility procurement cost and constructed based on a constraint function.

5. The method for optimizing the refining and chemical production plan according to claim 4, characterized in that, the formula of the preset target equation is expressed as follows: Max profit=∑ ms Price ms ·WM ms -∑ mp Cost mp ·WM mp -∑ ul UCost ul ·UB ul Among them, Max profit represents the maximum profit, Price ms is the unit selling price of material ms, Cost mp is the unit purchase price of material mp, UCost ul is the unit purchase price of utility ul, WM ms is the quantity of material ms sold, WM mp is the quantity of material mp purchased, UB ul is the quantity of utility ul purchased.

6. The method for optimizing the refining and chemical production plan according to claim 1, characterized in that, the analyzing the refining and chemical production plan optimization model to determine the refining and chemical production optimization plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product includes: extracting the constraint equation related to carbon emission transfer from the constraint equation and based on the non-linear constraint equation in the constraint function related to carbon emission transfer; constructing a first linear programming model based on the physical property variables in the non-linear constraint equation; constructing a second linear programming model based on the material quantity variables in the non-linear constraint equation; alternately solving the first linear programming model and the second linear programming model by a dual LP model based on distributed recursive technology to obtain the solution of the refining and chemical production plan optimization model; determining the optimized refining and chemical production plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product based on the solution of the refining and chemical production plan optimization model.

7. The method for optimizing the refining and chemical production plan according to claim 6, characterized in that, alternately solving the first linear programming model and the second linear programming model by a dual LP model based on distributed recursive technology to obtain the solution of the refining and chemical production plan optimization model includes: assigning values to the physical property parameters in the production operation parameters; Based on the said assignment, calculate the first linear programming model to obtain the solution of the first linear programming model; the solution of the first linear programming model is the value of the material quantity variable based on the physical property variables. Based on the solution of the first linear programming model, calculate the second linear programming model to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the updated value of the physical property variables. Calculate the relative deviation value between the assignment of the physical property variables in the first linear programming model and the solution of the second linear programming model. When the relative deviation value < the predetermined convergence accuracy value, the assignment of the physical property variables in the first linear programming model, the value of the material quantity variable obtained by solving the first linear programming model, and the objective function value are the solutions of the refining production plan optimization model. Based on the solution of the refining production plan optimization model, obtain the optimized refining production plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product.

8. A method for optimizing a refining production plan according to claim 7, wherein, the physical property variables include: the unit carbon emission of the atmospheric and vacuum side stream mi, the unit carbon emission of the material mq produced by the secondary unit e in the plan p, the unit carbon emission of the feed mf of the secondary unit e in the plan p, the unit carbon emission of the material mq produced by the secondary unit, the unit carbon emission of the blending product mb, and the unit carbon emission of the blending component mh. The material quantity variables include the quantity of the sold material ms, the quantity of the purchased material mp, the quantity of the purchased utility ul, the quantity of the side stream material mi produced by the atmospheric and vacuum unit c, the quantity of the crude oil mc processed in the unit c, the quantity of the material mq produced by the secondary unit e in the plan p, the processing quantity of the secondary unit e in the plan p, the quantity of the material mq produced by the secondary unit e, the quantity of the material mb blended in the blending tank b, and the quantity of the material mh used for blending the material mb in the blending tank b.

9. A device for optimizing a refining production plan, wherein, the device includes, a first construction module for constructing a constraint equation based on production operation parameters, and the production operation parameters include the unit carbon emission parameter of the material and the refinery material carbon footprint tracking data; a second construction module for constructing a refining production plan optimization model based on the constraint equation and a preset objective equation; a determination module for analyzing the refining production plan optimization model to determine the refining production optimization plan, the carbon footprint tracking value, and the unit carbon emission value of the oil product.

10. A device for optimizing a refining production plan according to claim 9, wherein, the steps executed by the determination module include: assign values to the physical property parameters in the production operation parameters; based on the said assignment, calculate the first linear programming model to obtain the solution of the first linear programming model; the solution of the first linear programming model is the value of the material quantity variable based on the physical property variables; based on the solution of the first linear programming model, calculate the second linear programming model to obtain the solution of the second linear programming model, and the solution of the second linear programming model is the updated value of the physical property variables. Calculate the relative deviation value between the assignment of physical property variables in the first linear programming model and the solution of the second linear programming model; When the relative deviation value < the predetermined convergence accuracy value, the assignment of physical property variables in the first linear programming model, the material quantity variable value and the objective function value obtained by solving the first linear programming model are the solutions of the refinery production plan optimization model; Based on the solutions of the refinery production plan optimization model, obtain the optimized refinery production plan, carbon footprint tracking value and unit carbon emission value of oil products.

11. Application of a method for optimizing a refinery production plan according to any one of claims 1-8 in calculating the unit carbon emission in each circulating material between computing devices.

12. A storage medium, characterized in that, The storage medium stores programs or instructions, and when the programs or instructions are run by a processor, the steps of the refinery production plan optimization method according to any one of claims 1 to 8 are implemented.

13. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the refinery production plan optimization method according to any one of claims 1 to 8 are implemented.

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