CN117973711A - Crude oil dispatching optimization method and device, electronic equipment and storage medium - Google Patents

Crude oil dispatching optimization method and device, electronic equipment and storage medium Download PDF

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CN117973711A
CN117973711A CN202211289650.3A CN202211289650A CN117973711A CN 117973711 A CN117973711 A CN 117973711A CN 202211289650 A CN202211289650 A CN 202211289650A CN 117973711 A CN117973711 A CN 117973711A
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long
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seed
moment
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秦巧珍
刘华林
刘强
魏志伟
杨磊
刘玺
董丰莲
汪洪涛
杨剑
徐泽进
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Petrochina Co Ltd
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Abstract

The disclosure relates to a crude oil scheduling optimization method and device, electronic equipment and storage medium, wherein the method comprises the following steps: based on preset assumption conditions, constructing a long-distance pipeline basic model in the crude oil scheduling optimization process, wherein the assumption conditions are as follows: at most two types of oil exist in the long-distance pipeline at the same time (the assumption condition is obtained based on the actual industrial application scene); supplementing constraint conditions corresponding to crude oil states in different pipelines to the long-distance pipeline basic model; constructing a discrete time crude oil scheduling mixed integer programming model, wherein the discrete time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with constraint conditions; and solving the whole discrete time crude oil scheduling mixed integer programming model to obtain a crude oil scheduling optimization scheme, which can accurately represent the transmission characteristics of the long-distance pipeline under a discrete time modeling frame, can solve the global optimization of the large-scale crude oil scheduling problem of an actual scene, and can also attach to the actual lifting solution rate.

Description

Crude oil dispatching optimization method and device, electronic equipment and storage medium
Technical Field
The disclosure relates to the technical field of petrochemical industry, in particular to a crude oil dispatching optimization method and device, electronic equipment and a storage medium.
Background
From the technical point of view, the refinery crude oil scheduling is a typical process industrial production scheduling problem, a large number of discrete variables and continuous variables exist in the production process, the problem of multi-constraint, multi-objective and random uncertainty optimization is a NP (Non-Polynomial) complete problem, and the solution scale grows exponentially with the increase of the problem. Thus, whether a problem exists or not cannot be known in advance, and even if a solution exists, it cannot be guaranteed that an optimal solution is obtained in a limited time, even a feasible solution.
At present, no ideal solving method exists for the refinery scheduling problem, and in practice, people simplify the problem from different angles, so that approximate answers are obtained. There are generally two broad categories of solutions: the first category belongs to strict optimization methods based on models; the second category belongs to simulation methods based on rules, and the production scheduling simulation technology belongs to the technology. The second category essentially depends on the experience of the dispatcher, and the optimization effect is limited and the demand of the dispatcher is high, so the application effect is general.
Based on a strict optimization method of the model, the existing model is divided into two modes of discrete time modeling and continuous time modeling based on different time characterizations. The crude oil dispatching long-distance pipeline transmission is characterized in that the crude oil at the inlet of the long-distance pipeline needs a certain transmission time to reach the outlet, and an oil head (oil stored in the long-distance pipeline) exists in the normal operation of the long-distance pipeline. The start and end times of continuous time modeling events are variables that can accurately represent this feature from pipe segment modeling, which often assumes instantaneous arrival of crude oil. A very critical indicator in crude oil scheduling is transmission stability, wherein the most important part is fluctuation of long-distance pipeline transmission, the indicator is nonlinear in continuous time modeling, and besides, other continuous time modeling of business scenes related to time window processing, such as oil tanker overdue, standing and the like, is a nonlinear expression, so that a large-scale scheduling problem cannot be solved in a continuous time modeling mode, and practical application is difficult.
In the discrete time modeling framework, the transmission characteristics of the long-distance pipeline are required to be accurately represented, and one method is to cut the model and divide the model into three parts of the long-distance pipeline before the long-distance pipeline is simulated. The problem with this approach is that global optimization cannot be guaranteed, and the three-stage model increases the number of operations and long-distance pipeline simulations, thus increasing the total operation time.
Accordingly, the prior art has the following problems: first, continuous time modeling approaches solve scale constraints: multiple indexes or constraints (fluctuation, overdue oil tanker, standing and the like) form nonlinear terms, so that the solving difficulty is high, the solving scale is limited, and the method cannot be applied to industrial scenes; second, the discrete-time modeling global model cannot accurately represent long-distance pipeline transmission characteristics: the discrete time modeling carries out slicing processing on time, and the state of each slice is stable, so that the expression transmitted by a long-distance pipeline arrives at the time or is a time slice with fixed intervals, and the two expression modes are not consistent with reality, and the actual speed is changed; thirdly, the discrete time modeling three-segment model cannot guarantee global optimum: taking a long pipeline as a division point, firstly modeling and solving a wharf-long pipeline inlet, then simulating the long pipeline, and finally modeling and solving a long pipeline outlet-atmospheric and vacuum device processing, wherein the solution at each stage is a local optimal solution and the reasonable allocation of global resources cannot be ensured; fourth, discrete time modeling three-section model operation time is long: the three-section structure is used for modeling and solving the two models, and comprises the time of long-distance pipeline simulation, and the total operation time is longer.
Disclosure of Invention
To solve or at least partially solve the above technical problems, embodiments of the present disclosure provide a method and apparatus for optimizing crude oil scheduling, an electronic device, and a storage medium.
In a first aspect, embodiments of the present disclosure provide a crude oil scheduling optimization method, including:
Constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on preset assumption conditions; the assumed conditions are: at most two types of oil exist in the long-distance pipeline at the same time;
Supplementing constraint conditions corresponding to crude oil states in different pipelines to the long-distance pipeline basic model;
Constructing a discrete time crude oil scheduling mixed integer programming model, wherein the discrete time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with the constraint condition;
and solving the whole discrete time crude oil dispatching mixed integer programming model to obtain a crude oil dispatching optimization scheme.
In one possible embodiment, the assumption is that: at most two types of oil exist in the long-distance pipeline at the same time;
the construction of the long-distance pipeline basic model in the crude oil dispatching optimization process comprises the following steps:
dividing a long-distance pipeline into four target objects, namely an inlet, a first oil section, a second oil section and an outlet;
the input oil quantity of the long-distance pipeline is equal to the output oil quantity, and the pipeline oil storage quantity of the long-distance pipeline is equal to the sum of the oil quantities of the first oil section and the second oil section in the long-distance pipeline;
Constraining the quantity of oil seeds at an inlet, a first oil section, a second oil section and an outlet of the long conveying pipeline;
based on different crude oil states of the long-distance pipeline, the updating of the oil type and oil quantity adjacent time states of each pipeline section is restrained.
In one possible embodiment, the long-pipeline base model includes the following expression:
y0,t＝y31,t+y32,t
v＝y1,t+y2,t
Wherein x 0,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the long-distance pipeline, x 1,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the first oil segment of the long-distance pipeline, x 2,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the second oil segment of the long-distance pipeline, x 3,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the outlet of the long-distance pipeline, y 0,t is the oil quantity at the time t of the inlet of the long-distance pipeline, y 1,t is the oil quantity at the time t of the first oil segment of the long-distance pipeline, y 2,t is the oil quantity at the time t of the second oil segment of the long-distance pipeline, y 31,t is the oil quantity of the first oil at the outlet t of the long-distance pipeline, y 32,t is the oil quantity of the second oil at the outlet t of the long-distance pipeline, z 1,t is the same as the first oil seed in the long-distance pipeline and the first oil segment in the long-distance pipeline, z 2,t is the first oil segment in the long-distance pipeline and v is the positive, and N is the number of the head.
In one possible embodiment, the different in-pipe crude oil conditions include:
the inlet oil seed = first pipe section oil seed = second pipe section oil seed, so that the first pipe section oil seed, the second pipe section oil seed and the long-distance pipeline outlet oil seed at the moment t+1 are the same as the oil seed at the moment t, one oil exists at the long-distance pipeline outlet, and the oil quantity is equal to the oil quantity at the inlet of the long-distance pipeline at the moment t;
The oil seed of the inlet oil is not equal to the oil seed of the first pipe section = second pipe section, so that the oil seed of the first pipe section at the moment t+1 is the same as the oil seed of the inlet oil of the long-distance pipeline at the moment t, and the oil seed of the second pipe section at the moment t+1 is the same as the oil seed of each oil seed at the moment t; the oil storage quantity of the first pipe section at the moment t+1 is equal to the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t, and the oil storage quantity of the second pipe section at the moment t+1 is equal to the oil storage quantity of the second pipe section at the moment t minus the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t;
Inlet oil seed = first pipe section oil seed +.second pipe section oil seed, make t +1 long-term pipeline inside oil seed the same as t-term long-term pipeline inlet oil seed when t-term long-term pipeline inlet oil is greater than long-term pipeline inside second pipe section oil storage, t +1 long-term pipeline outlet first oil is the same as t-term long-term pipeline inlet oil seed, oil quantity is equal to t-term long-term pipeline inlet oil quantity minus t-term long-term pipeline second pipe section oil storage, t +1 long-term pipeline outlet second oil is t-term long-term pipeline second pipe section oil seed, oil quantity is equal to t-term long-term pipeline second pipe section oil storage; when the oil quantity of the inlet of the long transmission pipeline at the moment t is smaller than or equal to the oil quantity of the second pipe section in the long transmission pipeline, the oil types of the two pipe sections in the long transmission pipeline at the moment t+1 are the same as the oil types at the moment t, the oil quantity of the first pipe section at the moment t+1 is equal to the oil quantity of the first pipe section at the moment t plus the oil quantity of the inlet of the long transmission pipeline, the oil quantity of the second pipe section at the moment t is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline, the oil type of the outlet of the t+1 is the same as the oil type of the second pipe section of the long transmission pipeline at the moment t, and the oil quantity is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline at the moment t.
In one possible implementation, supplementing the long-distance pipeline basic model with constraint conditions corresponding to different in-pipe crude oil states includes:
supplementing the long-distance pipeline basic model with the following constraint conditions:
if inlet oil seed = first pipe section oil seed = second pipe section oil seed, then the corresponding constraint is:
if the inlet oil seed is not equal to the first tube segment oil seed = second tube segment oil seed, the corresponding constraint is:
if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, then the corresponding initial constraint is:
Wherein the intermediate 0-1 variable z 3,t represents the relationship of y 0,t and y 2,t, and if y 0,t is less than y 2,t, then the value of z 3,t is 1,
If z 3,t = 1, an intermediate 0-1 variable z 4,t is introduced, and if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, the corresponding constraints include the following in addition to the initial constraints:
If z 3,t = 0, an intermediate 0-1 variable z 5,t is introduced, and if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, the corresponding constraints include the following in addition to the initial constraints:
in one possible embodiment, the discrete-time crude oil dispatch mixed integer programming model further comprises:
material balance model of crude oil transportation tanker: the oil discharge amount of the crude oil tanker in the period is equal to the carrying capacity of the crude oil tanker in the period;
Tank field storage tank material constraint model: the tank oil storage amount at the end of each moment in the storage tank period is equal to the last tank storage amount at the last moment plus the tank inlet amount at the moment minus the tank outlet amount at the moment, wherein the tank inlet amount at the moment comprises the oil discharge and tank inlet amount of a tanker and the pipeline transmission and input tank amount of other storage tanks, and the tank outlet amount at the moment comprises the tank outlet amount transmitted to other storage tanks or atmospheric and vacuum devices by pipelines;
atmospheric and vacuum device protocol selection model: the atmospheric and vacuum device must select a processing scheme at each moment, and process crude oil according to the processing scheme, wherein the total processing amount of the periodical oil seeds is more than or equal to the oil seed demand.
In one possible implementation, in the discrete-time crude oil dispatch mixed integer programming model, the storage tank inventory is maintained within a safe tank inventory upper and lower limit;
pipeline transmission follows a topological structure, the transmission quantity is within the upper and lower limit range of pipeline transmission, and the transmission oil seeds are matched with the oil seeds of the starting tank and the destination tank;
The optimization objective of the discrete-time crude oil scheduling mixed integer programming model is to minimize the total cost in the whole crude oil scheduling process, and the expression of the total cost obtained by adding the overdue cost of the oil tanker, the storage cost of the tank farm, the switching cost of the atmospheric and vacuum oil mixing scheme, the switching cost of the tank farm tank oil seed and the fluctuation cost of the pipeline is as follows:
Total cost = tanker overdue cost + tank farm storage cost + atmospheric and vacuum blending scheme switching cost + tank farm tank seed switching cost + pipeline surge cost.
In a second aspect, embodiments of the present disclosure provide a crude oil scheduling optimization apparatus, comprising:
The first construction module is used for constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on preset assumption conditions;
The supplementing module is used for supplementing constraint conditions corresponding to the crude oil states in different pipelines to the long-distance pipeline basic model;
the second construction module is used for constructing a discrete-time crude oil scheduling mixed integer programming model, wherein the discrete-time crude oil scheduling mixed integer programming model comprises a long-distance pipeline base model with constraint conditions;
And the solving module is used for integrally solving the discrete time crude oil scheduling mixed integer programming model to obtain a crude oil scheduling optimization scheme.
In a third aspect, embodiments of the present disclosure provide an electronic device including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the crude oil dispatching optimization method when executing the program stored in the memory.
In a fourth aspect, embodiments of the present disclosure provide a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the above-described crude oil scheduling optimization method.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has at least part or all of the following advantages:
According to the crude oil scheduling optimization method disclosed by the embodiment of the disclosure, a long-distance pipeline basic model in a crude oil scheduling optimization process is constructed based on the assumption that at most two types of oil exist in the long-distance pipeline at the same time (the assumption is determined based on actual industrial application scenes), and constraint conditions corresponding to crude oil states in different pipes are supplemented for the long-distance pipeline basic model; constructing a discrete time crude oil scheduling mixed integer programming model, wherein the discrete time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with constraint conditions; and the discrete time crude oil scheduling mixed integer programming model is integrally solved to obtain a crude oil scheduling optimization scheme, so that the transmission characteristics of the long-distance pipeline can be accurately represented under a discrete time modeling frame, the global optimization of the large-scale crude oil scheduling problem in an actual scene can be solved, and the actual hoisting solution rate can be attached.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the related art will be briefly described below, and it will be apparent to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 schematically illustrates a flow diagram of a crude oil dispatch optimization method in accordance with an embodiment of the present disclosure;
FIG. 2 schematically illustrates a structural schematic of a long-distance pipeline according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates a flow diagram of one example of an application of a crude oil dispatch optimization method in accordance with an embodiment of the present disclosure;
FIG. 4 schematically illustrates a simplified flow diagram of a crude oil dispatch optimization method in accordance with an embodiment of the present disclosure;
FIG. 5 schematically illustrates a block diagram of a crude oil dispatch optimization device in accordance with an embodiment of the present disclosure; and
Fig. 6 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are some, but not all, embodiments of the present disclosure. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the disclosure, are within the scope of the disclosure.
Referring to fig. 1, an embodiment of the present disclosure provides a crude oil scheduling optimization method, including:
S1, constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on preset assumption conditions; the assumed conditions are: at most two types of oil exist in the long-distance pipeline at the same time;
S2, supplementing constraint conditions corresponding to the crude oil states in different pipes to the long-distance pipeline basic model;
s3, constructing a discrete-time crude oil scheduling mixed integer programming model, wherein the discrete-time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with constraint conditions;
And S4, solving the whole discrete time crude oil dispatching mixed integer programming model to obtain a crude oil dispatching optimization scheme.
In the step S1, the assumption that at most two types of oil exist in the long-distance pipeline at the same time is determined based on the actual industrial application scenario.
Based on the assumption that at most two types of oil exist in the long-distance pipeline at the same time, the constructed long-distance pipeline basic model is irrelevant to service, and reflects the principle that the oil quantity entering from the inlet of the long-distance pipeline is equal to the oil quantity output from the outlet no matter what oil is stored in the long-distance pipeline, no matter how high the transmission speed is, so the model can be used as the basic model of the long-distance pipeline in crude oil dispatching.
In this embodiment, in step S1, the constructing a long-distance pipeline base model in the crude oil scheduling optimization process includes:
referring to fig. 2, the long-distance pipeline is divided into four target objects of an inlet, a first oil section, a second oil section and an outlet;
the input oil quantity of the long-distance pipeline is equal to the output oil quantity, and the pipeline oil storage quantity of the long-distance pipeline is equal to the sum of the oil quantities of the first oil section and the second oil section in the long-distance pipeline;
Constraining the quantity of oil seeds at an inlet, a first oil section, a second oil section and an outlet of the long conveying pipeline;
based on different crude oil states of the long-distance pipeline, the updating of the oil type and oil quantity adjacent time states of each pipeline section is restrained.
In this embodiment, in step S1, the long-distance pipeline base model includes the following expression:
y0,t＝y31,t+y32,t
v＝y1,t+y2,t
Wherein x 0,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the long-distance pipeline, x 1,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the first oil segment of the long-distance pipeline, x 2,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the second oil segment of the long-distance pipeline, x 3,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the outlet of the long-distance pipeline, y 0,t is the oil quantity at the time t of the inlet of the long-distance pipeline, y 1,t is the oil quantity at the time t of the first oil segment of the long-distance pipeline, y 2,t is the oil quantity at the time t of the second oil segment of the long-distance pipeline, y 31,t is the oil quantity of the first oil at the outlet t of the long-distance pipeline, y 32,t is the oil quantity of the second oil at the outlet t of the long-distance pipeline, z 1,t is the same as the first oil seed in the long-distance pipeline and the first oil segment in the long-distance pipeline, z 2,t is the first oil segment in the long-distance pipeline and v is the positive, and N is the number of the head.
In this embodiment, in step S2, the different in-pipe crude oil states include:
the inlet oil seed = first pipe section oil seed = second pipe section oil seed, so that the first pipe section oil seed, the second pipe section oil seed and the long-distance pipeline outlet oil seed at the moment t+1 are the same as the oil seed at the moment t, one oil exists at the long-distance pipeline outlet, and the oil quantity is equal to the oil quantity at the inlet of the long-distance pipeline at the moment t;
The oil seed of the inlet oil is not equal to the oil seed of the first pipe section = second pipe section, so that the oil seed of the first pipe section at the moment t+1 is the same as the oil seed of the inlet oil of the long-distance pipeline at the moment t, and the oil seed of the second pipe section at the moment t+1 is the same as the oil seed of each oil seed at the moment t; the oil storage quantity of the first pipe section at the moment t+1 is equal to the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t, and the oil storage quantity of the second pipe section at the moment t+1 is equal to the oil storage quantity of the second pipe section at the moment t minus the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t;
Inlet oil seed = first pipe section oil seed +.second pipe section oil seed, make t +1 long-term pipeline inside oil seed the same as t-term long-term pipeline inlet oil seed when t-term long-term pipeline inlet oil is greater than long-term pipeline inside second pipe section oil storage, t +1 long-term pipeline outlet first oil is the same as t-term long-term pipeline inlet oil seed, oil quantity is equal to t-term long-term pipeline inlet oil quantity minus t-term long-term pipeline second pipe section oil storage, t +1 long-term pipeline outlet second oil is t-term long-term pipeline second pipe section oil seed, oil quantity is equal to t-term long-term pipeline second pipe section oil storage; when the oil quantity of the inlet of the long transmission pipeline at the moment t is smaller than or equal to the oil quantity of the second pipe section in the long transmission pipeline, the oil types of the two pipe sections in the long transmission pipeline at the moment t+1 are the same as the oil types at the moment t, the oil quantity of the first pipe section at the moment t+1 is equal to the oil quantity of the first pipe section at the moment t plus the oil quantity of the inlet of the long transmission pipeline, the oil quantity of the second pipe section at the moment t is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline, the oil type of the outlet of the t+1 is the same as the oil type of the second pipe section of the long transmission pipeline at the moment t, and the oil quantity is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline at the moment t.
In this embodiment, in step S2, the constraint conditions corresponding to the crude oil states in the different pipes include:
The corresponding constraint of inlet oil seed = first pipe section oil seed = second pipe section oil seed is:
the constraint corresponding to the inlet oil seed not equal to the first pipe section oil seed=the second pipe section oil seed is:
Inlet oil seed = first tube segment oil seed +.second tube segment oil seed corresponding initial constraint is:
Wherein the intermediate 0-1 variable z 3,t represents the relationship of y 0,t and y 2,t, and if y 0,t is less than y 2,t, then the value of z 3,t is 1,
If z 3,t = 1, the intermediate 0-1 variable z 4,t is introduced, and the constraints corresponding to the inlet oil seed = first tube segment oil seed +.:
If z 3,t = 0, introducing the intermediate 0-1 variable z 5,t, the constraints corresponding to the inlet oil seed = first tube segment oil seed +.:
The application aims at improving a crude oil scheduling optimization model of discrete time strategy in a crude oil scheduling optimization method and device applied to a refinery, which is applied to the application number 202111102934.2, and a long-distance pipeline basic model with constraint conditions is added on the basis, so that the crude oil scheduling optimization model of the discrete time strategy is updated on the whole, and the discrete time crude oil scheduling mixed integer planning model is obtained. For details on the long-haul pipeline basic model, see the description of the previous embodiments.
The description of other parts of the discrete-time crude oil scheduling mixed integer planning model can be seen in detail in the description of a material balance model of a crude oil transportation tanker, a tank area storage tank material constraint model, an atmospheric and vacuum device scheme selection model, constraint conditions and the like in a crude oil scheduling optimization model of a discrete-time strategy, which is applied to a crude oil scheduling optimization method and device of a refinery, of application number 202111102934.2.
Specifically, in this embodiment, in step S3 and step S4, the discrete-time crude oil scheduling mixed integer programming model further includes:
material balance model of crude oil transportation tanker: the oil discharge amount of the crude oil tanker in the period is equal to the carrying capacity of the crude oil tanker in the period;
Tank field storage tank material constraint model: the tank oil storage amount at the end of each moment in the storage tank period is equal to the last tank storage amount at the last moment plus the tank inlet amount at the moment minus the tank outlet amount at the moment, wherein the tank inlet amount at the moment comprises the oil discharge and tank inlet amount of a tanker and the pipeline transmission and input tank amount of other storage tanks, and the tank outlet amount at the moment comprises the tank outlet amount transmitted to other storage tanks or atmospheric and vacuum devices by pipelines;
atmospheric and vacuum device protocol selection model: the atmospheric and vacuum device must select a processing scheme at each moment, and process crude oil according to the processing scheme, wherein the total processing amount of the periodical oil seeds is more than or equal to the oil seed demand.
In the embodiment, in the discrete time crude oil dispatching mixing integer programming model in the step S3 and the step S4, the storage quantity of the storage tank is kept within the upper limit and the lower limit of the storage tank;
pipeline transmission follows a topological structure, the transmission quantity is within the upper and lower limit range of pipeline transmission, and the transmission oil seeds are matched with the oil seeds of the starting tank and the destination tank;
The optimization objective of the discrete-time crude oil scheduling mixed integer programming model is to minimize the total cost in the whole crude oil scheduling process, and the expression of the total cost obtained by adding the overdue cost of the oil tanker, the storage cost of the tank farm, the switching cost of the atmospheric and vacuum oil mixing scheme, the switching cost of the tank farm tank oil seed and the fluctuation cost of the pipeline is as follows:
Total cost = tanker overdue cost + tank farm storage cost + atmospheric and vacuum blending scheme switching cost + tank farm tank seed switching cost + pipeline surge cost.
The material balance model of the tanker in the discrete time crude oil scheduling mixed integer programming model is as follows:
Equation (1) shows that if the actual departure time of the tanker exceeds the predicted latest departure time of the tanker, the tanker is overdue; equation (2) shows that the tanker can only transfer to the dock tank matching the oil seed and can only transfer within the effective time window (arrival time-latest departure time); equation (3) shows that the sea delivery amount of the whole period of the tanker is equal to the total amount of crude oil carried by the tanker; equation (4) represents the tanker material balance: the remaining amount at the end of the tanker time = the last remaining amount at the end of the up time minus the tanker sea input factory at the moment of the tanker.
The tank farm storage tank material constraint model in the discrete time crude oil scheduling mixed integer programming model is as follows:
the formula (5) shows that the tank of the tank farm is in one of three states of oil receiving, oil delivery and standing at any moment, wherein the oil delivery can be used for both external delivery and the oil tank can be used for the available state; equation (6) shows that when the oil tank is used as a crude oil transmission destination tank, the oil tank state is 'oil recovery'; equation (7) shows that after the oil is collected, the oil tank can enter into an oil-carrying (usable) state after the standing time requirement is met The oil-dispensing state cannot be entered in the (standing time), and if secondary oil collection occurs during standing, the standing time needs to be recalculated after the secondary oil collection is finished; the formula (8) and the formula (9) show that the oil tank can be used for carrying out the output when the oil tank is in an oil-carrying state; equation (10) represents the tank balance constraint: end of the moment inventory of the storage tank = end of the moment inventory of the storage tank + the quantity of the tank fed at the moment-the quantity of the tank discharged at the moment; equation (11) shows that when the oil type of the oil tank changes at adjacent time, a switch is determined; equation (12) indicates that the tank can only switch between crude oil types of the same type, where k 0 represents the set of types in which the initial oil types in the tank are located; equation (13) shows that the can cutting operation is allowed only if the can amount reaches the lower can stock limit, and since this expression is nonlinear, linearization results in equation (14).
The pipeline (including all pipelines, i.e., long-haul pipelines and non-long-haul pipelines) transport constraint model is as follows:
Equation (15) shows that transmission of each pipeline can only occur on the active pipeline and satisfies the transmission capacity limit; equation (16) shows that the transfer rate of each pipeline satisfies the limit of the upper and lower transfer capability limits; equations (17) - (21) represent pipeline topology constraints, in order from top to bottom: the method comprises the steps that an effective transmission pipeline is at most arranged at each moment of a wharf tank area and a commercial storage tank area, the effective transmission pipeline is at most arranged at each moment of the wharf tank area, the effective transmission pipeline is at most arranged at each moment of the commercial storage tank area, the effective transmission pipeline is required to be arranged at each moment of a land transportation node, and the effective transmission pipeline is at most arranged at each moment of a tank area to an atmospheric and vacuum device in a factory; formulas (22) - (24) represent pipeline transfer seed limits, which are in order from top to bottom: the land crude oil transmission is required to be matched with the oil seeds of an in-plant oil receiving tank, the transmission of a wharf tank area is required to be matched with the oil seeds of an auxiliary oil tank and an oil receiving tank, and the pipeline transmission from an in-plant tank to an atmospheric and vacuum tank area is required to be matched with the oil seeds of an in-plant tank;
The oil mixing scheme of the atmospheric and vacuum device is selected as follows:
Equation (25) shows that each atmospheric and vacuum equipment at each moment can only adopt one oil mixing scheme; equation (26) shows that crude oil feed to the atmospheric and vacuum tank farm in the plant matches atmospheric and vacuum processing requirements; equation (27) shows that the total processing amount of each oil type of the atmospheric and vacuum equipment meets the requirement of the full-cycle crude oil production plan; equation (28) indicates that the atmospheric and vacuum equipment at adjacent time points adopts different schemes and is regarded as the oil mixing scheme switching.
The goal of the overall schedule is to minimize the total cost, expressed in detail as follows:
The first term in equation (29) is the tanker overdue cost, the second term is the tank farm storage cost, the third term is the atmospheric and vacuum mixing scheme switching cost, the fourth term is the tank farm tank seed switching cost, and the fifth term is the pipeline fluctuation cost.
Definition of parameters and sets:
/>
/>
Decision variables are as follows:
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amount of relaxation introduced:
The continuous variable represents the tank upper limit relaxation amount of the tank c at time t. /(I)
Sc c,t: the continuous variable represents the tank storage lower limit relaxation amount of the tank c at time t.
Continuous variable, crude oil production plan slack, i.e.I.
And lowering the warehouse relaxation amount of the wharf tank area.
And (5) lowering the slack amount of the tank field in the factory.
The above-described crude oil scheduling optimization method is described below by taking a specific example as an illustration. The steps of the method are shown with reference to fig. 3.
Firstly, constructing a refinery crude oil scheduling mixed integer programming model based on discrete time scales;
The process of creating the crude oil scheduling mixed integer planning model can be seen in 202111102934.2 description of a crude oil scheduling optimization model of discrete time strategy in a crude oil scheduling optimization method and device for oil refineries.
Secondly, constructing a long-distance pipeline basic model according to industrial scene application;
in the actual industrial application scene, the crude oil long-distance pipeline is generally not frequently switched. Two oil types exist in the long-distance pipeline at the same time, so that the conventional scheduling scene can be satisfied. The inventors of the present invention therefore constructed a long-distance pipeline base model based on the assumption that at most two oils are present inside the long-distance pipeline at the same time, as follows:
variables of the long-haul pipeline base model are shown in table 1 below:
TABLE 1
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The constraint conditions corresponding to the long-distance pipeline basic model are as follows:
2.1 the number of oil species present at the same time is limited (outlet section is at most 2, the others are all 1), and the input oil quantity is equal to the output oil quantity.
y0,t＝y31,t+y32,t
2.2 The oil storage quantity of the long-distance pipeline is equal to the sum of the oil quantities of two oil sections in the long-distance pipeline, and v is the oil head storage quantity and is a parameter.
v＝y1,t+y2,t
2.3 Oil seed switching expression is as follows.
2.4 If the two kinds of oil in the long-distance pipeline are the same, only one oil section exists, the oil storage quantity of the first oil section is 0, and the oil quantity state is:
M is positive infinity
Thirdly, carding the situation that a long-distance pipeline basic model cannot cover and affects the updating of the pipeline section state;
The inventor of the invention discovers that the oil seeds and the oil quantity at the inlet of the long-distance pipeline are independent variables through combing the situation that the basic model of the long-distance pipeline cannot be covered and the state update of the pipe section is influenced, and no additional constraint is needed; in addition, the two oil sections in the long conveying pipeline and the oil seeds at the time t+1 of the outlet of the long conveying pipeline are related to the state of the previous pipeline section and the state of the current pipeline section at the time t. The long-distance pipeline model cannot cover the following situations:
3.1, inlet oil seed = first pipe section oil seed = second pipe section oil seed;
At this time, there is one oil at the outlet of the long-distance pipeline, and only one oil exists inside the long-distance pipeline. the oil types of the first pipe section, the second pipe section and the long conveying pipeline at the moment t+1 are the same as the oil types at the moment t, only one type of oil exists at the long conveying pipeline outlet, and the oil quantity is equal to the oil quantity at the inlet of the long conveying pipeline at the moment t.
3.2, Inlet oil seed is not equal to the first tube section oil seed = second tube section oil seed;
At this time, one oil exists at the outlet of the long-distance pipeline, and two kinds of oil exist inside the long-distance pipeline. the oil seed of the first pipe section at the moment t+1 is the same as the oil seed of the inlet of the long-distance pipeline at the moment t, and the oil seed of the second pipe section is the same as the oil seed of each of the long-distance pipeline at the moment t; the oil storage quantity of the first pipe section at the moment t+1 is equal to the oil storage quantity of the second pipe section at the moment t+1 minus the oil storage quantity of the long-distance pipeline at the moment t.
3.3, Inlet oil seed = first tube segment oil seed not equal to second tube segment oil seed;
The state at time t+1 is related to the oil storage quantity of the long-distance pipeline at time t and the oil storage quantity of the second pipe section inside the long-distance pipeline.
If the oil quantity of the inlet of the long conveying pipeline at the moment t is larger than the oil quantity stored in the second pipe section in the long conveying pipeline, the method comprises the following steps: the long-term pipeline outlet will have two kinds of oil, and only 1 kind of oil exists in the long-term pipeline. the oil seed in the long-distance pipeline at the time t+1 is the same as the oil seed at the inlet of the long-distance pipeline at the time t; the oil quantity of the first oil at the outlet of the t+1 long-distance pipeline is equal to the oil quantity of the inlet of the long-distance pipeline at the moment t and less the oil quantity of the second pipe section of the long-distance pipeline at the moment t; the second oil is the oil seed in the second pipe section of the long-distance pipeline at the moment t, and the oil storage quantity is equal to the oil storage quantity in the second pipe section of the long-distance pipeline at the moment t.
If the oil storage amount of the long conveying pipeline at the moment t is smaller than the oil storage amount of the second pipe section in the long conveying pipeline, the method comprises the following steps: the long-term delivery line outlet will now have one oil, and there are two oils inside the long-term delivery line. the oil types of two pipe sections in the long-distance pipeline at the time t+1 are the same as the oil types at the time t, the oil storage quantity of the first pipe section is equal to the oil storage quantity of the first pipe section at the time t plus the oil quantity of the inlet of the long-distance pipeline, and the oil storage quantity of the second pipe section is equal to the oil storage quantity of the second pipe section at the time t minus the oil quantity of the inlet of the long-distance pipeline; the outlet oil seed of the t+1 long-distance pipeline is equal to the oil seed of the second pipe section of the long-distance pipeline at the moment t, and the oil quantity is equal to the oil storage quantity of the second pipe section of the long-distance pipeline at the moment t minus the oil quantity of the inlet of the long-distance pipeline at the moment t;
Accordingly, the inventors of the present invention have found that there is a need to add constraints to the long-pipeline base model for the three states described above.
Fourthly, newly adding constraint to the long-distance pipeline basic model aiming at the three states in the third step;
Specific constraint conditions for these three states can be seen in detail in the above description of the constraint conditions corresponding to the crude oil states in different tubes in step S2, and will not be described here again.
And fifthly, adding the newly added constraint of the fourth step into the long-distance pipeline basic model of the third step, merging with the mixed integer planning model of the refinery crude oil scheduling in the first step, and rapidly solving to obtain a scheduling scheme.
The crude oil scheduling optimization adopts discrete time modeling, so that nonlinear expression items in the crude oil scheduling problem are avoided, the transmission characteristics of the long-distance pipeline are accurately represented under the frame of the discrete time modeling, the actual application scene is fitted, global optimization is realized, and the model calculation times and the long-distance pipeline simulation time are also saved.
Referring to fig. 5, an embodiment of the present disclosure provides a crude oil scheduling optimization apparatus, including:
The first construction module 11 is used for constructing a long-distance pipeline basic model in the crude oil scheduling optimization process based on preset assumption conditions; the assumed conditions are: at most two types of oil exist in the long-distance pipeline at the same time;
A supplementing module 12, configured to supplement the long-distance pipeline basic model with constraint conditions corresponding to different in-pipe crude oil states;
a second construction module 13 for constructing a discrete-time crude oil dispatch mixed integer programming model, wherein the discrete-time crude oil dispatch mixed integer programming model comprises a long-distance pipeline base model with constraint conditions;
And the solving module 14 is used for solving the whole discrete-time crude oil scheduling mixed integer programming model to obtain a crude oil scheduling optimization scheme.
The implementation process of the functions and roles of each unit in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present invention. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
In the second embodiment described above, any of the first building block 11, the supplementing block 12, the second building block 13, and the solving block 14 may be incorporated in one block to be implemented, or any of the blocks may be split into a plurality of blocks. Or at least some of the functionality of one or more of the modules may be combined with, and implemented in, at least some of the functionality of other modules. At least one of the first building block 11, the supplementary block 12, the second building block 13 and the solving block 14 may be implemented at least partly as a hardware circuit, for example a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or in hardware or firmware such as any other rational way of integrating or packaging the circuits, or in any one of or a suitable combination of three of software, hardware and firmware. Or at least one of the first building block 11, the supplementary block 12, the second building block 13 and the solving block 14 may be at least partly implemented as a computer program module which, when run, performs the corresponding function.
The crude oil scheduling optimizing device accurately represents the transmission characteristics of the long-distance pipeline through discrete time modeling, can globally optimize and fit reality, and is suitable for application in large-scale industrial scenes.
Referring to fig. 6, an electronic device provided by an embodiment of the present disclosure includes a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, where the processor 1110, the communication interface 1120, and the memory 1130 perform communication with each other through the communication bus 1140;
A memory 1130 for storing a computer program;
Processor 1110, when executing the program stored in memory 1130, implements the following crude oil scheduling optimization method:
constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on an actual industrial application scene;
Supplementing constraint conditions corresponding to crude oil states in different pipelines to the long-distance pipeline basic model;
constructing a discrete time crude oil scheduling mixed integer programming model, wherein the discrete time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with constraint conditions;
and solving the discrete time crude oil scheduling mixed integer programming model to obtain a crude oil scheduling optimization scheme.
The communication bus 1140 may be a peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices described above.
The memory 1130 may include random access memory (Random Access Memory, RAM) or non-volatile memory (nonvolatile memory), such as at least one disk memory. Optionally, the memory 1130 may also be at least one storage device located remotely from the processor 1110.
The processor 1110 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), etc.; but may also be a digital signal processor (DIGITAL SIGNAL Processing, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components.
Embodiments of the present disclosure also provide a computer-readable storage medium. The computer readable storage medium stores a computer program which, when executed by a processor, implements the crude oil dispatch optimization method described above.
The computer-readable storage medium may be embodied in the apparatus/means described in the above embodiments; or may exist alone without being assembled into the apparatus/device. The above-described computer-readable storage medium carries one or more programs that, when executed, implement a crude oil scheduling optimization method according to an embodiment of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method for optimizing crude oil scheduling, the method comprising:
Constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on preset assumption conditions; the assumed conditions are: at most two types of oil exist in the long-distance pipeline at the same time;
Supplementing constraint conditions corresponding to crude oil states in different pipelines to the long-distance pipeline basic model;
Constructing a discrete time crude oil scheduling mixed integer programming model, wherein the discrete time crude oil scheduling mixed integer programming model comprises a long-distance pipeline basic model with the constraint condition;
and solving the whole discrete time crude oil dispatching mixed integer programming model to obtain a crude oil dispatching optimization scheme.
2. The method of claim 1, wherein constructing a long-pipeline base model in a crude oil dispatch optimization process comprises:
dividing a long-distance pipeline into four target objects, namely an inlet, a first oil section, a second oil section and an outlet;
the input oil quantity of the long-distance pipeline is equal to the output oil quantity, and the pipeline oil storage quantity of the long-distance pipeline is equal to the sum of the oil quantities of the first oil section and the second oil section in the long-distance pipeline;
Constraining the quantity of oil seeds at an inlet, a first oil section, a second oil section and an outlet of the long conveying pipeline;
based on different crude oil states of the long-distance pipeline, the updating of the oil type and oil quantity adjacent time states of each pipeline section is restrained.
3. The method of claim 2, wherein the long-pipeline base model comprises the following expression:
y0,t＝y31,t+y32,t
v＝y1,t+y2,t
Wherein x 0,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the long-distance pipeline, x 1,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the first oil segment of the long-distance pipeline, x 2,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the second oil segment of the long-distance pipeline, x 3,i,t is a variable of 0-1, which represents whether the oil seed i is delivered at the time t of the outlet of the long-distance pipeline, y 0,t is the oil quantity at the time t of the inlet of the long-distance pipeline, y 1,t is the oil quantity at the time t of the first oil segment of the long-distance pipeline, y 2,t is the oil quantity at the time t of the second oil segment of the long-distance pipeline, y 31,t is the oil quantity of the first oil at the time t of the outlet of the long-distance pipeline, y 32,t is the oil quantity of the second oil at the outlet of the long-distance pipeline, z 1,t is the same as the first oil seed in the long-distance pipeline and the first oil segment in the long-distance pipeline, z 2,t is the first oil segment in the long-distance pipeline and the second oil segment in the long-distance pipeline, and v is the positive, and M is the positive.
4. The method of claim 2, wherein the different in-pipe crude oil conditions comprise:
the inlet oil seed = first pipe section oil seed = second pipe section oil seed, so that the first pipe section oil seed, the second pipe section oil seed and the long-distance pipeline outlet oil seed at the moment t+1 are the same as the oil seed at the moment t, one oil exists at the long-distance pipeline outlet, and the oil quantity is equal to the oil quantity at the inlet of the long-distance pipeline at the moment t;
The oil seed of the inlet oil is not equal to the oil seed of the first pipe section = second pipe section, so that the oil seed of the first pipe section at the moment t+1 is the same as the oil seed of the inlet oil of the long-distance pipeline at the moment t, and the oil seed of the second pipe section at the moment t+1 is the same as the oil seed of each oil seed at the moment t; the oil storage quantity of the first pipe section at the moment t+1 is equal to the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t, and the oil storage quantity of the second pipe section at the moment t+1 is equal to the oil storage quantity of the second pipe section at the moment t minus the oil storage quantity of the inlet of the long-distance transmission pipeline at the moment t;
Inlet oil seed = first pipe section oil seed +.second pipe section oil seed, make t +1 long-term pipeline inside oil seed the same as t-term long-term pipeline inlet oil seed when t-term long-term pipeline inlet oil is greater than long-term pipeline inside second pipe section oil storage, t +1 long-term pipeline outlet first oil is the same as t-term long-term pipeline inlet oil seed, oil quantity is equal to t-term long-term pipeline inlet oil quantity minus t-term long-term pipeline second pipe section oil storage, t +1 long-term pipeline outlet second oil is t-term long-term pipeline second pipe section oil seed, oil quantity is equal to t-term long-term pipeline second pipe section oil storage; when the oil quantity of the inlet of the long transmission pipeline at the moment t is smaller than or equal to the oil quantity of the second pipe section in the long transmission pipeline, the oil types of the two pipe sections in the long transmission pipeline at the moment t+1 are the same as the oil types at the moment t, the oil quantity of the first pipe section at the moment t+1 is equal to the oil quantity of the first pipe section at the moment t plus the oil quantity of the inlet of the long transmission pipeline, the oil quantity of the second pipe section at the moment t is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline, the oil type of the outlet of the t+1 is the same as the oil type of the second pipe section of the long transmission pipeline at the moment t, and the oil quantity is equal to the oil quantity of the second pipe section at the moment t minus the oil quantity of the inlet of the long transmission pipeline at the moment t.
5. The method of claim 4, wherein supplementing the long-pipeline base model with constraints corresponding to different in-pipeline crude oil conditions comprises:
supplementing the long-distance pipeline basic model with the following constraint conditions:
if inlet oil seed = first pipe section oil seed = second pipe section oil seed, then the corresponding constraint is:
if the inlet oil seed is not equal to the first tube segment oil seed = second tube segment oil seed, the corresponding constraint is:
if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, then the corresponding initial constraint is:
Wherein the intermediate 0-1 variable z 3,t represents the relationship of y 0,t and y 2,t, and if y 0,t is less than y 2,t, then the value of z 3,t is 1,
If z 3,t = 1, an intermediate 0-1 variable z 4,t is introduced, and if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, the corresponding constraints include the following in addition to the initial constraints:
If z 3,t = 0, an intermediate 0-1 variable z 5,t is introduced, and if inlet oil seed = first tube segment oil seed +.second tube segment oil seed, the corresponding constraints include the following in addition to the initial constraints:
6. The method of any of claims 1-5, wherein the discrete-time crude oil dispatch mixed integer programming model further comprises:
material balance model of crude oil transportation tanker: the oil discharge amount of the crude oil tanker in the period is equal to the carrying capacity of the crude oil tanker in the period;
Tank field storage tank material constraint model: the tank oil storage amount at the end of each moment in the storage tank period is equal to the last tank storage amount at the last moment plus the tank inlet amount at the moment minus the tank outlet amount at the moment, wherein the tank inlet amount at the moment comprises the oil discharge and tank inlet amount of a tanker and the pipeline transmission and input tank amount of other storage tanks, and the tank outlet amount at the moment comprises the tank outlet amount transmitted to other storage tanks or atmospheric and vacuum devices by pipelines;
atmospheric and vacuum device protocol selection model: the atmospheric and vacuum device must select a processing scheme at each moment, and process crude oil according to the processing scheme, wherein the total processing amount of the periodical oil seeds is more than or equal to the oil seed demand.
7. The method of claim 6, wherein in the discrete-time crude oil dispatch mixed integer programming model, the storage tank inventory is maintained within safe tank inventory upper and lower limits; pipeline transmission follows a topological structure, the transmission quantity is within the upper and lower limit range of pipeline transmission, and the transmission oil seeds are matched with the oil seeds of the starting tank and the destination tank;
The optimization objective of the discrete-time crude oil scheduling mixed integer programming model is to minimize the total cost in the whole crude oil scheduling process, and the expression of the total cost obtained by adding the overdue cost of the oil tanker, the storage cost of the tank farm, the switching cost of the atmospheric and vacuum oil mixing scheme, the switching cost of the tank farm tank oil seed and the fluctuation cost of the pipeline is as follows:
Total cost = tanker overdue cost + tank farm storage cost + atmospheric and vacuum blending scheme switching cost + tank farm tank seed switching cost + pipeline surge cost.
8. A crude oil dispatch optimization device, comprising:
the first construction module is used for constructing a long-distance pipeline basic model in the crude oil dispatching optimization process based on preset assumption conditions; the assumed conditions are: at most two types of oil exist in the long-distance pipeline at the same time;
The supplementing module is used for supplementing constraint conditions corresponding to the crude oil states in different pipelines to the long-distance pipeline basic model;
the second construction module is used for constructing a discrete-time crude oil scheduling mixed integer programming model, wherein the discrete-time crude oil scheduling mixed integer programming model comprises a long-distance pipeline base model with constraint conditions;
And the solving module is used for integrally solving the discrete time crude oil scheduling mixed integer programming model to obtain a crude oil scheduling optimization scheme.
9. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
A processor for implementing the crude oil dispatch optimization method of any one of claims 1-7 when executing a program stored on a memory.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the crude oil dispatch optimization method of any one of claims 1-7.
CN202211289650.3A 2022-10-20 2022-10-20 Crude oil dispatching optimization method and device, electronic equipment and storage medium Pending CN117973711A (en)

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CN103984990B (en) * 2014-05-09 2017-04-05 清华大学 Based on oil plant, discrete time modeling method is dispatched by full factory
US9957959B2 (en) * 2015-09-20 2018-05-01 Macau University Of Science And Technology Linear programming-based approach to scheduling of crude oil operations in refinery for energy efficiency optimization
CN109101719A (en) * 2018-08-08 2018-12-28 深圳埃克斯工业自动化有限公司 Crude oil refines the schedulable analysis method of plan and device in short term
CN109740983A (en) * 2018-12-26 2019-05-10 中国石油大学(北京) A kind of product oil dispatching method and device based on pressure control
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