Oil and gas intelligent pipe network digital conversion method and device and storage medium

Abstract

The invention provides an oil and gas intelligent pipe network digital conversion method and device and a storage medium, and relates to the technical field of digital information transmission. The method comprises the following steps: dividing a pipe network into a physical level, an energy level and an information level, constructing a digital model group, obtaining multiple pieces of equipment facility data from the physical level, converting the equipment facility data into corresponding energy flows through a physical-to-energy flow model, converting the energy flows into information flows of the information level through an energy-to-information flow model, and establishing a digital model group; and performing optimization decision analysis on the information flow through the information flow model, outputting a control instruction, converting the control instruction into a physical control quantity through the information flow physical control quantity model, and feeding back the physical control quantity to equipment corresponding to the physical hierarchy. According to the invention, the physical entity and the information space of the oil and gas intelligent pipe network and the energy space for implementing the full-service process of the intelligent pipe network are interacted and controlled in a digital information manner by using the digital model group, so that the informatization management capability of the oil and gas intelligent pipe network is improved.

Description

Technical Field

[0001] The present invention mainly relates to the field of digital information transmission technology, and specifically to a digital conversion method, device and storage medium for an oil and gas smart pipeline network. Background Art

[0002] In recent years, driven by new theories and technologies such as mobile Internet, big data, supercomputing, sensor networks, brain science, and strong demands for economic and social development, concepts such as smart manufacturing, smart grid, smart nuclear power, and smart transportation have emerged one after another. Intelligence is the development trend and inevitable choice of the future industrial field, and the smart oil and gas pipeline network came into being under such a background.

[0003] The current smart oil and gas pipeline network has made certain progress in pipeline safety control and optimized management, but there has been no systematic research and construction of the smart pipeline network, and the physical entity and information space of the smart pipeline network have not been organically integrated with the energy space for implementing the entire business process of the smart pipeline network. The smart oil and gas pipeline network currently does not have strong information management capabilities. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method, device and storage medium for digital conversion of oil and gas smart pipeline networks in view of the deficiencies in the prior art.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: A method for digital conversion of oil and gas smart pipeline network, comprising the following steps: Based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, a physical energy information conversion model group is constructed, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; In one control cycle, a plurality of equipment and facility data are obtained from the physical level, and each of the equipment and facility data is converted into a corresponding energy flow through the physical to energy flow model, and an energy flow matrix of the energy level is formed through all the energy flows; Converting the energy flow matrix into the information flow of the information level through the energy flow information flow model; Performing optimization decision analysis on the information flow through the information flow model and outputting control instructions; The control instruction is converted into a physical control quantity through the information flow physical control quantity model, and the physical control quantity is fed back to the device corresponding to the physical level.

[0006] Another technical solution of the present invention to solve the above technical problem is as follows: A digital conversion device for oil and gas smart pipe network, comprising: A model group construction module is used to construct a physical energy information conversion model group based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; An energy flow conversion module is used to obtain multiple equipment and facility data from the physical level within a control cycle, convert each equipment and facility data into a corresponding energy flow through the physical to energy flow model, and form an energy flow matrix of the energy level through all energy flows; An energy transfer information flow module, used for converting the energy flow matrix into the information flow of the information level through the energy transfer information flow model; An information flow optimization module, used to perform optimization decision analysis on the information flow through the information flow model and output control instructions; A physical control quantity conversion module is used to convert the control instruction into a physical control quantity through the information flow physical control quantity model, and feed back the physical control quantity to the device corresponding to the physical level.

[0007] Another technical solution of the present invention to solve the above-mentioned technical problem is as follows: a digital conversion device for an oil and gas smart pipeline network, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the digital conversion method for an oil and gas smart pipeline network as described above is implemented.

[0008] Another technical solution of the present invention to solve the above-mentioned technical problem is as follows: a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the digital conversion method of the oil and gas smart pipeline network as described above is implemented.

[0009] The beneficial effect of the present invention is that a physical energy information conversion model group is constructed, and the physical energy information conversion model group can be used to interact and control the physical entity and information space of the oil and gas smart pipeline network with the energy space that implements the entire business process of the smart pipeline network in the form of digital information, thereby achieving organic integration and improving the information management capabilities of the oil and gas smart pipeline network. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of a digital conversion method for an oil and gas smart pipeline network provided by an embodiment of the present invention; Figure 2 A flow chart of a digital conversion method for an oil and gas smart pipeline network provided by another embodiment of the present invention; Figure 3A schematic diagram of information transmission in physical space, energy space and information space provided by an embodiment of the present invention; Figure 4 A block diagram of the functional modules of the oil and gas smart pipeline digital conversion device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0011] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0012] The purpose of this invention is to provide an "energy-information-physics" digital conversion method (ECPS: Energy-Cyber-Physical Systems) for oil and gas smart pipe networks, establish a unified "energy-information-physics" model, organically integrate the physical entity and information space of the oil and gas smart pipe network with the energy space that implements the entire business process of the smart pipe network, and provide a basic theoretical method for the construction and operation of the smart pipe network and the integration of the oil and gas pipe network and the energy Internet. The following is a detailed introduction.

[0013] like Figure 1 As shown, an embodiment of the present invention provides a method for digital conversion of an oil and gas smart pipeline network, comprising the following steps: Based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, a physical energy information conversion model group is constructed, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; In one control cycle, a plurality of equipment and facility data are obtained from the physical level, and each of the equipment and facility data is converted into a corresponding energy flow through the physical to energy flow model, and an energy flow matrix of the energy level is formed through all the energy flows; Converting the energy flow matrix into the information flow of the information level through the energy flow information flow model; Performing optimization decision analysis on the information flow through the information flow model and outputting control instructions; The control instruction is converted into a physical control quantity through the information flow physical control quantity model, and the physical control quantity is fed back to the device corresponding to the physical level.

[0014] In the above embodiment, a physical energy information conversion model group is constructed, which can be understood as an "energy-information-physics" digital model. The physical energy information conversion model group can be used to interact and control the physical entity and information space of the oil and gas smart pipeline network with the energy space that implements the entire business process of the smart pipeline network in the form of digital information, thereby achieving organic integration, improving the information management capabilities of the oil and gas smart pipeline network, and providing basic theoretical methods for the construction and operation of smart pipeline networks and the integration of oil and gas pipeline networks with energy Internet.

[0015] Preferably, the method further includes the step of classifying the characteristics of the oil and gas smart pipeline network: Dividing the equipment and facility data generated by the oil and gas pipeline equipment and ancillary facilities in the oil and gas smart pipeline network at the physical level; The energy information generated by the oil and gas pipelines in the oil and gas smart pipeline network is divided into energy levels, wherein the energy information generated by the oil and gas pipelines includes energy entity information converted by the medium transported by the oil and gas pipeline equipment and energy loss information in the process of transporting energy by the oil and gas pipelines; The physical asset information of the pipeline network, the operating status information of the pipeline network and the energy information of the energy space in the oil and gas smart pipeline network are divided into information levels.

[0016] It should be understood that in order to organically integrate the physical entity and information space of the smart pipe network with the energy space that implements the entire business process of the smart pipe network, the present invention divides the smart oil and gas pipe network into a physical level (i.e., physical space), an energy level (i.e., energy space), and an information level (information space) according to various characteristics of the smart oil and gas pipe network; The main function of the physical space is to realize the management of real equipment and facilities, the perception of the operating status of the oil and gas pipeline network, and the exchange of information.

[0017] The main function of energy space is to realize energy management and interaction.

[0018] The main function of information space is to realize the digitization of physical assets of oil and gas pipeline networks, the control of physical assets and the optimization of energy space.

[0019] In the above embodiment, if Figure 2 As shown, the physical space, as the carrier of energy space and information space, interacts with the energy space through energy transmission and energy loss, and interacts with the information space through physical entities, real-time perception and control; the energy space, as the interaction between physical space and information space, interacts with the information space through the conversion of energy entropy and information entropy, and interacts with the physical space through the feedback of energy transmission and loss; the information space, as the mapping of energy space and physical space, maps the physical space through digital twins, and maps the energy space through information flow, eventually forming a cycle of physical carrier, information mapping and energy interaction.

[0020] like Figure 3 As shown, based on the above theory, taking the gas network in the oil and gas smart pipeline network as an example, the specific process is as follows: The process is divided into "gas network energy flow calculation process" and "information flow calculation process".

[0021] In the "Gas Network Energy Flow Calculation Process": Read gas network parameters; Initialize gas circuit parameters and gas consumption of each equipment in the station; Solve the energy flow of the gas network; Calculate the difference G between the calculated value of pipeline flow velocity and the base value of pipeline flow velocity; Determine whether G is less than or equal to the threshold value. If so, output the gas network energy flow result. If not, update the flow rate base value, return, and solve the gas network energy flow again. Finally, the energy flow results of each gas network are formed into an energy flow topology matrix and transmitted to the "information flow calculation process" through a pre-built interface; During the "Information Flow Calculation Process": receiving an energy flow topology matrix through an interface to form an information flow receiving matrix; If a branch disconnection is detected, an optimization decision analysis is performed on the information flow receiving matrix, a control instruction is output, an energy flow control instruction is formed, and the energy flow is updated; The energy flow control instructions are converted into physical control quantities, and the physical control quantities are fed back to the corresponding devices at the physical level.

[0022] Specifically, the optimization decision analysis is the optimal load reduction strategy for the gas network, and the optimal load reduction strategy for the gas network is respectively subject to flow balance constraints, gas source output constraints, pipeline flow constraints, node pressure constraints and gas load reduction constraints.

[0023] In this way, the physical entity and information space of the smart pipeline network are organically integrated with the energy space that implements the entire business process of the smart pipeline network.

[0024] In this embodiment, the physical-to-energy flow model represents the power relationship within a control cycle N, divides the smart pipe network into a topological relationship of points and lines, and then describes the information and energy flow between the points and lines in the form of a matrix. The points are specifically represented by the stations and valve rooms of the oil and gas pipelines, and the lines are specifically represented by the pipeline lines.

[0025] Preferably, the physical-to-energy-flow model is used to convert each device and facility data into a corresponding energy flow, and an energy flow matrix is ​​formed through all energy flows, specifically: Each station and valve room of the oil and gas pipeline is regarded as a node, and each oil and gas pipeline is regarded as a branch. The equipment and facility data generated by each station and valve room and the oil and gas pipeline is used to construct a pipeline network topology node-branch association matrix, and the energy flow state variables, energy flow control variables, energy flow disturbance variables, pipeline network element parameters and pipeline network topology node-branch association matrix of the oil and gas pipeline network are converted into corresponding energy flows through the physical conversion energy flow model. The physical conversion energy flow model is: , Among them, x is the energy flow state variable of the oil and gas pipeline network, u is the energy flow control variable, D is the energy flow disturbance variable, p is the network element parameter of the pipeline network, and A is the pipeline network topology node-branch association matrix; All energy flows are gathered together to form an energy flow matrix.

[0026] Preferably, the energy flow matrix is ​​converted into information flow through the energy flow information flow model, specifically: , Among them, z(N) is the information flow of the pipeline network state measurement column vector, is the pipeline network status measurement mapping matrix, They represent voltage amplitude, phase angle, active power, reactive power and switch status respectively, and T represents transposition.

[0027] Preferably, the information flow model is used to perform optimization decision analysis on the information flow and output control instructions, specifically: If a branch disconnection is detected, the information flow model is used to optimize the decision analysis of the pipeline network state measurement column vector and output a control instruction. The information flow model is: , Among them, z(N) is the information flow of the pipeline network state measurement column vector, F is the general form of the decision function, and y(N) is the control instruction.

[0028] Preferably, the control instruction is converted into a physical control quantity through the information flow physical control quantity model, specifically: Mapping the control instructions with corresponding devices in the physical layer to obtain a control mapping matrix; The control instructions are converted into physical control quantities of the oil and gas pipeline through the control mapping matrix and the information flow physical control quantity model. The information flow physical control quantity model is: , Where C is the control mapping matrix.

[0029] Preferably, after obtaining the physical control amount, the method further comprises the following steps: The input and output results of the physical level, energy level and information level within the control cycle are mapped to form a mapping model of the oil and gas smart pipeline network: , Among them, F in and F out are the total natural gas input and output at the energy level, t (1~n) F in , C (1~n) t (1~n) F in and N （1~n） F e They are the natural gas input energy flow, the natural gas energy flow after loss and the equipment loss electric power at the energy level, and D is the energy flow disturbance variable.

[0030] In the above embodiments, the physical space is mapped through the digital twin, and the energy space is mapped through the information flow, ultimately forming a cycle of physical carrier, information mapping, and energy interaction.

[0031] The following uses the natural gas pipeline leakage scenario as an example to illustrate the use of the physical energy information conversion model group in this method. When a natural gas pipeline leaks, the energy entity natural gas and energy loss will change in the energy space. The physical space pressure, temperature, and flow sensors collect natural gas pipeline operation data, and the leakage monitoring sensor collects leakage data. The information space receives information such as natural gas pipeline pressure, temperature, and flow, as well as sensor information for real-time monitoring of natural gas leaks, and then uses the information of the energy space and the information of the physical space to analyze using the "energy-information-physics" mathematical model (i.e., the physical energy information conversion model group) to obtain a conclusion on the natural gas leak. The information space issues control instructions for natural gas leaks, and the physical space receives instructions to control related equipment to achieve management of natural gas leaks.

[0032] like Figure 4 As shown, the embodiment of the present invention also provides a digital conversion device for an oil and gas smart pipeline network, comprising: A model group construction module is used to construct a physical energy information conversion model group based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; An energy flow conversion module is used to obtain multiple equipment and facility data from the physical level within a control cycle, convert each equipment and facility data into a corresponding energy flow through the physical to energy flow model, and form an energy flow matrix of the energy level through all energy flows; An energy transfer information flow module, used for converting the energy flow matrix into the information flow of the information level through the energy transfer information flow model; An information flow optimization module, used to perform optimization decision analysis on the information flow through the information flow model and output control instructions; A physical control quantity conversion module is used to convert the control instruction into a physical control quantity through the information flow physical control quantity model, and feed back the physical control quantity to the device corresponding to the physical level.

[0033] An embodiment of the present invention also provides an oil and gas smart pipeline network digital conversion device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the oil and gas smart pipeline network digital conversion method as described above is implemented.

[0034] An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program, and is characterized in that when the computer program is executed by a processor, the digital conversion method of the oil and gas smart pipeline network as described above is implemented.

[0035] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0036] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0037] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0038] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0039] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0040] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A digital conversion method for oil and gas smart pipeline network, characterized in that: The steps include: Based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, a physical energy information conversion model group is constructed, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; In one control cycle, a plurality of equipment and facility data are obtained from the physical level, and each of the equipment and facility data is converted into a corresponding energy flow through the physical to energy flow model, and an energy flow matrix of the energy level is formed through all the energy flows; Converting the energy flow matrix into the information flow of the information level through the energy flow information flow model; Performing optimization decision analysis on the information flow through the information flow model and outputting control instructions; The control instruction is converted into a physical control quantity through the information flow physical control quantity model, and the physical control quantity is fed back to the device corresponding to the physical level.

2. The oil and gas smart pipe network digital conversion method according to claim 1 is characterized in that: It also includes steps to classify the characteristics of the oil and gas smart pipeline network: Dividing the equipment and facility data generated by the oil and gas pipeline equipment and ancillary facilities in the oil and gas smart pipeline network at the physical level; The energy information generated by the oil and gas pipelines in the oil and gas smart pipeline network is divided into energy levels, wherein the energy information generated by the oil and gas pipelines includes energy entity information converted by the medium transported by the oil and gas pipeline equipment and energy loss information in the process of transporting energy by the oil and gas pipelines; The physical asset information of the pipeline network, the operating status information of the pipeline network and the energy information of the energy space in the oil and gas smart pipeline network are divided into information levels.

3. The oil and gas smart pipe network digital conversion method according to claim 1 is characterized in that: The physical-to-energy flow model is used to convert each equipment and facility data into corresponding energy flows, and an energy flow matrix is ​​constructed through all energy flows, specifically: Each station and valve room of the oil and gas pipeline is regarded as a node, and each oil and gas pipeline is regarded as a branch. The equipment and facility data generated by each station and valve room and the oil and gas pipeline is used to construct a pipeline network topology node-branch association matrix, and the energy flow state variables, energy flow control variables, energy flow disturbance variables, pipeline network element parameters and pipeline network topology node-branch association matrix of the oil and gas pipeline network are converted into corresponding energy flows through the physical conversion energy flow model. The physical conversion energy flow model is: ， Among them, x is the energy flow state variable of the oil and gas pipeline network, u is the energy flow control variable, D is the energy flow disturbance variable, p is the network element parameter of the pipeline network, and A is the pipeline network topology node-branch association matrix; All energy flows are gathered together to form an energy flow matrix.

4. The oil and gas smart pipe network digital conversion method according to claim 1 is characterized in that: The energy flow matrix is ​​converted into information flow through the energy flow information flow model, specifically: ， Among them, z(N) is the information flow of the pipeline network state measurement column vector, is the pipeline network status measurement mapping matrix, They represent voltage amplitude, phase angle, active power, reactive power and switch status respectively, and T represents transposition.

5. The oil and gas smart pipe network digital conversion method according to claim 4 is characterized in that: The information flow model is used to optimize the information flow and make decision analysis, and output control instructions, specifically: If a branch disconnection is detected, the information flow model is used to optimize the decision analysis of the pipeline network state measurement column vector and output a control instruction. The information flow model is: ， Among them, z(N) is the information flow of the pipeline network state measurement column vector, F is the general form of the decision function, and y(N) is the control instruction.

6. The oil and gas smart pipe network digital conversion method according to claim 1 is characterized in that: The control instruction is converted into a physical control quantity through the information flow physical control quantity model, specifically: Mapping the control instructions with corresponding devices in the physical layer to obtain a control mapping matrix; The control instructions are converted into physical control quantities of the oil and gas pipeline through the control mapping matrix and the information flow physical control quantity model. The information flow physical control quantity model is: ， Where C is the control mapping matrix.

7. The oil and gas smart pipe network digital conversion method according to any one of claims 1 to 6, characterized in that: After obtaining the physical control quantity, the steps include: The input and output results of the physical level, energy level and information level within the control cycle are mapped to form a mapping model of the oil and gas smart pipeline network: , Among them, F in and F out are the total natural gas input and output at the energy level, t (1~n) F in , C (1~n) t (1~n) F in and N （1~n） F e They are the natural gas input energy flow, the natural gas energy flow after loss and the equipment loss electric power at the energy level, and D is the energy flow disturbance variable.

8. A digital conversion device for oil and gas smart pipe network, characterized in that: include: A model group construction module is used to construct a physical energy information conversion model group based on the characteristics of the physical level, energy level and information level of the oil and gas smart pipeline network, wherein the physical energy information conversion model group includes a physical to energy flow model, an energy flow to information flow model, an information flow model and an information flow to physical control quantity model; An energy flow conversion module is used to obtain multiple equipment and facility data from the physical level within a control cycle, convert each equipment and facility data into a corresponding energy flow through the physical to energy flow model, and form an energy flow matrix of the energy level through all energy flows; An energy transfer information flow module, used for converting the energy flow matrix into the information flow of the information level through the energy transfer information flow model; An information flow optimization module, used to perform optimization decision analysis on the information flow through the information flow model and output control instructions; A physical control quantity conversion module is used to convert the control instruction into a physical control quantity through the information flow physical control quantity model, and feed back the physical control quantity to the device corresponding to the physical level.

9. An oil and gas smart pipeline network digital conversion device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the oil and gas smart pipeline network digital conversion method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the oil and gas smart pipeline network digital conversion method as described in any one of claims 1 to 7 is implemented.

Images