Method, device and medium for analyzing power communication transmission network based on digital twinning

Abstract

The embodiment of the present disclosure relates to an analysis method of a power communication transmission network based on digital twinning, which comprises: establishing a digital twinning model about the power communication transmission network based on physical attribute data of entity devices in the power communication transmission network; acquiring real-time operation data of the entity devices and inputting the digital twinning model to simulate and analogize real-time operation state of the power communication transmission network; and analyzing a twinning fault event corresponding to a fault event in the power communication transmission network based on simulation constraint conditions; and outputting the twinning fault event to realize early warning of the fault event of the power communication network. Through the method, the real scene of the power communication transmission network can be simulated, the fault reason of simulation can be analyzed, the early warning of the fault event of the power communication network can be realized, and the operation and maintenance personnel can be helped to quickly solve the fault problem.

Description

Technical Field

[0001] This application pertains to power data processing technology, specifically relating to an analysis method for power communication transmission networks based on digital twins. Background Technology

[0002] Currently, the optical cables in the backbone communication network are widely distributed, have many relationships, and are numerous. Due to the randomness of optical cable failures, the analysis of power communication transmission network failures, as well as the evaluation of the scope of impact and handling effectiveness of failures, can only be carried out in the actual network. This can easily affect network operation and pose a high security risk. Summary of the Invention

[0003] (a) Technical problems to be solved

[0004] In view of the above-mentioned shortcomings and deficiencies of the prior art, this application provides an analysis method for power communication transmission networks based on digital twins.

[0005] (II) Technical Solution

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] In a first aspect, embodiments of this application provide an analysis method for power communication transmission networks based on digital twins, comprising:

[0008] S1. Based on the physical attribute data of physical equipment in the power communication transmission network, establish a digital twin model of the power communication transmission network;

[0009] S2. Acquire real-time operating data of physical equipment and input it into the digital twin model to simulate the real-time operating status of the power communication transmission network; and, based on the simulation constraints, analyze and obtain the twin fault events corresponding to the fault events in the power communication transmission network.

[0010] S3. Output the twin fault events to achieve early warning of fault events in the power communication network;

[0011] The digital twin model includes:

[0012] A three-dimensional physical model is used to reflect the physical attribute data and real-time operation data of physical equipment in the power communication transmission network, as well as to display early warnings based on twin fault events output by the simulation analysis model; the physical attribute data is used to reflect the physical attributes of the physical equipment, and the real-time operation data is used to reflect the real-time working status of the physical equipment.

[0013] The simulation analysis model is used to analyze twin fault events in the power communication transmission network based on real-time operating data and simulation constraints, and output them to the physical entity three-dimensional model.

[0014] Preferably, the simulation constraints include active constraints and disturbance event constraints; wherein,

[0015] The active constraints include: resource constraints and time constraints;

[0016] The disturbance event constraints include: constraints set based on potential disturbance events in real-time operational data; the disturbance event constraints are obtained in advance based on the disturbance event feature extraction step.

[0017] Preferably, the disturbance event feature extraction step includes:

[0018] A1. Obtain historical disturbance events of the power communication transmission network, as well as the historical operational dynamic data corresponding to the occurrence of the historical disturbance events;

[0019] A2. Based on the hidden Markov model, data features are extracted from historical dynamic data to obtain event features corresponding to historical disturbance events;

[0020] A3. Input the event features into the disturbance identification model to obtain the disturbance event type;

[0021] Among them, the perturbation recognition model is a convolutional neural network model with adaptive weights trained on the dataset;

[0022] A4. Establish a disturbance event feature library as a constraint condition for disturbance events; the disturbance event feature library includes the disturbance event type and the event feature corresponding to the disturbance event type.

[0023] Preferably, the disturbance event constraints include: abnormal equipment temperature, high equipment utilization rate, significant decrease in transmission rate, abnormal total network packet loss, abnormal network receiving load, and abnormal network sending load.

[0024] Preferably, the active constraint is a pre-set constraint based on the resource requirements and time of the power communication transmission network;

[0025] The resource constraints include: changes in network configuration, changes in network devices, and increases or decreases in the number of network devices.

[0026] The time constraints include: maintenance plans, preventative maintenance, and temporary bandwidth limitations.

[0027] Preferably, the digital twin model includes a simulation analysis model based on simulation constraints. The simulation analysis model includes a simulation rule base. The simulation analysis model is used to perform simulation analysis based on the simulation rule base and simulation constraints to obtain twin fault events.

[0028] S2 includes:

[0029] S201. Obtain real-time operating data of physical equipment, including: equipment temperature, equipment utilization rate, transmission rate, total network packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment quantity increase / decrease plan, maintenance plan, preventive maintenance plan, temporary bandwidth limitation plan, etc.

[0030] S202. Input the real-time operating data into the digital twin model for simulation. Based on the simulation constraints, obtain simulation data, which includes equipment temperature, equipment utilization rate, transmission rate, total network packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment quantity increase / decrease plan, maintenance plan, preventive maintenance plan, temporary bandwidth limitation plan, etc.

[0031] S203. A simulation analysis model based on a digital twin model, which obtains twin fault events based on simulation data.

[0032] Preferably, the physical equipment of the power communication transmission network includes sites, OTN equipment, and optical cables, characterized in that S1 includes:

[0033] S101. Obtain the static data and initialization data of the physical device;

[0034] S102. Construct a three-dimensional physical model of the power data communication network based on the static data;

[0035] S103. Construct a simulation analysis model based on the simulation rule base;

[0036] S104. After fusing the initialization data from multiple sources, input the data into the three-dimensional physical entity model to drive the three-dimensional physical entity model to interact with the analysis model and obtain a digital twin model of the circuit data communication network.

[0037] In a second aspect, embodiments of this application provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the steps of the analysis method for power communication transmission networks based on digital twins as described in the first aspect.

[0038] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the analysis method for power communication transmission networks based on digital twins as described in the first aspect.

[0039] (III) Beneficial Effects

[0040] The technical solution provided in this application may include the following beneficial effects:

[0041] First, the present invention provides an analysis method for power communication transmission networks based on digital twins. Based on the digital twin model of the power transmission communication network, the method simulates the operation of the power transmission communication network, enabling the real-time status information of physical equipment to be accurately mapped onto the digital twin model, restoring the real operation scenario of the power communication transmission network, realizing equipment status visualization, and enabling early warning of fault events in the power communication network.

[0042] Secondly, this invention uses digital twin technology to provide early warning of fault events in the power communication network based on the real-time operating data of physical equipment, and to obtain the cause of the fault in real time, so as to help maintenance personnel quickly solve the fault problem. Attached Figure Description

[0043] Figure 1 This is a schematic flowchart of an analysis method for a power communication transmission network based on digital twins, provided in the embodiment. Detailed Implementation

[0044] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0046] Example 1

[0047] See Figure 1 This embodiment provides an analysis method for power communication transmission networks based on digital twins, including:

[0048] S1. Based on the physical attribute data of physical equipment in the power communication transmission network, establish a digital twin model of the power communication transmission network;

[0049] S2. Acquire real-time operating data of physical equipment and input it into the digital twin model to simulate the real-time operating status of the power communication transmission network; and, based on the simulation constraints, analyze and obtain the twin fault events corresponding to the fault events in the power communication transmission network.

[0050] S3. Output the twin fault events to achieve early warning of fault events in the power communication network;

[0051] The digital twin model includes:

[0052] A three-dimensional physical model is used to reflect the physical attribute data and real-time operation data of physical equipment in the power communication transmission network, as well as to display early warnings based on twin fault events output by the simulation analysis model; the physical attribute data is used to reflect the physical attributes of the physical equipment, and the real-time operation data is used to reflect the real-time working status of the physical equipment.

[0053] The simulation analysis model is used to analyze twin fault events in the power communication transmission network based on real-time operating data and simulation constraints, and output them to the physical entity three-dimensional model.

[0054] Furthermore, the simulation constraints include active constraints and disturbance event constraints; wherein,

[0055] The active constraints include: resource constraints and time constraints;

[0056] The disturbance event constraints include: constraints set based on potential disturbance events in real-time operational data; the disturbance event constraints are obtained in advance based on the disturbance event feature extraction step.

[0057] Furthermore, the disturbance event feature extraction step includes:

[0058] A1. Obtain historical disturbance events of the power communication transmission network, as well as the historical operational dynamic data corresponding to the occurrence of the historical disturbance events;

[0059] A2. Based on the hidden Markov model, data features are extracted from historical dynamic data to obtain event features corresponding to historical disturbance events;

[0060] A3. Input the event features into the disturbance identification model to obtain the disturbance event type;

[0061] Among them, the perturbation recognition model is a convolutional neural network model with adaptive weights trained on the dataset;

[0062] A4. Establish a disturbance event feature library as a constraint condition for disturbance events; the disturbance event feature library includes the disturbance event type and the event feature corresponding to the disturbance event type.

[0063] Furthermore, the disturbance event constraints include: abnormal equipment temperature, high equipment utilization rate, significant decrease in transmission rate, abnormal total network packet loss, abnormal network receiving load, and abnormal network sending load.

[0064] Furthermore, the active constraints are pre-set constraints based on the resource requirements and time of the power communication transmission network;

[0065] The resource constraints include: changes in network configuration, changes in network devices, and increases or decreases in the number of network devices.

[0066] The time constraints include: maintenance plans, preventative maintenance, and temporary bandwidth limitations.

[0067] Furthermore, the digital twin model includes a simulation analysis model based on simulation constraints. The simulation analysis model includes a simulation rule base. The simulation analysis model is used to perform simulation analysis based on the simulation rule base and simulation constraints to obtain twin fault events.

[0068] S2 includes:

[0069] S201. Obtain real-time operating data of physical equipment, including: equipment temperature, equipment utilization rate, transmission rate, total network packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment quantity increase / decrease plan, maintenance plan, preventive maintenance plan, temporary bandwidth limitation plan, etc.

[0070] S202. Input the real-time operating data into the digital twin model for simulation. Based on the simulation constraints, obtain simulation data, which includes equipment temperature, equipment utilization rate, transmission rate, total network packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment quantity increase / decrease plan, maintenance plan, preventive maintenance plan, temporary bandwidth limitation plan, etc.

[0071] S203. A simulation analysis model based on a digital twin model, which obtains twin fault events based on simulation data.

[0072] Furthermore, the physical equipment of the power communication transmission network includes sites, OTN equipment, and optical cables, characterized in that S1 includes:

[0073] S101. Obtain the static data and initialization data of the physical device;

[0074] S102. Construct a three-dimensional physical model of the power data communication network based on the static data;

[0075] S103. Construct a simulation analysis model;

[0076] S104. After fusing the initialization data from multiple sources, input the data into the three-dimensional physical entity model to drive the three-dimensional physical entity model to interact with the analysis model and obtain a digital twin model of the circuit data communication network.

[0077] This embodiment also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the above-described analysis method for power communication transmission networks based on digital twins.

[0078] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described analysis method for power communication transmission networks based on digital twins.

[0079] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0080] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0081] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0082] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0083] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0084] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. An analysis method of a power communication transmission network based on digital twinning, characterized by, The analysis method comprises: S1, establishing a digital twin model of the power communication transmission network based on physical attribute data of entity devices in the power communication transmission network; S2, obtaining real-time operation data of the entity devices and inputting the digital twin model to simulate and simulate the real-time operation state of the power communication transmission network; and based on the simulation constraint condition, analyzing to obtain a twin fault event corresponding to a fault event in the power communication transmission network; S3, outputting the twin fault event to realize early warning of the fault event of the power communication network; The digital twin model comprises: a physical entity three-dimensional model for reflecting physical attribute data and real-time operation data of entity devices in the power communication transmission network, and for early warning display based on the twin fault event output by the simulation analysis model; the physical attribute data is used to reflect the physical attributes of the entity devices, and the real-time operation data is used to reflect the real-time working state of the entity devices; a simulation analysis model for analyzing the twin fault event in the power communication transmission network based on the real-time operation data and the simulation constraint condition and outputting to the physical entity three-dimensional model; The entity devices of the power communication transmission network comprise sites, OTN devices and optical cables, and S1 comprises: S101, obtaining physical attribute data and initialization data of the entity devices; S102, constructing a physical entity three-dimensional model of the power data communication network based on the physical attribute data; S103, constructing a simulation analysis model; S104, inputting the initialization data after multi-source data fusion into the physical entity three-dimensional model to drive data interaction between the physical entity three-dimensional model and the analysis model, and obtaining a digital twin model of the circuit data communication network In S2, the simulation constraint condition comprises an active constraint condition and a disturbance event constraint condition; wherein, The active constraint condition comprises a resource constraint condition and a time constraint condition; The disturbance event constraint condition comprises a constraint condition set based on potential disturbance events in the real-time operation data; the disturbance event constraint condition is obtained based on a disturbance event feature extraction step in advance; The disturbance event feature extraction step comprises: A1, obtaining historical disturbance events of the power communication transmission network and historical operation dynamic data corresponding to the historical disturbance events when the historical disturbance events occur; A2, extracting data features of the historical operation dynamic data based on a hidden Markov model to obtain event features corresponding to the historical disturbance events; A3, inputting the event features into a disturbance recognition model to obtain a disturbance event type; Wherein, the disturbance recognition model is a convolutional neural network model with adaptive weights trained based on a data set; A4, establishing a disturbance event feature library as a disturbance event constraint condition; the disturbance event feature library comprises the disturbance event type and the event features corresponding to the disturbance event type.

2. The analysis method according to claim 1, characterized in that, The disturbance event constraint condition comprises device temperature anomaly, device usage rate being too high, transmission rate being obviously decreased, network total packet loss being abnormal, network receiving load being abnormal or network sending load being abnormal.

3. The analysis method of claim 2, wherein The active constraint is a constraint based on resource demand and time pre-setting of the power communication transmission network; The resource constraint includes network configuration change, network equipment change or network equipment number increase or decrease; The time constraint includes maintenance plan, preventive maintenance or temporary bandwidth limitation.

4. The analysis method according to claim 3, characterized in that, The simulation analysis model includes a simulation rule library, and is used for simulation analysis based on the simulation rule library and simulation constraints to obtain a twin fault event; The S2 includes: S201, obtaining real-time running data of an entity device, the real-time running data including device temperature, device usage, transmission rate, network total packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment number increase or decrease plan, maintenance plan, preventive maintenance plan or temporary bandwidth limitation plan; S202, inputting the real-time running data into a digital twin model for simulation simulation, obtaining simulation data based on the simulation constraints, the simulation data including device temperature, device usage, transmission rate, network total packet loss, network receiving load, network sending load, network configuration change plan, network equipment change plan, network equipment number increase or decrease plan, maintenance plan, preventive maintenance plan or temporary bandwidth limitation plan; S203, obtaining a twin fault event according to the simulation data based on a simulation analysis model of the digital twin model.

5. An electronic device, comprising: It includes: A memory, a processor and a computer program stored on the memory and executable on the processor, when the computer program is executed by the processor, the steps of the analysis method of the power communication transmission network based on the digital twin in any one of claims 1-4 are realized.

6. A computer-readable storage medium, characterized in that, The computer program is stored on the computer readable storage medium, and the steps of the analysis method of the power communication transmission network based on the digital twin in any one of claims 1-4 are realized when the computer program is executed by the processor.

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