Natural gas supply chain production operation early warning method, related method, device, equipment and medium

Abstract

The present disclosure relates to a natural gas supply chain production operation early warning method, related method, device, equipment and medium, and relates to the technical field of natural gas. The natural gas supply chain production operation early warning method comprises: obtaining an optimization model constructed according to a feasible region calculation model and production constraints of a natural gas supply chain; wherein the feasible region calculation model is obtained by the following manner: based on pre-established early warning indexes of natural gas supply chain production operation and the production constraints, a feasible region calculation model of the natural gas supply chain is constructed; wherein the early warning indexes are used to reflect the production operation situation of the natural gas supply chain in a preset period; inputting the obtained natural gas supply chain production operation data and demand data of a preset period into the optimization model to determine whether there is a feasible solution result; if not, the production operation of the natural gas supply chain is warned.

Description

Technical Field

[0001] This disclosure relates to the field of natural gas technology, and in particular to a method, related methods, apparatus, equipment and medium for early warning of production and operation in the natural gas supply chain. Background Technology

[0002] The natural gas supply chain is a large and complex system comprised of natural gas production, transportation, storage, and distribution. It serves as a link between natural gas resources and the market, enabling the transport of natural gas from upstream production to downstream end-users. Currently, various uncertainties exist in the operation of the natural gas supply chain, potentially affecting its safe and stable operation and threatening the gas safety of users. Therefore, early warning systems for natural gas production operations are of paramount importance for ensuring natural gas supply security.

[0003] However, existing natural gas supply chain early warning methods typically analyze and predict relevant indicators using methods such as time series analysis, stochastic process methods, and system dynamics methods. These methods can only provide annual early warnings for natural gas supply security. The indicators on which the early warnings are based are long-term indicators that can only reflect long-term trends. They cannot be used for early warnings of various short-term uncertainties in the natural gas supply chain and cannot determine whether the natural gas supply chain needs early warning in the short term. Summary of the Invention

[0004] To address the aforementioned technical problems, or at least partially address them, embodiments of this disclosure provide a method, related methods, apparatus, equipment, and medium for early warning of production and operation in a natural gas supply chain.

[0005] In a first aspect, embodiments of this disclosure provide a method for early warning of production operations in a natural gas supply chain. The method includes: obtaining an optimization model constructed based on a feasible domain calculation model and production constraints of the natural gas supply chain; wherein the feasible domain calculation model is obtained by: constructing a feasible domain calculation model of the natural gas supply chain based on pre-established early warning indicators for production operations in the natural gas supply chain and the production constraints; wherein the early warning indicators are used to reflect the production operation status of the natural gas supply chain within a preset period.

[0006] The acquired natural gas supply chain production and operation data and the demand data for a preset period are input into the optimization model to determine whether a feasible solution exists;

[0007] In the absence of a feasible solution, an early warning is issued for the production and operation of the natural gas supply chain.

[0008] According to embodiments of this disclosure, a feasible domain calculation model for the natural gas supply chain is constructed based on pre-established early warning indicators and production constraints for the production and operation of the natural gas supply chain, including:

[0009] Based on the aforementioned early warning indicators, the set of working points that satisfy the aforementioned production constraints is taken as the feasible region of the natural gas supply chain, and a calculation model for the feasible region is established; wherein, the working points include node flow, node pressure, pipeline flow, gas field production, liquefied natural gas (LNG) export volume, and gas injection and production volume of gas storage facilities.

[0010] According to embodiments of this disclosure, constructing an optimization model based on the feasible region calculation model and the production constraints includes: constructing an objective function containing the operating point based on the operating point in the feasible region calculation model; and constructing an optimization model based on the objective function and the production constraints as constraints.

[0011] According to embodiments of this disclosure, the objective function includes minimizing pipeline transportation costs and maximizing the gas supply to users.

[0012] According to embodiments of this disclosure, the constraints include equality constraints and inequality constraints; the equality constraints include one or more of the following: pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints; the inequality constraints include one or more of the following: bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints.

[0013] According to embodiments of this disclosure, the pipeline flow constraint is expressed as follows:

[0014]

[0015] Where, x ij Let V represent the flow from node i to node j; (i,j) and (j,l) represent the pipeline between node i and node j and the pipeline between node j and node l, respectively; V is the set of nodes and E is the set of pipelines.

[0016] The hydraulic constraint of the pipeline is expressed as follows:

[0017]

[0018] Among them, P i and P j Let be the pressures at nodes i and j, respectively, in MPa; λ be the hydraulic friction coefficient; and Z be the compressibility factor of natural gas under pipeline transportation conditions, in Δ. *Where is the relative density of natural gas, T is the gas transmission temperature (K), L is the calculated length of the gas transmission pipeline (km), D is the inner diameter of the gas transmission pipeline (m), and C0 is a constant.

[0019] The natural gas pipeline storage constraint is expressed as follows:

[0020]

[0021]

[0022] Among them, V s Let V0 be the pipe volume, and P be the pipe capacity. pj Here, T0 is the average pipeline pressure, T0 is the temperature under standard conditions, Z0 is the compressibility factor under standard conditions, P0 is the pressure under standard conditions, T is the gas transmission temperature, Z is the compressibility factor of natural gas under pipeline transmission conditions, and P... i and P j The pressures at nodes i and j are respectively;

[0023] When the gas storage facility is in the gas extraction phase, the inventory constraint of the gas storage facility is expressed as follows:

[0024]

[0025] When the gas storage facility is in the gas injection phase, the gas storage facility's inventory constraint is expressed as follows:

[0026]

[0027] Among them, V UGS,i Let i be the inventory of the i-th gas storage facility. Let be the initial inventory of the i-th gas storage facility. Let S be the gas injection / production volume of the i-th gas storage facility. u and D u This refers to a collection of gas storage facilities that are in the gas extraction and gas injection stages, respectively.

[0028] The LNG receiving terminal tank storage constraint is expressed as follows:

[0029]

[0030] Among them, V LNG,i For the tank storage of the i-th LNG receiving terminal, Let the initial tank storage be for the i-th LNG receiving terminal. Let S be the output volume of the i-th LNG receiving terminal. l A collection of LNG receiving terminals;

[0031] The requirement constraint is expressed as follows:

[0032]

[0033] Where i is the i-th distribution point, Qi,j is the j-th user at the i-th distribution point, and mi is the number of users at the i-th distribution point; the flow direction constraint of the bidirectional pipeline is expressed as follows:

[0034]

[0035] Among them, E b Represents a set of bidirectional pipes, y ij For the binary decision variables controlling the flow direction of the bidirectional pipeline;

[0036] The oil and gas field production capacity constraint is expressed as follows:

[0037]

[0038] The gas extraction capacity constraint of the gas storage facility is expressed as follows:

[0039]

[0040] The LNG receiving terminal's export capacity constraint is expressed as follows:

[0041]

[0042] The pipeline capacity constraint is expressed as follows:

[0043]

[0044] in, Let i be the production of the i-th oil and gas field. Let be the gas extraction volume of the i-th gas storage facility. Let i be the output volume of the i-th LNG receiving terminal. Let i be the maximum production capacity of the i-th oil and gas field. Let i be the maximum gas extraction capacity of the i-th gas storage facility. S represents the maximum export capacity of the i-th LNG receiving terminal. f S is a collection of oil and gas fields. u A collection of gas storage facilities in the gas extraction stage, S l C is a collection of LNG receiving terminals. ij The pipeline capacity between node i and node j;

[0045] The requirement constraint is expressed as follows:

[0046]

[0047] in, Let i be the flow rate at the i-th distribution point. and These are the minimum and maximum demands for the i-th distribution point, respectively.

[0048] The gas injection capacity constraint of the gas storage facility is expressed as follows:

[0049]

[0050] in, Let be the gas injection volume of the i-th gas storage facility. D represents the maximum gas injection capacity of the i-th gas storage facility. u This is a gas storage facility in the gas injection phase.

[0051] The node pressure constraint is expressed as follows:

[0052] P i,min ≤P i ≤P i,max ,

[0053] Among them, P i For the pressure of the i-th node, P i,min and P i,max Let be the lower and upper limits of the pressure at the i-th node, respectively, in MPa; the upstream and downstream pressure constraints of the compressor station are expressed as follows:

[0054]

[0055] in, These are the upstream pressure, downstream pressure, upstream pressure limit, and downstream pressure limit of the i-th compressor station, respectively.

[0056] The upstream and downstream pressure constraints of the regulating valve are expressed as follows:

[0057]

[0058]

[0059] in, These are the upstream pressure, downstream pressure, lower limit of downstream pressure, and upper limit of downstream pressure for the i-th regulating valve, respectively.

[0060] The pipe inventory constraint is expressed as follows:

[0061]

[0062] in, and These represent the minimum and maximum safe pipe inventory levels, respectively.

[0063] The gas storage facility's inventory constraint is expressed as follows:

[0064]

[0065] in, and These are the minimum and maximum allowable storage capacities of the i-th gas storage facility, respectively.

[0066] The LNG receiving terminal tank storage constraint is expressed as follows:

[0067]

[0068] in, and These are the minimum and maximum allowable tank storage for the i-th LNG, respectively.

[0069] According to embodiments of this disclosure, the optimization model includes a mixed-integer nonlinear programming model or a mixed-integer linear programming model.

[0070] According to embodiments of this disclosure, the early warning indicators include natural gas pipeline pressure indicators, natural gas pipeline inventory indicators, gas storage tank inventory indicators, and LNG receiving terminal tank inventory indicators; wherein, the natural gas pipeline pressure indicator indicates that the pressure at each node of the natural gas supply chain is within the range of the maximum and minimum allowable pressure at any given time; the natural gas pipeline inventory indicator indicates that the natural gas pipeline inventory is between the maximum and minimum safe inventory levels under the corresponding operating conditions at any given time; the gas storage tank inventory indicator indicates that the gas storage tank inventory is within the range of the maximum and minimum inventory levels at any given time; and the LNG receiving terminal tank inventory indicator indicates that the LNG receiving terminal tank inventory is within the range of the maximum and minimum tank inventory levels at any given time.

[0071] Secondly, embodiments of this disclosure provide a natural gas supply chain production operation early warning device, the device comprising: a model building module, used to build an optimization model based on a feasible domain calculation model and production constraints of the natural gas supply chain; wherein, the feasible domain calculation model is obtained by: building a feasible domain calculation model of the natural gas supply chain based on pre-established early warning indicators for the production operation of the natural gas supply chain and the production constraints; wherein, the early warning indicators are used to reflect the production operation status of the natural gas supply chain within a preset period;

[0072] The model solving module is used to input the acquired natural gas supply chain production and operation data and the demand data for a preset period into the optimization model to determine whether there is a feasible solution to the optimization model.

[0073] The early warning module is used to provide early warnings about the production and operation of the natural gas supply chain when no feasible solution exists.

[0074] According to an embodiment of this disclosure, the model building module is further configured to: based on the early warning indicators, take the set of working points that satisfy the production constraints as the feasible domain of the natural gas supply chain, and establish a feasible domain calculation model; wherein, the working points include node flow, node pressure, pipeline flow, gas field production, LNG export volume, and gas storage injection and production volume.

[0075] Thirdly, embodiments of this disclosure provide a method for establishing an optimization model for the production and operation of a natural gas supply chain. The method for establishing such a model includes:

[0076] Based on pre-established early warning indicators and production constraints of the natural gas supply chain, a feasible domain calculation model for the natural gas supply chain is constructed; wherein, the early warning indicators reflect the short-cycle production and operation status of the natural gas supply chain.

[0077] An optimization model is constructed based on the feasible domain calculation model and the production constraints.

[0078] Fourthly, embodiments of this disclosure provide an apparatus for establishing a production and operation optimization model for a natural gas supply chain. The aforementioned apparatus for establishing a production and operation optimization model for a natural gas supply chain includes:

[0079] The first construction module is used to construct a feasible domain calculation model for the natural gas supply chain based on pre-established early warning indicators and production constraints of the natural gas supply chain; wherein, the early warning indicators reflect the short-cycle production and operation status of the natural gas supply chain.

[0080] The second construction module is used to construct an optimization model based on the feasible domain calculation model and the production constraints.

[0081] Fifthly, embodiments of this disclosure provide an electronic device. The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus; the memory stores computer programs; and the processor, when executing the program stored in the memory, implements the aforementioned natural gas supply chain production operation early warning method, and / or the aforementioned natural gas supply chain production operation optimization model establishment method.

[0082] Sixthly, embodiments of this disclosure provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the natural gas supply chain production operation early warning method and / or the natural gas supply chain production operation optimization model establishment method described above.

[0083] The technical solutions provided in this disclosure have some or all of the following advantages: By establishing early warning indicators that reflect the short-cycle production and operation status of the natural gas supply chain, and constructing a feasible region of the natural gas supply chain based on the early warning indicators and production constraints, and determining whether a feasible solution exists in the feasible region, it is possible to determine whether an early warning is needed for the natural gas supply chain in the short cycle. In the case where no feasible solution exists, an early warning for the production and operation of the natural gas supply chain is issued. This solves the technical problem that the existing technology can only reflect long-term trends and cannot be used for early warning of various short-cycle uncertain events in the natural gas supply chain. It overcomes the shortcomings of existing natural gas supply chain early warning models, which can only make long-term trend predictions and early warnings. Furthermore, by using the current production and operation status to extrapolate the future short-cycle trends and predict contradictions in the natural gas supply chain, the ability to predict the operational risks of the natural gas supply chain is further improved. Attached Figure Description

[0084] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0085] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0086] Figure 1 A flowchart illustrating a natural gas supply chain production operation early warning method according to an embodiment of the present disclosure is shown schematically.

[0087] Figure 2 A flowchart illustrating operation S103 in a natural gas supply chain production operation early warning method according to an embodiment of the present disclosure is shown schematically.

[0088] Figure 3 A detailed implementation flowchart of a natural gas supply chain production operation early warning method according to another embodiment of this disclosure is illustrated schematically;

[0089] Figure 4 A schematic diagram of a natural gas supply chain production operation early warning device according to an embodiment of the present disclosure is shown.

[0090] Figure 5 A flowchart illustrating a method for establishing a natural gas supply chain production operation optimization model according to an embodiment of the present disclosure is shown schematically.

[0091] Figure 6 A schematic diagram of a device for establishing a production operation optimization model for a natural gas supply chain according to an embodiment of the present disclosure is shown.

[0092] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation

[0093] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0094] With the rapid development of my country's low-carbon economy, the demand for natural gas, as a clean and efficient fossil energy source, is showing a trend of rapid growth. At the same time, the proportion of natural gas in my country's primary energy consumption structure is also increasing year by year. The natural gas supply chain is a large and complex system composed of natural gas production, transportation, storage, and distribution, serving as the link between natural gas resources and the market. Through the natural gas supply chain system, natural gas can be transported from upstream production to downstream end users. Therefore, ensuring the safe and stable operation of the natural gas supply chain is of great significance to the security of natural gas supply.

[0095] However, the operation of the natural gas supply chain is subject to various uncertainties, such as maintenance and repair of oil and gas fields, reduction in the supply of imported gas resources, accidents in the backbone pipeline network, abnormal weather changes, and unforeseen events such as LNG ships being unable to unload normally. These events may cause an imbalance in production, import, storage, and sales, thereby affecting the safe and stable operation of the natural gas supply chain and threatening the gas safety of natural gas users.

[0096] Early warning systems for natural gas supply chain production and operation can, based on real-time acquisition of key production and operation indicators, extrapolate the potential consequences of unforeseen events on various links of the natural gas supply chain in terms of time, space, and intensity. This enhances the ability to predict operational risks in the natural gas supply chain and provides a foundation for developing dynamic optimization and adjustment plans and emergency response plans. Therefore, it is necessary and urgent to research natural gas supply chain operation early warning methods and devices, and to improve the ability to predict operational risks in the natural gas supply chain by extrapolating short-term trends and predicting conflicts based on current production and operation conditions.

[0097] However, existing natural gas supply chain early warning methods typically analyze and predict relevant indicators using methods such as time series analysis, stochastic process methods, and system dynamics methods. These methods can only provide annual early warnings for natural gas supply security. The indicators on which the early warnings are based are long-term indicators that can only reflect long-term trends. They cannot be used for early warnings of various short-term uncertainties in the natural gas supply chain, nor can they determine whether the natural gas supply chain needs early warning in the short term.

[0098] Therefore, embodiments of this disclosure provide a method for early warning of natural gas supply chain production operations. The method includes: obtaining an optimization model constructed based on a feasible domain calculation model and the production constraints; wherein the feasible domain calculation model is obtained by: constructing a feasible domain calculation model of the natural gas supply chain based on pre-established early warning indicators for natural gas supply chain production operations and the production constraints; wherein the early warning indicators are used to reflect the production operation status of the natural gas supply chain within a preset period.

[0099] The acquired natural gas supply chain production and operation data and the demand data for a preset period are input into the optimization model to determine whether a feasible solution exists;

[0100] In the absence of a feasible solution, an early warning is issued for the production and operation of the natural gas supply chain.

[0101] The technical solutions provided in this disclosure have some or all of the following advantages: By establishing early warning indicators that reflect the short-cycle production and operation status of the natural gas supply chain, and constructing a feasible region of the natural gas supply chain based on the early warning indicators and production constraints, and determining whether a feasible solution exists in the feasible region, it is possible to determine whether an early warning is needed for the natural gas supply chain in the short cycle. In the case where no feasible solution exists, an early warning for the production and operation of the natural gas supply chain is issued. This solves the technical problem that the existing technology can only reflect long-term trends and cannot be used for early warning of various short-cycle uncertain events in the natural gas supply chain. It overcomes the shortcomings of existing natural gas supply chain early warning models, which can only make long-term trend predictions and early warnings. Furthermore, by using the current production and operation status to extrapolate the future short-cycle trends and predict contradictions in the natural gas supply chain, the ability to predict the operational risks of the natural gas supply chain is further improved.

[0102] The first exemplary embodiment of this disclosure provides a method for early warning of production operations in a natural gas supply chain.

[0103] Figure 1 A flowchart illustrating a natural gas supply chain production operation early warning method according to an embodiment of the present disclosure is shown schematically.

[0104] Reference Figure 1 As shown, the above-mentioned early warning method for natural gas supply chain production and operation includes the following operations:

[0105] Operation S101: Obtain the optimization model constructed based on the feasible region calculation model and the production constraints of the natural gas supply chain; wherein, the feasible region calculation model is obtained in the following manner: based on the pre-established early warning indicators of the natural gas supply chain production and operation and the production constraints, the feasible region calculation model of the natural gas supply chain is constructed; wherein, the early warning indicators are used to reflect the production and operation status of the natural gas supply chain within a preset period;

[0106] In step S102, the acquired natural gas supply chain production and operation data and the demand data for a preset period are input into the optimization model to determine whether a feasible solution exists; if yes, step S103 is executed; otherwise, step S104 is executed.

[0107] Operation S103 provides early warning for the production and operation of the natural gas supply chain;

[0108] Operate S104 without issuing a warning.

[0109] In one possible implementation, the early warning indicators reflecting the short-cycle production and operation status of the natural gas supply chain can be early warning indicators for the natural gas supply chain proposed from multiple dimensions based on the process and business characteristics of the natural gas supply chain. Specifically, they may include:

[0110] Natural gas pipeline pressure specifications: At any given time, the pressure at each node of the natural gas supply chain must be within the range of the maximum and minimum allowable pressure.

[0111] Natural gas pipeline inventory index: At any given time, the natural gas pipeline inventory must be between the highest and lowest safe inventory levels under the corresponding operating conditions;

[0112] Gas storage inventory indicators: At any given time, the gas storage inventory must be within the range of the maximum and minimum inventory levels of the gas storage facility;

[0113] LNG receiving terminal tank storage indicators: At any given time, the LNG receiving terminal tank storage must be within the range of the maximum and minimum tank storage of the LNG receiving terminal.

[0114] In one possible implementation, operation S101 can be implemented as follows: based on the established natural gas supply chain early warning indicators, construct a set of working points that satisfy various production constraints of the natural gas supply chain, i.e., the feasible region of the natural gas supply chain, thereby establishing a feasible region calculation model for the natural gas supply chain. The feasible region calculation model for the natural gas supply chain can be expressed as follows:

[0115] Ω = {W|h(W) = 0, g(W) ≤ 0}

[0116] In the formula, Ω represents the feasible region of the natural gas supply chain; W represents the working point of the natural gas supply chain, which consists of hydraulic variables of the natural gas supply chain, including node flow, node pressure, pipeline flow, gas field production, LNG export volume, and gas injection and production volume of gas storage facilities; h(W) = 0 represents the equality constraint of the working point; g(W) ≤ 0 represents the non-equality constraint of the working point.

[0117] Figure 2 A flowchart illustrating operation S103 in a natural gas supply chain production operation early warning method according to an embodiment of the present disclosure is shown schematically.

[0118] In one possible implementation, refer to Figure 2 As shown, the above operation S101 may further include:

[0119] S1011, construct an objective function containing the operating point based on the operating point in the feasible region calculation model;

[0120] The historical scheduling data includes daily scheduling data before the current day within the statistical period, and the pipeline network includes gas sources, gas storage facilities, LNG stations, user nodes, and pipeline sections.

[0121] S1012, Based on the objective function and using the production constraints as constraints, construct an optimization model;

[0122] Based on the above operations, in this embodiment of the disclosure, by constructing an objective function that includes working points (working points include node flow rate, node pressure, pipeline flow rate, gas field production, LNG export volume, and gas storage injection and production volume), the early warning model is transformed into an optimization model, and the solution of the early warning model is transformed into the determination of whether the optimization model has a feasible region.

[0123] In one possible implementation, the objective function can be either minimizing pipeline transportation costs or maximizing the gas supply to users.

[0124] Optionally, the objective function can be an objective function associated with process parameters of the natural gas supply chain production operation, such as flow rate.

[0125] Optionally, the optimization model can be a nonlinear objective function model, such as a mixed-integer nonlinear programming (MINLP) model.

[0126] Of course, in some other alternative embodiments, the optimization model described above can also be a linear objective function model, such as a mixed integer linear programming (MILP) model.

[0127] Specifically, by solving the optimization model, when a feasible solution exists in the feasible region of the natural gas supply chain, no early warning is needed at this time; when no feasible solution exists, an early warning is needed, thereby realizing the function of early warning for the production and operation of the natural gas supply chain.

[0128] In this embodiment of the disclosure, the production and operation data of the natural gas supply chain can be existing production data obtained through the SCADA system, including but not limited to the pressure of different pipe segment nodes of the natural gas pipeline network, the relative density of natural gas, the transmission temperature, the length and diameter of the transmission pipeline, the pipeline inventory, pipeline volume, pipeline pressure and flow rate, whether the gas storage facility is in the gas extraction or gas injection stage, the initial and current inventory of the gas storage facility, the maximum gas extraction capacity, the initial tank inventory, current tank inventory and external transmission volume of the LNG receiving terminal, the maximum external transmission capacity, and the production and maximum production capacity of the oil and gas field.

[0129] In this embodiment of the disclosure, the demand data for a preset period in the natural gas supply chain can be short-term demand data predicted by users using conventional market demand forecasting methods. Since different types of users have different flow characteristics in applications such as city gas distributors, CNG (compressed natural gas) stations, power plants, and industrial customers, appropriate forecasting models can be used to obtain short-term demand data for different types of users, including but not limited to the upper and lower limits of flow for each user at each distribution point. Specific implementation methods can be detailed in existing technologies, and may include, but are not limited to, time series methods, BP neural networks, support vector machines, and logistic regression models.

[0130] In one possible implementation, the constraints include equality constraints and inequality constraints;

[0131] The equality constraints include pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints. The inequality constraints include bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints.

[0132] The pipeline flow constraint means that the sum of the flow entering a node equals the sum of the flow leaving the node, expressed as:

[0133]

[0134] Where, x ijLet V represent the flow from node i to node j; (i,j) and (j,l) represent the pipeline between node i and node j and the pipeline between node j and node l, respectively; V is the set of nodes and E is the set of pipelines.

[0135] The hydraulic constraint of the pipeline is expressed as follows:

[0136]

[0137] Among them, P i and P j Let be the pressures at nodes i and j, respectively, in MPa; λ be the hydraulic friction coefficient; and Z be the compressibility factor of natural gas under pipeline transportation conditions, in Δ. * Here, is the relative density of natural gas, T is the gas transmission temperature, K and L are the calculated lengths of the gas transmission pipeline in km, D is the inner diameter of the gas transmission pipeline in m, and C0 is a constant whose value depends on the units of each parameter. All the above parameters are parameters of the pipeline between node i and node j.

[0138] The natural gas pipeline storage constraint is expressed as follows:

[0139]

[0140]

[0141] Among them, V s Let V0 be the pipe volume, and P be the pipe capacity. pj Here, T0 is the average pipeline pressure, T0 is the temperature under standard conditions, Z0 is the compressibility factor under standard conditions, P0 is the pressure under standard conditions, T is the gas transmission temperature, Z is the compressibility factor of natural gas under pipeline transmission conditions, and P... i and P j These are the pressures at nodes i and j, respectively. All of the above parameters are parameters of the pipeline between node i and node j.

[0142] When the gas storage facility is in the gas extraction phase, the inventory constraint of the gas storage facility is expressed as follows:

[0143]

[0144] When the gas storage facility is in the gas injection phase, the gas storage facility's inventory constraint is expressed as follows:

[0145]

[0146] Among them, V UGS,i Let i be the inventory of the i-th gas storage facility. Let be the initial inventory of the i-th gas storage facility. Let S be the gas injection / production volume of the i-th gas storage facility. u and D uThis refers to a collection of gas storage facilities that are in the gas extraction and gas injection stages, respectively.

[0147] The LNG receiving terminal tank storage constraint is expressed as follows:

[0148]

[0149] Among them, V LNG,i For the tank storage of the i-th LNG receiving terminal, Let the initial tank storage be for the i-th LNG receiving terminal. Let S be the output volume of the i-th LNG receiving terminal. l A collection of LNG receiving terminals;

[0150] Demand constraint means that the outgoing volume of each distribution point is equal to the sum of the traffic of all users at that distribution point, expressed as:

[0151]

[0152] Where i is the i-th distribution point, Qi,j is the j-th user at the i-th distribution point, and mi is the number of users at the i-th distribution point; the flow direction constraint of the bidirectional pipeline is expressed as follows:

[0153]

[0154] Among them, the flow direction constraint of bidirectional pipelines indicates that there can be at most one flow direction in the pipeline, E b y represents a set of bidirectional pipes. ij For the binary decision variables controlling the flow direction of the bidirectional pipeline;

[0155] Since the gas supply flow rate cannot exceed the gas supply capacity, the constraints on oil and gas field production capacity, gas storage facility gas extraction capacity, and LNG receiving terminal export capacity are as follows:

[0156]

[0157]

[0158]

[0159] Since the flow rate of any pipeline in the supply chain will not exceed the pipeline's transport capacity, and the flow rate cannot be negative, the transport capacity constraint is expressed as follows:

[0160]

[0161] in, Let i be the production of the i-th oil and gas field. Let be the gas extraction volume of the i-th gas storage facility. Let i be the output volume of the i-th LNG receiving terminal. Let i be the maximum production capacity of the i-th oil and gas field. Let i be the maximum gas extraction capacity of the i-th gas storage facility. S represents the maximum export capacity of the i-th LNG receiving terminal. f S is a collection of oil fields. u A collection of gas storage facilities in the gas extraction stage, S l C is a collection of LNG receiving terminals. ij The pipeline capacity between node i and node j;

[0162] Since the gas supply to each user must be between the lower and upper limits of each user's demand, the demand constraint is expressed as follows:

[0163]

[0164] in, Let i be the flow rate at the i-th distribution point. and These are the minimum and maximum demands for the i-th distribution point, respectively.

[0165] Since the gas storage facility is divided into two stages: gas injection and gas extraction, when the gas storage facility is in the gas injection stage, the gas injection volume must be less than the maximum gas injection capacity of the gas storage facility. The gas injection capacity constraint of the gas storage facility is expressed by the following expression:

[0166]

[0167] in, Let be the gas injection volume of the i-th gas storage facility. D represents the maximum gas injection capacity of the i-th gas storage facility. u This is a gas storage facility in the gas injection phase.

[0168] The node pressure constraint is expressed as follows:

[0169] P i,min ≤P i ≤P i,max ,

[0170] Among them, P i For the pressure of the i-th node, P i,min and P i,max Let be the lower limit and upper limit of the pressure at the i-th node, respectively, in MPa;

[0171] It should be noted that, in addition to satisfying the node pressure constraints shown in the above formula, the upstream and downstream nodes of the compressor station and the regulating valve also need to satisfy their upstream and downstream pressure constraints. The upstream and downstream pressure constraints of the compressor station are expressed as follows:

[0172]

[0173] in, These are the upstream pressure, downstream pressure, upstream pressure limit, and downstream pressure limit of the i-th compressor station, respectively.

[0174] The upstream and downstream pressure constraints of the regulating valve are expressed as follows:

[0175]

[0176]

[0177] in, These are the upstream pressure, downstream pressure, lower limit of downstream pressure, and upper limit of downstream pressure for the i-th regulating valve, respectively.

[0178] The pipe inventory constraint is expressed as follows:

[0179]

[0180] in, and These are the minimum and maximum safe pipe stock, respectively. All of these parameters are for the pipe between node i and node j.

[0181] The gas storage facility's inventory constraint is expressed as follows:

[0182]

[0183] in, and These are the minimum and maximum allowable storage capacities of the i-th gas storage facility, respectively.

[0184] The LNG receiving terminal tank storage constraint is expressed as follows:

[0185]

[0186] in, and These are the minimum and maximum allowable tank storage for the i-th LNG, respectively.

[0187] In practical applications, since the natural gas supply chain includes many early warning indicators that can be considered, the constraints involved can be adjusted according to business needs.

[0188] In one possible implementation, if no feasible solution exists, it can be determined that an early warning is needed for the production and operation of the natural gas supply chain. The early warning for the production and operation of the natural gas supply chain can be specifically implemented by, for example, returning error information, so that business personnel can receive risk warnings in a timely manner and prepare response strategies in advance, thereby effectively improving the ability to predict the operation risks of the natural gas supply chain.

[0189] A second exemplary embodiment of this disclosure provides a method for early warning of production operations in a natural gas supply chain. Figure 3 A detailed implementation flowchart of a natural gas supply chain production operation early warning method according to another embodiment of this disclosure is illustrated.

[0190] In this embodiment, the natural gas supply chain production and operation early warning method may include preprocessing, that is, mainly preparing the basic data required by the model, inputting the basic data of the natural gas supply chain, and establishing a natural gas supply chain early warning indicator system through operation S101. The early warning indicators may include natural gas pipeline pressure indicators, natural gas pipeline storage indicators, gas storage tank inventory indicators, and LNG receiving terminal tank inventory indicators.

[0191] Then, based on operation S102, a feasible region of the natural gas supply chain is constructed, and a feasible region calculation model, i.e., an early warning model, is established. An objective function containing the operating point is constructed, and an optimization model is constructed using the production constraints as constraints, wherein the production constraints include equality constraints and inequality constraints in the natural gas supply chain.

[0192] By running the optimization model, it is determined whether there is a feasible solution to the optimization model. If there is no feasible solution, an early warning is required to provide an early warning for the production and operation of the natural gas supply chain. If there is a feasible solution, no early warning is required.

[0193] Optionally, post-processing can be performed after the above operations to analyze and display the results.

[0194] Based on the above operations, the natural gas supply chain production and operation early warning method according to the embodiments of this disclosure proposes natural gas supply chain early warning indicators from multiple dimensions, targeting the technological and business characteristics of the natural gas supply chain. These indicators include natural gas pipeline pressure indicators, natural gas pipeline inventory indicators, gas storage facility inventory indicators, and LNG receiving terminal tank inventory indicators. Based on the established natural gas supply chain early warning indicators, a set of working points satisfying various production constraints of the natural gas supply chain is constructed, namely the feasible region of the natural gas supply chain. This establishes a calculation model for the feasible region of the natural gas supply chain. Furthermore, by constructing an objective function containing working points (working points include node flow, node pressure, pipeline flow, gas field production, LNG export volume, and gas storage facility injection and production volume), the early warning model is transformed into an optimization model. Solving the early warning model is then transformed into determining whether the optimization model has a feasible region. By establishing a natural gas supply chain early warning indicator system and a natural gas supply chain feasible region, and determining whether a feasible solution exists within the feasible region, the function of natural gas supply chain production and operation early warning is achieved. This enables early warning of various short-cycle uncertainties in the natural gas supply chain, overcoming the shortcomings of existing natural gas supply chain early warning models that can only perform long-term trend prediction and early warning.

[0195] A third exemplary embodiment of this disclosure provides a natural gas supply chain production operation early warning device 400, with reference to Figure 4 As shown, the device includes:

[0196] The model building module 401 is used to construct an optimization model based on the feasible region calculation model and the production constraints of the natural gas supply chain; wherein, the feasible region calculation model is obtained by constructing the feasible region calculation model of the natural gas supply chain based on the pre-established early warning indicators of the production and operation of the natural gas supply chain and the production constraints; wherein, the early warning indicators are used to reflect the production and operation status of the natural gas supply chain within a preset period.

[0197] The model solving module 402 is used to input the acquired natural gas supply chain production and operation data and the demand data for a preset period into the optimization model to determine whether there is a feasible solution;

[0198] The early warning module 403 is used to provide early warnings about the production and operation of the natural gas supply chain when no feasible solution exists.

[0199] Optionally, the model building module 401 is further configured to: based on the early warning indicators, take the set of working points that satisfy the production constraints as the feasible domain of the natural gas supply chain, and establish a feasible domain calculation model; wherein, the working points include node flow, node pressure, pipeline flow, gas field production, LNG export volume and gas storage injection and production volume.

[0200] The natural gas supply chain production and operation early warning device provided in this embodiment establishes early warning indicators reflecting the short-cycle production and operation status of the natural gas supply chain. Based on the early warning indicators and production constraints, it constructs a feasible region for the natural gas supply chain and determines whether a feasible solution exists within the feasible region to determine whether an early warning is needed for the natural gas supply chain in the short cycle. In the case where no feasible solution exists, an early warning for the production and operation of the natural gas supply chain is issued. This solves the technical problem that existing technologies can only reflect long-term trends and cannot be used for early warning of various short-cycle uncertain events in the natural gas supply chain. It overcomes the shortcomings of existing natural gas supply chain early warning models, which can only make long-term trend predictions and early warnings. Furthermore, by extrapolating the future short-cycle trends and predicting contradictions in the natural gas supply chain based on the current production and operation status, it further enhances the ability to predict the operational risks of the natural gas supply chain.

[0201] A fourth exemplary embodiment of this disclosure provides a method for establishing a production and operation optimization model for a natural gas supply chain, the method comprising:

[0202] S501: Based on pre-established early warning indicators and production constraints of the natural gas supply chain, construct a feasible domain calculation model for the natural gas supply chain; wherein, the early warning indicators reflect the short-cycle production and operation status of the natural gas supply chain;

[0203] S502: Construct an optimization model based on the feasible domain calculation model and the production constraints.

[0204] In this embodiment of the disclosure, the specific implementation of steps S501 and S502 can be referred to the detailed description of the relevant steps of the natural gas supply chain production operation early warning method in the first exemplary embodiment above, and will not be repeated here.

[0205] A fourth exemplary embodiment of this disclosure provides a natural gas supply chain production and operation optimization model establishment apparatus 600, with reference to... Figure 6 As shown, the device includes:

[0206] The first construction module 601 is used to construct a feasible domain calculation model of the natural gas supply chain based on pre-established early warning indicators and production constraints of the natural gas supply chain; wherein, the early warning indicators reflect the short-cycle production and operation status of the natural gas supply chain.

[0207] The second construction module 602 is used to construct an optimization model based on the feasible domain calculation model and the production constraints.

[0208] The sixth exemplary embodiment of this disclosure provides an electronic device. Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown.

[0209] Reference Figure 7 As shown, the electronic device 700 provided in this embodiment includes a processor 701, a communication interface 702, a memory 703, and a communication bus 704. The processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704. The memory 703 is used to store computer programs. When the processor 701 executes the program stored in the memory, it implements the natural gas supply chain production operation early warning method and / or the natural gas supply chain production operation optimization model establishment method as described above.

[0210] A seventh exemplary embodiment of this disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the natural gas supply chain production operation early warning method described above, and / or the natural gas supply chain production operation optimization model establishment method described above.

[0211] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the natural gas supply chain production operation early warning method according to embodiments of this disclosure.

[0212] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0213] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0214] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for early warning of production and operation in a natural gas supply chain, characterized in that, include: Obtaining an optimization model based on a feasible region calculation model and production constraints of the natural gas supply chain includes: constructing an objective function containing the operating points in the feasible region calculation model; the objective function includes minimizing pipeline transportation costs and maximizing the gas supply to users; and constructing an optimization model based on the objective function and the production constraints as constraints. The feasible region calculation model is obtained as follows: a feasible region calculation model of the natural gas supply chain is constructed based on pre-established early warning indicators for natural gas supply chain production and operation and the production constraints; the early warning indicators are natural gas supply chain early warning indicators proposed from multiple dimensions based on the process and business characteristics of the natural gas supply chain, used to reflect the production and operation status of the natural gas supply chain within a preset period; the feasible region calculation model is expressed as follows: Wherein, W represents the working point in the natural gas supply chain, and the working point includes node flow rate, node pressure, pipeline flow rate, gas field production, LNG export volume, and gas injection / production volume in gas storage facilities. For working point equality constraints; The constraints are non-equilibrium constraints at the operating point; the equilibrium constraints include pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints; the non-equilibrium constraints include bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints. The acquired natural gas supply chain production and operation data and the demand data for a preset period are input into the optimization model to determine whether there is a feasible solution. If not, issue an early warning for the production and operation of the natural gas supply chain.

2. The method according to claim 1, characterized in that, Based on pre-established early warning indicators for natural gas supply chain production and operation and the aforementioned production constraints, a feasible region calculation model for the natural gas supply chain is constructed, including: Based on the aforementioned early warning indicators, the set of working points that satisfy the aforementioned production constraints is taken as the feasible region of the natural gas supply chain, and a feasible region calculation model is established.

3. The method according to claim 1, characterized in that, The pipeline flow constraint is expressed as follows: ， Where, x ij This represents the flow from node i to node j; and Let V represent the pipe between node i and node j, and E represent the pipe between node j and node l, respectively; V is the set of nodes, and E is the set of pipes. The hydraulic constraint of the pipeline is expressed as follows: ， Among them, P i and P j Let be the pressures at nodes i and j, respectively, in MPa; λ be the hydraulic friction coefficient; and Z be the compressibility factor of natural gas under pipeline transportation conditions, in ∆. ∗ Where is the relative density of natural gas, T is the gas transmission temperature (K), L is the calculated length of the gas transmission pipeline (km), D is the inner diameter of the gas transmission pipeline (m), and C0 is a constant. The natural gas pipeline storage constraint is expressed as follows: ， ， Among them, V s For pipeline storage, The volume of the pipeline. The average pressure in the pipeline. Temperature under standard conditions. The compression factor is given by the value of the compression factor under standard conditions. Where P is the pressure under standard conditions, T is the gas transmission temperature, Z is the compressibility factor of natural gas under pipeline transportation conditions, and P is the pressure under standard conditions. i and P j The pressures at nodes i and j are respectively; When the gas storage facility is in the gas extraction phase, the inventory constraint of the gas storage facility is expressed as follows: ， When the gas storage facility is in the gas injection phase, the gas storage facility's inventory constraint is expressed as follows: ， in, Let i be the inventory of the i-th gas storage facility. Let be the initial inventory of the i-th gas storage facility. Let be the gas injection / production volume of the i-th gas storage facility. and This refers to a collection of gas storage facilities that are in the gas extraction and gas injection stages, respectively. The LNG receiving terminal tank storage constraint is expressed as follows: ， in, For the tank storage of the i-th LNG receiving terminal, Let the initial tank storage be for the i-th LNG receiving terminal. Let i be the output volume of the i-th LNG receiving terminal. A collection of LNG receiving terminals; The requirement constraint is expressed as follows: ， Where i is the i-th distribution point, Qi,j is the j-th user of the i-th distribution point, and mi is the number of users of the i-th distribution point; The flow direction constraint for a bidirectional pipeline is expressed as follows: ， Among them, E b Represents a set of bidirectional pipes, y ij For the binary decision variables controlling the flow direction of the bidirectional pipeline; The oil and gas field production capacity constraint is expressed as follows: ， The gas extraction capacity constraint of the gas storage facility is expressed as follows: ， The LNG receiving terminal's export capacity constraint is expressed as follows: ， The pipeline capacity constraint is expressed as follows: ， in, Let i be the production of the i-th oil and gas field. Let be the gas extraction volume of the i-th gas storage facility. Let i be the output volume of the i-th LNG receiving terminal. Let i be the maximum production capacity of the i-th oil and gas field. Let i be the maximum gas extraction capacity of the i-th gas storage facility. Let i be the maximum export capacity of the i-th LNG receiving terminal. A collection of oil fields. A collection of gas storage facilities in the gas extraction stage. C is a collection of LNG receiving terminals. ij The pipeline capacity between node i and node j; The requirement constraint is expressed as follows: ， in, Let i be the flow rate at the i-th distribution point. and These are the minimum and maximum demands for the i-th distribution point, respectively; The gas injection capacity constraint of the gas storage facility is expressed as follows: ， in, Let be the gas injection volume of the i-th gas storage facility. This represents the maximum gas injection capacity of the i-th gas storage facility; This is a gas storage facility in the gas injection phase. The node pressure constraint is expressed as follows: ， Among them, P i For the pressure of the i-th node, P i,min and P i,max Let be the lower limit and upper limit of the pressure at the i-th node, respectively, in MPa; The upstream and downstream pressure constraints of the compressor station are expressed as follows: ， in, , , , These are the upstream pressure, downstream pressure, upstream pressure limit, and downstream pressure limit of the i-th compressor station, respectively. The upstream and downstream pressure constraints of the regulating valve are expressed as follows: ， ， in, , , , These are the upstream pressure, downstream pressure, lower limit of downstream pressure, and upper limit of downstream pressure for the i-th regulating valve, respectively. The pipe inventory constraint is expressed as follows: ， in, and These represent the minimum and maximum safe pipe inventory levels, respectively. The gas storage facility's inventory constraint is expressed as follows: ， in, and These are the minimum and maximum allowable storage capacities of the i-th gas storage facility, respectively. The LNG receiving terminal tank storage constraint is expressed as follows: ， in, and These are the minimum and maximum allowable tank storage for the i-th LNG, respectively.

4. The method according to claim 1, characterized in that, The optimization model includes a mixed-integer nonlinear programming model or a mixed-integer linear programming model.

5. The method according to any one of claims 1-4, characterized in that, The early warning indicators include natural gas pipeline pressure indicators, natural gas pipeline storage indicators, gas storage tank inventory indicators, and LNG receiving terminal tank inventory indicators. The natural gas pipeline pressure index indicates that the pressure at each node of the natural gas supply chain is within the range of the maximum and minimum allowable pressure at any given time. The natural gas pipeline inventory index indicates that the natural gas pipeline inventory is between the maximum and minimum safe inventory levels under the corresponding operating conditions at any given time. The gas storage tank inventory index indicates that the gas storage tank inventory is within the range of the maximum and minimum inventory levels at any given time. The LNG receiving terminal tank inventory index indicates that the LNG receiving terminal tank inventory is within the range of the maximum and minimum tank inventory levels at any given time.

6. A natural gas supply chain production and operation early warning device, characterized in that, include: The model building module is used to construct an optimization model based on the feasible region calculation model and the production constraints of the natural gas supply chain. This includes: constructing an objective function containing the operating points in the feasible region calculation model; the objective function includes minimizing pipeline transportation costs and maximizing the gas supply to users; and constructing an optimization model based on the objective function and the production constraints. The feasible region calculation model is obtained by: constructing a feasible region calculation model of the natural gas supply chain based on pre-established early warning indicators for the production and operation of the natural gas supply chain and the production constraints; wherein the early warning indicators are natural gas supply chain early warning indicators proposed from multiple dimensions based on the process and business characteristics of the natural gas supply chain, used to reflect the production and operation status of the natural gas supply chain within a preset period; the feasible region calculation model is expressed as follows: Wherein, W represents the working point in the natural gas supply chain, and the working point includes node flow rate, node pressure, pipeline flow rate, gas field production, LNG export volume, and gas injection / production volume in gas storage facilities. For working point equality constraints; The constraints are non-equilibrium constraints at the operating point; the equilibrium constraints include pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints; the non-equilibrium constraints include bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints. The model solving module is used to input the acquired natural gas supply chain production and operation data and the demand data for a preset period into the optimization model to determine whether there is a feasible solution; The early warning module is used to provide early warnings about the production and operation of the natural gas supply chain when no feasible solution exists.

7. A method for establishing an optimization model for the production and operation of a natural gas supply chain, characterized in that, include: Based on pre-established early warning indicators and production constraints of the natural gas supply chain, a feasible region calculation model for the natural gas supply chain is constructed. The early warning indicators are proposed from multiple dimensions, taking into account the process and business characteristics of the natural gas supply chain, and are used to reflect the production and operation status of the natural gas supply chain within a preset period. The feasible region calculation model is expressed as follows: Wherein, W represents the working point in the natural gas supply chain, and the working point includes node flow rate, node pressure, pipeline flow rate, gas field production, LNG export volume, and gas injection / production volume in gas storage facilities. For working point equality constraints; The constraints are non-equilibrium constraints at the operating point; the equilibrium constraints include pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints; the non-equilibrium constraints include bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints. Based on the feasible region calculation model and the production constraints, an optimization model is constructed, including: constructing an objective function containing the operating points in the feasible region calculation model; the objective function includes minimizing pipeline transportation costs and maximizing the gas supply to users; and constructing an optimization model based on the objective function and using the production constraints as constraints.

8. A device for establishing an optimization model for the production and operation of a natural gas supply chain, characterized in that, include: The first construction module is used to construct a feasible region calculation model for the natural gas supply chain based on pre-established early warning indicators and production constraints of the natural gas supply chain. The early warning indicators are proposed from multiple dimensions, targeting the technological and operational characteristics of the natural gas supply chain, and are used to reflect the production and operation status of the natural gas supply chain within a preset period. The feasible region calculation model is represented as follows: Wherein, W represents the working point in the natural gas supply chain, and the working point includes node flow rate, node pressure, pipeline flow rate, gas field production, LNG export volume, and gas injection / production volume in gas storage facilities. For working point equality constraints; The constraints are non-equilibrium constraints at the operating point; the equilibrium constraints include pipeline flow constraints, pipeline hydraulic constraints, natural gas pipeline storage constraints, gas storage facility inventory constraints, LNG receiving terminal tank storage constraints, and demand constraints; the non-equilibrium constraints include bidirectional pipeline flow direction constraints, oil and gas field production capacity constraints, gas storage facility gas extraction capacity constraints, LNG receiving terminal external transmission capacity constraints, pipeline transmission capacity constraints, demand restriction constraints, gas storage facility gas injection capacity constraints, node pressure constraints, compressor station upstream and downstream pressure constraints, regulating valve upstream and downstream pressure constraints, pipeline inventory constraints, gas storage facility inventory constraints, and LNG receiving terminal tank storage constraints. The second construction module is used to construct an optimization model based on the feasible region calculation model and the production constraints, including: constructing an objective function containing the operating point in the feasible region calculation model; the objective function includes minimizing pipeline transportation costs and maximizing the gas supply to users; and constructing an optimization model based on the objective function and using the production constraints as constraints.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When the processor executes the program stored in the memory, it implements the natural gas supply chain production operation early warning method according to any one of claims 1-5, and / or the natural gas supply chain production operation optimization model establishment method according to claim 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the natural gas supply chain production operation early warning method according to any one of claims 1-5, and / or the natural gas supply chain production operation optimization model establishment method according to claim 7.

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