Crude oil scheduling optimization method and device based on multi-period decomposition and reconstruction

Abstract

The present application provides a kind of crude oil scheduling optimization method and device based on multi-period decomposition reconstruction, the method comprises: according to the business process segmentation of crude oil scheduling, build crude oil arrival model, wharf tank area model, plant tank area model and atmospheric-vacuum processing model;With crude oil arrival constraint, wharf tank area constraint, plant tank area constraint and atmospheric-vacuum processing constraint as constraint condition, with the minimum objective function as the goal, solve crude oil arrival model, wharf tank area model, plant tank area model and atmospheric-vacuum processing model simultaneously;Based on the solution, optimize crude oil scheduling.The present application realizes the task decomposition of crude oil scheduling by the whole business process segmentation model and constraint control, realizes the short-period time decomposition of long-period plan by building multi-period model, finally realizes the decomposition reconstruction of multi-scale multi-task crude oil scheduling scheme, improves the executable of crude oil scheduling scheme, reduces the operation cost of whole process, improves the stability of device operation.

Description

Technical Field

[0001] This invention relates to the field of refining and chemical technology, and in particular to a crude oil scheduling optimization method and apparatus based on multi-cycle decomposition and reconstruction. Background Technology

[0002] Production scheduling is the decomposition of short-cycle tasks into long-cycle production plans, aiming to achieve the goals of the long-cycle production plan. Therefore, pre-arranging short-cycle scheduling can assist enterprises in making production preparations and business plans in advance. Crude oil scheduling is one of the most important links in production scheduling, affecting the entire enterprise's production and operation. Efficient and stable crude oil scheduling can ensure the safe and stable operation of the unit and the orderly progress of production and operation. Crude oil scheduling involves the coupling of multiple factors such as crude oil arrival arrangements, storage tank operations, storage tank inventory management, crude oil processing combinations, and the protection requirements of the atmospheric and vacuum distillation unit. From receiving crude oil at the terminal, through temporary storage in the terminal tank area, to further processing in the plant's tank area, and finally to its final delivery to the atmospheric and vacuum distillation unit, each link is closely related and mutually influential. In order to ensure the smooth execution of the production plan, it is necessary to formulate practical and feasible scheduling arrangements at each stage, thereby ensuring the stable operation of the atmospheric and vacuum distillation unit and maintaining the normal production and operation of the entire plant.

[0003] Currently, many enterprises' crude oil scheduling still relies on daily average ideal allocations based on long-term plans. However, this often fails to meet expected execution targets due to limitations imposed by factors such as port unloading, storage tank operations, and atmospheric and vacuum distillation feed ratio control, leading to production fluctuations and repeated rescheduling. Therefore, an efficient and feasible pre-scheduling method for crude oil scheduling is needed to improve the executability of crude oil scheduling plans, reduce operating costs, and enhance operational stability. Summary of the Invention

[0004] This invention provides a crude oil scheduling optimization method and apparatus based on multi-period decomposition and reconstruction, in order to overcome the deficiencies in the prior art.

[0005] This invention provides a crude oil scheduling optimization method based on multi-period decomposition and reconstruction, comprising the following steps: Based on the business process of crude oil dispatch, models for crude oil arrival at port, terminal tank farms, plant tank farms, and atmospheric and vacuum distillation processing are constructed in segments. Using constraints such as crude oil arrival, terminal tank farm, plant tank farm, and atmospheric and vacuum distillation as constraints, and minimizing the objective function as the objective, the crude oil arrival model, terminal tank farm model, plant tank farm model, and atmospheric and vacuum distillation model are solved simultaneously. Based on the solution results, optimize crude oil scheduling; The crude oil arrival constraints are used to control the quantity, blending, and orderly transportation of arriving crude oil; the terminal tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the terminal tank farm; the plant tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the plant tank farm; and the atmospheric and vacuum distillation processing constraints are used to control the quantity, nature, and proportion of atmospheric and vacuum distillation processing. The objective function is constructed based on the transportation costs, switching operation costs, and storage costs of each stage.

[0006] According to the present invention, a crude oil scheduling optimization method based on multi-period decomposition and reconstruction is provided. The crude oil arrival model includes A receiving modules. Each receiving module includes a first inlet and a first outlet. The first inlet is the inlet for each type of crude oil to enter the boundary area. The o-th type of arriving crude oil is connected to the p-th first inlet. The p-th first outlet is connected to the third inlet of the c-th first storage sub-module in the first storage module of the y-th tank in each period of the terminal tank farm model. The p-th first outlet is connected to the third inlet of the third storage sub-module in the first storage module of one or more tanks in each period of the terminal tank farm model.

[0007] According to the present invention, a crude oil scheduling optimization method based on multi-period decomposition and reconstruction is provided. The terminal tank farm model includes B periods, each period containing C tanks, and each tank containing a first inventory module and a second inventory module. The first inventory module of the b-th tank in each period includes D first inventory sub-modules, each first inventory sub-module including a second inlet, a third inlet, a second outlet, and a third outlet. The second inlet of the k-th first inventory sub-module of the first inventory module of the b-th tank in each period is connected to the fourth outlet of the k-th second inventory sub-module of the second inventory module of the b-th tank in the previous period. In the first cycle, the second inlet of each first storage submodule of the first storage module of each tank is connected to the outside boundary; the second outlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the fourth inlet of the kth second storage submodule of the second storage module of the same tank in the same cycle; the third inlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the first outlet of the s-th receiving module in the crude oil arrival model; and the third inlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the crude oil arrival... The first outlet of one or more receiving modules in the model is connected; the third outlet of the kth first inventory submodule of the first inventory module of the b-th tank in each cycle is connected to the fifth inlet of the t-th third inventory submodule of the third inventory module of the i-th tank in the corresponding cycle in the in-plant tank area model; the third outlet of the kth first inventory submodule of the first inventory module of the b-th tank in each cycle is connected to the fifth inlet of one or more third inventory submodules of the third inventory module of one or more tanks in the corresponding cycle in the in-plant tank area model; the second inventory module of the b-th tank in each cycle includes E second warehouses. Each storage sub-module includes a fourth inlet and a fourth outlet; the fourth inlet of the xth second storage sub-module in the b-th storage tank of each cycle is connected to the second outlet of the same first storage sub-module in the same storage tank of the same cycle; the fourth outlet of the xth second storage sub-module in the b-th storage tank of each cycle is connected to the second inlet of the xth first storage sub-module in the b-th storage tank of the next cycle; and the fourth outlet of each second storage sub-module in the last cycle is connected to the outside of the boundary area.

[0008] According to the present invention, a crude oil dispatch optimization method based on multi-period decomposition and reconstruction is provided, wherein the in-plant tank farm model includes F periods, each period contains G tanks; each tank contains a third inventory module and a fourth inventory module; The third storage module of the nth tank in each cycle contains H third storage sub-modules, each containing a fifth inlet, a fifth outlet, a sixth inlet, and a sixth outlet. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of the m-th first storage sub-module of the h-th tank in the corresponding cycle of the terminal tank farm model. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of one or more first storage sub-modules of one or more tanks in the corresponding cycle of the terminal tank farm model. The fifth outlet of the third storage sub-module of the nth tank in each cycle is connected to the third outlet of the corresponding cycle of the atmospheric and vacuum distillation processing model. The eighth inlet of the vth processing scheme of the uth processing device is connected; the fifth outlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the eighth inlet of the specific processing scheme of one or more processing devices in the atmospheric and vacuum processing model; the sixth inlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh outlet of the fourth storage submodule of the same tank in the previous cycle; the fifth inlet of the third storage submodule of the third storage module of each tank in the first cycle is connected to the outside; the sixth outlet of the zth third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh inlet of the same fourth storage submodule of the same tank in the same cycle. The fourth storage module of the nth tank in each cycle contains I fourth storage sub-modules, each containing a seventh inlet and a seventh outlet. The seventh inlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the sixth outlet of the same third storage sub-module in the third storage module of the same tank in the same cycle. The seventh outlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the seventh inlet of the same third storage sub-module in the third storage module of the nth tank in the next cycle. The seventh outlet of the fourth storage sub-module in the fourth storage module of all tanks in the last cycle is connected to the outside.

[0009] According to the present invention, a crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction is provided. The atmospheric and vacuum distillation processing model includes J cycles, each cycle includes K processing units, each unit includes L processing schemes, and each processing scheme includes an eighth inlet and an eighth outlet. The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of the e-th third storage sub-module in the third storage module of the w-th tank in the corresponding cycle of the tank farm model. The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of one or more third storage sub-modules in the third storage module of one or more tanks in the corresponding cycle of the tank farm model. The eighth outlet of each processing scheme of each processing unit in each cycle is connected to the outside of the boundary area.

[0010] According to the present invention, a crude oil scheduling optimization method based on multi-period decomposition and reconstruction is provided, wherein the crude oil arrival constraints include at least one of a first logistics constraint, a first physical property constraint, a first proportional constraint, and a first operational constraint. The first logistics constraint is the volume constraint of crude oil outside the boundary, which includes at least one of fixed value constraints and range constraints; the first logistics constraint is the speed constraint of transporting each type of crude oil arriving at the port to the terminal tank farm, which includes at least one of fixed value constraints and range constraints. The first physical property constraint is the physical property harmonic constraint of the receiving module; The first proportional constraint is the proportional control constraint of the first inlet of the external crude oil input receiving module. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range. The first operational constraint is the control constraint for the delivery of goods from the first outlet of the receiving module to the third inlet of each first inventory sub-module of the first inventory module of each tank in each cycle of the terminal tank area.

[0011] According to the present invention, a crude oil scheduling optimization method based on multi-period decomposition and reconstruction is provided, wherein the terminal tank area constraints include at least one of a second logistics constraint, a second physical property constraint, a second proportional constraint, a second inventory constraint, and a second operational constraint. The second logistics constraint includes the flow constraints of the second inlet, second outlet, third inlet and third outlet of each second inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints. The second logistics constraint includes the flow constraints of the fourth inlet and fourth outlet of each second inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints. The second logistics constraint is the conveying speed constraint from the third outlet of each second inventory sub-module of each storage tank in each cycle to the tank area in the plant. The conveying speed constraint includes at least one of fixed value constraint and range constraint. The second property constraint is the property harmonization constraint for each tank in each cycle; The second proportional constraint is the crude oil proportional control constraint input by the crude oil arrival model of each storage tank in each cycle. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range. The second inventory constraint is the inventory quantity constraint for each storage tank in each period. The inventory quantity constraint includes at least one of the fixed value constraint and the range constraint. The second operational constraint is the input and output constraint of each tank in each cycle, which controls the tank to not have both input and output states at the same time; the second operational constraint is the operational cost constraint.

[0012] According to the crude oil dispatch optimization method based on multi-period decomposition and reconstruction provided by the present invention, the constraints of the tank farm within the plant include at least one of the following: third logistics constraints, third physical property constraints, third proportional constraints, third inventory constraints, and third operational constraints. The third logistics constraint includes the material flow constraints of the fifth inlet, fifth outlet, sixth inlet and sixth outlet of each third inventory sub-module of each storage tank in each cycle. The material flow constraint includes at least one of fixed value constraint and range constraint. The third logistics constraint includes the flow constraints of the seventh inlet and seventh outlet of the fourth inventory sub-module of the fourth inventory module of each tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints. The third logistics constraint is the conveying speed constraint from the fifth outlet of each third inventory sub-module of each storage tank in each cycle to each scheme of each atmospheric and vacuum distillation unit. The conveying speed constraint includes at least one of fixed value constraint and range constraint. The third physical property constraint is the physical property harmonization constraint for each storage tank in each cycle; The third proportional constraint is the crude oil proportional control constraint input from the terminal tank area model of each storage tank in each cycle. The proportional control constraint is controlled by at least one of the following methods: a fixed proportion or a proportion range. The third inventory constraint is the inventory quantity constraint of each storage tank in each period. The inventory quantity constraint includes at least one of fixed value constraint and range constraint. The third operational constraint is the input-output constraint for each tank in each cycle, which controls the tank from having both input and output states simultaneously; the third operational constraint is the operational cost constraint.

[0013] According to the present invention, a crude oil scheduling optimization method based on multi-period decomposition and reconstruction is provided, wherein the atmospheric and vacuum distillation processing constraints include at least one of the fourth material flow constraints, the fourth physical property constraints, and the fourth proportional constraints; The fourth material flow constraint includes the material flow constraint of each processing device, and the material flow constraint includes at least one of fixed value constraint and range constraint; The fourth material flow constraint includes the material flow constraint of each processing scheme of each processing device, and the material flow constraint includes at least one of fixed value constraint and range constraint; The fourth property constraint is the feed property harmonization constraint for each processing device; The fourth proportional constraint is the crude oil proportional control constraint received by each processing unit from the tank farm model within the plant. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range.

[0014] The present invention also provides a crude oil scheduling optimization device based on multi-period decomposition and reconstruction, comprising the following modules: The construction unit is used to construct crude oil arrival models, terminal tank farm models, plant tank farm models, and atmospheric and vacuum distillation models in segments according to the business process of crude oil scheduling. The solution unit is used to solve the crude oil arrival model, the terminal tank farm model, the plant tank farm model, and the atmospheric and vacuum distillation model simultaneously, with the constraints of crude oil arrival, terminal tank farm, plant tank farm, and atmospheric and vacuum distillation processing as constraints, and with the objective function as the minimization objective function. The optimization unit is used to optimize crude oil scheduling based on the solution results; The crude oil arrival constraints are used to control the quantity, blending, and orderly transportation of arriving crude oil; the terminal tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the terminal tank farm; the plant tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the plant tank farm; and the atmospheric and vacuum distillation processing constraints are used to control the quantity, nature, and proportion of atmospheric and vacuum distillation processing. The objective function is constructed based on the transportation costs, switching operation costs, and storage costs of each stage.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction as described above.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction as described above.

[0017] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction as described above.

[0018] This invention provides a crude oil scheduling optimization method and apparatus based on multi-period decomposition and reconstruction. It constructs segmented models of each business node—crude oil arrival at port, terminal tank farm, plant tank farm, and atmospheric and vacuum distillation—according to the crude oil scheduling business process. Segmented control enables the orderly transportation and storage of arriving crude oil, achieving reasonable control over the properties, proportions, costs, and receiving / discharging logic of crude oil in storage tanks, ultimately meeting the needs of atmospheric and vacuum distillation. Through segmented models of the entire business process and constraint control, it achieves task decomposition of crude oil scheduling. By constructing multi-period models, it achieves short-period time decomposition of long-period plans, ultimately realizing the decomposition and reconstruction of multi-scale, multi-task crude oil scheduling schemes. This improves the executability of crude oil scheduling schemes, reduces overall operating costs, and enhances the operational stability of the apparatus. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the crude oil scheduling optimization method based on multi-period decomposition and reconstruction provided by the present invention.

[0021] Figure 2 This is a schematic diagram of the structure of the crude oil scheduling optimization device based on multi-cycle decomposition and reconstruction provided by the present invention.

[0022] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0024] To address the shortcomings of existing technologies, this invention provides a crude oil scheduling optimization method based on multi-period decomposition and reconstruction. It constructs a crude oil arrival model, a terminal tank farm model, a plant tank farm model, and an atmospheric and vacuum distillation (AFD) processing model according to business logic. The method utilizes crude oil arrival constraints to control the quantity, blending, and orderly transportation of arriving crude oil; terminal tank farm constraints to control the quantity, properties, proportion, and operation of inputs and outputs; plant tank farm constraints to control the quantity, properties, proportion, and operation of inputs and outputs; and atmospheric and vacuum distillation constraints to control the quantity, properties, and proportion of AFD processing. By constructing and solving a cost minimization objective function, it achieves pre-scheduling and task decomposition of crude oil scheduling schemes from the terminal to AFD processing based on production plans. This improves the executability of crude oil scheduling schemes and the stability of production operations.

[0025] Figure 1 This is a flowchart illustrating the crude oil scheduling optimization method based on multi-period decomposition and reconstruction provided by the present invention, as shown below. Figure 1 As shown, the method includes steps 110, 120 and 130.

[0026] Step 110: Construct crude oil arrival model, terminal tank farm model, plant tank farm model, and atmospheric and vacuum distillation model in segments according to the crude oil dispatching business process; Step 120: Using crude oil arrival constraints, terminal tank farm constraints, plant tank farm constraints, and atmospheric and vacuum distillation constraints as constraints, and minimizing the objective function as the objective, simultaneously solve the crude oil arrival model, terminal tank farm model, plant tank farm model, and atmospheric and vacuum distillation model; wherein, the minimizing objective function can be minimizing the transportation cost, switching operation cost, and storage cost of each link, etc. Step 130: Optimize crude oil scheduling based on the solution results; Among them, crude oil arrival constraints are used to control the quantity, blending and orderly transportation of crude oil arriving at the port; terminal tank area constraints are used to control the quantity, nature, proportion and operation of input and output of terminal tank areas; plant tank area constraints are used to control the quantity, nature, proportion and operation of input and output of plant tank areas; and atmospheric and vacuum distillation constraints are used to control the quantity, nature and proportion of atmospheric and vacuum distillation. The objective function is constructed based on the transportation cost, switching operation cost and storage cost of each link.

[0027] The crude oil arrival model includes A receiving modules. Each receiving module includes a first inlet and a first outlet. The first inlet is the entrance for each type of crude oil to enter the boundary area. The o-th type of arriving crude oil is connected to the p-th first inlet. The p-th first outlet is connected to the third inlet of the c-th first storage sub-module in the first storage module of the y-th tank in each cycle of the terminal tank farm model. The p-th first outlet is connected to the third inlet of one or more first storage sub-modules in the first storage module of one or more tanks in each cycle of the terminal tank farm model.

[0028] The terminal tank farm model consists of B cycles, each containing C tanks, and each tank contains a first inventory module and a second inventory module.

[0029] The first storage module of the b-th tank in each cycle includes D first storage sub-modules. Each first storage sub-module includes a second inlet, a third inlet, a second outlet, and a third outlet. The second inlet of the k-th first storage sub-module of the first storage module of the b-th tank in each cycle is connected to the fourth outlet of the k-th second storage sub-module of the second storage module of the b-th tank in the previous cycle. The second inlet of each first storage sub-module of the first storage module of each tank in the first cycle is connected to the outside of the boundary area. The second outlet of the k-th first storage sub-module of the first storage module of the b-th tank in each cycle is connected to the fourth inlet of the k-th second storage sub-module of the second storage module of the same tank in the same cycle. The k-th... The third inlet of the first storage submodule is connected to the first outlet of the s-th receiving module in the crude oil arrival model. The third inlet of the k-th first storage submodule of the first storage module of the b-th tank in each cycle is connected to the first outlet of one or more receiving modules in the crude oil arrival model. The third outlet of the k-th first storage submodule of the first storage module of the b-th tank in each cycle is connected to the fifth inlet of the t-th third storage submodule of the third storage module of the i-th tank in the plant tank farm model for the corresponding cycle. The third outlet of the k-th first storage submodule of the first storage module of the b-th tank in each cycle is connected to the fifth inlet of one or more third storage submodules of the third storage module of one or more tanks in the plant tank farm model for the corresponding cycle.

[0030] The second storage module of the b-th tank in each cycle includes E second storage sub-modules, each of which includes a fourth inlet and a fourth outlet. The fourth inlet of the x-th second storage sub-module of the second storage module of the b-th tank in each cycle is connected to the second outlet of the same first storage sub-module of the first storage module of the same tank in the same cycle. The fourth outlet of the x-th second storage sub-module of the second storage module of the b-th tank in each cycle is connected to the second inlet of the x-th first storage sub-module of the first storage module of the b-th tank in the next cycle. The fourth outlet of each second storage sub-module of the second storage module of each tank in the last cycle is connected to the outside of the boundary area.

[0031] In addition, the tank farm model includes F cycles, each containing G tanks; each tank contains a third inventory module and a fourth inventory module.

[0032] The third storage module of the nth tank in each cycle contains H third storage sub-modules, each containing a fifth inlet, a fifth outlet, a sixth inlet, and a sixth outlet. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of the m-th first storage sub-module of the h-th tank in the corresponding cycle of the terminal tank farm model. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of one or more first storage sub-modules of one or more tanks in the corresponding cycle of the terminal tank farm model. The fifth outlet of the third storage sub-module of the nth tank in each cycle is connected to the third outlet of the corresponding cycle of the atmospheric and vacuum distillation processing model. The eighth inlet of the vth processing scheme of the uth processing device is connected; the fifth outlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the eighth inlet of the specific processing scheme of one or more processing devices in the atmospheric and vacuum processing model; the sixth inlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh outlet of the fourth storage submodule of the same tank in the previous cycle; the fifth inlet of the third storage submodule of the third storage module of each tank in the first cycle is connected to the outside; the sixth outlet of the zth third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh inlet of the same fourth storage submodule of the same tank in the same cycle.

[0033] The fourth storage module of the nth tank in each cycle contains I fourth storage sub-modules, each containing a seventh inlet and a seventh outlet. The seventh inlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the sixth outlet of the same third storage sub-module in the third storage module of the same tank in the same cycle. The seventh outlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the seventh inlet of the same third storage sub-module in the third storage module of the nth tank in the next cycle. The seventh outlet of the fourth storage sub-module in the fourth storage module of all tanks in the last cycle is connected to the outside.

[0034] The atmospheric and vacuum distillation model includes J cycles, each cycle contains K processing devices, each device contains L processing schemes, and each processing scheme contains an eighth inlet and an eighth outlet.

[0035] The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of the e-th third storage sub-module in the third storage module of the w-th tank in the corresponding cycle of the tank farm model. The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of one or more third storage sub-modules in the third storage module of one or more tanks in the corresponding cycle of the tank farm model. The eighth outlet of each processing scheme of each processing unit in each cycle is connected to the outside of the boundary area.

[0036] In addition, crude oil arrival constraints include at least one of the following: first logistics constraints, first physical property constraints, first proportional constraints, and first operational constraints.

[0037] The first logistics constraint is the volume constraint of crude oil outside the boundary, which includes at least one of fixed value constraints and range constraints; the first logistics constraint is the speed constraint of transporting each type of crude oil arriving at the port to the terminal tank farm, which includes at least one of fixed value constraints and range constraints.

[0038] The first property constraint is the property harmonization constraint of the receiving module, such as sulfur content, acid value, API, etc. The property harmonization method includes one or more of the following: mass harmonization and volume harmonization. The constraint is controlled in the form of threshold constraint.

[0039] The first proportional constraint is the proportional control constraint of the first inlet of the external crude oil input receiving module. The proportional control constraint adopts one or more methods of control, such as a fixed proportion or a proportional range.

[0040] The first operational constraint is the control constraint transmitted from the first outlet of the receiving module to the third inlet of each first inventory sub-module of the first inventory module of each tank in each cycle of the terminal tank farm. An example is as follows: In the formula, COA i，out PTE represents the first export volume of the i-th receiving module in the crude oil arrival model. i，p，q，o LO represents the amount of crude oil arriving at port from the first outlet of the i-th receiving module to the third inlet of the o-th first storage module of the first storage module of the q-th tank in the p-th period of the terminal tank farm in the crude oil arrival model; t represents the crude oil arrival period corresponding to the i-th receiving module; LO represents the lower limit of the amount of crude oil arriving at port from the i-th receiving module to the third inlet of the o-th first storage module of the first storage module of the q-th tank in the p-th period of the terminal tank farm in each period; UP represents the upper limit of the amount of crude oil arriving at port from the i-th receiving module to the third inlet of the o-th first storage module of the first storage module of the q-th tank in the p-th period of the terminal tank farm in each period.

[0041] Specifically, the first outlet of the i-th receiving module is controlled to sequentially transport crude oil from the arrival cycle t. After the transport volume in cycle t reaches the upper limit, cycle t+1 transport begins until all the crude oil arriving at the port is transported, thus realizing the orderly transport of crude oil arriving at the port to the terminal storage tanks.

[0042] In addition, the constraints of the terminal tank farm include at least one of the following: second logistics constraints, second physical property constraints, second proportional constraints, second inventory constraints, and second operational constraints.

[0043] The second logistics constraint includes the flow constraints of the second inlet, second outlet, third inlet and third outlet of each second inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints.

[0044] The second logistics constraint includes the flow constraints of the fourth inlet and fourth outlet of each second inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints.

[0045] The second logistics constraint is the conveying speed constraint from the third outlet of each second inventory submodule of each tank in each cycle to the tank area within the plant. The conveying speed constraint includes at least one of fixed value constraint and range constraint.

[0046] The second property constraint is the property harmonization constraint for each tank in each cycle, such as sulfur content, acid value, API, etc. The property harmonization method includes one or more of the following: mass harmonization and volume harmonization. The constraint is controlled in the form of threshold constraint.

[0047] The second proportional constraint is the crude oil proportional control constraint input from the crude oil arrival model of each storage tank in each cycle. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportion range.

[0048] The second inventory constraint is the inventory quantity constraint for each storage tank in each period. The inventory quantity constraint includes at least one of the fixed value constraint and the range constraint.

[0049] The second operational constraint is the input / output constraint for each tank in each cycle, which controls the tank from having both input and output states simultaneously. An example is shown below: In the formula, dtq in，i，j dtq represents the third inlet quantity of all first inventory sub-modules of the first inventory module of the j-th storage tank in the i-th cycle; out，i，j For the first inventory module of the j-th tank in the i-th cycle, the third outlet quantity is the third outlet quantity of all first inventory sub-modules of the first inventory module; DI i，j and DO i，j It is an integer variable between 0 and 1.

[0050] Furthermore, the second operational constraint is the operational cost constraint.

[0051] Among them, the constraints of the tank area within the plant include at least one of the following: third logistics constraints, third physical property constraints, third proportional constraints, third inventory constraints, and third operational constraints.

[0052] The third logistics constraint includes the flow constraints of the fifth inlet, fifth outlet, sixth inlet and sixth outlet of each third inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints.

[0053] The third logistics constraint includes the flow constraints of the seventh inlet and seventh outlet of the fourth inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints.

[0054] The third logistics constraint is the conveying speed constraint from the fifth outlet of each third inventory sub-module of each storage tank in each cycle to each scheme of atmospheric and vacuum distillation unit. The conveying speed constraint includes at least one of fixed value constraint and range constraint.

[0055] The third property constraint is the property harmonization constraint for each tank in each cycle, such as sulfur content, acid value, API, etc. The property harmonization method includes one or more of the following: mass harmonization and volume harmonization. The constraint is controlled in the form of threshold constraint.

[0056] The third proportional constraint is the crude oil proportional control constraint input from the terminal tank area model of each storage tank in each cycle. The proportional control constraint is controlled by at least one of the following methods: a fixed proportion or a proportion range. The third inventory constraint is the inventory quantity constraint for each storage tank in each period. The inventory quantity constraint includes at least one of the fixed value constraint and the range constraint.

[0057] The third operational constraint is the input / output constraint for each tank in each cycle, which controls the tank to not have both input and output states simultaneously. An example is shown below: In the formula, ftq in，i，j ftq represents the fifth inlet quantity of all first inventory submodules of the third inventory module for the j-th tank in the i-th cycle; out，i，j FI represents the fifth outlet quantity of all third inventory sub-modules of the third inventory module for the j-th tank in the i-th cycle; i，j and FO i，j It is an integer variable between 0 and 1.

[0058] In addition, the third operational constraint is the operational cost constraint.

[0059] Furthermore, the atmospheric and vacuum distillation processing constraints include at least one of the fourth material flow constraints, the fourth physical property constraints, and the fourth proportional constraints.

[0060] The fourth logistics constraint includes the flow constraints of each processing unit, which include at least one of fixed value constraints and range constraints.

[0061] The fourth logistics constraint includes the material flow constraints of each processing scheme of each processing device. The material flow constraints include at least one of fixed value constraints and range constraints.

[0062] The fourth property constraint is the feed property blending constraint for each processing unit, such as sulfur content, acid value, API, etc. The property blending method includes one or more of mass blending and volume blending, and the constraint is controlled in the form of threshold constraint.

[0063] The fourth proportional constraint is the crude oil proportional control constraint received by each processing unit from the tank farm model within the plant. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range.

[0064] This invention constructs segmented models of crude oil arrival at ports, terminal tank farms, plant tank farms, and atmospheric and vacuum distillation processing nodes based on the crude oil dispatching business process. Segmented control enables the orderly transportation and storage of arriving crude oil, achieving reasonable control over the properties, proportions, costs, and receiving / discharging logic of crude oil in storage tanks, ultimately meeting the needs of atmospheric and vacuum distillation processing. Through segmented models of the entire business process and constraint control, the invention achieves task decomposition for crude oil dispatching. By constructing multi-period models, it achieves short-period time decomposition of long-period plans, ultimately realizing the decomposition and reconstruction of multi-scale, multi-task crude oil dispatching schemes. This improves the executability of crude oil dispatching schemes, reduces overall operating costs, and enhances the stability of plant operation.

[0065] As an optional embodiment, crude oil scheduling optimization is performed based on a monthly plan of 30 processing days and 1.09 million tons of processing volume, including four types of crude oil arriving at the port; the terminal tank area includes six storage tanks, of which three tanks store the same type of crude oil, and the remaining terminal tanks each store one type of crude oil arriving at the port; the plant tank area includes five storage tanks, of which four tanks each store one type of crude oil, and the other tank stores two types of crude oil, with a crude oil ratio of 3:17; there are two sets of atmospheric and vacuum distillation units. The first set of atmospheric and vacuum distillation units has two processing schemes, where the first processing scheme can process two types of crude oil, and the second scheme processes only one type of crude oil. The second set of atmospheric and vacuum distillation units has one processing scheme, processing two types of crude oil, with a crude oil ratio of 3:17.

[0066] The crude oil scheduling optimization device based on multi-period decomposition and reconstruction provided by the present invention will be described below. The crude oil scheduling optimization device based on multi-period decomposition and reconstruction described below can be referred to in correspondence with the crude oil scheduling optimization method based on multi-period decomposition and reconstruction described above.

[0067] Based on the above embodiments, Figure 2 This is a schematic diagram of the crude oil scheduling optimization device based on multi-period decomposition and reconstruction provided by the present invention, as shown below. Figure 2 As shown, the device includes: Construction unit 210 is used to construct crude oil arrival model, terminal tank farm model, plant tank farm model and atmospheric and vacuum distillation model in segments according to the business process of crude oil scheduling. Solver 220 is used to solve the crude oil arrival model, terminal tank area model, plant tank area model and atmospheric and vacuum distillation model simultaneously, with the constraints of crude oil arrival, terminal tank area, plant tank area and atmospheric and vacuum distillation as constraints, and the objective function as the minimization objective function. Optimization unit 230 is used to optimize crude oil scheduling based on the solution results; Among them, crude oil arrival constraints are used to control the quantity, blending and orderly transportation of crude oil arriving at the port; terminal tank area constraints are used to control the quantity, nature, proportion and operation of input and output of terminal tank areas; plant tank area constraints are used to control the quantity, nature, proportion and operation of input and output of plant tank areas; and atmospheric and vacuum distillation constraints are used to control the quantity, nature and proportion of atmospheric and vacuum distillation. The objective function is constructed based on the transportation cost, switching operation cost and storage cost of each link.

[0068] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 3As shown, the electronic device may include a processor 310, a communications interface 320, a memory 330, and a communication bus 340. The processor 310, communications interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions from the memory 330 to execute a crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction.

[0069] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0070] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction provided by the above methods.

[0071] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction provided by the above methods.

[0072] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0073] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A crude oil scheduling optimization method based on multi-period decomposition and reconstruction, characterized in that, include: Based on the business process of crude oil dispatch, models for crude oil arrival at port, terminal tank farms, plant tank farms, and atmospheric and vacuum distillation processing are constructed in segments. Using constraints such as crude oil arrival, terminal tank farm, plant tank farm, and atmospheric and vacuum distillation as constraints, and minimizing the objective function as the objective, the crude oil arrival model, terminal tank farm model, plant tank farm model, and atmospheric and vacuum distillation model are solved simultaneously. Based on the solution results, optimize crude oil scheduling; The crude oil arrival constraints are used to control the quantity, blending, and orderly transportation of arriving crude oil; the terminal tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the terminal tank farm; the plant tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the plant tank farm; and the atmospheric and vacuum distillation processing constraints are used to control the quantity, nature, and proportion of atmospheric and vacuum distillation processing. The objective function is constructed based on the transportation costs, switching operation costs, and storage costs of each stage.

2. The crude oil scheduling optimization method based on multi-period decomposition and reconstruction according to claim 1, characterized in that, The crude oil arrival model includes A receiving modules. Each receiving module includes a first inlet and a first outlet. The first inlet is the entrance for each type of crude oil to enter the boundary area. The o-th type of arriving crude oil is connected to the p-th first inlet. The p-th first outlet is connected to the third inlet of the c-th first storage sub-module in the first storage module of the y-th tank in each cycle of the terminal tank farm model. The p-th first outlet is connected to the third inlet of the third storage sub-module in the first storage module of one or more tanks in each cycle of the terminal tank farm model.

3. The crude oil scheduling optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the terminal tank farm model includes B periods, each period contains C tanks, and each tank contains a first storage module and a second storage module; the first storage module of the b-th tank in each period includes D first storage sub-modules, each first storage sub-module including a second inlet, a third inlet, a second outlet, and a third outlet; the second inlet of the k-th first storage sub-module of the first storage module of the b-th tank in each period is connected to the fourth inlet of the k-th second storage sub-module of the second storage module of the b-th tank in the previous period. For the first cycle, the second inlet of each first storage submodule of the first storage module of each tank is connected to the outside boundary; the second outlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the fourth inlet of the kth second storage submodule of the second storage module of the same tank in the same cycle; the third inlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the first outlet of the s-th receiving module in the crude oil arrival model; and the third inlet of the kth first storage submodule of the first storage module of the b-th tank in each cycle is connected to the crude oil arrival... The first outlet of one or more receiving modules in the port model is connected; the third outlet of the kth first inventory submodule of the first inventory module of the bth tank in each cycle is connected to the fifth inlet of the tth third inventory submodule of the third inventory module of the ith tank in the corresponding cycle in the in-plant tank area model; the third outlet of the kth first inventory submodule of the first inventory module of the bth tank in each cycle is connected to the fifth inlet of one or more third inventory submodules of the third inventory module of one or more tanks in the corresponding cycle in the in-plant tank area model; the second inventory module of the bth tank in each cycle includes E second warehouses. Each storage sub-module includes a fourth inlet and a fourth outlet; the fourth inlet of the xth second storage sub-module in the b-th storage tank of each cycle is connected to the second outlet of the same first storage sub-module in the same storage tank of the same cycle; the fourth outlet of the xth second storage sub-module in the b-th storage tank of each cycle is connected to the second inlet of the xth first storage sub-module in the b-th storage tank of the next cycle; and the fourth outlet of each second storage sub-module in the last cycle is connected to the outside of the boundary area.

4. The crude oil dispatch optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the in-plant tank farm model includes F periods, each period contains G tanks; each tank contains a third inventory module and a fourth inventory module; The third storage module of the nth tank in each cycle contains H third storage sub-modules, each containing a fifth inlet, a fifth outlet, a sixth inlet, and a sixth outlet. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of the m-th first storage sub-module of the h-th tank in the corresponding cycle of the terminal tank farm model. The fifth inlet of the z-th third storage sub-module of the nth tank in each cycle is connected to the third outlet of one or more first storage sub-modules of one or more tanks in the corresponding cycle of the terminal tank farm model. The fifth outlet of the third storage sub-module of the nth tank in each cycle is connected to the third outlet of the corresponding cycle of the atmospheric and vacuum distillation processing model. The eighth inlet of the vth processing scheme of the uth processing device is connected; the fifth outlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the eighth inlet of the specific processing scheme of one or more processing devices in the atmospheric and vacuum processing model; the sixth inlet of the third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh outlet of the fourth storage submodule of the same tank in the previous cycle; the fifth inlet of the third storage submodule of the third storage module of each tank in the first cycle is connected to the outside; the sixth outlet of the zth third storage submodule of the third storage module of the nth tank in each cycle is connected to the seventh inlet of the same fourth storage submodule of the same tank in the same cycle. The fourth storage module of the nth tank in each cycle contains I fourth storage sub-modules, each containing a seventh inlet and a seventh outlet. The seventh inlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the sixth outlet of the same third storage sub-module in the third storage module of the same tank in the same cycle. The seventh outlet of the z-th fourth storage sub-module in the fourth storage module of the nth tank in each cycle is connected to the seventh inlet of the same third storage sub-module in the third storage module of the nth tank in the next cycle. The seventh outlet of the fourth storage sub-module in the fourth storage module of all tanks in the last cycle is connected to the outside.

5. The crude oil scheduling optimization method based on multi-cycle decomposition and reconstruction according to claim 1, wherein the atmospheric and vacuum distillation processing model includes J cycles, each cycle includes K processing units, each unit includes L processing schemes, and each processing scheme includes an eighth inlet and an eighth outlet. The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of the e-th third storage sub-module in the third storage module of the w-th tank in the corresponding cycle of the tank farm model. The eighth inlet of the g-th processing scheme of the f-th processing unit in each cycle is connected to the fifth outlet of one or more third storage sub-modules in the third storage module of one or more tanks in the corresponding cycle of the tank farm model. The eighth outlet of each processing scheme of each processing unit in each cycle is connected to the outside of the boundary area.

6. The crude oil scheduling optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the crude oil arrival constraints include at least one of a first logistics constraint, a first physical property constraint, a first proportional constraint, and a first operational constraint; The first logistics constraint is the volume constraint of crude oil outside the boundary, which includes at least one of fixed value constraints and range constraints; the first logistics constraint is the speed constraint of transporting each type of crude oil arriving at the port to the terminal tank farm, which includes at least one of fixed value constraints and range constraints. The first physical property constraint is the physical property harmonic constraint of the receiving module; The first proportional constraint is the proportional control constraint of the first inlet of the external crude oil input receiving module. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range. The first operational constraint is the control constraint for the delivery of goods from the first outlet of the receiving module to the third inlet of each first inventory sub-module of the first inventory module of each tank in each cycle of the terminal tank area.

7. The crude oil scheduling optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the terminal tank area constraints include at least one of the following: second logistics constraints, second physical property constraints, second proportional constraints, second inventory constraints, and second operational constraints; the second logistics constraints include the material flow constraints of the second inlet, second outlet, third inlet, and third outlet of each second inventory sub-module of each tank in each period, and the material flow constraints include at least one of fixed value constraints and range constraints. The second logistics constraint includes the flow constraints of the fourth inlet and fourth outlet of each second inventory sub-module of each storage tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints. The second logistics constraint is the conveying speed constraint from the third outlet of each second inventory sub-module of each storage tank in each cycle to the tank area in the plant. The conveying speed constraint includes at least one of fixed value constraint and range constraint. The second property constraint is the property harmonization constraint for each tank in each cycle; The second proportional constraint is the crude oil proportional control constraint input by the crude oil arrival model of each storage tank in each cycle. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range. The second inventory constraint is the inventory quantity constraint for each storage tank in each period. The inventory quantity constraint includes at least one of the fixed value constraint and the range constraint. The second operational constraint is the input and output constraint of each tank in each cycle, which controls the tank to not have both input and output states at the same time; the second operational constraint is the operational cost constraint.

8. The crude oil dispatch optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the in-plant tank area constraints include at least one of the following: third logistics constraints, third physical property constraints, third proportional constraints, third inventory constraints, and third operational constraints; The third logistics constraint includes the material flow constraints of the fifth inlet, fifth outlet, sixth inlet and sixth outlet of each third inventory sub-module of each storage tank in each cycle. The material flow constraint includes at least one of fixed value constraint and range constraint. The third logistics constraint includes the flow constraints of the seventh inlet and seventh outlet of the fourth inventory sub-module of the fourth inventory module of each tank in each cycle. The flow constraints include at least one of fixed value constraints and range constraints. The third logistics constraint is the conveying speed constraint from the fifth outlet of each third inventory sub-module of each storage tank in each cycle to each scheme of each atmospheric and vacuum distillation unit. The conveying speed constraint includes at least one of fixed value constraint and range constraint. The third physical property constraint is the physical property harmonization constraint for each storage tank in each cycle; The third proportional constraint is the crude oil proportional control constraint input from the terminal tank area model of each storage tank in each cycle. The proportional control constraint is controlled by at least one of the following methods: a fixed proportion or a proportion range. The third inventory constraint is the inventory quantity constraint of each storage tank in each period. The inventory quantity constraint includes at least one of fixed value constraint and range constraint. The third operational constraint is the input-output constraint for each tank in each cycle, which controls the tank from having both input and output states simultaneously; the third operational constraint is the operational cost constraint.

9. The crude oil scheduling optimization method based on multi-period decomposition and reconstruction according to claim 1, wherein the atmospheric and vacuum distillation processing constraint includes at least one of the fourth material flow constraint, the fourth physical property constraint, and the fourth proportional constraint; The fourth material flow constraint includes the material flow constraint of each processing device, and the material flow constraint includes at least one of fixed value constraint and range constraint; The fourth material flow constraint includes the material flow constraint of each processing scheme of each processing device, and the material flow constraint includes at least one of fixed value constraint and range constraint; The fourth property constraint is the feed property harmonization constraint for each processing device; The fourth proportional constraint is the crude oil proportional control constraint received by each processing unit from the tank farm model within the plant. The proportional control constraint is controlled by one or more methods, such as a fixed proportion or a proportional range.

10. A crude oil dispatch optimization device based on multi-period decomposition and reconstruction, characterized in that, include: The construction unit is used to construct crude oil arrival models, terminal tank farm models, plant tank farm models, and atmospheric and vacuum distillation models in segments according to the business process of crude oil scheduling. The solution unit is used to solve the crude oil arrival model, the terminal tank farm model, the plant tank farm model, and the atmospheric and vacuum distillation model simultaneously, with the constraints of crude oil arrival, terminal tank farm, plant tank farm, and atmospheric and vacuum distillation processing as constraints, and with the objective function as the minimization objective function. The optimization unit is used to optimize crude oil scheduling based on the solution results; The crude oil arrival constraints are used to control the quantity, blending, and orderly transportation of arriving crude oil; the terminal tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the terminal tank farm; the plant tank farm constraints are used to control the quantity, nature, proportion, and operation of inputs and outputs of the plant tank farm; and the atmospheric and vacuum distillation processing constraints are used to control the quantity, nature, and proportion of atmospheric and vacuum distillation processing. The objective function is constructed based on the transportation costs, switching operation costs, and storage costs of each stage.

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