Oil refining control method, device, electronic device and storage medium

Abstract

The present invention provides a refinery control method, device, electronic device, and storage medium, wherein the method comprises: obtaining initial operating parameters under current refinery conditions, and determining a product distribution prediction result for the current refinery conditions based on the initial operating parameters and a product distribution prediction model; determining target operating parameters for the current refinery conditions based on preset optimization conditions and the product distribution prediction result; and controlling a catalytic cracking unit and a hydrogenation unit based on the target operating parameters; wherein the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the feedstock in the catalytic cracking unit. The method and device provided by the present invention achieve coordinated control of the hydrogenation unit and the catalytic cracking unit, improve the automation level of refinery control, and reduce hydrogen consumption during the refinery process.

Description

Technical Field

[0001] The present invention relates to the technical field of oil refining processing, and in particular to an oil refining control method, device, electronic equipment and storage medium. Background Art

[0002] Catalytic cracking technology is one of the important crude oil decarbonization processing technologies. Crude oil undergoes cracking, hydrogen transfer, isomerization and other processes to obtain dry gas, liquefied gas, gasoline, light cycle oil, slurry oil, coke and other products.

[0003] To obtain high-quality products, crude oil catalytic cracking units typically require a hydrogenation unit to hydrotreat the feedstock. However, existing technologies typically rely on operators to adjust the hydrogenation rate in the hydrogenation unit and the operating parameters of the catalytic cracking unit based on their experience. This results in poor synergistic control between the two units and is subject to human error, resulting in high hydrogen consumption during the refining process and failure to guarantee target product yields. Summary of the Invention

[0004] The present invention provides an oil refining control method, device, electronic equipment and storage medium, which are used to solve the technical problems in the prior art of relying on operators to control the hydrogenation unit and catalytic cracking unit separately, resulting in high hydrogen consumption and inability to guarantee the target product yield.

[0005] The present invention provides an oil refining control method, comprising:

[0006] Acquiring initial operating parameters under current refinery operating conditions, and determining a product distribution prediction result for the current refinery operating conditions based on the initial operating parameters and a product distribution prediction model;

[0007] Determining target operating parameters for the current refinery operating conditions based on preset optimization conditions and the product distribution prediction result;

[0008] controlling the catalytic cracking unit and the hydrogenation unit based on the target operating parameters;

[0009] The product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0010] According to the oil refining control method provided by the present invention, the product distribution prediction model is determined based on the following steps:

[0011] Determining an initial model based on an operating mechanism of a catalytic cracking reaction of raw materials in the catalytic cracking unit;

[0012] Correcting the initial model based on historical operating parameters and historical product distribution results under multiple refining conditions to obtain the product distribution prediction model;

[0013] The refining operating conditions are determined based on at least one of the type of the raw material, the reaction temperature of the catalytic cracking unit, and the reaction pressure of the catalytic cracking unit.

[0014] According to the oil refining control method provided by the present invention, the preset optimization condition is determined based on the flow rate and hydrogen content of each product in the product distribution prediction result.

[0015] According to the oil refining control method provided by the present invention, determining the target operating parameters of the current oil refining condition based on the preset optimization conditions and the product distribution prediction result includes:

[0016] Determining an objective function in the preset optimization condition based on a target flow rate of a first preset product and a target hydrogen content of a second preset product in the product distribution prediction result;

[0017] Determining the constraints in the preset optimization conditions based on the flow rate and hydrogen content of each product in the product distribution prediction result;

[0018] Based on the objective function, adjusting the initial operating parameters to obtain operating parameter adjustment values, and determining a product distribution optimization result of the current refining operating condition based on the operating parameter adjustment values ​​and the product distribution prediction model;

[0019] If the product distribution optimization result satisfies the constraint condition, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

[0020] According to the oil refining control method provided by the present invention, the control of the catalytic cracking unit and the hydrogenation unit based on the target operating parameters includes:

[0021] Determining target operating parameters of the catalytic cracking unit and target hydrogenation depth of the hydrogenation unit based on the target operating parameters;

[0022] The catalytic cracking unit is controlled based on the target operating parameters, and the hydrogenation unit is controlled based on the target hydrogenation severity.

[0023] According to the oil refining control method provided by the present invention, the initial operating parameters include raw material property parameters, initial operating parameters and an initial value of hydrogenation depth; the initial operating parameters include an initial value of the reaction temperature and an initial value of the reaction pressure in the catalytic cracking unit, and an initial value of the residence time of the raw material in the catalytic cracking unit.

[0024] The present invention provides an oil refining control device, comprising:

[0025] an acquisition unit, configured to acquire initial operating parameters under a current refining operating condition, and determine a product distribution prediction result under the current refining operating condition based on the initial operating parameters and a product distribution prediction model;

[0026] An optimization unit, configured to determine target operating parameters of the current refinery operating conditions based on preset optimization conditions and the product distribution prediction result;

[0027] a control unit, configured to control the catalytic cracking unit and the hydrogenation unit based on the target operating parameters;

[0028] The product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0029] The present invention provides an electronic device comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor implements the steps of the oil refining control method when executing the program.

[0030] The present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the oil refining control method when executed by a processor.

[0031] The present invention provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the oil refining control method are implemented.

[0032] The refinery control method, device, electronic device and storage medium provided by the embodiments of the present invention obtain the initial operating parameters under the current refinery operating conditions, and determine the product distribution prediction results of the current refinery operating conditions based on the initial operating parameters and the product distribution prediction model. Then, based on preset optimization conditions and the product distribution prediction results, the target operating parameters of the current refinery operating conditions are determined. Finally, the catalytic cracking unit and the hydrogenation unit are controlled according to the target operating parameters. Since the target operating parameters are determined based on the product distribution results that meet the preset optimization conditions, coordinated control of the hydrogenation unit and the catalytic cracking unit is achieved without the need for human intervention, thereby improving the automation level of refinery control. While ensuring the target product yield, the hydrogenation depth is adapted to the catalytic cracking reaction, thereby reducing hydrogen consumption in the refining process. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 A schematic flow chart of the oil refining control method provided by the present invention;

[0035] Figure 2 Schematic diagram of the reaction-separation coupling mathematical model provided by the present invention;

[0036] Figure 3 A schematic flow chart of the product distribution optimization method provided by the present invention;

[0037] Figure 4 It is a structural schematic diagram of the oil refining control device provided by the present invention;

[0038] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0039] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0040] The petroleum processing process primarily involves rebalancing the carbon, hydrogen, and other elements in crude oil. To achieve a better product distribution, a hydrogenation unit is typically installed upstream of the catalytic cracking unit. Wax oil or residual oil, after being treated in the hydrogenation unit, is then fed into the catalytic cracking unit as feedstock for catalytic cracking reactions, producing products such as dry gas, liquefied petroleum gas, gasoline, light cycle oil, slurry oil, and coke.

[0041] In related technologies, hydrogenation units and catalytic cracking units are controlled separately. Specifically, for hydrogenation units, the depth of hydrogenation is calculated based on empirical formulas; for catalytic cracking units, the hydrogen content of each product is determined by sampling and analyzing the product to assess the rationality of catalytic unit operation.

[0042] The control methods in related technologies only consider the operating efficiency of a single catalytic cracking unit and ignore the hydrogenation costs of various upstream raw material hydrogenation units.

[0043] Figure 1 The flow diagram of the oil refining control method provided by the present invention is as follows: Figure 1 As shown, the method includes:

[0044] Step 110, obtaining initial operating parameters under the current refining conditions, and determining a product distribution prediction result for the current refining conditions based on the initial operating parameters and a product distribution prediction model; wherein the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0045] Specifically, in the embodiments of the present invention, the oil refining unit includes a catalytic cracking unit and a hydrogenation unit located upstream of the catalytic cracking unit. The feedstock used for refining can be either wax oil or residual oil. The hydrogenation unit is used to increase the hydrogen content of the feedstock. The catalytic cracking unit is used to perform a catalytic cracking reaction on the hydrogenated feedstock to separate various products.

[0046] The current refining condition is the current working state of the refining. The refining condition can be divided according to the processing raw materials, reaction temperature, reaction pressure, etc.

[0047] Operating parameters correspond to refining conditions and are used to control the operating status of catalytic cracking units and hydrogenation units. These parameters include the operating parameters of catalytic cracking units and the hydrogenation depth of hydrogenation units. For example, for a catalytic cracking unit, these parameters include the unit's operating parameters, such as reaction temperature, reaction pressure, and reactant residence time. Furthermore, these parameters may include analytical data for feedstocks and products, such as density, distillation range, sulfur content, nitrogen content, and hydrogen content. For a hydrogenation unit, these parameters may include the hydrogenation depth of the feedstock.

[0048] Initial operating parameters are the initial values ​​of various parameters that control the oil refining unit when it enters the current oil refining operating mode. The initial operating parameters can be initial parameters determined based on the operating experience of the operator or the default parameters of the oil refining unit.

[0049] The product distribution prediction results are the multiple products generated after the catalytic cracking reaction, as well as the predicted flow rate and predicted hydrogen content of each product. For example, for wax oil, after the catalytic cracking reaction, it produces products such as dry gas, liquefied gas, gasoline, light cycle oil, slurry oil, and coke. Its product distribution prediction results are the predicted flow rate and predicted hydrogen content of each product. The predicted flow rate is the predicted flow rate of a certain product produced by the catalytic cracking unit, which can be expressed in tons per hour (t / h) and is used to measure the production of this product. The predicted hydrogen content is the predicted value of the mass ratio of hydrogen elements in a certain product produced by the catalytic cracking unit, which can be expressed in percentage (%) and is used to measure the product quality of this product.

[0050] A product distribution prediction model is used to predict the distribution of various products generated after a catalytic cracking reaction of a feedstock. It can be determined based on the operating mechanism of the catalytic cracking reaction of the feedstock in a catalytic cracking unit. For example, a product distribution prediction model can be established based on the chemical equation for the catalytic cracking reaction of the feedstock and the law of conservation of mass observed by various elements in the catalytic cracking reaction. Another example is the mathematical modeling of the reaction-separation system of a catalytic cracking unit using existing refinery process simulation software to generate a product distribution prediction model.

[0051] Step 120: Determine target operating parameters for the current refinery operation based on preset optimization conditions and product distribution prediction results.

[0052] Specifically, the preset optimization conditions are used to optimize the product distribution prediction results in the catalytic cracking reaction.

[0053] According to the preset optimization conditions, optimization is performed on the basis of the product distribution prediction results. The optimization process can be to adjust the initial operating parameters, change the flow rate and / or hydrogen content of each product to meet the preset optimization conditions, obtain the product distribution optimization result, and use the operating parameters corresponding to the product distribution optimization result as the target operating parameters.

[0054] Step 130: Control the catalytic cracking unit and the hydrogenation unit based on the target operating parameters.

[0055] Specifically, the target operating parameters are determined based on the product distribution optimization results of the refinery unit. Using the target operating parameters, the catalytic cracking unit and the hydrogenation unit can be coordinated and controlled.

[0056] When the target operating parameters are used to control the catalytic cracking unit and the hydrogenation unit, the hydrogenation unit and the catalytic cracking unit can achieve upstream and downstream coordination, so that when the hydrogenated raw materials output by the hydrogenation unit enter the catalytic cracking unit for reaction, they can obtain the ideal product distribution optimization results according to the requirements of the preset optimization conditions, and avoid adding excessive hydrogen elements to cause waste.

[0057] The refinery control method provided by an embodiment of the present invention obtains initial operating parameters under the current refinery operating conditions, determines the product distribution prediction results of the current refinery operating conditions based on the initial operating parameters and a product distribution prediction model, and then determines the target operating parameters of the current refinery operating conditions based on preset optimization conditions and the product distribution prediction results. Finally, the catalytic cracking unit and the hydrogenation unit are controlled according to the target operating parameters. Since the target operating parameters are determined based on the product distribution results that meet the preset optimization conditions, coordinated control of the hydrogenation unit and the catalytic cracking unit is achieved without the need for human intervention, thereby improving the automation level of refinery control, and making the hydrogenation depth compatible with the catalytic cracking reaction while ensuring the target product yield, thereby reducing hydrogen consumption in the refining process.

[0058] Based on the above embodiment, the product distribution prediction model is determined based on the following steps:

[0059] Determine the initial model based on the operating mechanism of the catalytic cracking reaction of raw materials in the catalytic cracking unit;

[0060] Based on historical operating parameters and historical product distribution results under multiple refining conditions, the initial model is calibrated to obtain a product distribution prediction model;

[0061] The refining operating conditions are determined based on at least one of the type of raw material, the reaction temperature of the catalytic cracking unit, and the reaction pressure of the catalytic cracking unit.

[0062] Specifically, an initial model can be established based on the operating mechanism of the catalytic cracking reaction of the feedstock in the catalytic cracking unit. For example, mature process simulation software such as Aspen Plus, Hysys, and Petrosim can be used to mathematically model the reaction-separation system of the catalytic cracking unit.

[0063] A reaction-separation coupling mathematical model of the catalytic cracking unit is constructed as the initial model to calculate the data distribution under different operating conditions, including product flow rate, hydrogen content, etc. When the model calculation value deviates significantly from the measured value, the parameters in the reaction model are corrected.

[0064] The parameter calibration process of the initial model includes:

[0065] First, historical operating parameters and historical product distribution results under multiple refining conditions are collected.

[0066] Next, the initial model uses historical operating parameters under a specific refinery condition as input to calculate the flow rate and hydrogen content of each product. The output of the initial model serves as the model calculation value, and the historical product distribution results under that refinery condition serve as the measured values. The historical product distribution results include the measured flow rate and hydrogen content of each product.

[0067] Determine whether the sum of the deviations between the model calculated values ​​and the measured values ​​of each product is greater than a preset value. If so, optimize the reaction kinetic parameters of the initial model under the refining conditions until the sum of the deviations is less than or equal to the preset value. Then, obtain the basic parameters of the model under the refining conditions and obtain a product distribution prediction model. If the sum of the deviations between the calculated products and the measured values ​​is less than or equal to the preset value, use the parameters of the initial model at this time as the basic parameters of the model under the refining conditions to obtain a product distribution prediction model.

[0068] Based on any of the above embodiments, the preset optimization conditions are determined based on the flow rate and hydrogen content of each product in the product distribution prediction result.

[0069] Specifically, the preset optimization condition can be determined based on the flow rate or hydrogen content of each product in the product distribution prediction results. For example, the preset optimization condition can be that the sum of the flow rates of liquefied gas and gasoline is the largest among the flow rates of each product, and / or that the sum of the hydrogen content of dry gas and coke is the smallest among the hydrogen content of each product. For another example, the preset optimization condition can be that the flow rate of one or more products is greater than a preset flow rate threshold.

[0070] Based on any of the above embodiments, step 120 includes:

[0071] Determining an objective function in the preset optimization conditions based on a target flow rate of the first preset product and a target hydrogen content of the second preset product in the product distribution prediction result;

[0072] Determine the constraints in the preset optimization conditions based on the flow rate and hydrogen content of each product in the product distribution prediction results;

[0073] Based on the objective function, the initial operating parameters are adjusted to obtain operating parameter adjustment values, and based on the operating parameter adjustment values ​​and the product distribution prediction model, the product distribution optimization result of the current refining condition is determined;

[0074] If the product distribution optimization result meets the constraint conditions, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

[0075] Specifically, because the oil refining process produces multiple products, each with different utility values, the product distribution prediction results can be optimized by setting an objective function and preset products. The first preset product is a product optimized for the target flow rate, for example, the first preset product may include liquefied petroleum gas and gasoline. The second preset product is a product optimized for hydrogen content, for example, the second preset product may include dry gas and coke.

[0076] If the preset optimization conditions include the objective function of maximizing the output of liquefied gas and gasoline and minimizing the hydrogen content in dry gas and coke, it can be expressed as follows:

[0077] min y1=(F 干气 x 干气,H +F 焦炭 x 焦炭,H ) / (F 原料 x 原料,H )

[0078] maxy2=(F 液化气 +F 汽油 ) / F 原料

[0079] Where y1 is the objective function 1, y2 is the objective function 2, and x 原料,H is the mass fraction of hydrogen in the raw material, x 干气,H is the mass fraction of hydrogen in dry gas, x 焦炭,H is the mass fraction of hydrogen in coke, F 原料 is the flow rate of raw materials, F 液化气 is the flow rate of liquefied gas, F 汽油 is the gasoline flow rate, F 干气 is the flow rate of dry gas, F 焦炭 is the flow rate of coke.

[0080] In addition, the preset optimization conditions may also include constraints, which can be determined based on the flow rate and hydrogen content of each product in the product distribution prediction results. For example, the flow rate of each product should satisfy the mass conservation constraint, or the flow rate of a certain product should be greater than a preset flow threshold.

[0081] According to the objective function, the initial operating parameters are adjusted to obtain the operating parameter adjustment values, and the product distribution optimization results of the current refining conditions are determined based on the operating parameter adjustment values ​​and the product distribution prediction model.

[0082] To adjust the initial operating parameters, Matlab software can be used to establish a multi-objective optimization mathematical model for the device, call an optimization algorithm, and associate it with the product distribution prediction model. The optimization algorithm can include fuzzy optimization algorithm, multi-objective queue competition algorithm, genetic algorithm, neural network algorithm, etc.

[0083] If the product distribution optimization result of the current refining condition meets the constraint conditions, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

[0084] If the product distribution optimization result of the current refining condition does not meet the constraint conditions, it will be adjusted again according to the product distribution optimization result of the current refining condition and the objective function until the product distribution optimization result that meets the constraint conditions is obtained, and the corresponding operating parameter adjustment value will be used as the target operating parameter of the current refining condition.

[0085] Based on any of the above embodiments, step 130 includes:

[0086] Determining target operating parameters for the catalytic cracking unit and target hydrogenation depth for the hydrogenation unit based on the target operating parameters;

[0087] The catalytic cracking unit is controlled based on target operating parameters, and the hydrogenation unit is controlled based on a target hydrogenation severity.

[0088] Specifically, operating parameters may include the operating parameters of the catalytic cracking unit and the hydrogenation depth of the hydrogenation unit. Operating parameters include the reaction temperature, reaction pressure, and reactant residence time in the catalytic cracking unit. The reaction pressure can be selected from the outlet pressure of the unit. The hydrogenation depth refers to the completeness of the hydrotreating process, which converts unsaturated bonds in the feedstock into saturated bonds under the action of hydrogen and catalyst.

[0089] Target operating parameters include the target operating parameters for the catalytic cracking unit and the target hydrogenation depth for the hydrotreating unit. Based on the target operating parameters corresponding to the product distribution optimization results of the current refining conditions, the catalytic cracking unit and the hydrotreating unit can be coordinated and controlled simultaneously, ensuring that the hydrotreated feedstock meets the requirements of the catalytic cracking reaction while avoiding the addition of excessive hydrogen and reducing hydrogen consumption.

[0090] Based on any of the above embodiments, the initial operating parameters include raw material property parameters, initial operating parameters and initial value of hydrogenation depth, and the initial operating parameters include initial value of reaction temperature and initial value of reaction pressure in the catalytic cracking unit, as well as initial value of residence time of the raw material in the catalytic cracking unit.

[0091] Specifically, feedstock property parameters are physical or chemical properties of the feedstock itself, such as density, carbon residue, viscosity, and elemental mass fraction. Initial operating parameters are used to operate the catalytic cracking unit and provide a reaction environment for the catalytic cracking reaction. These initial operating parameters specifically include the initial values ​​of the reaction temperature and pressure in the catalytic cracking unit, as well as the initial value of the feedstock residence time in the catalytic cracking unit.

[0092] The initial value of the hydrogenation depth is the initial value of the hydrogenation depth set in the hydrogenation unit when entering the current refining operating conditions.

[0093] Based on any of the above embodiments, an embodiment of the present invention provides a wax oil processing control method, the method comprising:

[0094] Step 1: Collect basic data of the device and operating data corresponding to different working conditions, and establish a basic database.

[0095] The unit includes a hydrogenation unit and a catalytic cracking unit. The catalytic cracking unit is a parallel type with high and low reaction and regeneration. The reaction section adopts the MIP-CGP (clean gasoline production technology for increasing propylene and isomerized alkanes) process technology with an internal riser. The regeneration section adopts a parallel two-vessel regeneration technology. The first regenerator uses incomplete regeneration technology and is equipped with two sets of external heat exchangers. The second regenerator uses complete regeneration technology and is equipped with a regenerated catalyst degassing tank. The flue gases from the first and second regenerators are mixed in the flue and supplemented with air, causing the carbon monoxide to burn. The high-temperature flue gas is heated by the high heat exchanger and, after cooling, is sent to the third-stage cyclone separator.

[0096] Historical data was collated and categorized into several operating conditions based on the unit's raw material processing volume, slag blending amount, recycled oil volume, reactor outlet temperature, and reactor outlet pressure. Taking one of these operating conditions as the current operating condition, the relevant key parameters of the data are presented. The key raw material properties, catalyst parameters, and operating parameters for this condition are shown in Tables 1, 2, and 3, respectively.

[0097] Table 1 Main properties of crude oil

[0098] project Numerical project Numerical <![CDATA[Density (20 °C), kg / m 3 > 903.7 Distillation range, ℃ Residual carbon value, % 4.08 Initial distillation point 180.9 <![CDATA[Viscosity (80 °C), mm 2 / s]]> 34.32 5％ 271.5 Relative molecular mass 509 10％ 357.5 Element mass fraction, % 20％ 412.9 C 86.78 30％ 446.6 H 12.91 40％ 494.9 S 0.28 50％ 540.4 N 0.18 60％ 577.8

[0099] Table 2 Main parameters of catalyst

[0100]

[0101]

[0102] Table 3 Operating parameters

[0103]

[0104]

[0105] Step 2: Construct a reaction-separation coupling mathematical model for the catalytic cracking unit and calculate the data distribution under different operating conditions, including product flow rate, hydrogen content, etc. When the model calculation value deviates significantly from the measured value, the parameters in the reaction model are corrected.

[0106] Based on the unit type, feedstock, and product distribution, the present embodiment uses Hysys to construct a coupled reaction-separation mathematical model for a catalytic cracking unit. After inputting information such as feedstock, products, and key operating conditions into the model framework, the reaction kinetics model uses the software's default settings, i.e., the default kinetic parameters provided by Hysys for catalytic cracking reactions and heat balance calculations.

[0107] Figure 2 Schematic diagram of the reaction-separation coupling mathematical model provided by the present invention, such as Figure 2As shown, based on the deviations between the calculated results of the catalytic cracking reaction-separation mathematical model and the measured results, a judgment is made as to whether the sum of the deviations between the calculated and measured results for each product is greater than a preset value. If so, the reaction kinetic parameters of the model under that operating condition are optimized until the sum of the deviations is less than or equal to the preset value, thereby obtaining the basic model parameters for that operating condition. If the sum of the deviations is less than or equal to the preset value, the reaction kinetic parameters at that time are used as the basic model parameters for that operating condition.

[0108] For example, under the current operating conditions, the calculation results of the reaction-separation coupling mathematical model are shown in Table 4.

[0109] Table 4 Model calculation results

[0110]

[0111]

[0112] Step 3: Establish a multi-objective optimization mathematical model for product distribution, with the optimization objectives of maximizing the output of liquefied gas and gasoline and minimizing the hydrogen content in dry gas and coke.

[0113] Matlab was used to establish a multi-objective optimization mathematical model for product distribution in a catalytic cracking unit based on optimal hydrogen distribution and maximum target product yield.

[0114] Among them, the objective function is:

[0115] miny1=(F 干气 x 干气,H +F 焦炭 x 焦炭,H ) / (F 原料 x 原料,H )

[0116] maxy2=(F 液化气 +F 汽油 ) / F 原料油

[0117] When the optimization goal is to minimize the hydrogen content in the raw material, the objective function can also be:

[0118] miny1=x 原料,H

[0119] The constraints are:

[0120] (1) Balance constraints

[0121] F 原料 =F 干气 +F 液化气 +F 汽油 +F 轻循环油 +F 焦炭

[0122] F 原料 x 原料,H =F 干气 x 干气,H +F 液化气 x 液化气,H +F 汽油 x 汽油,H +F 轻循环油 x 轻循环油,H +F 油浆 x 油浆,H +F 焦炭 x 焦炭,H

[0123] (2) Other constraints

[0124] Liquefied gas product flow rate ≥47t / h;

[0125] Gasoline product flow rate ≥110t / h;

[0126] C3+ content constraint in dry gas, with the constraint condition being that the volume fraction of C3+ light hydrocarbons is ≤ 3%;

[0127] The C2 content in the liquefied gas is constrained, with the C2 volume fraction being ≤ 0.4%;

[0128] The C5 content in liquefied gas is constrained, with the C5 volume fraction being ≤1%;

[0129] Gasoline ASTM D86 dry point constraint, constraint conditions are 200~204℃;

[0130] Crude oil flow restriction, 160t / h≤F 原料 ≤250t / h;

[0131] The residual carbon CT of the crude oil is limited to 3.0%≤CT≤8.0%;

[0132] Feed oil hydrogen content constraint, 11.0% ≤ x 原料,H ≤14.0%;

[0133] Reactor outlet temperature constraint, 480℃≤t 反应器出口 ≤520℃;

[0134] Reaction pressure constraint, 0.25MPa≤P 反应 ≤0.40MPa;

[0135] Stable gasoline circulation rate, 25-45t / h;

[0136] Reabsorbent flow rate of reabsorption tower, 30-60t / h;

[0137] Reabsorbent temperature in reabsorption tower: 30-40℃;

[0138] Product hydrogen content constraints:

[0139] a. The hydrogen content in dry gas and coke is less than that in liquid oil products.

[0140] F 干气 x 干气,H +F 焦炭 x 焦炭,H <F 液化气 x 液化气,H +F 汽油 x 汽油,H +F 轻循环油 x 轻循环油,H +F 油浆 x 油浆,H

[0141] b. The hydrogen content in liquefied gas is greater than that in slurry oil.

[0142] F 液化气 x 液化气,H >F 油浆 x 油浆,H

[0143] Where: y1 is objective function 1; y2 is objective function 2; x 原料,H is the mass fraction of hydrogen in the raw material, F 原料 is the flow rate of raw materials; F 干气 is the dry gas flow rate, t / h; x 干气,H is the mass fraction of hydrogen in dry gas, %; F 液化气 is the liquefied gas flow rate, t / h; x 液化气,H is the mass fraction of hydrogen in liquefied gas, %; F 汽油 is the gasoline flow rate, t / h; x 汽油,H is the mass fraction of hydrogen in gasoline, %; F 轻循环油 is the light circulating oil flow rate, t / h; x 轻循环油,H is the mass fraction of hydrogen in light cycle oil, %; F 油浆 is the oil slurry flow rate, t / h; x 油浆,H is the mass fraction of hydrogen in the oil slurry, %; F 焦炭 is the coke flow rate, t / h; x 焦炭 , H is the mass fraction of hydrogen in coke, %; CT is the residual carbon in raw materials, %; t 反应器出口 is the outlet temperature of reactor (No. 1, No. 2), ℃; P 反应 is the reaction pressure, MPa.

[0144] Step 4: Obtain the optimal product distribution and target operating parameters under the current working conditions

[0145] Figure 3 A schematic diagram of the process for optimizing product distribution provided by the present invention is shown in FIG. Figure 3 As shown in the figure, a data transmission platform between Matlab and Hysys was established to achieve data linkage between the optimization model and the reaction-separation model of the catalytic cracking unit. The multi-objective optimization algorithm of Matlab was then used to optimize the solution. The operating parameters corresponding to the optimized product distribution were used as the target operating parameters to control the catalytic cracking unit and hydrogenation unit.

[0146] The optimal product distribution under the current operating conditions is shown in Table 5. A multi-objective optimization model for FCC product distribution was used to solve the product distribution and feedstock hydrogen content requirement, while meeting the unit's production target (liquefied gas + gasoline). Under optimized unit operation, reducing the hydrogen content of the FCC feed from 12.91% to 12.12% would not affect the unit's production target, and the product quality remained acceptable. This reduction in hydrogen content in the FCC feed also reduced the depth of hydrogenation in the upstream gas oil hydrotreating unit, reducing hydrogen consumption by 15,800 tons / year.

[0147] Table 5 Optimization solution calculation results

[0148]

[0149] Based on any of the above embodiments, Figure 4 It is a structural diagram of the oil refining control device provided by the present invention, such as Figure 4 As shown, the device includes:

[0150] An acquisition unit 410 is configured to acquire initial operating parameters under the current refinery operating conditions, and determine a product distribution prediction result under the current refinery operating conditions based on the initial operating parameters and a product distribution prediction model;

[0151] The optimization unit 420 is used to determine the target operating parameters of the current refinery operation conditions based on the preset optimization conditions and the product distribution prediction results;

[0152] A control unit 430 is used to control the catalytic cracking unit and the hydrogenation unit based on target operating parameters;

[0153] Among them, the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0154] The refinery control device provided by the embodiment of the present invention obtains initial operating parameters under the current refinery operating conditions, and determines the product distribution prediction results of the current refinery operating conditions based on the initial operating parameters and a product distribution prediction model. Then, based on preset optimization conditions and the product distribution prediction results, the target operating parameters of the current refinery operating conditions are determined. Finally, the catalytic cracking unit and the hydrogenation unit are controlled according to the target operating parameters. Since the target operating parameters are determined based on the product distribution results that meet the preset optimization conditions, coordinated control of the hydrogenation unit and the catalytic cracking unit is achieved without the need for human intervention, thereby improving the automation level of refinery control. While ensuring the target product yield, the hydrogenation depth is adapted to the catalytic cracking reaction, thereby reducing hydrogen consumption in the refining process.

[0155] Based on any of the above embodiments, the device further includes:

[0156] A model determination unit, for determining an initial model based on an operating mechanism of a catalytic cracking reaction of raw materials in a catalytic cracking unit;

[0157] Based on historical operating parameters and historical product distribution results under multiple refining conditions, the initial model is calibrated to obtain a product distribution prediction model;

[0158] The refining operating conditions are determined based on at least one of the type of raw material, the reaction temperature of the catalytic cracking unit, and the reaction pressure of the catalytic cracking unit.

[0159] Based on any of the above embodiments, the preset optimization conditions are determined based on the flow rate and hydrogen content of each product in the product distribution prediction result.

[0160] Based on any of the above embodiments, the optimization unit is configured to:

[0161] Determining an objective function in the preset optimization conditions based on a target flow rate of the first preset product and a target hydrogen content of the second preset product in the product distribution prediction result;

[0162] Determine the constraints in the preset optimization conditions based on the flow rate and hydrogen content of each product in the product distribution prediction results;

[0163] Based on the objective function, the initial operating parameters are adjusted to obtain operating parameter adjustment values, and based on the operating parameter adjustment values ​​and the product distribution prediction model, the product distribution optimization result of the current refining condition is determined;

[0164] If the product distribution optimization result meets the constraint conditions, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

[0165] Based on any of the above embodiments, the control unit is configured to:

[0166] Determining target operating parameters for the catalytic cracking unit and target hydrogenation depth for the hydrogenation unit based on the target operating parameters;

[0167] The catalytic cracking unit is controlled based on target operating parameters, and the hydrogenation unit is controlled based on a target hydrogenation severity.

[0168] Based on any of the above embodiments, the initial operating parameters include raw material property parameters, initial operating parameters and initial value of hydrogenation depth, and the initial operating parameters include initial value of reaction temperature and initial value of reaction pressure in the catalytic cracking unit, as well as initial value of residence time of the raw material in the catalytic cracking unit.

[0169] Based on any of the above embodiments, Figure 5 A schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 5 As shown, the electronic device may include: a processor (Processor) 510, a communication interface (Communications Interface) 520, a memory (Memory) 530 and a communication bus (Communications Bus) 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other via the communication bus 540. The processor 510 may call the logic commands in the memory 530 to execute the following method:

[0170] Obtain the initial operating parameters under the current refining conditions, and determine the product distribution prediction results of the current refining conditions based on the initial operating parameters and the product distribution prediction model; determine the target operating parameters of the current refining conditions based on the preset optimization conditions and the product distribution prediction results; control the catalytic cracking unit and the hydrogenation unit based on the target operating parameters; wherein the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0171] In addition, the logical commands in the above-mentioned memory 530 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several commands to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0172] The processor in the electronic device provided by the embodiment of the present invention can call the logic instructions in the memory to implement the above method. Its specific implementation method is consistent with the implementation method of the above method and can achieve the same beneficial effects, which will not be repeated here.

[0173] An embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method provided in each of the above embodiments is implemented, for example, including:

[0174] Obtain the initial operating parameters under the current refining conditions, and determine the product distribution prediction results of the current refining conditions based on the initial operating parameters and the product distribution prediction model; determine the target operating parameters of the current refining conditions based on the preset optimization conditions and the product distribution prediction results; control the catalytic cracking unit and the hydrogenation unit based on the target operating parameters; wherein the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit.

[0175] When the computer program stored on the non-transitory computer-readable storage medium provided by the embodiment of the present invention is executed, the above method is implemented. Its specific implementation method is consistent with the implementation method of the aforementioned method and can achieve the same beneficial effects, which will not be repeated here.

[0176] An embodiment of the present invention provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0177] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0178] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of commands for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiment.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for controlling oil refining, characterized in that: include: Acquiring initial operating parameters under current refinery operating conditions, and determining a product distribution prediction result for the current refinery operating conditions based on the initial operating parameters and a product distribution prediction model; Determining target operating parameters for the current refinery operating conditions based on preset optimization conditions and the product distribution prediction result; controlling the catalytic cracking unit and the hydrogenation unit based on the target operating parameters; Wherein, the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit; The preset optimization conditions are determined based on the flow rate and hydrogen content of each product in the product distribution prediction result; Determining target operating parameters of the current refining condition based on preset optimization conditions and the product distribution prediction result includes: Determining an objective function in the preset optimization condition based on a target flow rate of a first preset product and a target hydrogen content of a second preset product in the product distribution prediction result; Determining the constraints in the preset optimization conditions based on the flow rate and hydrogen content of each product in the product distribution prediction result; Based on the objective function, adjusting the initial operating parameters to obtain operating parameter adjustment values, and determining a product distribution optimization result of the current refining operating condition based on the operating parameter adjustment values ​​and the product distribution prediction model; If the product distribution optimization result satisfies the constraint condition, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

2. The oil refining control method according to claim 1, characterized in that: The product distribution prediction model is determined based on the following steps: Determining an initial model based on an operating mechanism of a catalytic cracking reaction of raw materials in the catalytic cracking unit; Correcting the initial model based on historical operating parameters and historical product distribution results under multiple refining conditions to obtain the product distribution prediction model; The refining operating conditions are determined based on at least one of the type of the raw material, the reaction temperature of the catalytic cracking unit, and the reaction pressure of the catalytic cracking unit.

3. The oil refining control method according to claim 1 or 2, characterized in that: The controlling of the catalytic cracking unit and the hydrogenation unit based on the target operating parameters includes: Determining target operating parameters of the catalytic cracking unit and target hydrogenation depth of the hydrogenation unit based on the target operating parameters; The catalytic cracking unit is controlled based on the target operating parameters, and the hydrogenation unit is controlled based on the target hydrogenation severity.

4. The oil refining control method according to claim 1 or 2, characterized in that: The initial operating parameters include raw material property parameters, initial operating parameters and initial value of hydrogenation depth. The initial operating parameters include initial value of reaction temperature and initial value of reaction pressure in the catalytic cracking unit, and initial value of residence time of the raw material in the catalytic cracking unit.

5. An oil refining control device, characterized in that: include: an acquisition unit, configured to acquire initial operating parameters under a current refining operating condition, and determine a product distribution prediction result under the current refining operating condition based on the initial operating parameters and a product distribution prediction model; An optimization unit, configured to determine target operating parameters of the current refinery operating conditions based on preset optimization conditions and the product distribution prediction result; a control unit, configured to control the catalytic cracking unit and the hydrogenation unit based on the target operating parameters; Wherein, the product distribution prediction model is determined based on the operating mechanism of the catalytic cracking reaction of the raw materials in the catalytic cracking unit; The preset optimization conditions are determined based on the flow rate and hydrogen content of each product in the product distribution prediction result; Determining target operating parameters of the current refining condition based on preset optimization conditions and the product distribution prediction result includes: Determining an objective function in the preset optimization condition based on a target flow rate of a first preset product and a target hydrogen content of a second preset product in the product distribution prediction result; Determining the constraints in the preset optimization conditions based on the flow rate and hydrogen content of each product in the product distribution prediction result; Based on the objective function, adjusting the initial operating parameters to obtain operating parameter adjustment values, and determining a product distribution optimization result of the current refining operating condition based on the operating parameter adjustment values ​​and the product distribution prediction model; If the product distribution optimization result satisfies the constraint condition, the operating parameter adjustment value corresponding to the product distribution optimization result is used as the target operating parameter of the current refining condition.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the oil refinery control method according to any one of claims 1 to 4 are implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the oil refinery control method according to any one of claims 1 to 4 are implemented.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the oil refinery control method according to any one of claims 1 to 4 are implemented.

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