A method, device and application for refining production plan optimization

Abstract

The application discloses a kind of refining production plan optimization method, device and application, the method includes, based on production operation parameter construction constraint equation, the production operation parameter includes the unit carbon emission parameter of material and refinery material carbon footprint tracking data;Based on the constraint equation and the target equation set in advance, construct refining production plan optimization model;The refining production plan optimization model is analyzed, and the carbon footprint tracking value and oil product unit carbon emission value are determined in refining production optimization plan.The method of the application establishes the physical property transfer structure of "sub-scheme, sub-raw material" of secondary processing device, establishes the corresponding physical property calculation equation, so as to realize the method of carbon emission transfer from feed to discharge in secondary processing device.Based on the double LP model alternating solution algorithm of distribution recursion technology, the refining production plan optimization model containing the whole plant carbon footprint tracking structure and product unit carbon emission constraint with inter-device circulating material is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of refining and chemical processing technology, and in particular to a method, apparatus and application for optimizing refining and chemical production planning. Background Technology

[0002] The petroleum refining process is complex. Multiple crude oils undergo processing in atmospheric and vacuum distillation units, followed by secondary processing units such as continuous reforming, residue hydrotreating, catalytic cracking, gasoline and diesel hydrotreating, and alkylation, as well as product blending, to produce a wide range of products including gasoline, kerosene, diesel, lubricating oil, paraffin wax, and asphalt. Traditionally, refining companies use specialized refining planning optimization software to create mathematical programming models when developing production plans. These models comprehensively consider constraints such as raw material supply, product demand, unit capacity, and product specifications, aiming to maximize the economic benefits of the refining company and solve for a production plan that satisfies these constraints.

[0003] Refining and chemical enterprises are major carbon emitters. With the advancement of the national "dual carbon" goals, these enterprises are required to simultaneously conduct plant-wide carbon footprint tracking when formulating production plans. When generating production scheduling schemes, they should be able to progressively transfer the carbon emissions from the production process to the final products, obtaining the unit carbon emissions for each product, i.e., "carbon labels." Furthermore, when formulating production plans, the upper limit of unit carbon emissions for specific products can be used as a constraint, ensuring that the resulting production plan meets the low-carbon requirements of those specific products.

[0004] To achieve the above objectives, the refining and chemical planning optimization model needs to establish carbon emission transfer structures from feed to discharge for atmospheric and vacuum distillation units, secondary processing units, and blending tanks. In secondary processing units, since some units have multiple production plans, and each plan may use more than one type of raw material, it is necessary to establish carbon emission transfer structures for each plan and each raw material. However, current refining and chemical planning optimization software lacks the function of transferring carbon emissions by plan and by raw material, making it unable to model and solve for the business requirements of plant-wide carbon footprint tracking and product unit carbon emission constraints.

[0005] Because a refining and chemical enterprise typically has multiple production units and various materials, resulting in a complex production process, a refining and chemical planning optimization model that incorporates the entire plant's carbon transfer structure contains numerous nonlinear equations. Directly assigning such a model to a nonlinear solver (such as Baron) makes it difficult to guarantee a solution within an acceptable timeframe. Existing technologies utilize distributed recursive techniques for solving refining and chemical planning optimization models, as follows: Figure 1 As shown, step 4, calculating new physical properties based on the material quantity results, does not provide a specific implementation method in the literature. Currently, the common practice in the industry is to calculate the physical properties of each material sequentially from front to back based on the material flow order throughout the plant. The drawback of this method is that it cannot calculate the physical properties of circulating materials between units. Summary of the Invention

[0006] The purpose of this invention is to provide a method, apparatus, and application for optimizing refining and chemical production planning. To achieve the above objective, this invention provides the following technical solution:

[0007] A first aspect of the present invention provides a method for optimizing refining and chemical production planning, the method comprising:

[0008] Constraint equations are constructed based on production and operation parameters, which include unit carbon emission parameters of materials and refinery material carbon footprint tracking data.

[0009] Based on the constraint equations and the pre-set objective equations, a refining and chemical production planning optimization model is constructed.

[0010] The refining and chemical production planning optimization model was analyzed to determine the refining and chemical 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 transmission, plant-wide material balance equations, upper and lower limit constraint equations for plant capacity, and utility consumption calculation equations.

[0012] Furthermore, the constraint equations related to carbon emission transmission include the calculation equations for the quantity of atmospheric and vacuum distillation side stream material, the calculation equations for the physical properties of atmospheric and vacuum distillation side stream material, the calculation equations for the quantity of material from the secondary processing unit, the calculation equations for the unit carbon emission of the material produced by the secondary processing unit, the upper limit constraint equations for the unit carbon emission of the material produced by the secondary processing unit, the calculation equations for the quantity of material from the blending tank, the calculation equations for the physical properties of the blended product, and the upper limit constraint equations for the carbon emission of the blended product.

[0013] Furthermore, the pre-set objective equation is a refinery profit maximization function based on constraint functions, constructed from product sales revenue, raw material procurement costs, and utility procurement costs.

[0014] Furthermore, the formula for the pre-set 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] Where Max profit represents the maximum profit, and Pricems The unit price (ms) of the material, and the cost. mp UCost is the purchase price of material MP. ul For the unit price of the utility works ul, WM ms For the quantity of materials sold (ms), WM mp UB is the quantity of the purchased material (mp). ul The quantity of utilities procured.

[0017] Furthermore, the analysis of the refining and chemical production planning optimization model to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products includes:

[0018] Extract the constraint equations related to carbon emission transfer from the constraint equations, based on the nonlinear constraint equations in the constraint functions related to carbon emission transfer;

[0019] Based on the material property variables in the nonlinear constraint equations, a first linear programming model is constructed.

[0020] Based on the material quantity variables in the aforementioned nonlinear constraint equations, a second linear programming model is constructed.

[0021] The dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model;

[0022] Based on the solution of the aforementioned refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are determined.

[0023] Furthermore, the dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model, including:

[0024] Assign values ​​to the physical property parameters in the production and operation parameters;

[0025] Based on the assigned values, the first linear programming model is calculated 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 variable;

[0026] Based on the solution of the first linear programming model, the solution of the second linear programming model is calculated, and the solution of the second linear programming model is the updated value of the property variables.

[0027] Calculate the relative deviation between the assigned values ​​of the property variables in the first linear programming model and the solution of the second linear programming model;

[0028] When the relative deviation value is less than the predetermined convergence accuracy value, the property variable assignment in the first linear programming model, the material quantity variable value obtained by solving the first linear programming model, and the objective function value are the solutions of the refining and chemical production plan optimization model.

[0029] Based on the solution of the refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained.

[0030] Furthermore, the physical property variables include: the unit carbon emission of the atmospheric and vacuum distillation side line mi, the unit carbon emission of the material mq produced by scheme p in the secondary unit e, the unit carbon emission of the feed mf of scheme p in the secondary unit e, the unit carbon emission of the material mq produced by the secondary unit, the unit carbon emission of the blended product mb, and the unit carbon emission of the blended component mh.

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

[0032] A second aspect of the present invention provides an apparatus for optimizing refining and chemical production plans, the apparatus comprising,

[0033] The first construction module is used to construct constraint equations based on production and operation parameters, including unit carbon emission parameters of materials and refinery material carbon footprint tracking data.

[0034] The second construction module is used to construct a refining and chemical production plan optimization model based on the constraint equations and the pre-set target equations.

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

[0036] Furthermore, the steps performed by the determining module include:

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

[0038] Based on the assigned values, the first linear programming model is calculated 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 variable;

[0039] Based on the solution of the first linear programming model, the solution of the second linear programming model is calculated, and the solution of the second linear programming model is the updated value of the property variables.

[0040] Calculate the relative deviation between the assigned values ​​of the property variables in the first linear programming model and the solution of the second linear programming model;

[0041] When the relative deviation value is less than the predetermined convergence accuracy value, the property variable assignment in the first linear programming model, the material quantity variable value obtained by solving the first linear programming model, and the objective function value are the solutions of the refining and chemical production plan optimization model.

[0042] Based on the solution of the refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained.

[0043] A third aspect of the invention provides the application of the method for optimizing refining and chemical production planning as described above to the unit carbon emissions of circulating materials between computing devices.

[0044] A fourth aspect of the present invention provides a storage medium on which a program or instructions are stored, the program or instructions being executed by a processor to implement the steps of the refining production planning optimization method as described above.

[0045] A fifth aspect of the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described refining and chemical production planning optimization method.

[0046] The technical effects and advantages of this invention are as follows:

[0047] 1. A method is proposed to establish a property transfer structure of "scheme and raw material" for secondary processing units in the refining and chemical planning optimization model, and to establish corresponding property calculation equations, so as to realize the carbon emission transfer from feed to discharge in the secondary processing unit.

[0048] 2. A dual LP model alternating solution algorithm based on distributed recursion technology is proposed, which can effectively solve the refining and chemical production planning optimization model that includes the whole plant carbon footprint tracking structure and product unit carbon emission constraints, and has inter-unit circulating materials.

[0049] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0050] Figure 1A schematic diagram of the distributed recursive technique for optimizing existing refining and chemical processing plans;

[0051] Figure 2 This is a schematic diagram of a method for optimizing refining and chemical production plans provided by an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of material recycling in a refining and chemical production planning optimization method provided by an embodiment of the present invention;

[0053] Figure 4 A schematic diagram illustrating the principle of a distributed recursive technique for solving a refining and chemical production planning optimization model, provided in an embodiment of the present invention.

[0054] Figure 5 Provided for embodiments of the present invention Figure 4 Flowchart of the middle school entrance examination;

[0055] Figure 6 Provided for embodiments of the present invention Figure 4 Another flowchart;

[0056] Figure 7 A schematic diagram of a refining and chemical production planning optimization device provided in an embodiment of the present invention;

[0057] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] To address the shortcomings of existing technologies, this invention discloses a method for optimizing refining and chemical production plans, such as... Figure 2 As shown, the method includes,

[0060] A constraint equation is constructed based on production and operation parameters, including the unit carbon emission parameter of materials and refinery material carbon footprint tracking data. Based on the constraint equation and the pre-set target equation, a refining and chemical production plan optimization model is constructed. The refining and chemical production plan optimization model is analyzed to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products.

[0061] In a specific embodiment of the present invention, in the refining and chemical production planning optimization model, the "unit carbon emission" of materials is modeled as a "physical property," and the symbols in the model are explained in Table 1:

[0062] Table 1. Explanation of Symbols in the Refining and Chemical Production Planning Optimization Model

[0063]

[0064]

[0065]

[0066] The objective function of the refining and chemical production planning optimization model is to maximize the overall plant profit. The pre-set objective equation is a refinery profit maximization function based on constraint functions, constructed based on product sales revenue, raw material procurement costs, and utility procurement costs.

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

[0068] The 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] Where Max profit represents the maximum profit, and Price ms The unit price (ms) of the material, and the cost. mp UCost is the purchase price of material MP. ul For the unit price of the utility works ul, WM ms For the quantity of materials sold (ms), WM mp UB is the quantity of the purchased material (mp). ul The quantity of utilities procured.

[0071] The constraint equations include: constraint equations related to carbon emission transfer, plant-wide material balance equations, upper and lower limit constraint equations for plant capacity, and utility consumption calculation equations.

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

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

[0074] (1) Equation for calculating the material quantity of the atmospheric and vacuum distillation side stream:

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

[0076] Among them, WM c,mi WM is the amount of side stream material mi produced by atmospheric and vacuum distillation unit c. c,mc The amount of crude oil mc processed in unit c, CCTU c,mc,mi The yield of the side stream mi of crude oil mc in atmospheric and vacuum distillation unit c is denoted as mi.

[0077] (2) Equation for calculating carbon emissions from atmospheric and vacuum diversion side rays:

[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] Among them, MQ mi,CO2 WM represents the unit carbon emissions per mi of the atmospheric and vacuum distillation side line. c,mc The amount of crude oil mc processed in the atmospheric and vacuum distillation unit c, CCTU c,mc,mi CCTUQ represents the cut yield of the side stream mi of crude oil mc in the atmospheric and vacuum distillation unit c. c,mc,mi,CO2WM represents the unit carbon emissions (Mi) of the side stream mi of crude oil mc in the atmospheric and vacuum distillation unit c. c,mi The amount of side stream material mi produced by atmospheric and vacuum distillation unit c.

[0082] The above parameters CCTUQ c,mc,mi,CO2 It can be obtained based on the amount of carbon emitted per unit of crude oil processed by the unit, combined with principles such as quality allocation, calorific value allocation, or product value allocation.

[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 secondary processing unit of the refining production planning optimization model of the present invention is achieved through a "scheme-based, raw material-based" property transfer structure. The refining production planning optimization model of the present invention can calculate the unit carbon emission of different raw materials. Taking a wax oil hydrorefining unit of a refinery as an example, as shown in Table 2:

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

[0085]

[0086]

[0087] As shown in the table above, the device has two processing schemes. Scheme 1 uses reduced heat and hydrogen as raw materials, while Scheme 2 uses coking heavy wax oil and hydrogen as raw materials. Both schemes produce hydrogenated dry gas from wax oil, hydrogenated naphtha from wax oil, and hydrogenated wax oil, but the yields are different. In addition, the unit carbon emissions of the two schemes are also different.

[0088] For this device, the carbon emissions from each raw material, as well as the carbon emissions from the energy consumed by the scheme, need to be distributed to the products hydrogenated naphtha 2DA and hydrogenated wax oil 2DD through the property transfer structure. Then, the unit carbon emissions of a certain product obtained from each scheme are weighted and averaged according to the output to obtain the unit carbon emissions of the product.

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

[0090] (1) Equation for calculating the amount of material 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 WUP represents the amount of material mq produced by scheme p in secondary unit e. e,pFor the processing quantity of scheme p in secondary device e, UPR e,p,mq For the secondary unit e, the yield of the output material mq from scheme p is WM e,mq This refers to the amount of material mq produced by the secondary unit e.

[0094] Equation for calculating the amount of material consumed by the secondary unit:

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

[0096]

[0097] Among them, WPM e，p，mf WUP represents the amount of material mf consumed in scheme p of the secondary unit e. e,p For the processing quantity of scheme p in secondary device e, UPR e,p,mf For the secondary device e, the unit consumption of material mf in scheme p is WM. e,mf The amount of material mf consumed by the secondary device e.

[0098] (2) Equation for calculating the unit carbon emissions of materials produced by the secondary unit:

[0099]

[0100] Equivalent to:

[0101]

[0102] Among them, MPQ e,p,mq,CO2 MQ represents the unit carbon emissions of material mq produced by scheme p in secondary unit e. mf,CO2 The unit carbon emissions of feed mf for scheme p of secondary device e; A e,p,mf,mq,CO2 and B e,p,mq,CO2 In scheme p of device e, UPR represents the unit carbon emissions of feed mf and the coefficient by which carbon emissions from energy consumption in this scheme are transferred to product mq. e,p,mf For the secondary device e, the unit consumption of feed mf in scheme p; MQ mq,CO2 The carbon emissions per unit of material (mq) produced by the secondary unit.

[0103] In the formula above, the transfer coefficient A can be calculated from the raw material consumption per unit and the product yield of the corresponding scheme, while the transfer coefficient B can be calculated from the carbon emissions due to energy consumption and the product yield of the corresponding scheme.

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

[0105]

[0106] In the formula, The upper limit of carbon emissions per unit of material MQ is set according to business needs.

[0107] 3. Blending tank:

[0108] (1) Equation for calculating the material quantity of blended products

[0109]

[0110] Among them WM b，mb XB represents the amount of material mb being blended in blending tank b. b，mb,mh The amount of blending component mh used in blending material mb in blending tank b.

[0111] (2) Equations for calculating the physical properties of blended products

[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] Among them, MQ mb,CO2 To balance the unit carbon emissions of the product (mb), MQ mh,CO2 To determine the unit carbon emissions of the blending component mh in product mb, XB b,mb,mh The amount of component mh used in the blending material mb in blending tank b, WM b,mb The amount of material mb being blended in blending tank b.

[0116] (3) Equation for the upper limit constraint of carbon emissions of blended products:

[0117]

[0118] In the formula, The upper limit of unit carbon emissions for blended products is set according to business needs.

[0119] In addition to the constraint equations related to carbon emission transfer, the refining and chemical production planning optimization model also includes the plant-wide material balance equation, the upper and lower limit constraint equations for unit capacity, and the equations for calculating utility consumption.

[0120] in,

[0121] For the purchased material mp, the plant-wide material balance equation is:

[0122]

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

[0124] For sales material ms, the plant-wide material balance equation is:

[0125]

[0126]

[0127] Among them, WM ms For the sales volume of material ms, WM c,mi WM is the amount of side stream material mi produced by atmospheric and vacuum distillation unit c. b,mb WM represents the amount of material mb being blended in blending tank b. e,mq Let mq be the amount of material produced by the secondary unit e. For any sales material ms, the above formula holds true when mi, mb, and mq equal mp, that is, the sales volume of a material is equal to the sum of the amounts of that 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, the variables in the constraint equations of the above-mentioned refining and chemical production planning optimization model can be divided into two main categories: one is material quantity variables, and the other is physical property value variables, as shown in Table 3:

[0129] Table 3. Variable Classification Table in the Refining and Chemical Production Planning Optimization Model

[0130]

[0131]

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

[0133] Since a refining and chemical enterprise typically has multiple production units and materials, and the production process is complex, a refining and chemical planning optimization model that includes the carbon transfer structure of the entire plant contains a large number of nonlinear equations. If the above model is directly handed over to a nonlinear solver (such as Baron), it is difficult to guarantee that the solution will be completed within an acceptable time.

[0134] In one specific embodiment of the present invention, the materials include recycled materials and non-recycled materials. Recycled materials refer to the feed material of one device, which, after being processed by this device and several subsequent devices, is used to produce the same material again, and then returned to this device as feed material. For example... Figure 3 Material A shown in the diagram is a circulating material between devices. Figure 3 This is a schematic diagram illustrating the material recycling process in a refining and chemical production planning optimization method provided by an embodiment of the present invention. Figure 3 As shown, in this embodiment, it is necessary to track the refinery's carbon footprint. In 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 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 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, the order of materials cannot be determined, therefore, the unit carbon emissions of each material cannot be calculated. Assuming there are no recycled materials in the diagram, then... Figure 2 The materials in the process have a specific order, so the unit carbon emission of each material can be obtained by deducing the order.

[0135] If a plant-wide carbon footprint tracking structure is established, then in device 1, the unit carbon emission of material C needs to be calculated from the unit carbon emissions of materials A and B; in device 2, the unit carbon emission of material G needs to be calculated from the unit carbon emissions of materials C and E; and in device 3, the unit carbon emission of material A needs to be calculated from the unit carbon emissions of materials G and H. In this situation, using existing technologies such as... Figure 1The technical method described above cannot determine the order of materials, thus making it impossible to calculate the unit carbon emission of each material. To address this, this embodiment proposes an alternating solution algorithm for two linear programming (LP) models based on distributed recursion. By assigning values ​​to physical property parameters (property value variables) to make them constant, and by assigning values ​​to material quantity parameters to make them constant, the nonlinear function contains only material quantity parameters or physical property parameters, thereby transforming the nonlinear function into a linear function. This significantly reduces the computational load required for the solution and effectively lowers the solution time.

[0136] Therefore, in a specific embodiment of the present invention, a dual LP model alternating solution algorithm based on distributed recursion technology is proposed. A model is established, whose constraint equations include: carbon emission calculation equations for the atmospheric and vacuum distillation side stream, unit carbon emission calculation equations for materials produced by the secondary unit, unit carbon emission calculation equations for materials mq produced by scheme p in secondary unit e, and product property calculation equations. For the nonlinear equations—the carbon emission calculation equations for the atmospheric and vacuum distillation side stream, the unit carbon emission calculation equations for materials produced by the secondary unit, and the property calculation equations for the blended products—the material quantity variables are fixed according to the calculation results of the previous model, thereby transforming the nonlinear equations into linear equations. Applying the LP solver to solve the above sub-models yields the property variable values. This allows for the analysis of the refining and chemical production planning optimization model, determining the refining and chemical production optimization plan, carbon footprint tracking values, and unit carbon emission values ​​for oil products, effectively solving the aforementioned problems.

[0137] In a specific embodiment of the present invention, the refining and chemical production planning optimization model is analyzed to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products, including:

[0138] Extract the constraint equations related to carbon emission transfer from the constraint equations, based on the nonlinear constraint equations in the constraint functions related to carbon emission transfer;

[0139] Based on the material property variables in the nonlinear constraint equations, a first linear programming model is constructed.

[0140] Based on the material quantity variables in the aforementioned nonlinear constraint equations, a second linear programming model is constructed.

[0141] The dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model;

[0142] Based on the solution of the aforementioned refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are determined.

[0143] In a specific embodiment of the present invention, a dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model, including:

[0144] The physical property parameters in the production and operation parameters are assigned values; these values ​​serve as the initial values ​​of the physical property variables in the first linear programming model.

[0145] Based on the assigned values, the first linear programming model is calculated 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 variable;

[0146] Based on the solution of the first linear programming model, the solution of the second linear programming model is calculated, and the solution of the second linear programming model is the updated value of the property variables.

[0147] Calculate the relative deviation between the assigned values ​​of the property variables in the first linear programming model and the solution of the second linear programming model;

[0148] When the relative deviation value is less than the predetermined convergence accuracy value, the property variables assigned in the first linear programming model, the material quantity variables obtained by solving the first linear programming model, and the objective function value are the solution of the refining and chemical production plan optimization model; the convergence accuracy value is set according to the business requirements for the accuracy of 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 refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained.

[0150] In a specific embodiment of the present invention, the method for obtaining the initial values ​​of the physical property variables of the first linear programming model is as follows: remove the constraints related to physical properties in the refining and chemical planning optimization model, that is, transform the nonlinear model of the refining and chemical planning optimization into a linear model that only contains constraints related to material quantity, and then apply a linear programming solver to solve it, thereby obtaining a set of values ​​of material quantity variables. Then, based on the values ​​of these material quantity variables, apply the P2 model (second linear programming model) to solve it, thereby obtaining a set of values ​​of physical property variables, which are used as the initial values ​​of physical properties in the P1 model (first linear programming model).

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

[0152] The physical property variables in the original model are set as parameters, and the physical property calculation equation is transformed into a residual calculation equation using auxiliary variables. Then, given the initial values ​​of the physical property variables in the original model, the physical property parameters in model P2 are updated, and the LP solver is called to obtain the solution of the first linear programming model. The solution of the first linear programming model is the solution based on the material quantity variable of the physical property variables.

[0153] The solution of the first linear programming model is substituted into the solution of the second linear programming model to obtain the solution of the second linear programming model. The solution of the second linear programming model is the solution based on the material property variables.

[0154] Calculate the relative deviation between the assigned values ​​of the property variables in the first linear programming model and the solution of the second linear programming model;

[0155] When the relative deviation value is less than the predetermined convergence accuracy value, the calculation is terminated and the solution of the model is output, wherein the physical property variables in the first linear programming model are assigned the solution of the refining and chemical production plan optimization model.

[0156] When the relative deviation value is greater than or equal to the predetermined convergence accuracy value, the initial values ​​of the property variables of the first linear programming model are reassigned, and the dual LP model based on the distributed recursion technique is used to solve the first linear programming model and the second linear programming model alternately, so that the relative deviation value between the assigned property variables in the first linear programming model and the solution of the second linear programming model is less than the predetermined convergence accuracy value.

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

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

[0159] Based on the assigned physical property parameters, the linear programming solver is invoked to solve the optimization model of the transformed refining and chemical production plan, and the material quantity values ​​are obtained.

[0160] Based on the material quantity value and the linear programming model, the updated values ​​of the physical property parameters are obtained;

[0161] In this embodiment, the material quantity values ​​obtained by the refining and chemical production planning optimization model based on the assigned physical property parameters are used as input to the linear programming model to obtain updated values ​​of the physical property parameters.

[0162] Based on the updated value, the refining and chemical production plan optimization model, and the linear programming model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained.

[0163] Figure 5 This is a schematic diagram illustrating the process of analyzing the refining and chemical production planning optimization model in a refining and chemical production planning optimization method provided in an embodiment of the present invention. Figure 5 As shown, in an optional embodiment, the material quantity parameter corresponds to a non-circulating material. Based on the updated value, the refining and chemical production plan optimization model, and the linear programming model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained, including:

[0164] S301. Update the assigned physical property parameters using the updated values, 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 and chemical production plan optimization model.

[0165] S302. Based on the material quantity and the material flow sequence in the refinery, calculate from front to back to obtain the updated values ​​of the physical property parameters.

[0166] In this embodiment, the updated values ​​of physical property parameters are obtained by sequential calculation based on the order of each material (flow sequence).

[0167] S303. Calculate the relative deviation of the physical properties between the current updated value and the previous updated value;

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

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

[0170] Figure 6 This is another schematic diagram of step S105 in a refining and chemical production planning optimization method provided in an embodiment of the present invention. For example... Figure 6 As shown, in an optional embodiment, the material quantity parameter corresponds to recycled material. Based on the updated value, the refining and chemical production plan optimization model, and the linear programming model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained, including:

[0171] S401. Update the assigned physical property parameters using the updated values, 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 and chemical production plan optimization model.

[0172] S402. Based on the material quantity value and the linear programming model, obtain the updated value of the physical property parameter;

[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 and obtain updated values ​​of the physical property parameters.

[0174] S403. Calculate the relative deviation of the physical properties between the current updated value and the previous updated value;

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

[0176] In this embodiment, the material property variables are obtained by applying a linear programming model and solving the linear programming problem. Specifically, for the nonlinear constraint functions: the unit carbon emission calculation function of the atmospheric and vacuum distillation side line, the unit carbon emission calculation function of the material produced by the secondary processing unit, and the unit carbon emission calculation function of the blended product, the material quantity variables are fixed according to the calculation results of the previous model, thereby transforming the nonlinear function into a linear function. The material property variables can be obtained by applying the LP solver to solve the current model.

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

[0178] Using the method of this embodiment, a refining and chemical production planning optimization model for a certain refinery is established, which includes a refinery carbon footprint tracking structure and a partial constraint on the unit carbon emission of oil products. The scale of the refining and chemical production planning optimization model is shown in Table 4.

[0179] Table 4

[0180]

[0181] Using the method of this embodiment, the optimization model for refining and chemical production planning based on Table 4 can be solved within 1 minute. In addition to the optimized refining and chemical production plan, the calculation results of the optimization model for refining and chemical production planning also include the unit carbon emissions (carbon footprint tracking value) of the materials entering and leaving each secondary unit, as shown in Table 5, which is the carbon balance result of the wax oil hydrotreating unit; and the unit carbon emissions (unit carbon emissions value of oil products).

[0182] Table 5

[0183]

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

[0185] Table 6

[0186]

[0187]

[0188] Among them, the unit carbon emission of 92# National VI gasoline reached the upper limit of 0.56 set by the refining and chemical production planning optimization model, that is, the model can solve for a production scheme that makes the unit carbon emission of the product meet the upper limit constraint.

[0189] In this embodiment, the refining production planning optimization model constructs a property transfer structure for secondary processing units based on "different schemes and different raw materials," and establishes corresponding property calculation functions. This enables the transfer of carbon emissions from feed to discharge in secondary processing units. Constraint functions related to carbon emission transfer are extracted from the property calculation functions (constraint functions). Based on the nonlinear constraint functions related to carbon emission transfer, a linear programming model is constructed. An alternating solution algorithm using a dual-LP model based on distributed recursion is used to alternately solve the refining production planning optimization model and the linear programming model. This effectively solves the optimized refining production plan, which includes the refinery's carbon footprint tracking structure, product unit carbon emission constraints, and inter-unit circulating materials. Thus, by comprehensively considering refinery carbon footprint tracking and product unit carbon emission constraints, an optimized refining production plan is obtained. This ensures that the optimized refining production plan meets the low-carbon requirements of specific products, thereby improving the refinery's ecological and environmental benefits and achieving optimal economic and ecological benefits. Furthermore, by utilizing the alternating solution algorithm of the dual LP model, the resources required for solving the problem can be effectively reduced, the solution efficiency can be greatly improved, and thus the efficiency of generating refining and chemical production plans in refineries can be increased.

[0190] Based on the same inventive concept, such as Figure 7 As shown, this embodiment of the invention also provides an apparatus for optimizing refining and chemical production plans, the apparatus comprising,

[0191] The first construction module is used to construct constraint equations based on production and operation parameters, including unit carbon emission parameters of materials and refinery material carbon footprint tracking data.

[0192] The second construction module is used to construct a refining and chemical production plan optimization model based on the constraint equations and the pre-set target equations.

[0193] The determination module is used to analyze the refining and chemical production planning optimization model to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products.

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

[0195] Based on the physical property variables in the constraint equations, a first linear programming model for residual calculation equations is constructed.

[0196] Based on the material quantity variables in the constraint equations, a second linear programming model is constructed.

[0197] The dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model;

[0198] Based on the solution of the aforementioned refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are determined.

[0199] Based on the same inventive concept, this invention also provides an application of a method for optimizing refining and chemical production plans in calculating the unit carbon emissions of circulating materials between computing devices.

[0200] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the refining and chemical production planning optimization method in any of the above possible implementations.

[0201] Alternatively, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0202] Based on the same inventive concept, see [link to inventive concept] Figure 8 This invention also provides an electronic device, including a memory 101 (e.g., 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, it implements the steps of the refining and chemical production planning optimization method in any of the above possible implementations, which can be equivalent to the aforementioned refining and chemical production planning optimization device. Of course, the processor can also be used to process other data or perform calculations. This electronic device can be a PC, server, terminal, or other similar device.

[0203] like Figure 8 As shown, the electronic device may also include: memory 103, network interface 104, and internal bus 105. In addition to these components, other hardware may also be included, which will not be described in detail here.

[0204] It should be noted that the above-mentioned refining and chemical production planning 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 in which it is located reading the computer program instructions stored in the non-volatile memory into the memory 103 for execution.

[0205] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is 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 make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing refining and chemical production planning, characterized in that, The method includes, Constraint equations are constructed based on production and operation parameters, which include unit carbon emission parameters of materials and refinery material carbon footprint tracking data. Based on the constraint equations and the pre-set objective equations, a refining and chemical production planning optimization model is constructed. The refining and chemical production planning optimization model was analyzed to determine the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products. The analysis of the refining and chemical production planning optimization model determines the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products, including: Extract the constraint equations related to carbon emission transfer from the constraint equations, based on the nonlinear constraint equations in the constraint functions related to carbon emission transfer; Based on the material property variables in the nonlinear constraint equations, a first linear programming model is constructed. Based on the material quantity variables in the aforementioned nonlinear constraint equations, a second linear programming model is constructed. The dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model; Based on the solution of the aforementioned refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are determined.

2. The method for optimizing refining and chemical production planning according to claim 1, characterized in that, The constraint equations include: constraint equations related to carbon emission transfer, plant-wide material balance equations, upper and lower limit constraint equations for plant capacity, and utility consumption calculation equations.

3. The method for optimizing refining and chemical production planning according to claim 2, characterized in that, The constraint equations related to carbon emission transmission include the calculation equations for the quantity of atmospheric and vacuum distillation side stream material, the calculation equations for the physical properties of atmospheric and vacuum distillation side stream material, the calculation equations for the quantity of material in the secondary processing unit, the calculation equations for the unit carbon emission of the material produced by the secondary processing unit, the upper limit constraint equations for the unit carbon emission of the material produced by the secondary processing unit, the calculation equations for the quantity of material in the blending tank, the calculation equations for the physical properties of the blended product, and the upper limit constraint equations for the carbon emission of the blended product.

4. The method for optimizing refining and chemical production planning according to claim 1, characterized in that, The pre-set objective equation is a refinery profit maximization function based on constraint functions, constructed from product sales revenue, raw material procurement costs, and utility procurement costs.

5. The method for optimizing refining and chemical production planning according to claim 4, characterized in that, The formula for the pre-set objective equation is expressed as follows: Where Max profit represents the maximum profit. The unit price of the material is ms. The unit price of material MP. The unit price for the public works UL. The quantity of materials sold is measured in milliseconds (ms). The quantity (mp) of the purchased materials. The quantity of utilities procured.

6. The method for optimizing refining and chemical production planning according to claim 1, characterized in that, The dual LP model based on distributed recursion technology alternately solves the first and second linear programming models to obtain the solution of the refining and chemical production plan optimization model, including: Assign values ​​to the physical property parameters in the production and operation parameters; Based on the assigned values, the first linear programming model is calculated 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 variable; Based on the solution of the first linear programming model, the solution of the second linear programming model is calculated, and the solution of the second linear programming model is the updated value of the property variables. Calculate the relative deviation between the assigned values ​​of the property variables in the first linear programming model and the solution of the second linear programming model; When the relative deviation value is less than the predetermined convergence accuracy value, the property variable assignment in the first linear programming model, the material quantity variable value obtained by solving the first linear programming model, and the objective function value are the solutions of the refining and chemical production plan optimization model. Based on the solution of the refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are obtained.

7. The method for optimizing refining and chemical production planning according to claim 6, characterized in that, The physical property variables include: the unit carbon emission of the atmospheric and vacuum distillation side line mi, the unit carbon emission of the material mq produced by scheme p in secondary unit e, the unit carbon emission of the feed mf of scheme p in secondary unit e, the unit carbon emission of the material mq produced by the secondary unit, the unit carbon emission of the blended product mb, and the unit carbon emission of the blended component mh. The material quantity variables include the quantity of material ms sold, the quantity of material mp purchased, the quantity of utility ul purchased, the quantity of side-stream material mi produced by atmospheric and vacuum distillation unit c, the quantity of crude oil mc processed in unit c, the quantity of material mq produced by scheme p in secondary unit e, the processing amount of scheme p in secondary unit e, the quantity of material mq produced by secondary unit e, the quantity of material mb blended in blending tank b, and the quantity of material mh used in blending material mb in blending tank b.

8. An apparatus for optimizing refining and chemical production planning, characterized in that, The device includes, The first construction module is used to construct constraint equations based on production and operation parameters, including unit carbon emission parameters of materials and refinery material carbon footprint tracking data. The second construction module is used to construct a refining and chemical production plan optimization model based on the constraint equations and the pre-set target equations. The determination module is used to analyze the refining and chemical production planning optimization model to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products. The analysis of the refining and chemical production planning optimization model to determine the refining and chemical production optimization plan, carbon footprint tracking value, and unit carbon emission value of oil products includes: Extract the constraint equations related to carbon emission transfer from the constraint equations, based on the nonlinear constraint equations in the constraint functions related to carbon emission transfer; Based on the material property variables in the nonlinear constraint equations, a first linear programming model is constructed. Based on the material quantity variables in the aforementioned nonlinear constraint equations, a second linear programming model is constructed. The dual LP model based on distributed recursion technology is used to alternately solve the first linear programming model and the second linear programming model to obtain the solution of the refining and chemical production plan optimization model; Based on the solution of the aforementioned refining and chemical production planning optimization model, the optimized refining and chemical production plan, carbon footprint tracking value, and unit carbon emission value of oil products are determined.

9. The application of the method for optimizing refining and chemical production planning as described in any one of claims 1-7 to the calculation of unit carbon emissions in each circulating material between units.

10. A storage medium, characterized in that, A program or instruction is stored on a storage medium, and the program or instruction is executed by a processor to implement the steps of the refining and chemical production planning optimization method as described in any one of claims 1 to 7.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the refining and chemical production planning optimization method according to any one of claims 1 to 7.

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