Control method and system of crude oil supply network

Abstract

The invention discloses a control method and system for a crude oil supply network, and is applied to the field of petroleum intelligent decision making. According to the method, a crude oil supply integrated model is established, different stages of a marine transportation inventory route problem and a crude oil scheduling problem are regarded as a whole in an optimization solving process of the model, and production and scheduling constraint conditions of each stage are met at the same time, so that global optimization is realized, and the production efficiency and the economic benefits are improved.

Description

[0001] Priority Statement

[0002] This application claims priority to Chinese Patent Application No. 202510349443.X, filed on March 24, 2025, entitled “Data Processing Method and System for Crude Oil Dispatch”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of intelligent decision-making in crude oil, and in particular to a control method and system for a crude oil supply network. Background Technology

[0004] At the operational level, crude oil supply involves issues related to maritime storage routes and crude oil dispatching.

[0005] The issue of maritime inventory routing involves arranging a fleet of vessels to travel between ports to meet product demand while adhering to lower and higher inventory limits at both production and consumption ports.

[0006] In crude oil dispatching problems, the primary objective is to meet the demands of crude oil distillation units (such as atmospheric and vacuum distillation units) in terms of both quantity and quality. Achieving this typically requires scheduling a series of operations, including unloading crude oil into storage tanks, transfers between tanks, and feed operations to the crude oil distillation units. A network consisting of crude oil terminals, pipelines, and refineries needs to be designed, taking into account inter-refinery connections and nonlinearities related to product blending. Key decisions include defining flow rates, operating variables, inventory management, and facility allocation.

[0007] Existing technologies generally address these two problems independently. However, for an integrated supply chain, addressing these problems independently may lead to the loss of supply chain information, making the solutions difficult to implement and ineffective in practical applications. Solving each problem individually typically aims only at optimizing a local effect at a specific stage. Therefore, planning each stage separately cannot achieve global optimization; it always comes at the cost of sacrificing the benefits of other stages to reduce the economic cost of the current stage.

[0008] Solving the shipping route problem and the crude oil dispatch problem independently may fail to coordinate the allocation of shared resources. For example, storage tanks define the boundary between the shipping route problem and the crude oil dispatch problem. The shipping route problem typically assumes that storage tanks can be used to receive crude oil carried by ships arriving at the terminal at irregular intervals, while the dynamics of the tanks are also affected by inflow and outflow operations managed by the crude oil dispatch problem, leading to potential mismatches in the level and composition of crude oil in the tanks. Furthermore, operational constraints, such as rules preventing simultaneous import and export operations in storage tanks, may not be met when solving the shipping route problem and the crude oil dispatch problem independently. These limitations necessitate that crude oil supply operational decisions seek solutions that simultaneously address both problems.

[0009] Therefore, it is evident that existing technologies have the following drawbacks:

[0010] First, the lack of comprehensive consideration of constraints (especially complex constraints) in maritime inventory routing and crude oil dispatching makes it difficult to achieve global optimization. Because these two stages of the problem only pursue the optimization of local effects, overall production efficiency and economics suffer. A particular stage's plan may aim to reduce its own costs while ignoring the impact on other processes, resulting in overall resource waste.

[0011] Second, the lack of effective coordination between the planned shipping routes for inventory and the crude oil supply plan has led to disruptions in the production process and increased costs.

[0012] Third, increased operating costs and a lack of close coordination between various processes may lead to an increase in the number of changes in oil transfer operations, thereby increasing operating costs and affecting production stability.

[0013] In conclusion, independently resolving issues related to maritime storage routes and crude oil dispatching will affect the economics of each stage, leading to a waste of resources in the actual crude oil supply and even affecting the normal production rhythm. Summary of the Invention

[0014] In order to effectively improve the economic benefits and production efficiency of each stage of crude oil supply, this application provides a method and system for controlling the crude oil supply chain.

[0015] In a first aspect, embodiments of this application provide a method for controlling a crude oil supply network. The network includes multiple nodes, including nodes belonging to a maritime route and subsequent nodes of that route. The method includes: establishing an integrated crude oil supply model, the model including multiple variables, multiple constraints, and an objective function. The multiple variables include: at each time step in multiple time steps, the predicted crude oil inventory of the multiple nodes, the predicted operating status of multiple oil tanks, and the predicted operating status and predicted crude oil transmission volume of multiple pipelines; each of the multiple constraints defines a condition that at least some of the multiple variables must satisfy; the objective function includes one or more optimization objectives, wherein each optimization objective is defined by at least some of the multiple variables. The method further includes: optimizing the multiple variables according to the multiple constraints and the objective function to obtain a target optimization result, the target optimization result including the multiple variables satisfying the multiple constraints; generating a crude oil supply plan based on the target optimization result; and controlling the actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines according to the crude oil supply plan.

[0016] In some embodiments, the one or more optimization objectives include an operation change objective, which aims to minimize operation changes during scheduling.

[0017] In some embodiments, the one or more optimization objectives further include a stability objective, which aims to minimize the changes in the physical properties of the oil collected by the atmospheric and vacuum distillation unit during scheduling.

[0018] In some embodiments, the one or more optimization objectives further include special operation objectives, which are used to minimize the number of simultaneous receipt and payment operations during scheduling.

[0019] In some embodiments, the plurality of variables includes the following variables:

[0020] x o,d,t This indicates whether the pipeline from the starting point o to the ending point d is open at time step t;

[0021] This represents the amount of oil transferred in the pipeline from the starting point o to the ending point d at time step t;

[0022] This represents the amount of oil of type i transported by the pipeline from the starting point o to the ending point d at time step t.

[0023] This represents the total inventory of all oil types at node o at time step t;

[0024] This represents the inventory of oil type i at time step t at node o;

[0025] ZS o,t,s , indicating whether oil tank o is in state s at time step t, s∈S={paying oil, receiving oil, standing still, receiving and paying simultaneously};

[0026] zq o,t,i This indicates whether oil tank o has oil type i at time step t;

[0027] r d,t,e , indicating the amount of crude oil component e received by the atmospheric and vacuum distillation unit d at time step t.

[0028] In some embodiments, the objective function is as follows:

[0029] ω1·OperationChangeObj+ω2·StableObj+ω3·SpecialObj;

[0030]

[0031] StableObj=∑ d,t,e |r d,t,e -r d,t-1,e |;

[0032] SpeacialOpeObj=∑ o,t zs o,t,边收边付 ;

[0033] Where OperationChangeObj represents the operation change target, StableObj represents the stability target, SpecialOpeObj represents the special operation target, and ω represents the weight.

[0034] In some embodiments, the plurality of constraints include a plurality of linear constraints and a property harmonic constraint based on the McCormick envelope method.

[0035] In some embodiments, the plurality of linear constraints include at least one of the following constraints: pipeline transmission oil volume limit, node receiving / discharging oil volume limit, node capacity limit, limit on the number of nodes for receiving / discharging oil sources / destination, limit on the number of oil types at nodes, node operating status limit, crude oil source limit, tank area crude oil transportation limit, and atmospheric and vacuum distillation unit processing limit. The node operating status limit includes at least one of the following requirements: status description requirement, simultaneous receiving and discharging can only occur on permitted tanks, simultaneous receiving and discharging cannot result in oil type mixing, and settling time requirement.

[0036] Secondly, embodiments of this application provide a control system for a crude oil supply network. The network includes multiple nodes, including nodes belonging to a maritime route and subsequent nodes of that route. The system includes a modeling module, an optimization module, a planning module, and a control module. The modeling module is used to establish an integrated crude oil supply model, which includes multiple variables, multiple constraints, and an objective function. The multiple variables include: at each time step in multiple time steps, the predicted crude oil inventory of the multiple nodes, the predicted operating status of multiple oil tanks, and the predicted operating status and predicted crude oil transmission volume of multiple pipelines; each of the multiple constraints defines a condition that at least some of the multiple variables must satisfy; the objective function includes one or more optimization objectives, wherein each optimization objective is defined by at least some of the multiple variables. The optimization module is used to optimize the multiple variables according to the multiple constraints and the objective function to obtain a target optimization result, the target optimization result including the multiple variables that satisfy the multiple constraints. The planning module is used to generate a crude oil supply plan based on the target optimization result. The control module is used to control the actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines in accordance with the crude oil supply plan.

[0037] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the control method for the crude oil supply network as described in the first aspect.

[0038] Fourthly, this application provides a computer-readable storage medium including program code that, when the storage medium is run on an electronic device, causes the electronic device to execute the control method for the crude oil supply network as described in the first aspect.

[0039] Fifthly, according to an embodiment of this application, a computer program product includes computer instructions stored in a computer-readable storage medium; when a processor of an electronic device retrieves the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, causing the electronic device to perform the control method for the crude oil supply network as described in the first aspect.

[0040] The technical solution provided in this application has the following advantages:

[0041] (1) Unlike the traditional model of making separate plans for each process, the problem of shipping inventory routes and crude oil scheduling is modeled as a whole problem. The production constraints and optimization objectives of each stage are taken into account, and overall coordination optimization (i.e. global optimization) is achieved.

[0042] (2) Global optimization enables the shipping inventory route plan to be naturally connected with the crude oil dispatch plan, and combined with the operation change target, it can reduce the overall operation cost, thereby improving production efficiency.

[0043] (3) An integrated model was constructed to accurately describe the various complex relationships in crude oil supply, and the McCormic method was used to provide a solid foundation for subsequent iterative solutions (optimization). The model can coordinate and match batch plans at each stage and realize the possibility of linear iterative optimization.

[0044] (4) The technical solution has good flexibility and adaptability, and can adapt to crude oil supply planning problems of different scales and characteristics, and has broad application prospects.

[0045] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0047] Figure 1 This is a topological diagram of the crude oil supply network.

[0048] Figure 2 An exemplary flowchart illustrating a control method for a crude oil supply network provided in an embodiment of this application.

[0049] Figure 3 An exemplary block diagram of a control system for a crude oil supply network provided in an embodiment of this application.

[0050] Figure 4 An exemplary block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0052] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0053] As a vital pillar of the national economy, the petroleum refining industry has demonstrated strong growth momentum driven by steady global economic growth and accelerated industrialization. Through a series of complex physical and chemical processes, this industry transforms crude oil into various petroleum products, such as gasoline, diesel, kerosene, lubricating oil, solvent oil, and asphalt, which are widely used in transportation, energy, chemical, and construction industries.

[0054] Figure 1 This is a schematic diagram of an exemplary crude oil supply network topology. (Example: ...) Figure 1 As shown, the initial part of the crude oil supply network includes sea routes and land pipelines. The sea routes originate from cruise ships and terminate at the docks. The maritime inventory problem involves nodes from cruise ships to the docks, while the crude oil dispatch problem involves nodes from the docks to the Crude Distillation Unit (CDU). The boundary between these two problems is the dock nodes (such as storage tanks).

[0055] Crude oil dispatching is a crucial link in the refinery's production and operation process, and its importance is self-evident. Crude oil dispatching is the initial stage of refinery production scheduling and serves as the source of raw material supply for the refinery's production process. Effective crude oil dispatching ensures a stable and timely supply of crude oil, thereby guaranteeing the refinery's production and operation. (Reference) Figure 1Refinery crude oil scheduling involves a series of complex processes, including the unloading of crude oil from tankers at the terminal to storage tanks in the storage and transportation plant, waiting for desalting and separation before being transported to on-site storage tanks, then to feed tanks for crude oil mixing, and finally feeding the mixed crude oil into the crude oil distillation unit (such as an atmospheric and vacuum distillation unit) for processing. These processes require ensuring the continuity of production in the refinery's crude oil distillation unit based on crude oil unloading and tank inventory, and comprehensively considering factors such as the unloading of crude oil from tankers, pipeline transportation of crude oil at the terminal and within the plant, tank allocation and storage, crude oil mixing, and the sequential transportation of crude oil to the crude oil distillation unit, taking into account the distillation unit's process conditions, production plan, and processing volume.

[0056] Crude oil dispatch involves a large amount of data, including data from multiple stages such as crude oil transportation, storage, and processing. Data sources are diverse, including tanker unloading records, tank farm inventory data, and distillation unit process parameters. An efficient data processing system is needed to achieve real-time data acquisition, storage, analysis, and application.

[0057] Crude oil can be transported in various ways, including by sea and pipeline. A reasonable transportation plan needs to be developed based on the supply of crude oil and the needs of refineries to ensure timely supply.

[0058] Crude oil inventory management involves multiple tanks and storage facilities, requiring the assurance of accurate and timely inventory levels. An inventory early warning system needs to be established to promptly detect inventory anomalies and take appropriate measures. Inventory management also needs to consider factors such as the shelf life and potential losses of crude oil to ensure the quality and safety of the stored crude oil.

[0059] Crude oil blending involves mixing different types of crude oil in specific proportions to meet the production requirements of distillation units. The blending process must consider multiple factors, including the properties of the crude oil, processing conditions, and product quality. Therefore, precise blending models and optimization algorithms are needed to automate and intelligently manage the blending process.

[0060] To address the problems existing in current crude oil supply technologies, this application provides an integrated modeling strategy capable of coordinating and matching crude oil supply batch plans at various stages, establishing an integrated crude oil supply model. The optimization solution process of the integrated crude oil supply model treats different stages of the maritime inventory route problem and the crude oil scheduling problem as a whole, simultaneously satisfying the production and scheduling constraints of each stage. It also considers the constraints of different time stages on the preceding / next stage to uniformly formulate production plans, achieving global optimization, such as minimizing the number of operational changes and optimizing the oil transportation process, thereby improving production efficiency and economic benefits.

[0061] Figure 2 This is a flowchart of a control method for a crude oil supply network provided in an embodiment of this application. (Reference) Figure 1The crude oil supply network includes nodes along shipping routes and subsequent nodes along those routes. For example... Figure 2 As shown, process 200 includes the following steps.

[0062] Step 210: Establish an integrated crude oil supply model, which includes multiple variables, multiple constraints, and an objective function.

[0063] The plurality of variables include: at each of the plurality of time steps, the predicted crude oil inventory of the plurality of nodes, the predicted operating status of the plurality of oil tanks, and the predicted operating status and predicted crude oil transmission volume of the plurality of pipelines; each of the plurality of constraints defines a condition that at least some of the plurality of variables must satisfy, such as the range of values ​​of the variables or the relationship between the variables; the objective function includes one or more optimization objectives, wherein each optimization objective is defined by at least some of the plurality of variables.

[0064] The length of each time step can be set according to production needs. For example, half a day can be set as a time step, and the multiple time steps are 14 time steps corresponding to the next week.

[0065] Pipelines can refer to pipelines (such as land pipelines) or routes (such as sea routes). Each pipeline has a starting point and an ending point, both of which are nodes. The direction from the starting point to the ending point is the direction of crude oil transmission (crude oil flow direction).

[0066] Crude oil inventory can include total inventory (i.e., the sum of inventory of all oil types) and inventory of each oil type. Crude oil transport volume can include total transport volume (i.e., the sum of transport volume of all oil types) and transport volume of each oil type.

[0067] In some embodiments, the one or more optimization objectives include an operation change objective, which aims to minimize operation changes during scheduling.

[0068] In some embodiments, the one or more optimization objectives further include a stability objective, which aims to minimize the changes in the physical properties of the crude oil received by the atmospheric and vacuum distillation unit during the scheduling period. The stability objective can be measured by summing the differences in the amounts of the same crude oil component received by the same atmospheric and vacuum distillation unit at adjacent time steps.

[0069] In some embodiments, the one or more optimization objectives further include a special operation objective, which aims to minimize the number of simultaneous receiving and paying operations during scheduling. Simultaneous receiving and paying operations refer to nodes simultaneously performing oil receiving and paying operations, meaning that a node experiences both crude oil inflows and outflows at the same time. Simultaneous receiving and paying operations are special operations that cannot be completely eliminated and negatively impact the stability of crude oil properties; limiting the number of such operations helps ensure the stability of crude oil properties.

[0070] In some embodiments, the plurality of constraints includes a plurality of linear constraints and a property harmonic constraint based on the McCormick envelope method. The property harmonic constraint is a complex nonlinear constraint. By using the McCormick envelope method to linearly approximate this nonlinear constraint, the solution efficiency can be significantly improved by solving the model using a solver.

[0071] In some embodiments, the plurality of linear constraints include at least one of the following constraints: pipeline transmission oil volume limit, node receiving / distribution oil volume limit, node capacity limit, node receiving source / distribution destination node number limit, node oil type limit, node operating status limit, crude oil source limit, tank area crude oil transportation limit, and atmospheric and vacuum distillation unit processing limit; wherein, the node operating status limit includes at least one of the following requirements: status description requirement, receiving and distributing simultaneously can only occur on permitted oil tanks, receiving and distributing simultaneously cannot result in oil type mixing, and settling time requirement.

[0072] For more details on the integrated model, such as the specific definitions of the multiple linear constraints, the multiple variables, and the objective function, please refer to the integrated model based on McCormick relaxation, which will be introduced later.

[0073] Step 220: Optimize the multiple variables according to the multiple constraints and objective function to obtain the target optimization result.

[0074] The objective optimization result includes the multiple variables that satisfy the multiple constraints. Step 220, the model solving process, can be implemented using a solver. The objective optimization result of the crude oil scheduling model is the feasible solution of the model. The objective function is a core concept in optimization problems, used to guide the optimization process in the desired direction; it defines the index that needs to be maximized or minimized. A feasible solution is considered to be one that satisfies all the constraints of the model.

[0075] Step 230: Generate a crude oil supply plan based on the target optimization results.

[0076] The crude oil supply plan includes: at each of the plurality of time steps, the planned crude oil inventory at the plurality of nodes (e.g., the planned inventory of each type of oil), the planned operating status of the plurality of oil tanks (e.g., oil disbursement / receiving / stagnation / simultaneous receipt and disbursement), and the planned operating status of the plurality of pipelines (e.g., whether they are operational) and the planned crude oil transmission volume (e.g., the planned transmission volume of each type of oil).

[0077] In a crude oil supply plan, each variable can take the value of the same variable from the target optimization result. For example, the planned crude oil transmission volume of the multiple pipelines in the crude oil supply plan is equal to the predicted transmission volume of the multiple pipelines in the target optimization result.

[0078] Step 240: Control the actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines in accordance with the crude oil supply plan.

[0079] Nodes and pipelines can be equipped with various sensors (e.g., for oil quantity detection, flow detection, and status detection) and automation devices (such as electrically controlled valves) to achieve automated control. Specifically, the crude oil supply plan can be pre-input into the controller, which then executes the crude oil supply plan. That is, at each of the multiple time steps, the actual crude oil inventory of the multiple nodes (e.g., the actual inventory of each type of oil), the actual operating status of the multiple oil tanks (e.g., oil dispensing / receiving / standing / simultaneous receiving and dispensing), and the actual operating status of the multiple pipelines (e.g., whether they are open) and the actual crude oil transmission volume (e.g., the actual transmission volume of each type of oil) are controlled.

[0080] The following describes a preferred embodiment of the crude oil supply integration model based on McCormick relaxation provided in this application.

[0081] 1. Symbol Definition

[0082] 1.1 The following is the set of parameters that the model needs to consider:

[0083] V: The set of all nodes (oil tanks, special pipelines considered as nodes, docks, atmospheric and vacuum distillation units, etc.);

[0084] V pl : A set of special pipes that are considered as nodes;

[0085] V cdu A collection of atmospheric and vacuum distillation units;

[0086] V source : A set of nodes (terminals, pipelines, etc.) that input crude oil to be dispatched to a refinery, based on a given oil transportation plan;

[0087] V ope A set of nodes (such as oil tanks) that require decision-making regarding their operational status;

[0088] V pure : A set of nodes where mixing of crude oil within the tank is not permitted;

[0089] V bsbf A set of nodes that can simultaneously receive and pay;

[0090] The set of parent nodes of node o (nodes that can apply oil to node o), o∈V;

[0091] The set of child nodes of node o (nodes that can collect oil from node o), o∈V;

[0092] T: The set of time steps requiring a decision;

[0093] I: The set of oil types to be considered;

[0094] S: The set of states of a node, S = {Paying oil, Receiving oil, Standing still, Receiving and paying simultaneously};

[0095] E: The set of crude oil components limited by the atmospheric and vacuum distillation unit;

[0096] R i,e The content of component e in oil type i, i∈I, e∈E, 0≤R i,e ≤1;

[0097] Valid pipe,time The total number of start-end-time variables that need to be considered is {(o,d,t)|o,d∈V,t∈T}, and the relevant variables of (o,d,t) are the variables that need to be decided in the model.

[0098] Valid tank,time,oil The total number of oil tanks, time, and oil type that need to be considered is {(o,t,i)|o∈V,t∈...}

[0099] The relevant variables of T, I∈I}, (o, t, i) are the variables that need to be decided in the model; Valid detail The total number of start-end-time-oil types that need to be considered is {(o,d,t,i)|o,d∈V,t∈T,i∈I}, and the relevant variables of (o,t,i) are the variables that need to be decided in the model.

[0100] The maximum amount of fuel that can be delivered from the starting point o to the ending point d within a time step.

[0101] The maximum amount of oil collected at node o within a time step.

[0102] The maximum amount of fuel that node o can pay within a time step.

[0103] The upper limit on the number of oil-receiving nodes for node o within a time step.

[0104] The upper limit on the number of nodes to which node o can send fuel within a time step.

[0105] The upper limit of oil storage at node o within a time step.

[0106] DT o : The required settling time after oil collection at node o

[0107] Plan o,t,i : The planned amount of oil for oil type i at time step t at node o.

[0108] IR: Tank-pipe-tank paths that should not be used, {(tank1,pl,tank2,t)|tank1,tank2,pl∈V,t∈T,pl is a special pipe considered as a node}.

[0109] 1.2 The following are the linear variables that the model needs to consider:

[0110] x o,d,t : 0-1 variable, indicating whether the pipeline from the starting point o to the ending point d is open at time step t;

[0111] A continuous variable, representing the amount of oil transferred in the pipeline from the starting point o to the ending point d at time step t;

[0112] A continuous variable, representing the amount of oil of type i transported by the pipeline from the starting point o to the ending point d at time step t;

[0113] A continuous variable representing the total stock of all oil types at node o at time step t;

[0114] A continuous variable, representing the inventory of oil type i at time step t at node o;

[0115] zs o,t,s : 0-1 variable, indicating whether oil tank o is in state s at time step t, s∈S={paying oil, receiving oil, standing still, receiving and paying simultaneously};

[0116] zq o，t，i : A 0-1 variable, indicating whether oil tank o has oil type i at time step t;

[0117] r d，t，e : A continuous variable, representing the amount of crude oil component e received by the atmospheric and vacuum distillation unit d at time step t.

[0118] 2. Model

[0119] 2.1 The following are the linear constraints considered in the model:

[0120] a. Limitations on oil volume transported via pipeline:

[0121]

[0122] Used to control the total amount of oil transferred in all types of oil in the pipeline.

[0123] b. Limits on the amount of oil received and delivered at each node:

[0124]

[0125] The oil receiving and disbursement at a node are subject to upper limits.

[0126] Node oil capacity limit:

[0127]

[0128] The amount of oil a node can hold is limited by an upper limit.

[0129] c. Limits on the number of nodes for receiving oil / delivering oil:

[0130]

[0131] There are limitations on the number of nodes regarding where oil is received and where it is sent. d. Limitation on the number of oil types per node:

[0132]

[0133] The number of oil types at each node is subject to an upper limit.

[0134] e. Node operation state restrictions:

[0135] a) State description:

[0136]

[0137] A node has at least one state.

[0138]

[0139] If oil flows from o to d, then the state of o is "discharge oil".

[0140]

[0141] If oil flows from o to d, then the state of d is receiving oil.

[0142]

[0143] If there is both receiving and paying for oil at the same time, then the status is "receiving and paying simultaneously".

[0144]

[0145] The state of receiving or distributing oil cannot coexist with the state of being at rest.

[0146] b) Payment on delivery can only occur on permitted oil tanks:

[0147]

[0148] Only some pipelines allow for simultaneous collection and payment.

[0149] c) Oil mixing must be avoided during the simultaneous receipt and payment process.

[0150]

[0151] In the above constraints, M is equal to the number of oil types that node o can theoretically accommodate in the model minus 1.

[0152] d) Setting time requirement:

[0153]

[0154] There is a time interval between receiving oil and the next oil delivery.

[0155] g. Restrictions on crude oil sources:

[0156]

[0157] The source of crude oil will be restricted according to the plan.

[0158] h. Restrictions on crude oil transport between tank areas:

[0159]

[0160] Because there are multiple special pipelines between the two tank areas of the refinery, these pipelines have no volume definition but are subject to transport efficiency limits, source node number limits, and destination node number limits. The sum of the source and destination node numbers does not exceed 1, so these pipelines are described as nodes. This means that within time step t, it is not permissible for tank1 to flow through pl and then into tank2.

[0161] i. Manufacturing limitations of atmospheric and vacuum distillation units:

[0162]

[0163]

[0164] The processing capacity of the atmospheric and vacuum distillation unit is subject to upper and lower limits.

[0165] 2.2 The following is the objective function of the model:

[0166] min:ω1·OperationChangeObj+ω2·StableObj+ω3·SpecialObj (22)

[0167] The `a.OperationChangeObj` target aims to minimize operation changes during scheduling.

[0168]

[0169] To minimize model symmetry, the penalty weights for changes in operations at different nodes o at different time steps t are different.

[0170] Even if the operation of node o changes at time t, ZS o，t，s zs may also exist in LP relaxation models. o，t，s -zs o，t-1，s =0, therefore, in order to ensure that the operational changes are directly reflected in the objective value of the LP relaxation problem of the model, an objective term |y| is added. o，d，t，i -y o，d，t-1，i |

[0171] b. The StableObj objective aims to minimize the changes in the physical properties of the oil collected by the atmospheric and vacuum distillation unit during the scheduling period:

[0172] StableObj=∑ d，t，e |r d，t,e -r d,t-1,e | (24)

[0173] c. The SpecialOpeObj target aims to minimize the unavoidable and negatively impacting crude oil property stability during the scheduling period:

[0174] SpeicalOpeObj=∑ o,t ZS o,t,边收边付 (25)

[0175] 3. Handling property harmony constraints using the McCormic envelope method

[0176] Material property harmonization constraint: For oil tanks, if there are two or more types of crude oil in the tank, the proportion of a certain type of crude oil to be delivered must be equal to the inventory proportion of that type of crude oil in the tank when delivering oil.

[0177]

[0178] 3.1 Added parameter definitions

[0179] The following data was used during linearization:

[0180] Valid mcThe entire set of start-end-time-oil type data that needs to be linearized.

[0181] PWL v o,d,t,i: Given (o,d,t,i)∈Validmc, for The number of segments when performing a piecewise approximation;

[0182] PWL y o,d,t,i: Given (o,d,t,i)∈Validmc, for The number of segments when performing a piecewise approximation;

[0183] The upper limit of the amount of oil transported by the pipeline from the starting point o to the ending point d at time t;

[0184] The lower bound of the amount of oil transported by the pipeline from the starting point o to the ending point d at time step t;

[0185] The upper bound of the amount of oil of type i transported by the pipeline from the starting point o to the ending point d at time step t;

[0186] The lower bound of the amount of oil of type i transported by the pipeline from the starting point o to the ending point d at time step t;

[0187] The upper bound of the total inventory of all oil types at node o at time step t;

[0188] The lower bound of the total inventory of all oil types at node o at time step t;

[0189] The upper bound of the inventory of oil type i at node o at time step t;

[0190] The lower bound of the inventory of oil type i at node o at time step t.

[0191] 3.2 For nonlinear constraints, the McCormick envelope method is used to perform linear fitting on the nonlinear constraints:

[0192] a. to Perform a linear approximation:

[0193]

[0194]

[0195] These constraints use known upper bound solutions. Perform a linear approximation fit.

[0196] b. Perform a linear approximation:

[0197] The structure is exactly the same as the previous part; simply replace the variables and upper / lower bound parameters.

[0198] c. Linear approximation of the property harmonic constraint:

[0199]

[0200] The left and right ends of the nonlinearity are fitted with linear variables.

[0201] Figure 3 An exemplary block diagram of a control system for a crude oil supply network provided in an embodiment of this application. (See reference...) Figure 1 The crude oil supply network includes nodes along shipping routes and subsequent nodes along those routes. For example... Figure 3 As shown, system 300 includes a modeling module 310, an optimization module 320, a planning module 330, and a control module 340.

[0202] Modeling module 310 is used to establish an integrated crude oil supply model, which includes multiple variables, multiple constraints, and an objective function. The multiple variables include: at each time step in multiple time steps, the predicted crude oil inventory of the multiple nodes, the predicted operational status of multiple oil tanks, and the predicted operational status and predicted crude oil transmission volume of multiple pipelines; each of the multiple constraints defines a condition that at least some of the multiple variables must satisfy; the objective function includes one or more optimization objectives, wherein each optimization objective is defined by at least some of the multiple variables.

[0203] The optimization module 320 is used to optimize the multiple variables according to the multiple constraints and the objective function to obtain the target optimization result, wherein the target optimization result includes the multiple variables that satisfy the multiple constraints.

[0204] The planning module 330 is used to generate a crude oil supply plan based on the optimization results of the target.

[0205] The control module 340 is used to control the actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines in accordance with the crude oil supply plan.

[0206] For more details about System 300 and its modules, please refer to [link / reference]. Figure 2 And its related descriptions.

[0207] refer to Figure 4This application also provides an electronic device 400. The electronic device 400 includes a processor 410 and a memory 420. The memory stores program code, which, when executed by the processor 410, causes the processor 410 to execute the crude oil supply network control method provided in this application embodiment.

[0208] This application also provides a computer-readable storage medium including program code. When the storage medium is run on an electronic device, the program code is used to cause the electronic device to execute the control method for the crude oil supply network provided in this application.

[0209] This application also provides a computer program product, which includes computer instructions stored in a computer-readable storage medium; when the processor of an electronic device obtains the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, causing the electronic device to execute the crude oil supply network control method provided in this application.

[0210] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for controlling a crude oil supply network, characterized in that, The network includes multiple nodes, which include nodes belonging to the shipping route and subsequent nodes of the shipping route. The method includes: An integrated crude oil supply model is established, comprising multiple variables, multiple constraints, and an objective function. The multiple variables include: at each time step, the predicted crude oil inventory of the multiple nodes, the predicted operational status of multiple oil tanks, and the predicted operational status and predicted crude oil transmission volume of multiple pipelines. Each constraint defines a condition that at least some of the multiple variables must satisfy. The objective function includes one or more optimization objectives, each defined by at least some of the multiple variables. The multiple variables are optimized according to the multiple constraints and the objective function to obtain the objective optimization result, which includes the multiple variables that satisfy the multiple constraints; A crude oil supply plan is generated based on the optimization results of the aforementioned objectives; The actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines are controlled in accordance with the crude oil supply plan.

2. The method as described in claim 1, characterized in that, The one or more optimization objectives include an operation change objective, which aims to minimize operation changes during scheduling.

3. The method as described in claim 2, characterized in that, The one or more optimization objectives also include a stability objective, which aims to minimize the changes in the physical properties of the oil collected by the atmospheric and vacuum distillation unit during the scheduling period.

4. The method as described in claim 3, characterized in that, The one or more optimization objectives also include special operation objectives, which are used to minimize the number of simultaneous receipt and payment operations during scheduling.

5. The method as described in claim 4, characterized in that, The multiple variables Includes the following variables: x o,d,t This indicates whether the pipeline from the starting point o to the ending point d is open at time step t; This represents the amount of oil transferred in the pipeline from the starting point o to the ending point d at time step t; This represents the amount of oil of type i transported by the pipeline from the starting point o to the ending point d at time step t. This represents the total inventory of all oil types at node o at time step t; This represents the inventory of oil type i at time step t at node o; zs o,t,s , indicating whether oil tank o is in state s at time step t, s∈S={paying oil, receiving oil, standing still, receiving and paying simultaneously}; zq o,t,i This indicates whether oil tank O has oil type i at time step t; r d,t,e , indicating the amount of crude oil component e received by the atmospheric and vacuum distillation unit d at time step t.

6. The method as described in claim 5, characterized in that, The objective function is as follows: ω1·OperationChangeObj+ω2·StableObj+ω3·SpecialObj; StableObj=∑ d,t,e |r d,t,e -r d , t-1,e |; SpecialOpeObj=∑ o,t hp o,t,边收边付 ; Where OperationChangeObj represents the operation change target, StableObj represents the stability target, SpecialOpeObj represents the special operation target, and ω represents the weight.

7. The method as described in claim 1, characterized in that, The multiple constraints include multiple linear constraints and property harmonic constraints based on the McCormick envelope method.

8. The method as described in claim 7, characterized in that, The multiple linear constraints include at least one of the following constraints: pipeline transmission oil volume limit, node receiving / distribution oil volume limit, node capacity limit, node receiving source / distribution destination node number limit, node oil type limit, node operating status limit, crude oil source limit, tank area crude oil transportation limit, and atmospheric and vacuum distillation unit processing limit; wherein, the node operating status limit includes at least one of the following requirements: status description requirement, simultaneous receiving and distributing can only occur on permitted oil tanks, simultaneous receiving and distributing cannot result in oil type mixing, and settling time requirement.

9. A control system for a crude oil supply network, characterized in that, The network includes multiple nodes, which include nodes belonging to the shipping route and subsequent nodes of the shipping route. The system includes: A modeling module is used to establish an integrated crude oil supply model. The model includes multiple variables, multiple constraints, and an objective function. The multiple variables include: at each time step, the predicted crude oil inventory of the multiple nodes, the predicted operational status of the multiple oil tanks, and the predicted operational status and predicted crude oil transmission volume of the multiple pipelines. Each constraint defines a condition that at least some of the multiple variables must satisfy. The objective function includes one or more optimization objectives, each defined by at least some of the multiple variables. An optimization module is used to optimize the multiple variables according to the multiple constraints and the objective function to obtain a target optimization result, wherein the target optimization result includes the multiple variables that satisfy the multiple constraints; The planning module is used to generate a crude oil supply plan based on the optimization results of the target. The control module is used to control the actual crude oil inventory of the multiple nodes, the actual operating status of the multiple oil tanks, and the actual operating status and actual crude oil transmission volume of the multiple pipelines in accordance with the crude oil supply plan.

10. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the method of any one of claims 1 to 8.

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