Methods for continuously ensuring gas supply to gas pipeline network terminals

Abstract

The present application provides a method for continuously ensuring gas supply to gas pipeline network terminals, the method comprising: dividing the gas pipeline network into slices to obtain the slice division results, the slice division results are used to indicate the corresponding slices and levels of the gas pipeline network, the level includes one or more slices; modeling each slice in the last level and predicting the real-time gas source data of the last slice in real time; based on the real-time gas source data of the last slice, calculating the real-time gas source data of each level layer by layer; based on the real-time gas source data of the level, using the pressure regulating station to perform real-time regulation so that the terminal can dynamically and stably obtain the gas supply from the gas pipeline network gas source. After dividing the pipeline network into slices, the method monitors and predicts the gas source data of the slices and levels in real time, thereby constructing a comprehensive, precise and reliable regulation strategy to meet the gas demand of the pipeline network terminals.

Description

Technical Field

[0001] The present application relates to the field of smart city management technology, and in particular to a method for continuously ensuring gas consumption at gas pipeline network terminals. Background Art

[0002] The acceleration of urbanization and the promotion of clean energy have made gas, as a clean and efficient energy, more and more widely used in residents' lives, industrial production and commercial fields. The rapid development of the gas industry has made gas dispatching an important link in ensuring the stability and safety of gas supply. With the continuous development of technologies such as the Internet of Things, big data, and cloud computing, the construction of smart gas has become an important direction for promoting the transformation and upgrading of the gas industry. The urban gas system is usually composed of multiple gas stations, pressure regulating stations, pipeline networks and gas users, and has the characteristics of wide distribution, complex structure, and variable operating parameters. These characteristics require gas dispatching to comprehensively consider multiple factors, such as gas source supply, pipeline network operation status, user gas demand, etc., in order to achieve overall optimization and efficient operation of the gas system.

[0003] Existing technologies mainly include gas source regulation, pipeline regulation, gas tank regulation, LNG regulation and load forecasting regulation. The existing regulation algorithms are all to adjust the pressure or flow of the gas source end for the entire large area. The impact of changes in the top-level gas source on the bottom-level users cannot be directly reflected, and the regulation effect is not obvious. It is difficult to meet the refined and efficient daily regulation requirements. Therefore, how to make more refined dynamic adjustments to the pipeline network pressure has become an urgent problem to be solved.

[0004] Patent CN117273331A discloses a flow regulation method for a long-distance heating system based on the evaluation of the variable flow capacity of the heating network, which is characterized in that it includes: constructing a dynamic model of the heating network of the long-distance heating system, setting the heat source side, the heating network head station side, the pressure isolation station side and the primary pipe network side as different nodes, and connecting them through the heating network pipeline; based on the constructed dynamic model of the heating network of the long-distance heating system, evaluating the variable flow capacity of the heating network of the long-distance heating system, analyzing the dynamic changes of pressure and flow at different nodes in the heating network pipeline under the condition of variable flow operation and regulation, establishing the law of change of hydraulic characteristic parameters and setting safety constraints of the heating network; constructing a heat load prediction model of the entire heating network on the primary pipe network side of the long-distance heating system, and calculating the total load demand of the long-distance heating system. curve; according to the total load demand curve of the long-distance heating system, the flow regulation strategy and corresponding temperature change parameters on the heat source side are calculated; at the same time, a mechanism simulation model is established for the first station side and the pressure isolation station side of the heating network, and online simulation calculations are performed based on the flow regulation parameters and temperature change parameters on the heat source side. With the highest energy-saving efficiency ratio as the objective function, the regulation strategy and valve opening regulation strategy between the multiple pump groups in the first station side and the pressure isolation station side of the heating network that meet the constraints of heat source flow and heating network safety are calculated; based on the evaluation information of the variable flow capacity of the heating network, the flexible flow adjustment range is calculated, and the flow regulation strategy on the heat source side and the regulation strategy between the multiple pump groups and the valve opening regulation strategy are flexibly adjusted, so that the long-distance heating system can operate in a safe and stable state. This method only involves the use of a prediction model to simulate and calculate the temperature. The result is not accurate enough, the calculation process is relatively complicated, and it does not have the ability of transient calculation and dynamic adjustment.

[0005] Based on this, the present application provides a method for continuously ensuring gas consumption at the terminals of the gas pipeline network to improve the existing technology. Summary of the invention

[0006] The purpose of this application is to provide a method for continuously ensuring gas consumption at the gas pipeline network terminals. After the pipeline network is divided into areas and levels, adjustments are made to each area separately, thereby constructing a comprehensive, precise and reliable dynamic adjustment strategy to meet the gas consumption needs of the user side.

[0007] The purpose of this application is achieved by the following technical solutions:

[0008] In a first aspect, the present application provides a method for continuously ensuring gas supply to a gas pipeline network terminal, and real-time monitoring and adjustment of the gas pipeline network terminal is performed so that the terminal can dynamically and stably obtain gas supply from a gas pipeline network gas source, and the method includes:

[0009] Performing slice division on the gas pipe network to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas;

[0010] Model each area in the last level and predict the real-time gas source data of the last level area in real time;

[0011] Based on the real-time gas source data of the last layer, the real-time gas source data of each layer is calculated layer by layer;

[0012] Based on the real-time gas source data at the above levels, real-time adjustments are made using the pressure regulating station so that each terminal can obtain supply from the gas pipeline network in a dynamic and stable manner.

[0013] The beneficial effects of this technical solution are: firstly, the pipe network structure is divided into layers, and the layer division results are obtained, which helps to divide the main network into multiple small areas to adjust the pipeline pressure more accurately; then, multiple small areas are divided into a hierarchical structure, which can participate in the pressure adjustment between layers, and can better understand the resource distribution of the pipe network, which helps to optimize resource allocation and utilization. By obtaining gas source data and pressure regulation parameters, data support can be provided for pipe network operation analysis and decision-making. First, the area is modeled and predicted based on the gas source data, and the real-time gas source data of the area can be obtained. According to the real-time origin data of the area, the hierarchical area data is calculated layer by layer. Compared with adjusting the gas source only from the top layer, this method divides the whole into blocks, so that the adjustment effect is better, and the underpressure adjustment of the user is more direct. By adjusting each area, the flow and pressure fluctuations of each area can be more accurately controlled, thereby improving the stability of the entire pipe network. After the pipe network is divided into areas and hierarchical divisions, each area is adjusted separately, so as to build a comprehensive, precise and reliable dynamic adjustment strategy to meet the gas demand on the user side.

[0014] In some optional implementations, the gas pipe network is sliced ​​to obtain a slice division result, and the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, and the level includes one or more slice areas, including:

[0015] Divide the gas pipeline network into multiple areas;

[0016] Adjacent areas are merged to obtain multiple levels, and the levels are connected by one or more pressure regulating stations.

[0017] The beneficial effect of the technical solution is that the establishment of a hierarchical structure helps to optimize the operating efficiency of the pipeline network, because the pressure regulating station, as a connection point, can effectively regulate and manage the pressure between different areas, reduce pressure fluctuations and energy losses. Through the connection of the pressure regulating station, the centralized management and control of the pipeline network pressure can be achieved, and the operating efficiency of the entire pipeline network can be improved. As a connection point between levels, the pressure regulating station can monitor and adjust the pressure between different areas in real time, reduce pressure fluctuations, and improve the operating stability of the pipeline network. The pressure of the pipeline network can be adjusted in real time according to the connection of the pressure regulating station to ensure the stability of the pipeline network operation. The establishment of a hierarchical structure helps to better understand the resource distribution of the pipeline network and optimize resource allocation and utilization. Users can adjust the pressure of the pipeline network according to the connection of the pressure regulating station to ensure the reasonable allocation of pipeline network resources. The pressure regulating station in the hierarchical structure can strengthen the safety monitoring and management of the pipeline network. The pressure of the pipeline network can be adjusted according to the connection of the pressure regulating station to prevent potential safety hazards, improve the safety of the pipeline network, and ensure the scalability and upgrade capabilities of the pipeline network. The connection between the hierarchical structure and the pressure regulating station can provide data support for pipeline network operation analysis and decision-making, and provide a basis for pipeline network optimization.

[0018] In some optional embodiments, the step of modeling each area in the last level and predicting the real-time gas source data of the last level area in real time includes:

[0019] Obtain gas source data of the terminal nodes of the pipeline network;

[0020] Based on the gas source data of the terminal nodes of the pipeline network, obtain the gas source data of the pressure regulating station;

[0021] Based on the historical data of each area in the last level, the gas source data of the terminal nodes of the pipeline network and the gas source data of the pressure regulating station, the area is modeled using a simulation algorithm;

[0022] Model the area and obtain real-time gas source data of the last layer area.

[0023] The beneficial effect of this technical solution is that by obtaining the gas source data of the terminal nodes and pressure regulating stations of the pipeline network, the operating status of the area can be more comprehensively understood. By using simulation algorithms to model the area, data can be effectively analyzed, valuable information can be extracted, and data utilization efficiency can be improved. The gas source data obtained by modeling can reflect the resource distribution and demand situation of the area. According to the gas source data corresponding to the area, the simulation algorithm is used to obtain the real-time gas source data of the last-layer area. Simulation calculations can replace or reduce physical experiments, thereby saving costs and time, and facilitating rapid iteration and improvement; by obtaining the gas source data of the terminal nodes of the pipeline network, the gas source data of the pressure regulating station, and the historical data of the area, the data information of each link can be analyzed, which is conducive to accurate modeling of the area and improving the credibility of the results.

[0024] In some optional implementations, the step of modeling the slice area and obtaining the real-time gas source data of the last slice area in real time includes:

[0025] Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data;

[0026] If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed;

[0027] If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data;

[0028] Based on the sum of the differences between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained.

[0029] The beneficial effects of this technical solution are: judging whether the real-time gas source data of each last-layer area is less than the minimum operating data respectively, if the real-time gas source data of all last-layer areas are not less than the minimum operating data, no operation is performed; if there are one or more users whose demand pressure is less than the minimum operating data (i.e., underpressure nodes), the sum of the difference between the minimum operating data and the real-time gas source data of the underpressure last-layer area is calculated, and the lower-level pressure regulation parameters can be inferred based on the sum of the difference between the minimum operating data and the real-time gas source data of the underpressure last-layer area, so as to better retrieve the underpressure nodes and adjust the pressure of the underpressure nodes, avoid redundant adjustments, save computing resources, and enable the gas source pressure of each user to reach a unified standard value.

[0030] In some optional implementations, the obtaining of the real-time gas source data of the last slice based on the sum of the difference between the lowest operating data and the real-time gas source data of the undervoltage node includes:

[0031] Determine whether the sum of the difference between the lowest operating data and the real-time gas source data of the last layer area is less than a preset threshold;

[0032] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is less than a preset threshold, recursively search the real-time gas source data of the undervoltage node and detect whether the gas source data meets the lifting suspension condition;

[0033] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is not less than the preset threshold, the underpressure node is obtained by using the source tracing algorithm;

[0034] Based on the preset boost interval, the real-time gas source data of the last layer area is obtained to increase the pressure of the under-pressure node.

[0035] The beneficial effect of this technical solution is that by judging whether the sum of the differences is less than the preset threshold, unnecessary pressure increase operations can be avoided and the operation efficiency of the pipeline network can be improved. According to the preset increase interval, the pipeline gas source of the under-pressure node can be pressure-increased to ensure that the pipeline network operates in the best state. Recursively searching the real-time gas source data of the under-pressure node and detecting whether the gas source pressure meets the conditions for terminating the increase can timely discover and deal with the under-pressure problem, reduce pressure fluctuations, and improve the stability of the pipeline network operation. The pipeline gas source of the under-pressure node can be obtained according to the traceability algorithm, and the pipeline gas source of the under-pressure node can be pressure-increased to ensure the stability of the pipeline network operation, which helps to optimize the allocation of pipeline network resources and ensure the rational use of pipeline network resources. According to the preset increase interval, the pipeline gas source of the under-pressure node can be pressure-increased to ensure the rational allocation of pipeline network resources. The preset increase interval can also judge the degree of pressure increase more accurately.

[0036] In some optional implementations, the real-time gas source data of each level is calculated layer by layer based on the real-time gas source data of the last layer, including:

[0037] Based on the real-time gas source data of the last layer area, the adjustment parameters of the last layer are obtained;

[0038] Based on the adjustment parameters of the last level, flow data of the pressure regulating station between the last level and the previous level are obtained;

[0039] The flow data of the pressure regulating station is input into the upper level as the demand pressure of the terminal node of the pipeline network, and the real-time gas source data of each level is obtained through traversal calculation.

[0040] The beneficial effect of the technical solution is that by obtaining the flow data of the pressure regulating station between the upper level and the lower level, the needs of users can be predicted and met more accurately, and the operation efficiency of the pipeline network can be improved. The pressure of the pipeline network can be adjusted in real time according to the upper pressure regulating parameters to ensure that the pipeline network operates in the best state. Traversing and calculating the upper pressure regulating parameters can timely discover and deal with problems in the pressure data, reduce pressure fluctuations, and improve the stability of the pipeline network operation. Obtaining the flow data of the pressure regulating station between the upper level and the lower level based on the lower pressure regulating parameters helps to optimize resource allocation and ensure the rational use of pipeline network resources. The pressure of the pipeline network can be adjusted according to the upper pressure regulating parameters to prevent potential safety hazards and improve the safety of the pipeline network. Obtaining the flow data of the pressure regulating station between the upper level and the lower level based on the lower pressure regulating parameters can provide data support for the expansion and upgrade of the pipeline network, ensuring the scalability and upgrade capabilities of the pipeline network. The flow calculated by the lower level area is assigned to the user-end flow of the upper level area. This layer-by-layer interaction makes the regulation effect of the entire pipeline network more direct and effective, and ultimately achieves a better regulation effect.

[0041] In a second aspect, the present application provides a device for continuously ensuring gas consumption at a gas network terminal, the device comprising a processor, and the processor is configured to implement the following steps:

[0042] A slice division module, used for performing slice division on the gas pipe network to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas;

[0043] The area data acquisition module is used to model each area in the last level and predict the real-time gas source data of the last level area in real time;

[0044] The layer data acquisition module is used to calculate the real-time gas source data of each layer layer by layer based on the real-time gas source data of the last layer area;

[0045] The real-time regulation module is used to perform real-time regulation based on the real-time gas source data of the said level by using the pressure regulating station so that each terminal can obtain supply from the gas source of the gas pipeline network dynamically and stably.

[0046] In some optional implementations, the processor is further configured to perform slice division on the gas pipe network in the following manner to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas:

[0047] Divide the gas pipeline network into multiple areas;

[0048] Adjacent areas are merged to obtain multiple levels, and the levels are connected by one or more pressure regulating stations.

[0049] In some optional embodiments, the processor is further configured to model each slice in the last layer and predict the real-time gas source data of the last slice in real time in the following manner:

[0050] Obtain gas source data of the terminal nodes of the pipeline network;

[0051] Based on the gas source data of the terminal nodes of the pipeline network, obtain the gas source data of the pressure regulating station;

[0052] Based on the historical data of each area in the last level, the gas source data of the terminal nodes of the pipeline network and the gas source data of the pressure regulating station, the area is modeled using a simulation algorithm;

[0053] Model the area and obtain real-time gas source data of the last layer area.

[0054] In some optional embodiments, the processor is further configured to model the slice area in the following manner to obtain real-time gas source data of the last slice area in real time, including:

[0055] Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data;

[0056] If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed;

[0057] If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data;

[0058] Based on the sum of the differences between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained.

[0059] In some optional embodiments, the processor is further configured to obtain the real-time gas source data of the last slice area based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node in the following manner, including:

[0060] Determine whether the sum of the difference between the lowest operating data and the real-time gas source data of the last layer area is less than a preset threshold;

[0061] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is less than a preset threshold, recursively search the real-time gas source data of the undervoltage node and detect whether the gas source data meets the lifting suspension condition;

[0062] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is not less than the preset threshold, the underpressure node is obtained by using the source tracing algorithm;

[0063] Based on the preset boost interval, the real-time gas source data of the last layer area is obtained to increase the pressure of the under-pressure node.

[0064] In some optional embodiments, the processor is further configured to calculate the real-time gas source data of each layer layer by layer based on the real-time gas source data of the last layer slice area in the following manner, including:

[0065] Based on the real-time gas source data of the last layer area, the adjustment parameters of the last layer are obtained;

[0066] Based on the adjustment parameters of the last level, flow data of the pressure regulating station between the last level and the previous level are obtained;

[0067] The flow data of the pressure regulating station is input into the upper level as the demand pressure of the terminal node of the pipeline network, and the real-time gas source data of each level is obtained through traversal calculation.

[0068] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program.

[0069] In a fourth aspect, the present application provides a system for continuously ensuring gas consumption at a gas pipeline network terminal, the system comprising:

[0070] The above electronic equipment.

[0071] In a fifth aspect, the present application provides a chip storing a computer program, wherein the computer program implements the steps of any of the above methods when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The present application is further described below in conjunction with the accompanying drawings and implementation methods.

[0073] Figure 1 A flow chart of a method for continuously ensuring gas supply to gas pipeline network terminals provided in an embodiment of the present application is shown.

[0074] Figure 2 A schematic diagram of a process for obtaining real-time gas source data of a last layer area provided in an embodiment of the present application is shown.

[0075] Figure 3 A schematic diagram of a hierarchical structure provided in an embodiment of the present application is shown.

[0076] Figure 4 A structural schematic diagram of a region 4 modeling provided in an embodiment of the present application is shown.

[0077] Figure 5 A structural schematic diagram of full-area modeling provided in an embodiment of the present application is shown.

[0078] Figure 6 A structural block diagram of a device for continuously ensuring gas supply to a gas network terminal provided by an embodiment of the present application is shown.

[0079] Figure 7 A structural framework diagram of an electronic device provided in an embodiment of the present application is shown.

[0080] Figure 8 A schematic diagram of the structure of a system for continuously ensuring gas supply to gas pipeline network terminals provided in an embodiment of the present application is shown.

[0081] Fig. 9 A schematic diagram of the structure of a program product provided in an embodiment of the present application is shown.

[0082] Fig.10 A schematic diagram of a boost interval provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0083] Below, the embodiments of the present application are further described in conjunction with the accompanying drawings and specific implementation methods. It should be noted that, under the premise of no conflict, the embodiments or technical features described below can be arbitrarily combined to form a new implementation method.

[0084] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can represent: a, b, c, a and b, a and c, b and c, a and b and c, where a, b and c can be single or multiple. It is worth noting that "at least one" can also be interpreted as "one or more items".

[0085] It should also be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any implementation or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other implementations or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0086] Method Embodiment

[0087] See also Figure 1 , Figure 1 A flow chart of a method for continuously ensuring gas supply to gas pipeline network terminals provided in an embodiment of the present application is shown.

[0088] The embodiment of the present application provides a method for continuously ensuring gas supply to a gas pipeline network terminal, and real-time monitoring and adjustment are performed on the gas pipeline network terminal so that the terminal can dynamically and stably obtain gas supply from a gas pipeline network gas source. The method includes:

[0089] Step S101: Divide the gas pipe network into slices to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas;

[0090] Step S102: Modeling each area in the last layer and predicting the real-time gas source data of the last layer area in real time;

[0091] Step S103: Based on the real-time gas source data of the last layer, calculate layer by layer to obtain the real-time gas source data of each layer;

[0092] Step S104: Based on the real-time gas source data of the said level, the pressure regulating station is used to perform real-time regulation so that each terminal can obtain supply from the gas source of the gas pipeline network dynamically and stably.

[0093] Therefore, the pipeline network structure is first divided into layers and the results of the layer division are obtained, which helps to split the pipeline network into multiple small areas so that the pipeline pressure can be adjusted more accurately. Then, the multiple small areas are divided into a hierarchical structure to achieve pressure adjustment between layers, which can better understand the resource distribution of the pipeline network and help optimize resource allocation and utilization.

[0094] By obtaining gas source data and pressure regulation parameters, data support can be provided for pipeline network operation analysis and decision-making. First, the area is modeled and predicted based on the gas source data, and the real-time gas source data of the area can be obtained. According to the real-time origin data of the area, the area data of the level is calculated layer by layer.

[0095] Compared with only adjusting the gas source from the top level, this method divides the whole into blocks, which makes the adjustment effect better and the underpressure adjustment for users more direct. By adjusting each area, the flow and pressure fluctuations of each area can be controlled more accurately, thereby improving the stability of the entire pipeline network.

[0096] After dividing the pipeline network into areas and levels, adjustments are made to each area separately to build a comprehensive, precise and reliable regulation strategy to meet the gas needs of users.

[0097] In the embodiment of the present application, the air source (Supervisory Control and Data Acquisition) system is an automation system for monitoring and controlling industrial processes. Air source data refers to data collected and transmitted by the air source system, which can be used to monitor the status of industrial processes, perform fault diagnosis, optimize production processes, and provide decision support.

[0098] In some optional embodiments, in order to make the overall pipe network calculation more accurate and precise and to facilitate subsequent iterative calculations, it is necessary to divide a large area into multiple small areas without pressure regulating stations according to the connection of the pressure regulating stations, and then perform bottom-up iterative calculations hierarchically for each area.

[0099] In some optional embodiments, one or more areas may be divided into a hierarchical structure, and the upper and lower areas are connected by one or more pressure regulating stations.

[0100] The present application does not limit the number of levels, which can be, for example, N levels from the last level upwards, where N is a positive integer, such as level 7, level 6, level 5, and level 4.

[0101] The present application does not limit the number of zones, which may be 1, 2, 3, 4, 5, 10, etc.

[0102] In some optional implementations, the gas pipe network is sliced ​​to obtain a slice division result, and the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, and the level includes one or more slice areas, including:

[0103] Divide the gas pipeline network into multiple areas;

[0104] Adjacent areas are merged to obtain multiple levels, and the levels are connected by one or more pressure regulating stations.

[0105] Therefore, the establishment of a hierarchical structure helps optimize the operating efficiency of the pipeline network, because the pressure regulating station, as a connection point, can effectively regulate and manage the pressure between different areas, reduce pressure fluctuations and energy losses. Through the connection of the pressure regulating station, the centralized management and control of the pipeline network pressure can be achieved, improving the operating efficiency of the entire pipeline network.

[0106] As a connection point between levels, the pressure regulating station can monitor and adjust the pressure between different areas in real time, reduce pressure fluctuations, and improve the operation stability of the pipeline network. According to the connection of the pressure regulating station, the pressure of the pipeline network can be adjusted in real time to ensure the stability of the pipeline network operation.

[0107] The establishment of a hierarchical structure helps to better understand the resource distribution of the pipeline network and optimize resource allocation and utilization. Users can adjust the pressure of the pipeline network according to the connection of the pressure regulating station to ensure the reasonable allocation of pipeline network resources. The pressure regulating station in the hierarchical structure can strengthen the safety monitoring and management of the pipeline network.

[0108] According to the connection of the pressure regulating station, the pressure of the pipeline network can be adjusted to prevent potential safety hazards, improve the safety of the pipeline network, and ensure the scalability and upgrade capabilities of the pipeline network. The connection between the hierarchical structure and the pressure regulating station can provide data support for pipeline network operation analysis and decision-making, and provide a basis for the optimization of the pipeline network.

[0109] The embodiment of the present application does not limit the number of pressure regulating stations, which may be 1, 2, 3, 4, 5, 10, etc.

[0110] In the embodiment of the present application, a pressure reducing station (PRS) is a facility in the natural gas transmission system that is used to reduce the pressure of a high-pressure natural gas pipeline to meet the pressure requirements of downstream users or distribution systems. The main function of the pressure regulating station is to ensure that the pressure of natural gas can be safely and stably reduced when it is transported from a high-pressure pipeline to a low-pressure pipeline or directly supplied to users.

[0111] See also Figure 2 , Figure 2 A schematic diagram of a process for obtaining real-time gas source data of a last layer area provided in an embodiment of the present application is shown.

[0112] In some optional embodiments, the step of modeling each area in the last level and predicting the real-time gas source data of the last level area in real time includes:

[0113] Step S201: Acquire gas source data of the terminal node of the pipeline network;

[0114] Step S202: based on the gas source data of the pipeline network terminal node, obtaining the gas source data of the pressure regulating station;

[0115] Step S203: Modeling the area using a simulation algorithm based on the historical data of each area in the last level, the gas source data of the pipeline network terminal node, and the gas source data of the pressure regulating station;

[0116] Step S204: Model the area and obtain real-time gas source data of the last layer area in real time.

[0117] Therefore, by obtaining the gas source data of the pipeline network terminal nodes and pressure regulating stations, we can have a more comprehensive understanding of the operation status of the area. Using simulation algorithms to model the area can effectively analyze data, extract valuable information, and improve data utilization efficiency.

[0118] The gas source data obtained by modeling can reflect the resource distribution and demand of the area. According to the gas source data corresponding to the area, the simulation algorithm is used to obtain the real-time gas source data of the last area. Simulation calculation can replace or reduce physical experiments, thereby saving costs and time, and facilitating rapid iteration and improvement;

[0119] By obtaining the gas source data of the pipeline terminal nodes, the gas source data of the pressure regulating station and the historical data of the area, the data information of each link can be analyzed, which is conducive to accurate modeling of the area and improves the credibility of the results.

[0120] In some optional implementations, after the entire area is divided into multiple areas and layered processing is performed, each area is modeled to obtain gas source data for each area. Taking a single area after the area is divided as an example, the gas transmission end of the area is a pressure regulating station, which is called a root node, and the gas end is a pipeline terminal, which is called a leaf node. In the present invention, the data of the leaf nodes can be obtained from the urban gas company. Secondly, for the data of the root node, the gas source data is modeled by using a simulation algorithm to obtain the historical data of the area, and all areas are modeled from bottom to top to obtain the gas source data of the entire area.

[0121] In some optional implementations, the step of modeling the slice area and acquiring the real-time gas source data of the last slice area in real time includes:

[0122] Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data;

[0123] If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed;

[0124] If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data;

[0125] Based on the sum of the differences between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained.

[0126] Therefore, firstly, according to the gas source data corresponding to the area, the simulation algorithm is used to obtain the real-time gas source data of the last area. The simulation calculation can replace or reduce the physical test, thus saving cost and time, and facilitating rapid iteration and improvement.

[0127] Determine whether the real-time gas source data of each last layer area is less than the minimum operating data. If the real-time gas source data of all last layer areas are not less than the minimum operating data, do not perform any operation.

[0128] If there are one or more users whose demand pressure is lower than the minimum operating data (i.e., underpressure nodes), the sum of the difference between the minimum operating data and the real-time gas source data of the last underpressure area is calculated. The lower-level pressure regulation parameters can be inferred based on the sum of the difference between the minimum operating data and the real-time gas source data of the last underpressure area, so that the underpressure nodes can be better retrieved and the pressure of the underpressure nodes can be adjusted, avoiding redundant adjustments.

[0129] This saves computing resources and enables each user's gas source pressure to reach a unified standard value.

[0130] In some optional embodiments, a simulated annealing algorithm with hierarchical adjustment and a tracing algorithm is used to adjust the under-pressure area. First, the boundary value data is obtained, and then a simulation calculation is performed. The calculated pressures on all user sides are compared with the lowest operating data lower limit of the actual pipeline network to see if there are any users with under-pressure. If no user is under-pressure, then the normal pipeline network operating conditions will be met at this moment; and when a user does not meet the lowest operating data lower limit, the sum of all pressure differences that do not meet the requirements will be calculated, and then the value will be compared with the set threshold.

[0131] When the sum of the pressure difference values ​​is less than the set threshold, the new solution is accepted, and then it is determined whether the search is sufficient; when the sum of the pressure difference values ​​is greater than or equal to the set threshold, it is determined whether the termination condition is reached. In the present invention, the termination condition is the last level of the lifting interval. During this period, the gas source will be lifted layer by layer, and finally, multiple groups of gas source boundary values ​​will be generated so that the user pressure calculated by simulation is not underpressure.

[0132] In some optional implementations, the obtaining of the real-time gas source data of the last slice based on the sum of the difference between the lowest operating data and the real-time gas source data of the undervoltage node includes:

[0133] Determine whether the sum of the difference between the lowest operating data and the real-time gas source data of the last layer area is less than a preset threshold;

[0134] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is less than a preset threshold, recursively search the real-time gas source data of the undervoltage node and detect whether the gas source data meets the lifting suspension condition;

[0135] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is not less than the preset threshold, the underpressure node is obtained by using the source tracing algorithm;

[0136] Based on the preset boost interval, the real-time gas source data of the last layer area is obtained to increase the pressure of the under-pressure node.

[0137] Therefore, by judging whether the sum of the differences is less than the preset threshold, unnecessary pressure increase operations can be avoided and the operation efficiency of the pipeline network can be improved. The pressure of the pipeline gas source at the under-pressure node can be increased according to the preset increase interval to ensure that the pipeline network operates in the best state.

[0138] Recursively search the real-time gas source data of the under-pressure node and detect whether the gas source pressure meets the conditions for stopping the increase. This can timely discover and handle the under-pressure problem, reduce pressure fluctuations, and improve the stability of the pipeline network operation. The pipeline gas source of the under-pressure node can be obtained according to the traceability algorithm, and the pressure of the pipeline gas source of the under-pressure node can be increased to ensure the stability of the pipeline network operation, which helps to optimize the allocation of pipeline network resources and ensure the rational use of pipeline network resources.

[0139] The preset boost interval can be used to boost the pressure of the pipeline gas source at the under-pressure node to ensure the reasonable allocation of pipeline network resources. The preset boost interval can also more accurately judge the degree of pressure increase.

[0140] The embodiment of the present application does not limit the preset threshold value, and the preset threshold value refers to an acceptable pressure difference.

[0141] In the embodiment of the present application, the lifting termination condition refers to a pressure lifting value at which lifting can be terminated, that is, a pressure value that is not under-pressure.

[0142] In some optional implementations, the real-time gas source data of each level is calculated layer by layer based on the real-time gas source data of the last layer, including:

[0143] Based on the real-time gas source data of the last layer area, the adjustment parameters of the last layer are obtained;

[0144] Based on the adjustment parameters of the last level, flow data of the pressure regulating station between the last level and the previous level are obtained;

[0145] The flow data of the pressure regulating station is input into the upper level as the demand pressure of the terminal node of the pipeline network, and the real-time gas source data of each level is obtained through traversal calculation.

[0146] Therefore, by obtaining the flow data of the pressure regulating station between the upper and lower levels, the needs of users can be predicted and met more accurately, and the operation efficiency of the pipeline network can be improved. The pressure of the pipeline network can be adjusted in real time according to the upper pressure regulating parameters to ensure that the pipeline network operates in the best state.

[0147] Traversing and calculating the upper-level pressure regulation parameters can timely discover and deal with problems in pressure data, reduce pressure fluctuations, and improve the stability of pipeline network operation. Obtaining flow data of pressure regulation stations between the upper and lower levels based on the lower-level pressure regulation parameters helps optimize resource allocation and ensure the rational use of pipeline network resources.

[0148] The pressure of the pipeline network can be adjusted according to the upper pressure regulation parameters to prevent potential safety hazards and improve the safety of the pipeline network. The flow data of the pressure regulating station between the upper and lower levels can be obtained based on the lower pressure regulation parameters to provide data support for the expansion and upgrade of the pipeline network, ensuring the scalability and upgrade capabilities of the pipeline network.

[0149] The flow calculated by the lower-level area is assigned to the user-end flow of the upper-level area. This layer-by-layer interaction makes the regulation effect of the entire pipeline network more direct and effective, and ultimately achieves a better regulation effect.

[0150] In a specific embodiment: See Figure 3 , Figure 3A schematic diagram of a hierarchical structure provided by an embodiment of the present application is shown. Figure 4 , Figure 4 FIG. 4 shows a schematic diagram of a structural modeling of a region 4 provided in an embodiment of the present application. Figure 5 , Figure 5 FIG. 1 shows a schematic diagram of a full-area modeling structure provided by an embodiment of the present application. Fig.10 , Fig.10 A schematic diagram of a boost interval provided in an embodiment of the present application is shown.

[0151] In order to make the overall pipe network calculation more accurate and precise and facilitate the subsequent Newton iteration calculation, it is necessary to divide a large area into multiple small areas without pressure regulating stations according to the connection of the pressure regulating station, and then perform bottom-up Newton iteration calculations on each area in a hierarchical manner.

[0152] like Figure 3 As shown in the figure, the whole large area is divided into several small areas according to the pressure regulating stations. Figure 3 In the figure, the lower area of ​​area 1 is area 2 and area 3, the lower area of ​​area 2 is area 4 and area 5, and the lower area of ​​area 3 is area 6 and area 7. There is another LNG gas filling station connected to area 2. On the contrary, the upper area of ​​area 4 and area 5 is area 2, the upper area of ​​area 6 and area 7 is area 3, and the upper area of ​​area 2 and area 3 is area 1.

[0153] In order to make the overall pipe network calculation more standardized and reasonable, it is usually necessary to calculate multiple small pieces and then calculate them in different levels. Figure 3 As shown, the upper and lower layers are connected by one or more pressure regulating stations.

[0154] After the entire area is divided into multiple areas and layered, each area is modeled to obtain the gas source data of each area. Figure 4 As shown, the gas transmission end of the area is the pressure regulating station, which is called the root node, and the gas consumption end is the user, which is called the leaf node.

[0155] In the present invention, the data of leaf nodes can be obtained from urban gas enterprises. Secondly, for the data of root nodes, the historical data of the area is modeled using a simulation algorithm to obtain gas source data. Figure 4 , Figure 5 In the example, historical modeling is performed on area 4, and then the data of pressure regulating stations a and b are obtained through the data of users 1, 2, and 3. Then all areas are modeled from bottom to top to obtain the gas source data of the entire area.

[0156] After modeling each area, the future gas source data of each small area can be obtained. Next, in order to better meet the minimum user pressure limit on the user side, the assigned data can be adjusted in a directional manner. In the present invention, a simulated annealing algorithm with hierarchical adjustment and a traceability algorithm is used to adjust the underpressure area. The overall flow chart of a single area is as follows: Figure 5 shown.

[0157] First, the boundary value data is obtained, and then a simulation calculation is performed to compare the calculated pressures on all user sides with the lower limit of the lowest operating data of the actual pipeline network to see if there are any users with under-pressure. If no user is under-pressure, then the normal pipeline network operating conditions will be met at that moment; and when a user does not meet the lower limit of the lowest operating data, the sum of all pressure differences that do not meet the requirements will be calculated, and then the value will be compared with the set threshold.

[0158] When the sum of the pressure differences is less than the set threshold, the new solution is accepted, and then it is determined whether the search is sufficient; when the sum of the pressure differences is greater than or equal to the set threshold, it is determined whether the termination condition is reached. In the present invention, the termination condition is the last level of the lifting interval, that is, the interval [50%, 60%). During this period, the gas source will be lifted layer by layer. Fig.10 As shown, gas_1*(1+r1%), gas_2*(1+r2%), gas_3*(1+r3%), where r1, r2, r3 are the random boost values ​​of gas sources 1, 2, and 3 in a certain boost interval. Finally, multiple sets of gas source boundary values ​​will be generated so that the user pressure calculated by simulation is not under-pressure.

[0159] like Figure 3 As shown, after the adjustment of areas 4, 5, 6, and 7 in the third layer is completed, the areas 2 and 3 in the second layer are adjusted. Generally speaking, after the entire large area is divided into multiple small areas through the pressure regulating station, the lower area corresponding to the pressure regulating station will use it as a gas source, and the upper area corresponding to the pressure regulating station will treat it as a user. In the gas source assignment, the user end is generally assigned to flow data, and the gas source end is assigned to pressure or flow data. Therefore, each time the calculation of the lower area is completed, the flow data calculated by the pressure regulating station assigned to pressure will be used as the user end of the upper area and assigned to flow data.

[0160] Device Embodiment

[0161] See also Figure 6 , Figure 6 A structural block diagram of a device for continuously ensuring gas supply to a gas network terminal provided by an embodiment of the present application is shown.

[0162] The embodiment of the present application also provides a device for continuously ensuring gas supply to gas pipe network terminals. The specific implementation method thereof is consistent with the implementation method and the technical effects achieved in the above method embodiment, and some contents will not be repeated here.

[0163] The present application provides a device for continuously ensuring gas consumption at a gas network terminal, the device comprising a processor, and the processor is configured to implement the following steps:

[0164] The slice division module 101 is used to divide the gas pipe network into slices to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas;

[0165] The area data acquisition module 102 is used to model each area in the last level and predict the real-time gas source data of the last level area in real time;

[0166] The layer data acquisition module 103 is used to calculate the real-time gas source data of each layer layer by layer based on the real-time gas source data of the last layer area;

[0167] The real-time adjustment module 104 is used to perform real-time adjustment based on the real-time gas source data of the hierarchy using the pressure regulating station so that each terminal can dynamically and stably obtain gas supply from the gas pipeline network.

[0168] In some optional implementations, the processor is further configured to perform slice division on the gas pipe network in the following manner to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas:

[0169] Divide the gas pipeline network into multiple areas;

[0170] Adjacent areas are merged to obtain multiple levels, and the levels are connected by one or more pressure regulating stations.

[0171] In some optional embodiments, the processor is further configured to model each slice in the last layer and predict the real-time gas source data of the last slice in real time in the following manner:

[0172] Obtain gas source data of the terminal nodes of the pipeline network;

[0173] Based on the gas source data of the terminal nodes of the pipeline network, obtain the gas source data of the pressure regulating station;

[0174] Based on the historical data of each area in the last level, the gas source data of the terminal nodes of the pipeline network and the gas source data of the pressure regulating station, the area is modeled using a simulation algorithm;

[0175] Model the area and obtain the real-time gas source data of the last layer area in real time.

[0176] In some optional embodiments, the processor is further configured to model the slice area in the following manner to obtain real-time gas source data of the last slice area in real time, including:

[0177] Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data;

[0178] If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed;

[0179] If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data;

[0180] Based on the sum of the differences between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained.

[0181] In some optional embodiments, the processor is further configured to obtain the real-time gas source data of the last slice area based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node in the following manner, including:

[0182] Determine whether the sum of the difference between the lowest operating data and the real-time gas source data of the last layer area is less than a preset threshold;

[0183] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is less than a preset threshold, recursively search the real-time gas source data of the undervoltage node and detect whether the gas source data meets the lifting suspension condition;

[0184] If the sum of the differences between the lowest operating data and the real-time gas source data of the last layer is not less than the preset threshold, the underpressure node is obtained by using the source tracing algorithm;

[0185] Based on the preset boost interval, the real-time gas source data of the last layer area is obtained to increase the pressure of the under-pressure node.

[0186] In some optional embodiments, the processor is further configured to calculate the real-time gas source data of each layer layer by layer based on the real-time gas source data of the last layer slice area in the following manner, including:

[0187] Based on the real-time gas source data of the last layer area, the adjustment parameters of the last layer are obtained;

[0188] Based on the adjustment parameters of the last level, flow data of the pressure regulating station between the last level and the previous level are obtained;

[0189] The flow data of the pressure regulating station is input into the upper level as the demand pressure of the terminal node of the pipeline network, and the real-time gas source data of each level is obtained through traversal calculation.

[0190] Device Embodiment

[0191] An embodiment of the present application also provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program. The specific implementation method is consistent with the implementation method and the technical effect achieved in the above method embodiment, and some contents will not be repeated here.

[0192] See also Figure 7 , Figure 7 A structural framework diagram of an electronic device provided in an embodiment of the present application is shown.

[0193] The electronic device includes at least one memory 210, at least one processor 220, and a bus 230 connecting different platform systems.

[0194] The memory 210 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 211 and / or a cache memory 212 , and may further include a read-only memory (ROM) 213 .

[0195] The memory 210 also stores a computer program, which can be executed by the processor 220, so that the processor 220 implements the steps of any of the above methods.

[0196] The memory 210 may also include a utility 214 having at least one program module 215, such program module 215 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0197] Accordingly, the processor 220 may execute the above-mentioned computer program and may execute the utility 214 .

[0198] The processor 220 may be implemented by one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic components.

[0199] Bus 230 may be a local bus representing one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or any of a variety of bus architectures.

[0200] The electronic device may also communicate with one or more external devices 240 such as keyboards, pointing devices, Bluetooth devices, etc., and may also communicate with one or more devices that can interact with the electronic device, and / or communicate with any device (such as a router, a modem, etc.) that enables the electronic device to communicate with one or more other computing devices. Such communication may be performed through the input and output interface 250. In addition, the electronic device may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 260. The network adapter 260 may communicate with other modules of the electronic device through the bus 230. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0201] System Example

[0202] See also Figure 8 , Figure 8 A schematic diagram of the structure of a system for continuously ensuring gas supply to gas pipeline network terminals provided in an embodiment of the present application is shown.

[0203] The embodiment of the present application also provides a system for continuously ensuring gas consumption at a gas pipeline network terminal, the system comprising:

[0204] The above electronic equipment.

[0205] Medium Embodiment

[0206] An embodiment of the present application also provides a chip, which stores a computer program. When the computer program is executed by a processor, the steps of any of the above methods are implemented. The specific implementation method is consistent with the implementation method and the technical effect achieved in the above method embodiment, and some contents will not be repeated here.

[0207] See also Fig. 9 , Fig. 9 A schematic diagram of the structure of a program product provided in an embodiment of the present application is shown.

[0208] The program product is used to implement any of the above methods. The program product can use a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited to this. In the embodiment of the present application, the readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The program product can use any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0209] The chip may include a data signal propagated in the baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium may also be any readable medium, which may send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or used in combination with it. The program code contained on the readable storage medium may be transmitted with any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above. The program code for performing the operation of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as C language, Python language, or similar programming languages. The program code may be executed entirely on a user computing device, partially on a user device, as an independent software package, partially on a user computing device, partially on a remote computing device, or entirely on a remote computing device or server. Where a remote computing device is involved, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0210] This application is explained from the perspectives of purpose of use, effectiveness, progress and novelty, and has met the functional enhancement and usage requirements emphasized by the Patent Law. The above description and drawings of this application are only the preferred embodiments of this application, and are not intended to limit this application. Therefore, all structures, devices, features, etc. that are similar or identical to this application, that is, all equivalent replacements or modifications made in accordance with the scope of the patent application of this application, should fall within the scope of protection of the patent application of this application.

Claims

1. A method for continuously ensuring gas consumption at gas pipeline network terminals, characterized in that: Real-time monitoring and adjustment of the gas network terminal is performed so that the terminal can dynamically and stably obtain gas supply from the gas network source. The method includes: Performing slice division on the gas pipe network to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas; Model each area in the last level and predict the real-time gas source data of the last level area in real time; The step of modeling each area in the last level and predicting the real-time gas source data of the last level area in real time includes: Obtain gas source data of the terminal nodes of the pipeline network; Based on the gas source data of the terminal nodes of the pipeline network, obtain the gas source data of the pressure regulating station; Based on the historical data of each area in the last level, the gas source data of the terminal nodes of the pipeline network and the gas source data of the pressure regulating station, the area is modeled using a simulation algorithm; Model the area and obtain the real-time gas source data of the last layer area in real time; The step of modeling the area and obtaining the real-time gas source data of the last layer area in real time includes: Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data; If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed; If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data; Based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained; The method of obtaining the real-time gas source data of the last layer area based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node includes: Determine whether the sum of the difference between the minimum operating data and the real-time gas source data of the underpressure node is less than a preset threshold; If the sum of the difference between the lowest operating data and the real-time gas source data of the under-pressure node is less than a preset threshold, recursively search the real-time gas source data of the under-pressure node and detect whether the gas source data meets the suspension promotion condition; If the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is not less than the preset threshold, the underpressure node is obtained by using the tracing algorithm; Based on the preset boost interval, obtain the real-time gas source data of the last layer to boost the pressure of the under-pressure node; Based on the real-time gas source data of the last layer, the real-time gas source data of each layer is calculated layer by layer; Based on the real-time gas source data of the above levels, the pressure regulating station is used to make real-time adjustments so that the terminals can obtain gas supply from the gas pipeline network dynamically and stably; As a connection point between levels, the pressure regulating station monitors and adjusts the pressure between different areas in real time, reduces pressure fluctuations, improves the operating stability of the pipeline network, and adjusts the pressure of the pipeline network in real time to ensure the stability of the pipeline network operation.

2. The method for continuously ensuring gas consumption at the gas pipeline network terminal according to claim 1, characterized in that: The gas pipe network is divided into slices to obtain a slice division result, and the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, and the level includes one or more slice areas, including: Divide the gas pipeline network into multiple areas; Adjacent areas are merged to obtain multiple levels, and the levels are connected by one or more pressure regulating stations.

3. The method for continuously ensuring gas consumption at the gas pipeline network terminal according to claim 2 is characterized in that: The real-time gas source data of each layer is calculated layer by layer based on the real-time gas source data of the last layer, including: Based on the real-time gas source data of the last layer area, the adjustment parameters of the last layer are obtained; Based on the adjustment parameters of the last level, flow data of the pressure regulating station between the last level and the previous level are obtained; The flow data of the pressure regulating station is input into the upper level as the demand pressure of the terminal node of the pipeline network, and the real-time gas source data of each level is obtained through traversal calculation.

4. A device for continuously ensuring gas consumption at the terminal of a gas pipeline network, characterized in that: The device comprises: A slice division module, used for performing slice division on the gas pipe network to obtain a slice division result, wherein the slice division result is used to indicate a slice area and a level corresponding to the gas pipe network, wherein the level includes one or more slice areas; The area data acquisition module is used to model each area in the last level and predict the real-time gas source data of the last level area in real time; The step of modeling each area in the last level and predicting the real-time gas source data of the last level area in real time includes: Obtain gas source data of the terminal nodes of the pipeline network; Based on the gas source data of the terminal nodes of the pipeline network, obtain the gas source data of the pressure regulating station; Based on the historical data of each area in the last level, the gas source data of the terminal nodes of the pipeline network and the gas source data of the pressure regulating station, the area is modeled using a simulation algorithm; Model the area and obtain the real-time gas source data of the last layer area in real time; The step of modeling the area and obtaining the real-time gas source data of the last layer area in real time includes: Determine whether the gas source data of the terminal node of the pipeline network is less than the minimum operating data; If the gas source data of all pipeline network terminal nodes are not less than the minimum operating data, no operation will be performed; If there are one or more underpressure nodes, the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is obtained, wherein the underpressure node refers to the pipeline network terminal node whose real-time gas source data is less than the lowest operating data; Based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node, the real-time gas source data of the last layer area is obtained; The method of obtaining the real-time gas source data of the last layer area based on the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node includes: Determine whether the sum of the difference between the minimum operating data and the real-time gas source data of the underpressure node is less than a preset threshold; If the sum of the difference between the lowest operating data and the real-time gas source data of the under-pressure node is less than a preset threshold, recursively search the real-time gas source data of the under-pressure node and detect whether the gas source data meets the suspension promotion condition; If the sum of the difference between the lowest operating data and the real-time gas source data of the underpressure node is not less than the preset threshold, the underpressure node is obtained by using the tracing algorithm; Based on the preset boost interval, obtain the real-time gas source data of the last layer to boost the pressure of the under-pressure node; The layer data acquisition module is used to calculate the real-time gas source data of each layer layer by layer based on the real-time gas source data of the last layer area; A real-time adjustment module, which is used to perform real-time adjustment using a pressure regulating station based on the real-time gas source data of the said level so that the terminal can obtain supply from the gas source of the gas pipeline network dynamically and stably; As a connection point between levels, the pressure regulating station monitors and adjusts the pressure between different areas in real time, reduces pressure fluctuations, improves the operating stability of the pipeline network, and adjusts the pressure of the pipeline network in real time to ensure the stability of the pipeline network operation.

5. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the steps of implementing the method according to any one of claims 1 to 3.

6. A system for continuously ensuring gas consumption at gas pipeline network terminals, characterized in that: The system for continuously ensuring gas consumption at the gas pipeline network terminal includes: The electronic device as claimed in claim 5.

7. A chip, characterized in that: The chip stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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