Lightning protection composite insulator insulation cooperation detection and structure optimization method based on digital twinning

Abstract

The invention relates to a lightning protection composite insulator insulation cooperation detection and structure optimization method based on digital twinning. The method comprises the following steps: obtaining a structure parameter, a real-time environment parameter and an operation electrical parameter of a lightning protection composite insulator to be detected; constructing a digital twinborn simulation field domain model; establishing a preliminary digital twinborn simulation platform; obtaining an updated preliminary digital twinborn simulation platform; establishing an insulation cooperation equivalent model to obtain an optimized design scheme; and carrying out real-time monitoring and early warning on the insulation cooperation condition of the lightning protection composite insulator according to the insulation cooperation equivalent model. According to the invention, the insulation state of the insulator and the lightning arrester can be monitored in real time, real-time tracking of the insulation performance is realized, and once the insulation performance is abnormal, early warning can be immediately given out to remind operation and maintenance personnel to take measures in time, so that equipment faults or safety accidents caused by insulation failure are effectively avoided; performance bottlenecks and potential problems of the equipment can be found in time, and targeted maintenance suggestions are provided for operation and maintenance personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of machine learning and digital twin, and in particular to an insulation coordination detection and structural optimization method for a lightning protection combined insulator based on digital twin. Background Art

[0002] The background technology of integrating digital twin technology into the insulation coordination of insulators and lightning arresters is based on the urgent need of the current power system for efficient, safe and intelligent operation and maintenance.

[0003] In the power system, lightning protection combined insulators, as key components of transmission lines, bear the important responsibilities of isolating conductors from the ground potential, preventing current leakage, and resisting lightning strikes. However, with the continuous expansion of the scale and complexity of power systems, the traditional lightning protection combined insulator structure insulation coordination failure detection and structural optimization methods can no longer meet the modern power system's requirements for efficiency, precision, and intelligence, and their limitations are becoming increasingly prominent.

[0004] From the perspective of insulator failure detection, traditional detection methods mainly rely on manual inspections and regular testing. This method is not only time-consuming and labor-intensive, but also inefficient, and it is difficult to achieve real-time monitoring and prediction of insulation performance. Since insulators are affected by a variety of factors during operation, such as environmental conditions, equipment aging, material properties, etc., these factors may cause insulation performance to gradually decline, or even insulation coordination failure. However, traditional detection methods often intervene only after the insulation performance has significantly declined or an accident has occurred, which undoubtedly increases the operation risk of the power system.

[0005] In terms of insulator structure optimization, existing methods are usually based on empirical formulas and static analysis, lacking sufficient consideration of actual operating conditions. This method often fails to accurately predict the performance of insulators under different conditions, resulting in limited optimization effects. In lightning protection design, traditional methods may rely too much on the performance of lightning arresters and ignore the insulation coordination of the insulators themselves. In addition, with the continuous emergence of new materials and new technologies, traditional structural optimization methods have become difficult to adapt to new application scenarios and performance requirements.

[0006] Traditional methods also have many shortcomings in data processing and analysis. With the expansion of the scale of power systems, the operating data of insulators has shown an explosive growth trend. However, traditional data processing methods are often unable to cope with such a large amount of data, resulting in low data processing efficiency and even the loss of key information. In addition, traditional data analysis methods often rely on manual experience and judgment, lack objectivity and accuracy, and are difficult to achieve accurate prediction and optimization of insulation performance. Summary of the invention

[0007] In order to solve the problem that the monitoring efficiency of the lightning protection combination insulator is low, there is hysteresis, and the health prediction accuracy of the lightning protection combination insulator is poor due to the failure to simulate the lightning protection combination insulator during the status monitoring of the lightning protection combination insulator, the purpose of the present invention is to provide an insulation coordination detection and structural optimization method for the lightning protection combination insulator based on digital twins, which can monitor the insulation status of insulators and lightning arresters in real time, realize real-time tracking of insulation performance through high-precision sensors, and immediately issue an early warning once the insulation performance is abnormal.

[0008] To achieve the above object, the present invention adopts the following technical solution: a method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twins, the method comprising the following steps in order:

[0009] (1) Obtain the structural parameters of the lightning protection combined insulator to be tested, and collect the real-time environmental parameters and operating electrical parameters of the lightning-prone area through detection sensors;

[0010] (2) Establish a three-dimensional geometric model based on the structural parameters of the lightning protection combined insulator to be tested; establish the corresponding environmental climate field based on the real-time environmental parameters, and the three-dimensional geometric model and the environmental climate field jointly construct a digital twin simulation field model;

[0011] (3) Load the corresponding electrical properties and thermal conductivity properties to the three-dimensional geometric model in the digital twin simulation field model to establish a preliminary digital twin simulation platform;

[0012] (4) Perform real-time simulation analysis on the lightning protection combined insulator based on the preliminary digital twin simulation platform, iteratively update the preliminary digital twin simulation platform based on the deviation between the simulation results and the real-time operating electrical parameters, and obtain an updated preliminary digital twin simulation platform;

[0013] (5) Obtain the insulation coordination parameter data of the lightning protection combined insulator through the updated preliminary digital twin simulation platform, establish an insulation coordination equivalent model, and combine the real-time environmental parameters and operating electrical parameters collected in step (1) to obtain an optimized design scheme;

[0014] (6) Real-time monitoring and early warning of the insulation coordination of lightning protection combination insulators are carried out based on the insulation coordination equivalent model.

[0015] The step (1) specifically includes the following steps:

[0016] (1a) Collect the structural parameters of the lightning protection combined insulator, which include the geometric shape, material properties and connection method of the lightning protection combined insulator. The geometric shape includes the gap distance, cover depth and appearance size of the lightning arrester. The material properties include the conductivity, insulation and thermal expansion coefficient of the surface insulation material. The connection method includes bolt connection and welding.

[0017] (1b) According to the actual structure and detection requirements of the lightning protection combination insulator, climate sensors are deployed in the working area of ​​the lightning arrester and the insulator, and detection sensors are deployed on the surface of the lightning protection combination insulator. The detection sensors include voltage sensors, current sensors, temperature sensors and electric field sensors.

[0018] The step (2) specifically includes the following steps:

[0019] (2a) Based on the three-dimensional modeling software, create a three-dimensional geometric model of the lightning arrester and insulator according to the collected structural parameters of the lightning protection combined insulator, and assign corresponding material properties to the lightning arrester and insulator in the three-dimensional geometric model;

[0020] (2b) Based on the Unity virtual reality software development platform, the environmental climate field including temperature, humidity, pollution level, wind speed and wind direction is established in combination with real-time environmental parameters. A three-dimensional geometric model is imported into the environmental climate field to construct a Unity virtual scene.

[0021] (2c) The Unity virtual scene and Comsol finite element simulation software are linked through IP network communication technology to achieve data interoperability and form a digital twin simulation field model.

[0022] The step (3) specifically includes the following steps:

[0023] (3a) Loading corresponding electrical properties to the three-dimensional geometric model: adding volt-ampere characteristics and nonlinear resistance characteristics to the arrester core rod in the simulation field, and adding dielectric constant and magnetic permeability properties to various materials in the field; the various materials in the field include air, silicone rubber, rainwater, soil, and connecting hardware;

[0024] (3b) Load the corresponding thermal conductivity properties to the three-dimensional geometric model: add the thermal conductivity, thermal expansion coefficient, resistivity temperature coefficient, and constant-pressure heat capacity coefficient to the surface insulation materials of the arrester and insulator in the simulation field;

[0025] (3c) Combining electrical properties and thermal conduction properties, the Maxwell equations and Fourier heat conduction differential equations are added to the digital twin simulation field model to build a preliminary digital twin simulation platform.

[0026] The step (4) specifically includes the following steps:

[0027] (4a) Conduct simulation experiments based on the preliminary digital twin simulation platform to simulate the operating status and performance of lightning arresters and insulators;

[0028] (4b) The operating data of the lightning protection combined insulator collected in real time by the detection sensor is integrated with the preliminary digital twin simulation platform, and the preliminary digital twin simulation platform is used to perform simulation analysis. During the simulation analysis and optimization process, the difference between the simulation results and the actual situation is continuously monitored, and timely feedback is given to the preliminary digital twin simulation platform for correction and optimization. According to the feedback information and actual needs, the preliminary digital twin simulation platform is continuously iterated and updated to obtain an updated preliminary digital twin simulation platform.

[0029] The step (5) specifically includes the following steps:

[0030] (5a) Obtain insulation coordination parameter data of lightning protection combined insulators through the updated preliminary digital twin simulation platform, wherein the insulation coordination parameter data includes key indicators of temperature, vibration, and electrical characteristics of the insulators;

[0031] (5b) combining real-time environmental parameters and operating electrical parameters to establish an insulation coordination equivalent model and extract key data and information in real time, the key data and information including insulation resistance, leakage current, and voltage distribution;

[0032] (5c) Based on the calculation results of the insulation coordination equivalent model, evaluate whether the performance of the insulation coordination meets the design requirements or expected goals and obtain the performance evaluation results;

[0033] (5d) Based on the performance evaluation results, the insulation coordination design is optimized and adjusted to obtain an optimized design. The optimized design includes improving insulation materials, adjusting insulation structure, and optimizing voltage distribution measures.

[0034] (5e) The optimized design solution is re-input into the preliminary digital twin simulation platform and a simulation experiment is conducted again to verify whether the optimization effect achieves the expected goal.

[0035] The step (6) specifically refers to: based on the insulation coordination equivalent model, real-time calculation and prediction of the distributed voltage, distributed electric field strength and temperature distribution of the lightning protection combined insulator are performed, and the monitoring data results are transmitted to the monitoring center through the communication network. The monitoring center analyzes and processes these data to understand the operating conditions of the lightning arrester and insulator in real time.

[0036] It can be seen from the above technical scheme that the beneficial effects of the present invention are: First, real-time monitoring and fault warning: digital twin technology can monitor the insulation status of insulators and lightning arresters in real time, and realize real-time tracking of insulation performance through high-precision sensors. Once the insulation performance is abnormal, it can immediately issue an early warning to remind the operation and maintenance personnel to take timely measures, thereby effectively avoiding equipment failure or safety accidents caused by insulation failure; Second, optimized design and performance evaluation: digital twin technology can simulate the actual working status of insulators and lightning arresters in the design stage, help engineers optimize the design scheme, and ensure more reasonable insulation coordination; through simulation and optimization algorithms, digital twin technology can quickly analyze the advantages and disadvantages of different design schemes , so as to select the best solution and improve the reliability and performance of the equipment; during the operation of the equipment, digital twin technology can monitor the performance parameters of the equipment in real time, such as voltage distribution, current density, etc., and perform performance evaluation, which helps to timely discover the performance bottlenecks and potential problems of the equipment and provide targeted maintenance suggestions for operation and maintenance personnel; third, fault diagnosis and prediction: digital twin technology can use technologies such as big data analysis, machine learning and artificial intelligence to diagnose and predict faults of insulators and lightning arresters. By comparing the real-time data with the real equipment, it can timely discover the abnormal status of the equipment and provide corresponding solutions, which helps to reduce equipment maintenance time and improve equipment availability and production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0038] like Figure 1 As shown, a method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twins, the method includes the following steps in sequence:

[0039] (1) Obtain the structural parameters of the lightning protection combined insulator to be tested, and collect the real-time environmental parameters and operating electrical parameters of the lightning-prone area through detection sensors;

[0040] (2) Establish a three-dimensional geometric model based on the structural parameters of the lightning protection combined insulator to be tested; establish the corresponding environmental climate field based on the real-time environmental parameters, and the three-dimensional geometric model and the environmental climate field jointly construct a digital twin simulation field model;

[0041] (3) Load the corresponding electrical properties and thermal conductivity properties to the three-dimensional geometric model in the digital twin simulation field model to establish a preliminary digital twin simulation platform;

[0042] (4) Perform real-time simulation analysis on the lightning protection combined insulator based on the preliminary digital twin simulation platform, iteratively update the preliminary digital twin simulation platform based on the deviation between the simulation results and the real-time operating electrical parameters, and obtain an updated preliminary digital twin simulation platform;

[0043] (5) Obtain the insulation coordination parameter data of the lightning protection combined insulator through the updated preliminary digital twin simulation platform, establish an insulation coordination equivalent model, and combine the real-time environmental parameters and operating electrical parameters collected in step (1) to obtain an optimized design scheme;

[0044] (6) Real-time monitoring and early warning of the insulation coordination of lightning protection combination insulators are carried out based on the insulation coordination equivalent model.

[0045] The step (1) specifically includes the following steps:

[0046] (1a) Collect the structural parameters of the lightning protection combined insulator, which include the geometric shape, material properties and connection method of the lightning protection combined insulator. The geometric shape includes the gap distance, cover depth and appearance size of the lightning arrester. The material properties include the conductivity, insulation and thermal expansion coefficient of the surface insulation material. The connection method includes bolt connection and welding.

[0047] (1b) According to the actual structure and detection requirements of the lightning protection combination insulator, climate sensors are deployed in the working area of ​​the lightning arrester and the insulator, and detection sensors are deployed on the surface of the lightning protection combination insulator. The detection sensors include voltage sensors, current sensors, temperature sensors and electric field sensors.

[0048] The step (2) specifically includes the following steps:

[0049] (2a) Based on the three-dimensional modeling software, create a three-dimensional geometric model of the lightning arrester and insulator according to the collected structural parameters of the lightning protection combined insulator, and assign corresponding material properties to the lightning arrester and insulator in the three-dimensional geometric model;

[0050] (2b) Based on the Unity virtual reality software development platform, the environmental climate field including temperature, humidity, pollution level, wind speed and wind direction is established in combination with real-time environmental parameters. A three-dimensional geometric model is imported into the environmental climate field to construct a Unity virtual scene.

[0051] (2c) The Unity virtual scene and Comsol finite element simulation software are linked through IP network communication technology to achieve data interoperability and form a digital twin simulation field model.

[0052] The step (3) specifically includes the following steps:

[0053] (3a) Loading corresponding electrical properties to the three-dimensional geometric model: adding volt-ampere characteristics and nonlinear resistance characteristics to the arrester core rod in the simulation field, and adding dielectric constant and magnetic permeability properties to various materials in the field; the various materials in the field include air, silicone rubber, rainwater, soil, and connecting hardware;

[0054] (3b) Load the corresponding thermal conductivity properties to the three-dimensional geometric model: add the thermal conductivity, thermal expansion coefficient, resistivity temperature coefficient, and constant-pressure heat capacity coefficient to the surface insulation materials of the arrester and insulator in the simulation field;

[0055] (3c) Combining electrical properties and thermal conduction properties, the Maxwell equations and Fourier heat conduction differential equations are added to the digital twin simulation field model to build a preliminary digital twin simulation platform.

[0056] The step (4) specifically includes the following steps:

[0057] (4a) Conduct simulation experiments based on the preliminary digital twin simulation platform to simulate the operating status and performance of lightning arresters and insulators;

[0058] (4b) The operating data of the lightning protection combined insulator collected in real time by the detection sensor is integrated with the preliminary digital twin simulation platform, and the preliminary digital twin simulation platform is used to perform simulation analysis. During the simulation analysis and optimization process, the difference between the simulation results and the actual situation is continuously monitored, and timely feedback is given to the preliminary digital twin simulation platform for correction and optimization. According to the feedback information and actual needs, the preliminary digital twin simulation platform is continuously iterated and updated to obtain an updated preliminary digital twin simulation platform.

[0059] The step (5) specifically includes the following steps:

[0060] (5a) Obtain insulation coordination parameter data of lightning protection combined insulators through the updated preliminary digital twin simulation platform, wherein the insulation coordination parameter data includes key indicators of temperature, vibration, and electrical characteristics of the insulators;

[0061] (5b) combining real-time environmental parameters and operating electrical parameters to establish an insulation coordination equivalent model and extract key data and information in real time, the key data and information including insulation resistance, leakage current, and voltage distribution;

[0062] (5c) Based on the calculation results of the insulation coordination equivalent model, evaluate whether the performance of the insulation coordination meets the design requirements or expected goals and obtain the performance evaluation results;

[0063] (5d) Based on the performance evaluation results, the insulation coordination design is optimized and adjusted to obtain an optimized design. The optimized design includes improving insulation materials, adjusting insulation structure, and optimizing voltage distribution measures.

[0064] (5e) The optimized design solution is re-input into the preliminary digital twin simulation platform and a simulation experiment is conducted again to verify whether the optimization effect achieves the expected goal.

[0065] The step (6) specifically refers to: based on the insulation coordination equivalent model, real-time calculation and prediction of the distributed voltage, distributed electric field strength and temperature distribution of the lightning protection combined insulator are performed, and the monitoring data results are transmitted to the monitoring center through the communication network. The monitoring center analyzes and processes these data to understand the operating conditions of the lightning arrester and insulator in real time.

[0066] In summary, the present invention can monitor the insulation status of insulators and lightning arresters in real time, and realize real-time tracking of insulation performance through high-precision sensors. Once the insulation performance is abnormal, an early warning can be issued immediately to remind the operation and maintenance personnel to take timely measures, thereby effectively avoiding equipment failure or safety accidents caused by insulation failure; the actual working status of insulators and lightning arresters can be simulated in the design stage to help engineers optimize the design scheme and ensure that the insulation coordination is more reasonable; through simulation and optimization algorithms, digital twin technology can quickly analyze the advantages and disadvantages of different design schemes, so as to select the best scheme and improve the reliability and performance of the equipment; during the operation of the equipment, digital twin technology can monitor the performance parameters of the equipment in real time, such as voltage distribution, current density, etc., and perform performance evaluation, which helps to timely discover the performance bottlenecks and potential problems of the equipment and provide targeted maintenance suggestions for the operation and maintenance personnel; it can use technologies such as big data analysis, machine learning and artificial intelligence to diagnose and predict the faults of insulators and lightning arresters. By comparing with the real-time data of real equipment, it can timely discover the abnormal status of the equipment and provide corresponding solutions, which helps to reduce equipment maintenance time and improve equipment availability and production efficiency.

Claims

1. A method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twins, characterized in that: The method comprises the following steps in order: (1) Obtain the structural parameters of the lightning protection combined insulator to be tested, and collect the real-time environmental parameters and operating electrical parameters of the lightning-prone area through detection sensors; (2) Establish a three-dimensional geometric model based on the structural parameters of the lightning protection combined insulator to be tested; establish the corresponding environmental climate field based on the real-time environmental parameters, and the three-dimensional geometric model and the environmental climate field jointly construct a digital twin simulation field model; (3) Load the corresponding electrical properties and thermal conductivity properties to the three-dimensional geometric model in the digital twin simulation field model to establish a preliminary digital twin simulation platform; (4) Perform real-time simulation analysis on the lightning protection combined insulator based on the preliminary digital twin simulation platform, iteratively update the preliminary digital twin simulation platform based on the deviation between the simulation results and the real-time operating electrical parameters, and obtain an updated preliminary digital twin simulation platform; (5) Obtain the insulation coordination parameter data of the lightning protection combined insulator through the updated preliminary digital twin simulation platform, establish an insulation coordination equivalent model, and combine the real-time environmental parameters and operating electrical parameters collected in step (1) to obtain an optimized design scheme; (6) Real-time monitoring and early warning of the insulation coordination of lightning protection combination insulators are carried out based on the insulation coordination equivalent model.

2. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (1) specifically includes the following steps: (1a) Collect the structural parameters of the lightning protection combined insulator, which include the geometric shape, material properties and connection method of the lightning protection combined insulator. The geometric shape includes the gap distance, cover depth and appearance size of the lightning arrester. The material properties include the conductivity, insulation and thermal expansion coefficient of the surface insulation material. The connection method includes bolt connection and welding. (1b) According to the actual structure and detection requirements of the lightning protection combination insulator, climate sensors are deployed in the working area of ​​the lightning arrester and the insulator, and detection sensors are deployed on the surface of the lightning protection combination insulator. The detection sensors include voltage sensors, current sensors, temperature sensors and electric field sensors.

3. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (2) specifically includes the following steps: (2a) Based on the three-dimensional modeling software, create a three-dimensional geometric model of the lightning arrester and insulator according to the collected structural parameters of the lightning protection combined insulator, and assign corresponding material properties to the lightning arrester and insulator in the three-dimensional geometric model; (2b) Based on the Unity virtual reality software development platform, the environmental climate field including temperature, humidity, pollution level, wind speed and wind direction is established in combination with real-time environmental parameters. A three-dimensional geometric model is imported into the environmental climate field to construct a Unity virtual scene. (2c) The Unity virtual scene and Comsol finite element simulation software are linked through IP network communication technology to achieve data interoperability and form a digital twin simulation field model.

4. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (3) specifically includes the following steps: (3a) Loading corresponding electrical properties to the three-dimensional geometric model: adding volt-ampere characteristics and nonlinear resistance characteristics to the arrester core rod in the simulation field, and adding dielectric constant and magnetic permeability properties to various materials in the field; the various materials in the field include air, silicone rubber, rainwater, soil, and connecting hardware; (3b) Load the corresponding thermal conductivity properties to the three-dimensional geometric model: add the thermal conductivity, thermal expansion coefficient, resistivity temperature coefficient, and constant-pressure heat capacity coefficient to the surface insulation materials of the arrester and insulator in the simulation field; (3c) Combining electrical properties and thermal conduction properties, the Maxwell equations and Fourier heat conduction differential equations are added to the digital twin simulation field model to build a preliminary digital twin simulation platform.

5. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (4) specifically includes the following steps: (4a) Conduct simulation experiments based on the preliminary digital twin simulation platform to simulate the operating status and performance of lightning arresters and insulators; (4b) The operating data of the lightning protection combined insulator collected in real time by the detection sensor is integrated with the preliminary digital twin simulation platform, and the preliminary digital twin simulation platform is used to perform simulation analysis. During the simulation analysis and optimization process, the difference between the simulation results and the actual situation is continuously monitored, and timely feedback is given to the preliminary digital twin simulation platform for correction and optimization. According to the feedback information and actual needs, the preliminary digital twin simulation platform is continuously iterated and updated to obtain an updated preliminary digital twin simulation platform.

6. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (5) specifically includes the following steps: (5a) Obtain insulation coordination parameter data of lightning protection combined insulators through the updated preliminary digital twin simulation platform, wherein the insulation coordination parameter data includes key indicators of temperature, vibration, and electrical characteristics of the insulators; (5b) combining real-time environmental parameters and operating electrical parameters to establish an insulation coordination equivalent model and extract key data and information in real time, the key data and information including insulation resistance, leakage current, and voltage distribution; (5c) Based on the calculation results of the insulation coordination equivalent model, evaluate whether the performance of the insulation coordination meets the design requirements or expected goals and obtain the performance evaluation results; (5d) Based on the performance evaluation results, the insulation coordination design is optimized and adjusted to obtain an optimized design. The optimized design includes improving insulation materials, adjusting insulation structure, and optimizing voltage distribution measures. (5e) The optimized design solution is re-input into the preliminary digital twin simulation platform and a simulation experiment is conducted again to verify whether the optimization effect achieves the expected goal.

7. The method for insulation coordination detection and structural optimization of lightning protection combined insulators based on digital twin according to claim 1 is characterized in that: The step (6) specifically refers to: based on the insulation coordination equivalent model, real-time calculation and prediction of the distributed voltage, distributed electric field strength and temperature distribution of the lightning protection combined insulator are performed, and the monitoring data results are transmitted to the monitoring center through the communication network. The monitoring center analyzes and processes these data to understand the operating conditions of the lightning arrester and insulator in real time.

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