A forward looking crude oil replacement scenario planning method

Abstract

The application discloses a kind of prospective crude oil alternative scheme planning methods, according to the property value of supply interruption crude oil, several alternative crude oils are screened, then the property value of alternative crude oil and purchase price are input into mixed crude oil proportioning calculation model to calculate, so that a plurality of mixed crude oil proportions are obtained, and a group of crude oil mixing schemes are obtained.In addition, in order to combine the crude oil mixing scheme calculated by the mixed crude oil proportioning calculation model with the actual refinery production work, a linear digital simulation model is established according to the actual refinery device, the yield and related property values of the products extracted from the side line of the crude oil mixing scheme output by the mixed crude oil proportioning calculation model are calculated under the actual production state, the best crude oil mixing scheme is selected according to the yield and related property values of the products extracted from the side line of the crude oil mixing scheme and the price of the mixed crude oil, and then the alternative crude oil is purchased according to the best crude oil mixing scheme.

Description

Technical Field

[0001] This invention relates to the field of crude oil selection technology, and more specifically to a forward-looking crude oil alternative planning method. Background Technology

[0002] The crude oil supply chain is a vast network, significantly impacted by changes in crude oil exploration, petroleum resource supply, crude oil prices, and geopolitical factors. To stabilize production, companies typically plan their procurement in advance based on crude oil inventories, optimizing production and meeting demand by controlling the proportions of various crude oils. However, with the rising international crude oil prices and various unforeseen circumstances during crude oil procurement, there is currently no crude oil substitute that can quickly and effectively address unforeseen situations during procurement.

[0003] Normally, purchasing personnel determine the types of crude oil to be purchased based on the production plan. However, unforeseen circumstances, such as localized wars, often arise during the procurement process, making it impossible to procure one or more types of crude oil as originally planned. Based on the actual market situation, purchasing personnel provide several alternative types of crude oil that are available for procurement, allowing dispatchers to select the most suitable crude oil for the next production cycle.

[0004] Traditional crude oil dispatching for handling unforeseen procurement situations largely relies on the experience of dispatchers, aiming to achieve material balance and selecting oils within production constraints. However, such selections made by dispatchers in a very short time often have many disadvantages, such as extremely high procurement prices, product properties that do not meet actual needs, or increased energy consumption. Furthermore, the quality of the selected substitute crude oil depends heavily on the experience and skill of the dispatchers, which is not only time-consuming and labor-intensive but also fails to select the most suitable substitute oil and blend ratio within a short period. This leads to excessive time spent on procurement decisions, the risk of supply disruptions, and impacts subsequent production plans. Summary of the Invention

[0005] The following provides a brief overview of one or more aspects to offer a basic understanding of them. This overview is not an exhaustive summary of all conceived aspects, nor is it intended to identify key or decisive elements of all aspects, nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form to prepare for the more detailed descriptions that follow.

[0006] The purpose of this invention is to solve the above-mentioned problems and provide a forward-looking crude oil substitution planning method. This method involves screening several candidate crude oils based on the physical properties of crude oils experiencing supply disruptions, and then inputting the physical properties and purchase price of these candidate crude oils into a crude oil blending ratio calculation model for calculation. This yields multiple crude oil blending ratios, which constitute a set of crude oil blending schemes. Furthermore, to integrate the crude oil blending schemes calculated by the crude oil blending ratio calculation model with actual refinery production, this embodiment establishes a linear digital simulation model based on the actual refinery units. This model is used to calculate the distillate production and physical properties of the distillate fraction extracted from the side stream of the atmospheric and vacuum distillation unit under actual production conditions. Then, based on the distillate production, physical properties, and crude oil price from the side stream of the atmospheric and vacuum distillation unit, the optimal crude oil blending scheme is selected, and substitute crude oil is purchased according to the optimal crude oil blending scheme.

[0007] The technical solution of this invention is as follows:

[0008] This invention provides a forward-looking crude oil alternative planning method, comprising the following steps:

[0009] Obtain information on alternative crude oils from multiple sources;

[0010] Calculate the blending ratio of crude oil based on the information of alternative crude oils, and obtain multiple crude oil blending schemes;

[0011] Calculate the distillate production and physical properties of the distillate extracted from the side stream of the atmospheric and vacuum distillation unit under different crude oil mixing schemes based on the corresponding crude oil blending ratios of each crude oil mixing scheme.

[0012] Based on the distillate production, distillate properties, and blended crude oil price of each crude oil blending scheme, the optimal crude oil blending scheme is selected, and alternative crude oil procurement information is obtained.

[0013] According to an embodiment of the forward-looking crude oil substitution planning method of the present invention, the forward-looking crude oil substitution planning method uses a blended crude oil ratio calculation model to calculate the blended crude oil ratio; wherein, the candidate crude oil information includes candidate crude oil physical property values ​​and candidate crude oil purchase prices, and after obtaining candidate crude oil information of multiple candidate crude oils, the forward-looking crude oil substitution planning method inputs the obtained candidate crude oil physical property values ​​and candidate crude oil purchase prices into the blended crude oil ratio calculation model for calculation to obtain multiple blended crude oil ratios.

[0014] According to an embodiment of the forward-looking crude oil substitution planning method of the present invention, the blended crude oil ratio calculation model establishes an objective function based on the purchase price of the blended crude oil corresponding to the candidate crude oils, and constrains the objective function using the actual required range of blended crude oil properties, thereby optimizing the blended crude oil ratio through the actual required range of blended crude oil properties; wherein, the actual required range of blended crude oil properties includes the range of API values ​​and the range of sulfur content of blended crude oil, and the blended crude oil ratio calculation model establishes the following optimization objective function through the range of API values ​​and the range of sulfur content of blended crude oil:

[0015]

[0016] in,

[0017] h(x) n This represents the purchase price of the blended crude oil corresponding to the nth blended crude oil ratio.

[0018] P n This represents the percentage of the nth type of crude oil that can be purchased.

[0019] C n This represents the purchase price of the nth type of crude oil at its corresponding percentage.

[0020] B i This represents the proportion of the i-th alternative crude oil.

[0021] BC i This represents the purchase price of the i-th alternative crude oil.

[0022] A n This represents the API value of the nth type of crude oil available for purchase.

[0023] BA i This represents the API value of the i-th alternative crude oil.

[0024] minApi represents the minimum API value required for the actual blend of crude oil.

[0025] maxApi represents the maximum API value required for the actual blend of crude oil.

[0026] S n This represents the sulfur content of the available crude oil in the nth batch.

[0027] BS i This represents the sulfur content of the i-th candidate crude oil.

[0028] f(x) n This represents the API value of the blended crude oil corresponding to the nth blended crude oil ratio.

[0029] g(x) nThis indicates the sulfur content of the blended crude oil corresponding to the nth blended crude oil ratio.

[0030] According to an embodiment of the forward-looking crude oil substitution planning method of the present invention, after establishing an optimized objective function based on the API value range and sulfur content range of the mixed crude oil, the method inputs the obtained candidate crude oil property values ​​into the mixed crude oil blending calculation model for calculation. The candidate crude oil property values ​​include the candidate crude oil API value, the candidate crude oil sulfur content, and the candidate crude oil purchase price. After inputting the obtained crude oil property values ​​and candidate crude oil purchase prices into the mixed crude oil blending calculation model, the method calculates the mixed crude oil purchase price corresponding to different mixed crude oil blending ratios, and constrains the mixed crude oil blending ratios corresponding to the candidate crude oils according to the API value range and sulfur content of the mixed crude oils, thereby obtaining mixed crude oil blending ratios within various practically required ranges of mixed crude oil property values.

[0031] According to an embodiment of the forward-looking crude oil alternative planning method of the present invention, before the blended crude oil ratio calculation model calculates the blended crude oil ratio, multiple alternative crude oils are selected based on the physical property values ​​of crude oils with supply disruptions, and the alternative crude oil information of the alternative crude oils is obtained according to the crude oil evaluation table. Then, the alternative crude oil information of the selected alternative crude oils is input into the blended crude oil ratio calculation model for calculation, thereby obtaining multiple blended crude oil ratios; wherein, the physical property values ​​of crude oils with supply disruptions include the API value and sulfur content of crude oils with supply disruptions.

[0032] According to one embodiment of the forward-looking crude oil substitution planning method of the present invention, after obtaining multiple crude oil blending schemes through a blending crude oil ratio calculation model, the method uses a linear digital simulation model to calculate the distillate production and distillate properties extracted from the side line of the atmospheric and vacuum distillation unit corresponding to each crude oil blending scheme. Then, based on the distillate production and distillate properties extracted from the side line of the atmospheric and vacuum distillation unit corresponding to each crude oil blending scheme, as well as the blending crude oil price, the optimal crude oil blending scheme is selected, thereby obtaining alternative crude oil procurement information.

[0033] According to an embodiment of the forward-looking crude oil substitution planning method of the present invention, the forward-looking crude oil substitution planning method establishes a linear digital simulation model based on actual refinery units; wherein, the linear digital simulation model abstracts each actual refinery unit model into a linear digital simulation refinery unit model, and simulates the actual production state of the corresponding actual refinery unit by controlling the input and output information of each refinery unit model, and obtains the distillate oil production and distillate oil physical property values ​​extracted from the side line of the atmospheric and vacuum distillation unit under the actual production state.

[0034] According to an embodiment of the forward-looking crude oil alternative planning method of the present invention, the linear digital simulation model digitizes the input information of each refinery unit model into events, and constructs a multi-event combination of atmospheric and vacuum distillation unit production scheduling scheme by adjusting the events corresponding to each refinery unit model; wherein, the linear digital simulation model sets corresponding output calculation methods for the events of different refinery unit models, and after each refinery unit model obtains the corresponding input information through multiple set events, it calculates the obtained input information using the bound output calculation method to obtain the output information of the corresponding refinery unit model.

[0035] According to an embodiment of the forward-looking crude oil substitution planning method of the present invention, the events are divided into non-adjustable events and dynamically adjustable events; wherein, non-adjustable events include unit yield, reaction temperature, and tower pressure, and dynamically adjustable events include the proportion of each crude oil involved in production, sulfur content, dry point, and API value; wherein, after the linear digital simulation model obtains the corresponding actual refinery unit production indicators through the non-adjustable events set by the refinery unit model, it adjusts the proportion of crude oil involved in production, sulfur content, dry point, and API value by adjusting the input information of the dynamically adjustable events, and then calculates the input information of the dynamically adjustable events using the corresponding output calculation method to obtain the output information of each refinery unit model.

[0036] According to one embodiment of the forward-looking crude oil alternative planning method of the present invention, the linear digital simulation model establishes a material balance calculation model based on the actual crude oil processing capacity of the atmospheric and vacuum distillation unit, and ensures the material balance of each atmospheric and vacuum distillation unit and each intermediate storage tank through the material balance calculation model.

[0037] According to one embodiment of the forward-looking crude oil substitution planning method of the present invention, the forward-looking crude oil substitution planning method calculates the distillate production and distillate properties extracted from the side line of the atmospheric and vacuum distillation unit corresponding to different crude oil blending schemes through a linear digital simulation model. Based on the distillate production, distillate properties, and blended crude oil prices of the atmospheric and vacuum distillation unit, a complete set of reports for the atmospheric and vacuum distillation unit is generated. The optimal crude oil blending scheme is selected based on the complete set of reports for the atmospheric and vacuum distillation unit, and alternative crude oil procurement information is obtained.

[0038] Compared with existing technologies, this invention has the following advantages: To quickly obtain alternative crude oil procurement information, this invention establishes an objective function for a mixed crude oil blending ratio calculation model based on the purchase price of the selected crude oil. The objective function is then constrained by the actual required range of mixed crude oil properties, thus obtaining a mixed crude oil blending ratio calculation model for quickly calculating the blending ratio of the alternative crude oil. When calculating the blending ratio of the alternative crude oil using this model, the purchase price of the mixed crude oil corresponding to different blending ratios is calculated based on the crude oil properties and the purchase price of the selected crude oil. The blending ratio of the selected crude oil is constrained by the range of API values ​​and sulfur content of the mixed crude oil. The blending ratio with the lowest purchase price is selected based on the API value range and sulfur content of the mixed crude oil. Then, a linear digital simulation model based on actual refinery units is used to calculate the side-stream extracted product output and related properties of the atmospheric and vacuum distillation unit corresponding to different blending ratios. Based on the side-stream extracted product output and related properties of the atmospheric and vacuum distillation unit, and the price of the mixed crude oil, the optimal crude oil blending scheme is selected, and alternative crude oil is procured according to the optimal blending scheme. Compared with existing technologies, this invention, when faced with procurement emergencies, can quickly obtain the lowest-priced blending ratio of alternative crude oil within the actual required blending property range using a blending crude oil ratio calculation model. Then, it uses a linear digital simulation model to calculate the side-line extraction product output and related property values ​​of different blending crude oil ratios under actual production conditions in the atmospheric and vacuum distillation unit, and generates a complete set of reports for the atmospheric and vacuum distillation unit. This allows for the rapid selection of alternative crude oils and the determination of the blending crude oil ratio during actual production, improving the planning efficiency of alternative crude oil solutions, avoiding the risk of oil supply interruptions, ensuring the smooth operation of the production process, and ultimately improving the company's economic benefits and reducing economic losses. Attached Figure Description

[0039] The above-described features and advantages of the present invention will be better understood after reading the following detailed description of embodiments of the present disclosure in conjunction with the accompanying drawings. In the drawings, components are not necessarily drawn to scale, and components having similar related properties or features may have the same or similar reference numerals.

[0040] Figure 1 This is a structural diagram illustrating an embodiment of the forward-looking crude oil alternative planning method of the present invention.

[0041] Figure 2 This is a structural diagram illustrating an embodiment of the forward-looking crude oil alternative planning device of the present invention. Detailed Implementation

[0042] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should be noted that the aspects described below with reference to the accompanying drawings and specific embodiments are merely exemplary and should not be construed as limiting the scope of protection of the present invention in any way.

[0043] This document discloses an embodiment of a forward-looking crude oil alternative planning method. Figure 1 This is a structural diagram illustrating an embodiment of the forward-looking crude oil substitution planning method of the present invention. Please refer to... Figure 1 The following is a detailed explanation of each step in the forward-looking crude oil alternative planning methodology.

[0044] Step S1: Obtain information on multiple alternative crude oils.

[0045] During crude oil dispatching, if the supply of a certain type of crude oil is interrupted, the planned blend of crude oil for production and processing may lack the crude oil in the original production ratio. Therefore, it is necessary to select a substitute crude oil to replace the interrupted crude oil, and the blend ratio of crude oil will change accordingly. In the actual screening process of alternative crude oils, the number of alternative crude oils should not be too large, generally controlled at 8-12 types.

[0046] Specifically, in this embodiment, without considering excessive additional factors, eight crude oils are randomly selected as candidate crude oils. These are then modified based on actual conditions. The physical properties of the interrupted crude oil are used to adjust the candidate crude oils. Based on the physical properties of the interrupted crude oil, several oils with API values ​​and sulfur content very similar to the interrupted crude oil are selected from the eight randomly selected crude oils as candidate crude oils. Then, the candidate crude oil information is obtained from a crude oil evaluation table, and the corresponding blending ratio is calculated based on this information, resulting in multiple candidate blending ratios. These blending ratios form a set of crude oil blending schemes. This method of first randomizing and then constraining the selection of candidate crude oils ensures that each candidate crude oil has a blending ratio that satisfies the constraints when calculating the blending ratio, providing more choices for crude oil substitution schemes. If candidate crude oils are only randomly selected, some constraints may not be met, meaning that the candidate crude oil may be eliminated due to the inability to obtain the corresponding blending ratio, ultimately reducing the number of candidate schemes.

[0047] Furthermore, in this embodiment, the API value, sulfur content, and purchase price of each candidate crude oil are generally available from the crude oil evaluation table. However, when the API value of the candidate crude oil is not available in the crude oil evaluation table, but crude oil density information is available, the API value of the candidate crude oil can be calculated using the following formula:

[0048] API = (141.5 / relative density) - 131.5

[0049] Step S2: Calculate the blending ratio of crude oil based on the information of the alternative crude oils to obtain multiple crude oil blending schemes.

[0050] In this embodiment, after obtaining several candidate crude oils with API values ​​and sulfur content very similar to those of crude oils with supply disruptions through step S1, a crude oil blending ratio calculation model is used to calculate the blending ratio. The candidate crude oil information includes the physical properties and purchase price of the candidate crude oils. After obtaining the candidate crude oil information selected in step S1, the obtained physical properties and purchase price are input into the crude oil blending ratio calculation model for calculation, thereby obtaining various blending ratios.

[0051] Specifically, in this embodiment, to calculate the blended crude oil ratio with the lowest purchase price within the actual required range of crude oil property values, an objective function for the blended crude oil ratio calculation model is established based on the purchase price of the selected crude oils. This objective function is then constrained by the actual required range of crude oil property values. The blended crude oil ratio is optimized through this range to obtain the blended crude oil ratio calculation model. The actual required range of crude oil property values ​​includes the range of API values ​​and the range of sulfur content. After inputting the information of the selected crude oils into the blended crude oil ratio calculation model, the model calculates the blended crude oil ratio with the lowest purchase price within the actual required range of crude oil property values ​​using the following optimization objective function:

[0052]

[0053] Where, h(x) n P represents the purchase price of the blended crude oil corresponding to the nth blended crude oil ratio. n C represents the percentage of the nth type of crude oil that can be purchased. n B represents the purchase price of the nth type of crude oil at its corresponding percentage. i BC represents the proportion of the i-th alternative crude oil. i Let A represent the purchase price of the i-th alternative crude oil. n BA represents the API value of the nth type of crude oil available for purchase. i S represents the API value of the i-th alternative crude oil, minApi represents the minimum API value of the actual required blend of crude oils, maxApi represents the maximum API value of the actual required blend of crude oils, and S n BS represents the sulfur content of the nth available crude oil. i Let f(x) represent the sulfur content of the i-th candidate crude oil. n Let g(x) represent the API value of the blended crude oil corresponding to the nth blending ratio. nThis represents the sulfur content of the blended crude oil corresponding to the nth crude oil blending ratio. The above constraints are not ranked in terms of importance, but must be satisfied simultaneously. Based on satisfying the constraints, the blending ratio of the crude oil is solved in conjunction with the objective function.

[0054] In one implementation, the required API value of the blended crude oil is determined to be between 28 and 32, and the sulfur content is determined to be between 0.3 and 1.6%. Assuming there are 8 types of crude oil available for selection and 3 types available for purchase, one type of crude oil is selected from the 8 and input into the blending crude oil ratio calculation model for mixing. By randomly generating the ratio 300 times, 300 sets of blended crude oil ratios are obtained. These 300 sets of blended crude oil ratios are then substituted into the aforementioned optimization objective function for optimization, thereby obtaining the blended crude oil ratio that satisfies the requirements of an API value between 28 and 32, a sulfur content between 0.3 and 1.6, and the lowest possible purchase price.

[0055] Furthermore, in this embodiment, the crude oil blending calculation model needs to control the proportion of each crude oil in the blending ratio to ensure that the proportion of each crude oil in the final blending ratio is not less than 5%, thus ensuring that the blending ratio is more consistent with actual production conditions. If the proportion of a single crude oil is not controlled, resulting in a blending ratio of 0.0000002%, this would be inconsistent with actual production verification.

[0056] Step S3: Calculate the distillate production and physical properties of the distillate extracted from the side stream of the atmospheric and vacuum distillation unit under different crude oil mixing schemes based on the blending ratio of each crude oil mixing scheme.

[0057] In this embodiment, after obtaining a set of mixed crude oil ratios that meet the constraints through step S2, the side-stream product output and related physical property values ​​of the atmospheric and vacuum distillation unit under actual production conditions are calculated using a linear digital simulation model for different mixed crude oil ratios. Based on the distillate oil output, distillate oil physical property values, and mixed crude oil price of the atmospheric and vacuum distillation unit, the optimal crude oil mixing scheme is selected, thereby obtaining alternative crude oil procurement information.

[0058] Specifically, in this embodiment, different atmospheric and vacuum distillation side-streams are generally used as the products in actual production. These side-streams are primarily used for catalytic cracking feedstocks. They include: First atmospheric and vacuum distillation line: jet fuel, light diesel, high-grade coal, and grinding oil; Second atmospheric and vacuum distillation line: light diesel and diesel hydrotreating feedstock; and Third atmospheric and vacuum distillation line: heavy diesel. Since the actual conditions of the refinery's units can change according to the refinery's production development and production plan, it is necessary to have an understanding of the latest status of the refinery's units to avoid deviating from actual production. Therefore, when calculating the yield and related physical properties of the side-stream extracted products from the atmospheric and vacuum distillation unit, a linear digital simulation model is established based on the actual refinery units' calculated yield and related physical properties of the side-stream extracted products from the atmospheric and vacuum distillation unit. Then, the linear digital simulation model is used to calculate the yield and related physical properties of the distillate extracted from the side-stream of the atmospheric and vacuum distillation unit under actual production conditions for each candidate crude oil and its corresponding blend ratio.

[0059] Specifically, in this embodiment, the linear digital simulation model summarizes the necessary inputs of each actual refinery unit into individual events, i.e., the digitization of input information. By controlling the input and output information of each refinery unit model, it simulates the actual production state of the corresponding actual refinery unit, obtaining the distillate production and distillate property values ​​extracted from the side stream of the atmospheric and vacuum distillation unit under actual production conditions. The linear digital simulation model sets corresponding output calculation methods for the events of different refinery unit models. After each refinery unit model obtains the corresponding input information through multiple set events, it uses the bound output calculation method to calculate the obtained input information to obtain the output information of the corresponding refinery unit model.

[0060] Furthermore, in this embodiment, events in the linear digital simulation model are divided into non-adjustable events and dynamically adjustable events. Non-adjustable events include unit yield, reaction temperature, and tower pressure, while dynamically adjustable events include the proportions of the crude oils involved in production, sulfur content, dry point, API value, etc. The linear digital simulation model adjusts the proportions of the crude oils involved in production, sulfur content, dry point, and API value by adjusting the input information of the dynamically adjustable events, while keeping other events unchanged. Then, the corresponding output calculation method is used to calculate the input information of the dynamically adjustable events, thereby obtaining the output information of each refinery unit model.

[0061] Specifically, in this embodiment, since the refinery's production plan is not fixed and changes with production targets, the production throughput is given in the form of events. By adjusting the input information of the corresponding events, the production throughput is dynamically adjusted, making the calculation of the product output and related physical properties extracted from the side stream of the atmospheric and vacuum distillation unit more consistent with actual production conditions. Furthermore, in this embodiment, when calculating the distillate oil output and related physical properties extracted from the side stream of the atmospheric and vacuum distillation unit, since the variables involved in the calculation process change dynamically after event binding when the blended crude oil ratio changes, the blended crude oil ratio will affect the output and related physical properties of the distillate oil extracted from the side stream of the atmospheric and vacuum distillation unit, even with constant inputs such as the atmospheric and vacuum distillation unit throughput. Therefore, the blended crude oil ratio is given in the form of events, allowing the entire calculation model to be used multiple times.

[0062] Furthermore, in this embodiment, since subsequent secondary units such as desulfurization units are involved in actual operation, and the sulfur content is related to the final sulfur product yield, which affects the company's profits, the sulfur content is given in the form of an event. The sulfur content of the mixed crude oil is dynamically adjusted by adjusting the input information of the corresponding event. As for setting the dry point as an event, the dry point can be dynamically controlled according to production requirements or the company's quarterly production targets, thereby changing the distillate oil yield from the side stream of the atmospheric and vacuum distillation unit and some physical properties of the distillate oil.

[0063] In this embodiment, when adjusting the operation sequence and input information of each event to obtain a multi-event combination of mixed crude oil scheduling scheme, in order to maintain material balance among the atmospheric and vacuum distillation units and intermediate storage tanks of the production line, the linear digital simulation model considers the upper and lower limits of the intermediate storage tanks to determine the processing volume of mixed crude oil based on the actual situation, and establishes a material balance calculation model based on the actual mixed crude oil processing volume. This material balance calculation model ensures material balance among the units. The feed rate of each unit is given in the form of events. Since the refinery's production plan is not fixed and changes with production targets, in actual operation, the feed rate of each unit and other settings are determined based on the actual data of a certain refinery. Once the feed rate of each unit is given in the form of events, it can be dynamically adjusted according to actual production needs, better reflecting the actual production situation.

[0064] Step S4: Select the optimal crude oil blending scheme based on the distillate oil production, distillate oil properties, and blended crude oil price from the side stream of the atmospheric and vacuum distillation unit corresponding to each crude oil blending scheme, and obtain alternative crude oil procurement information.

[0065] In this embodiment, after calculating the side-stream product output and related physical property values ​​of different crude oil blending schemes corresponding to the atmospheric and vacuum distillation unit, a complete set of reports on the atmospheric and vacuum distillation unit is generated based on the side-stream distillate output, distillate physical property values, and blended crude oil prices. These reports are provided to the dispatching staff for reference. The dispatching staff then selects the most suitable alternative crude oil from among various candidate crude oils using these reports, and determines its corresponding blending ratio as the optimal crude oil blending scheme, thereby obtaining alternative crude oil procurement information. The following example uses a blend of Marin, Nanbar, Antal, and Ural (light) crude oil to illustrate this embodiment.

[0066] In this embodiment, it is assumed that the blended crude oil originally planned to be produced by the refinery consists of four types of crude oil: Marin, Nanba, Anta, and Ural (light). When the supply of Ural (light) crude oil is interrupted for some reason, the purchasing personnel provide the following eight alternative crude oils based on the actual situation: Oman, Victory Blend, Duri, Iran (heavy), Mondo, Iran Light, Kimboa, and Rongcado Light. The API values ​​for these eight crude oils are as follows: Marin (19.7, sulfur content 0.75); Nanba (39.5, sulfur content 0.23); Anta (28.7, sulfur content 0.265); Oman (31.71, sulfur content 1.4); Victory Blend (18.54, sulfur content 1.1); Duri (23.27, sulfur content 0.29); Iran (heavy) (29.8, sulfur content 2.02); Mondo (30.3, sulfur content 0.39); Iranian Light (32.78, sulfur content 1.5); Kimboa (25.3, sulfur content 0.56); and Rongcado Light (28.6, sulfur content 0.54). When calculating the blending ratios for these eight crude oils using a blending ratio calculation model, the required API value range and sulfur content range for the actual blended crude oils were set to 28-33 and 0.3-1.6, respectively. The physical properties of these eight candidate crude oils were input into a blending crude oil ratio calculation model. Executing this model yielded the blending ratios and information for the seven candidate crude oils that met all constraints. This blending crude oil information included the blending ratio, API value, and sulfur content. This blending crude oil information was then used in a refinery linearized digital simulation model to calculate the blending ratios for different candidate crude oils, as well as the distillate production and physical properties of the distillate extracted from the side stream of the atmospheric and vacuum distillation unit. Specific data are as follows:

[0067] The blending ratio when Oman crude oil is used as a substitute is: Marin 29.00%, South Brazil 5.00%, Anta 5.00%, Oman 61.00%. The side-stream extraction yield, sulfur content, and density of a 12,000-tonne atmospheric and vacuum distillation unit. The output of crude oil from the primary flue gas pipeline was 1414.14 tons, with a sulfur content of 0.22% and a density of 0.71%. The output of flue gas from the first flue gas pipeline was 787.53 tons, with a sulfur content of 2.67% and a density of 0.78%. The output of flue gas from the second flue gas pipeline was 1063.51 tons, with a sulfur content of 4.36% and a density of 0.83%. The output of flue gas from the third flue gas pipeline was 781.02 tons, with a sulfur content of 8.88% and a density of 0.86%. The output of crude oil from the top of the reduced-pressure reactor was 0.00 tons, with a sulfur content of 0.00% and a density of 0.00%. The output of crude oil from the first flue gas pipeline was 288.55 tons, with a sulfur content of 39.23% and a density of 0.87%. The output of crude oil from the second flue gas pipeline was 1934.57 tons, with a sulfur content of 8.39% and a density of 0.90%. The output of crude oil from the third flue gas pipeline was 2149.88 tons, with a sulfur content of 8.26% and a density of 0.94%. The output of crude oil from the fourth flue gas pipeline was 22.56 tons, with a sulfur content of 136.8% and a density of 0.97%. The output of reduced-pressure reactor slag was 3343.87 tons, with a sulfur content of 12.97% and a density of 1.02%.

[0068] The blending ratio when Oman crude oil is used as a substitute is: Marin 29.00%, South Brazil 5.00%, Anta 5.00%, Oman 61.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year from atmospheric and vacuum distillation unit II. The production of gas from the three top gas plants was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of gas from the primary atmospheric top gas plant was 1167.29, with a sulfur content of 0.30 and a density of 0.71; the production of gas from the first atmospheric top gas plant was 644.37, with a sulfur content of 3.10 and a density of 0.79; the production of gas from the second atmospheric top gas plant was 800.69, with a sulfur content of 4.11 and a density of 0.83; the production of gas from the third atmospheric top gas plant was 624.81, with a sulfur content of 8.88 and a density of 0.86; the production of gas from the first heavy-duty boiler was 406.85, with a sulfur content of 32.35 and a density of 0.87; the production of gas from the second heavy-duty boiler was 861.89, with a sulfur content of 10.30 and a density of 0.90; the production of gas from the third heavy-duty boiler was 1233.40, with a sulfur content of 11.38 and a density of 0.94; and the production of residual oil was 3853.98, with a sulfur content of 10.40 and a density of 1.01.

[0069] The blending ratio when Duri is used as a substitute crude oil is: Marin 23.00%, Nanba 29.00%, Anta 20.00%, Duri 28.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 12,000 tons / day of atmospheric and vacuum distillation unit I. The output of the primary flue gas slag was 1495.93 tons, with a sulfur content of 0.17% and a density of 0.72%. The output of flue gas slag from flue gas slag line 1 was 894.55 tons, with a sulfur content of 2.20% and a density of 0.80%. The output of flue gas slag line 2 was 1161.27 tons, with a sulfur content of 3.03% and a density of 0.84%. The output of flue gas slag line 3 was 825.09 tons, with a sulfur content of 5.47% and a density of 0.87%. The output of the reduced pressure gas slag was 0.00 tons, with a sulfur content of 0.00% and a density of 0.00%. The output of the reduced pressure gas slag line 1 was 269.85 tons, with a sulfur content of 26.05% and a density of 0.88%. The output of the reduced pressure gas slag line 2 was 2130.27 tons, with a sulfur content of 4.41% and a density of 0.90%. The output of the reduced pressure gas slag line 3 was 2053.14 tons, with a sulfur content of 4.27% and a density of 0.95%. The output of the reduced pressure gas slag line 4 was 191.13 tons, with a sulfur content of 78.88% and a density of 0.97%. The output of the reduced pressure gas slag was 2955.95 tons, with a sulfur content of 7.23% and a density of 1.15%.

[0070] The blending ratio when Duri is used as a substitute crude oil is: Marin 23.00%, Nanba 29.00%, Anta 20.00%, Duri 28.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year for atmospheric and vacuum distillation unit II. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1228.69, with a sulfur content of 0.23 and a density of 0.72; the production of the first atmospheric gas was 771.94, with a sulfur content of 2.47 and a density of 0.80; the production of the second atmospheric gas was 840.77, with a sulfur content of 2.85 and a density of 0.84; the production of the third atmospheric gas was 649.32, with a sulfur content of 5.56 and a density of 0.87; the production of the first heavy-duty gas was 383.50, with a sulfur content of 21.28 and a density of 0.88; the production of the second heavy-duty gas was 1037.59, with a sulfur content of 4.80 and a density of 0.91; the production of the third heavy-duty gas was 1230.54, with a sulfur content of 5.64 and a density of 0.94; and the production of residual oil was 3450.93, with a sulfur content of 5.71 and a density of 1.13.

[0071] The blending ratio when Iranian (heavy) crude oil is used as a substitute is: Marin 29.00%, Nanba 29.00%, Antara 19.00%, and Iranian (heavy) 23.00%. The side-stream extraction yield, sulfur content, and density of a 12,000-tonne atmospheric and vacuum distillation unit are as follows. The output of crude oil from the primary flue gas pipeline was 1582.20 tons, with a sulfur content of 0.13% and a density of 0.73%. The output of crude oil from the first flue gas pipeline was 946.23 tons, with a sulfur content of 1.69% and a density of 0.80%. The output of crude oil from the second flue gas pipeline was 1244.45 tons, with a sulfur content of 2.01% and a density of 0.84%. The output of crude oil from the third flue gas pipeline was 807.8 tons, with a sulfur content of 4.02% and a density of 0.87%. The output of crude oil from the top of the reduced-pressure boiler was 0.00 tons, with a sulfur content of 0.00% and a density of 0.00%. The output of crude oil from the first flue gas pipeline was 278.20 tons, with a sulfur content of 19.33% and a density of 0.88%. The output of crude oil from the second flue gas pipeline was 1977.84 tons, with a sulfur content of 3.99% and a density of 0.90%. The output of crude oil from the third flue gas pipeline was 1954.28 tons, with a sulfur content of 3.56% and a density of 0.94%. The output of crude oil from the fourth flue gas pipeline was 169.59 tons, with a sulfur content of 63.20% and a density of 0.97%. The output of reduced-pressure boiler slag was 3017.38 tons, with a sulfur content of 4.99% and a density of 1.14%.

[0072] The blending ratio when Iranian (heavy) crude oil is used as a substitute is: Marin 29.00%, Nanba 29.00%, Antara 19.00%, and Iranian (heavy) 23.00%. The side-stream extraction yield, sulfur content, and density of a 9600-tonne atmospheric and vacuum distillation unit are as follows. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1299.46, with a sulfur content of 0.18 and a density of 0.73; the production of the first atmospheric gas was 825.02, with a sulfur content of 1.89 and a density of 0.80; the production of the second atmospheric gas was 893.82, with a sulfur content of 1.85 and a density of 0.84; the production of the third atmospheric gas was 646.24, with a sulfur content of 4.02 and a density of 0.87; the production of the first heavy-duty gas was 395.06, with a sulfur content of 15.90 and a density of 0.88; the production of the second heavy-duty gas was 900.01, with a sulfur content of 4.83 and a density of 0.90; the production of the third heavy-duty gas was 1209.31, with a sulfur content of 4.58 and a density of 0.94; and the production of residual oil was 3424.36, with a sulfur content of 4.07 and a density of 1.01.

[0073] The blending ratio when Mondo is used as a substitute crude oil is: Marin 28.00%, Nanba 26.00%, Anta 27.00%, Mondo 19.00%. The side-stream extraction yield, sulfur content, and density of atmospheric and vacuum distillation unit I at a throughput of 12,000 tons are as follows: Initial atmospheric top yield: 1872.61 tons, sulfur content 0.19%, density 0.72; First atmospheric top yield: 1095.21 tons, sulfur content 2.17%, density 0.79; Second atmospheric top yield: 1354.94 tons, sulfur content 3.53%, density 0.84; Third atmospheric top yield: 814.93 tons, sulfur content 8.48%, density 0.86; Vacuum distillation top yield: 0.00 tons, sulfur content: 0.00%, density: 0.00. The output of the first-stage reactor is 298.40 tons, with a sulfur content of 37.37% and a density of 0.88. The output of the second-stage reactor is 2108.37 tons, with a sulfur content of 7.03% and a density of 0.90%. The output of the third-stage reactor is 1900.88 tons, with a sulfur content of 6.44% and a density of 0.95%. The output of the fourth-stage reactor is 158.88 tons, with a sulfur content of 120.51% and a density of 0.98%. The output of the slag from the reactor is 2367.48 tons, with a sulfur content of 12.27% and a density of 1.20%.

[0074] The blending ratio when Mondo is used as a substitute crude oil is: Marin 28.00%, Namba 26.00%, Anta 27.00%, Mondo 19.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year from atmospheric and vacuum distillation unit II. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1536.95, with a sulfur content of 0.25 and a density of 0.72; the production of the first atmospheric gas was 951.05, with a sulfur content of 2.47 and a density of 0.80; the production of the second atmospheric gas was 970.20, with a sulfur content of 3.38 and a density of 0.84; the production of the third atmospheric gas was 646.68, with a sulfur content of 8.55 and a density of 0.86; the production of the first heavy-duty gas was 424.60, with a sulfur content of 30.57 and a density of 0.88; the production of the second heavy-duty gas was 983.40, with a sulfur content of 7.94 and a density of 0.90; the production of the third heavy-duty gas was 1169.39, with a sulfur content of 8.34 and a density of 0.94; and the production of residual oil was 2911.01, with a sulfur content of 9.03 and a density of 1.18.

[0075] When the substitute crude oil is Iranian light crude, the blend ratio is: Marin 29.00%, Nanba 29.00%, Anta 19.00%, Iranian light crude 23.00%. The side-stream extraction yield, sulfur content, and density of a 12,000-tonne atmospheric and vacuum distillation unit are as follows. The output of crude oil from the primary flue gas pipeline was 1831.82 tons, with a sulfur content of 0.08% and a density of 0.72%. The output of crude oil from the first flue gas pipeline was 1089.70 tons, with a sulfur content of 1.42% and a density of 0.80%. The output of crude oil from the second flue gas pipeline was 1343.56 tons, with a sulfur content of 2.12% and a density of 0.84%. The output of crude oil from the third flue gas pipeline was 858.74 tons, with a sulfur content of 4.60% and a density of 0.87%. The output of crude oil from the top of the reduced gas pipeline was 0.00 tons, with a sulfur content of 0.00% and a density of 0.00%. The output of crude oil from the first flue gas pipeline was 302.98 tons, with a sulfur content of 21.41% and a density of 0.88%. The output of crude oil from the second flue gas pipeline was 2032.43 tons, with a sulfur content of 4.42% and a density of 0.90%. The output of crude oil from the third flue gas pipeline was 1886.60 tons, with a sulfur content of 4.13% and a density of 0.94%. The output of crude oil from the fourth flue gas pipeline was 156.16 tons, with a sulfur content of 4.13% and a density of 0.94%. The output of crude oil slag was 2433.61 tons, with a sulfur content of 7.10% and a density of 1.15%.

[0076] When the substitute crude oil is Iranian light crude oil, the blend ratio is: Marin 29.00%, Nanba 29.00%, Anta 19.00%, Iranian light crude oil 23.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year of atmospheric and vacuum distillation unit II. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1506.65, with a sulfur content of 0.13 and a density of 0.72; the production of the first atmospheric gas was 942.50, with a sulfur content of 1.64 and a density of 0.80; the production of the second atmospheric gas was 962.91, with a sulfur content of 1.98 and a density of 0.84; the production of the third atmospheric gas was 686.99, with a sulfur content of 4.60 and a density of 0.87; the production of the first heavy-duty gas was 427.16, with a sulfur content of 17.70 and a density of 0.88; the production of the second heavy-duty gas was 931.40, with a sulfur content of 5.16 and a density of 0.90; the production of the third heavy-duty gas was 1158.70, with a sulfur content of 5.35 and a density of 0.94; and the production of residual oil was 2976.96, with a sulfur content of 5.36 and a density of 1.13.

[0077] The blending ratio when using Kimboa as a substitute crude oil is: Marin 27.00%, Nanba 28.00%, Anta 9.00%, Kimboa 36.00%. The side-stream extraction yield, sulfur content, and density of the atmospheric and vacuum distillation unit (AFD) with a throughput of 12,000 tons are as follows: Initial atmospheric top yield: 1901.01 tons, sulfur content: 0.16%, density: 0.72; AFD I yield: 1118.98 tons, sulfur content: 1.95%, density: 0.79; AFD II yield: 1375.55 tons, sulfur content: 3.39%, density: 0.83; AFD III yield: 845.62 tons, sulfur content: 8.94%, density: 0.86; Vacuum distillation top yield: 0.00 tons, sulfur content: 0.00%, density: 0.00. The output of the first-stage reactor is 314.27 tons, with a sulfur content of 39.60% and a density of 0.88; the output of the second-stage reactor is 1887.59 tons, with a sulfur content of 8.73% and a density of 0.90%; the output of the third-stage reactor is 1956.11 tons, with a sulfur content of 7.38% and a density of 0.94%; the output of the fourth-stage reactor is 167.13 tons, with a sulfur content of 150.42% and a density of 0.98%; and the output of the slag is 2419.51 tons, with a sulfur content of 15.15% and a density of 1.07%.

[0078] The blending ratio when using Kimboa as a substitute crude oil is: Marin 27.00%, Nanba 28.00%, Anta 9.00%, Kimboa 36.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year from atmospheric and vacuum distillation unit II. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1565.84, with a sulfur content of 0.22 and a density of 0.72; the production of the first atmospheric gas was 955.21, with a sulfur content of 2.23 and a density of 0.79; the production of the second atmospheric gas was 998.39, with a sulfur content of 3.27 and a density of 0.83; the production of the third atmospheric gas was 676.50, with a sulfur content of 8.94 and a density of 0.86; the production of the first heavy-duty gas was 431.98, with a sulfur content of 33.49 and a density of 0.87; the production of the second heavy-duty gas was 819.74, with a sulfur content of 10.58 and a density of 0.90; the production of the third heavy-duty gas was 1142.18, with a sulfur content of 10.02 and a density of 0.94; and the production of residual oil was 3006.44, with a sulfur content of 11.15 and a density of 1.06.

[0079] The blending ratio when replacing crude oil with Rongcado Light is: Marin 29.00%, Namba 29.00%, Antar 19.00%, Rongcado Light 23.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 12,000 tons / year from atmospheric and vacuum distillation unit I. The output of the primary flue gas slag was 1643.31 tons, with a sulfur content of 0.11% and a density of 0.73%. The output of flue gas slag from the first flue gas slag line was 1035.47 tons, with a sulfur content of 1.60% and a density of 0.80%. The output of flue gas slag from the second flue gas slag line was 1386.27 tons, with a sulfur content of 2.02% and a density of 0.84%. The output of flue gas slag from the third flue gas slag line was 879.51 tons, with a sulfur content of 4.44% and a density of 0.86%. The output of the reduced pressure gas slag was 0.00 tons, with a sulfur content of 0.00% and a density of 0.00%. The output of the first flue gas slag line was 311.34 tons, with a sulfur content of 20.98% and a density of 0.88%. The output of the second flue gas slag line was 2106.06 tons, with a sulfur content of 4.30% and a density of 0.90%. The output of the third flue gas slag line was 1989.46 tons, with a sulfur content of 3.97% and a density of 0.94%. The output of the fourth flue gas slag line was 169.45 tons, with a sulfur content of 75.98% and a density of 0.97%. The output of the reduced pressure gas slag was 2457.08 tons, with a sulfur content of 7.64% and a density of 1.14%.

[0080] The blending ratio when replacing crude oil with Rongcado Light is: Marin 29.00%, Namba 29.00%, Antar 19.00%, Rongcado Light 23.00%. Side-stream extraction yield, sulfur content, and density at a throughput of 9600 tons / year from atmospheric and vacuum distillation unit II. The production of the three-top gas was 0.00, with a sulfur content of 0.00 and a density of 0.00; the production of the primary atmospheric gas was 1352.54, with a sulfur content of 0.16 and a density of 0.73; the production of the first atmospheric gas pipeline was 900.47, with a sulfur content of 1.80 and a density of 0.80; the production of the second atmospheric gas pipeline was 999.03, with a sulfur content of 1.87 and a density of 0.84; the production of the third atmospheric gas pipeline was 703.61, with a sulfur content of 4.44 and a density of 0.86; the production of the first-line sulfur-reduced gas pipeline was 437.90, with a sulfur content of 17.41 and a density of 0.88; the production of the second-line sulfur-reduced gas pipeline was 986.27, with a sulfur content of 4.91 and a density of 0.91; the production of the third-line sulfur-reduced gas pipeline was 1237.37, with a sulfur content of 5.08 and a density of 0.94; and the production of residual oil was 2976.10, with a sulfur content of 5.77 and a density of 1.13.

[0081] Furthermore, in this implementation, while ensuring material balance in the crude oil processing process, it enables rapid resolution of sudden crude oil supply interruptions during procurement, and timely provision of new blended crude oil ratios. Based on the production, property values, and blended crude oil properties of the distillate oil extracted from the side stream of the atmospheric and vacuum distillation unit, a complete set of reports for the atmospheric and vacuum distillation unit is generated as a short-term production plan report. Production personnel can select the crude oil blending scheme with the higher output from this blended crude oil report, and adjust the production plan and make procurement decisions based on the optimal crude oil blending scheme to ensure the continuous and stable operation of the refinery, thereby improving the economic benefits of the refining and chemical enterprise.

[0082] This specification also discloses a forward-looking crude oil alternative planning device. Figure 2This is a structural diagram illustrating an embodiment of the forward-looking crude oil alternative planning device of the present invention. Figure 2 As shown, the forward-looking crude oil alternative planning device includes an internal communication bus 301, a processor 302, a read-only memory (ROM) 303, a random access memory (RAM) 304, a communication port 305, and a hard disk 307. The internal communication bus 301 enables data communication between components of the crude oil dispatch optimization device for handling procurement contingencies. The processor 302 can perform judgments and issue prompts. In some embodiments, the processor 302 may consist of one or more processors. The communication port 305 enables data transmission and communication between the crude oil dispatch optimization device for handling procurement contingencies and external input / output devices. In some embodiments, the crude oil dispatch optimization device for handling procurement contingencies can send and receive information and data from the network through the communication port 305. In some embodiments, the crude oil dispatch optimization device for handling procurement contingencies can transmit data and communicate with external input / output devices in a wired manner through the input / output terminal 306.

[0083] Furthermore, in this embodiment, the forward-looking crude oil alternative planning device may also include different forms of program storage units and data storage units, such as hard disk 307, read-only memory (ROM) 303 and random access memory (RAM) 304. These program storage units and data storage units store various data files used for computer processing and / or communication, as well as possible program instructions executed by processor 302. Processor 302 executes these instructions to implement the main part of the method, and then the results processed by processor 302 are transmitted to an external output device through communication port 305 and displayed on the user interface of the output device.

[0084] For example, the implementation process document of the crude oil dispatch optimization device for responding to procurement emergencies described above can be a computer program, stored in hard disk 307, and can be loaded into processor 302 for execution to implement the method of this application. When the implementation process document of the forward-looking crude oil alternative plan is a computer program, it can also be stored as an article of manufacture in a computer-readable storage medium. For example, computer-readable storage media can include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic stripes), optical discs (e.g., compact discs (CDs), digital multifunction discs (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read-only memory (EPROM), cards, sticks, key drives).

[0085] The prior description of this disclosure is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0086] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in a generalized manner in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in different ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the invention.

[0087] The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein can be implemented or performed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but in alternatives, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors cooperating with a DSP core, or any other such configuration.

[0088] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor such that the processor can read and write information to / from the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside as discrete components in the user terminal.

[0089] In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functionality may be stored or transmitted as one or more instructions or code on or through a computer-readable medium. A computer-readable medium includes both computer storage media and communication media, encompassing any medium that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium accessible to a computer. By way of example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage, disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and is accessible to a computer. Any connection is also legitimately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of a medium. As used in this article, disk and disc include compact discs (CDs), laser discs, optical discs, digital multi-purpose discs (DVDs), floppy disks, and Blu-ray discs. Disks typically reproduce data magnetically, while discs reproduce data optically using lasers. Combinations of these should also be included within the scope of computer-readable media.

Claims

1. A forward-looking crude oil alternative planning method, characterized in that, Includes the following steps: Obtain information on alternative crude oils from multiple sources; Based on candidate crude oil information, the blending ratio of crude oil is calculated to obtain multiple crude oil blending schemes, including: calculating the blending ratio of crude oil using a blending ratio calculation model; wherein, the candidate crude oil information includes the physical properties and purchase price of candidate crude oils. After obtaining the candidate crude oil information of multiple candidate crude oils, the forward-looking crude oil substitution scheme planning method inputs the obtained physical properties and purchase prices of candidate crude oils into the blending ratio calculation model for calculation to obtain multiple blending ratios. The blending ratio calculation model establishes an objective function based on the purchase price of the blending crude oils corresponding to the candidate crude oils, and constrains the objective function using the actual required range of physical properties of the blending crude oils, optimizing the blending ratio through the actual required range of physical properties of the blending crude oils; wherein, the actual required range of physical properties of the blending crude oils includes the range of API values ​​and the range of sulfur content of the blending crude oils. The blending ratio calculation model establishes the following optimization objective function through the range of API values ​​and the range of sulfur content of the blending crude oils: ； in, This represents the purchase price of the blended crude oil corresponding to the nth blended crude oil ratio. This represents the percentage of the nth type of crude oil that can be purchased. This represents the purchase price of the nth type of crude oil at its corresponding percentage. This represents the proportion of the i-th alternative crude oil. This represents the purchase price of the i-th alternative crude oil. This represents the API value of the nth type of crude oil available for purchase. This represents the API value of the i-th alternative crude oil. This indicates the minimum API value required for the actual blend of crude oil. This indicates the maximum API value of the actual required blend of crude oil. This represents the sulfur content of the crude oil available for purchase in the nth batch. This represents the sulfur content of the i-th candidate crude oil. This represents the API value of the blended crude oil corresponding to the nth blended crude oil ratio. This indicates the sulfur content of the blended crude oil corresponding to the nth blended crude oil ratio; Based on the blending ratio of each crude oil blending scheme, a linear digital simulation model is used to calculate the distillate production and distillate properties extracted from the side stream of the atmospheric and vacuum distillation unit under different crude oil blending schemes. This includes: establishing a linear digital simulation model based on the actual refinery unit; wherein, the linear digital simulation model abstracts each actual refinery unit model into a linear digital simulation refinery unit model, and simulates the actual production state of the corresponding actual refinery unit by controlling the input and output information of each refinery unit model, thereby obtaining the distillate production and distillate properties extracted from the side stream of the atmospheric and vacuum distillation unit under the actual production state; The linear digital simulation model digitizes the input information of each refinery unit model into events, and constructs a multi-event combination production scheduling scheme for atmospheric and vacuum distillation units by adjusting the events corresponding to each refinery unit model. The linear digital simulation model sets corresponding output calculation methods for the events of different refinery unit models. After each refinery unit model obtains the corresponding input information through multiple set events, it uses the bound output calculation method to calculate the obtained input information to obtain the output information of the corresponding refinery unit model. The events are divided into non-adjustable events and dynamically adjustable events. Non-adjustable events include unit yield, reaction temperature, and tower pressure, while dynamically adjustable events include the proportions of crude oils involved in production, sulfur content, dry point, and API value. The linear digital simulation model obtains the corresponding actual refinery unit production indicators through the non-adjustable events set in the refinery unit models. Then, it adjusts the proportions of crude oils involved in production, sulfur content, dry point, and API value by adjusting the input information of the dynamically adjustable events. Finally, it calculates the input information of the dynamically adjustable events using the corresponding output calculation method to obtain the output information of each refinery unit model. Based on the distillate production, distillate properties, and blended crude oil price of each crude oil blending scheme, the optimal crude oil blending scheme is selected, and alternative crude oil procurement information is obtained.

2. The forward-looking crude oil substitution planning method according to claim 1, wherein the forward-looking crude oil substitution planning method establishes an optimized objective function based on the API value range and sulfur content range of the blended crude oil, and then inputs the obtained physical property values ​​of the candidate crude oils into the blended crude oil proportioning calculation model for calculation; wherein, The candidate crude oil properties include the API value, sulfur content, and purchase price. The forward-looking crude oil substitution planning method inputs the obtained crude oil properties and candidate crude oil purchase prices into the blended crude oil ratio calculation model, calculates the blended crude oil purchase price corresponding to different blended crude oil ratios, and constrains the blended crude oil ratios corresponding to the candidate crude oils based on the blended crude oil API value range and blended crude oil sulfur content, thereby obtaining blended crude oil ratios within various actual required blended crude oil property value ranges.

3. The forward-looking crude oil substitution planning method according to claim 1, characterized in that, Before calculating the blended crude oil ratio, the blended crude oil ratio calculation model selects multiple alternative crude oils based on the physical property values ​​of crude oils with supply disruptions, and obtains alternative crude oil information from the crude oil evaluation table. Then, the alternative crude oil information of the selected alternative crude oils is input into the blended crude oil ratio calculation model for calculation, thereby obtaining multiple blended crude oil ratios. Among them, the physical property values ​​of crude oils with supply disruptions include the API value and sulfur content of crude oils with supply disruptions.

4. The forward-looking crude oil substitution planning method according to claim 1, characterized in that, The linear digital simulation model establishes a material balance calculation model based on the actual crude oil processing volume of the atmospheric and vacuum distillation unit, and ensures the material balance of each atmospheric and vacuum distillation unit and each intermediate storage tank through the material balance calculation model.

5. The forward-looking crude oil substitution planning method according to claim 1, characterized in that, The forward-looking crude oil substitution planning method calculates the distillate production and properties of different crude oil blending schemes by using a linear digital simulation model. Based on the distillate production, properties, and blended crude oil prices of the atmospheric and vacuum distillation unit, a complete set of reports for the atmospheric and vacuum distillation unit is generated. The optimal crude oil blending scheme is selected based on the complete set of reports for the atmospheric and vacuum distillation unit, and alternative crude oil procurement information is obtained.

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