Box transformer substation fault rapid diagnosis and self-healing recovery method based on electric red-ong system

Abstract

The invention relates to a box transformer substation fault rapid diagnosis and self-healing recovery method based on an electric red-hong system, which comprises the following steps of: S1, setting an electric red-hong operating system terminal and a fault database, and deploying various electric red-hong sensors in a box transformer substation; s2, the electric red operation system terminal collects operation data and environment monitoring data of the box-type substation in real time through all electric red sensors, and monitors, analyzes and diagnoses the operation data and the environment monitoring data so as to judge fault data; s3, the electric red-operating system terminal preprocesses the fault data and extracts a fault characteristic value, and the fault characteristic value is compared with the fault diagnosis model to judge the fault type and the fault position; s4, the electric red operating system terminal formulates a self-healing recovery strategy; and S5, the electric red operating system terminal generates a self-healing recovery instruction according to the self-healing recovery strategy, and then issues the self-healing recovery instruction to the protection measurement and control unit to execute the self-healing recovery instruction so as to realize rapid recovery of power supply. The fault diagnosis speed and accuracy of the box-type substation can be improved, self-healing recovery of the box-type substation is realized, and the power failure time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment, and particularly relates to a method for rapid fault diagnosis and self-healing recovery of a box-type substation based on an electric Hong system. Background Art

[0002] A box-type substation is a complete set of power distribution equipment. It has a compact structure, and each box constitutes an independent system. The combination method is flexible and changeable, and it can be freely combined according to the actual situation to meet the needs of safe operation. It is applicable to places such as urban distribution networks, commercial centers, residential communities, and industrial parks. As a key node in power distribution (especially in urban power grids, industrial parks, and residential power supply scenarios), the operation stability of the box-type substation directly affects the power supply reliability.

[0003] During the operation of the box-type substation, various unknown faults may occur, such as short-circuit faults, overload faults, insulation faults, mechanical faults, and environmental climate impacts, resulting in problems such as low maintenance efficiency, high operation and maintenance costs, slow recovery time, and long power outage time. The traditional fault diagnosis methods mainly rely on manual experience and simple protection device action information (such as circuit breaker tripping information). However, this manual diagnosis method not only has defects such as slow diagnosis speed and long time consumption (generally taking dozens of minutes to several hours), single technical means, low accuracy of fault location (such as only being able to identify the section rather than the exact fault point), and non-domestic independent and secure and controllable technical property rights, but also cannot remotely monitor, maintain, analyze, and diagnose the fault data of the box-type substation, lacks self-healing recovery means, and the historical operation data of key components is not systematically stored. If the historical operation data of each key component of the box-type substation is lost, there will be no technical reserve for diagnostic analysis, resulting in no basis for fault analysis. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for rapid fault diagnosis and self-healing recovery of a box-type substation based on an electric Hong system, which can improve the speed and accuracy of fault diagnosis of the box-type substation, realize the self-healing recovery of the box-type substation, predict equipment faults in advance, and reduce the power outage time. The adopted technical solutions are as follows: A method for rapid fault diagnosis and self-healing recovery of a box-type substation based on an electric Hong system, characterized by including the following steps: S1. Set up an electric Hong operating system terminal and a fault database, and deploy a variety of electric Hong sensors inside the box-type substation, and wirelessly connect the electric Hong operating system terminal with all electric Hong sensors; S2. The electric Hong operating system terminal real-time collects the operation data and environmental monitoring data of each key part of the box-type substation through all electric Hong sensors, and monitors, analyzes, and diagnoses these data to determine the fault data; S3. The terminal of the Dianhong operating system preprocesses the fault data and extracts the fault characteristic values, and compares them with the fault diagnosis models in the fault database to determine the fault type and accurately locate the fault location; S4. The terminal of the Dianhong operating system formulates corresponding self-healing and recovery strategies according to the diagnosed fault type and fault location; S5. The terminal of the Dianhong operating system generates self-healing and recovery instructions according to the self-healing and recovery strategies, and then sends them to the protection and measurement control unit corresponding to the box-type substation. The protection and measurement control unit executes the self-healing and recovery instructions to achieve rapid power supply recovery.

[0005] The Dianhong sensor terminal refers to the terminal that applies the Dianhong operating system and has functions such as data acquisition, storage, analysis, transmission, display, and control. The Dianhong sensor means that all sensors are implanted with the Dianhong operating system, and such Dianhong sensors also fully reflect the characteristics of the Dianhong operating system: unified Internet of Things model, plug-and-play, and national production, etc.

[0006] In this rapid fault diagnosis and self-healing recovery method for box-type substations, in step S1, the terminal of the Dianhong operating system is used as the core and foundation of the whole system, and a variety of Dianhong sensors are deployed at key parts of the box-type substation (such as the high-voltage room, transformer room, and low-voltage room) for real-time online monitoring, realizing plug-and-play of sensors without configuration, simplifying wiring, with high fault recognition accuracy and fast speed. The technical property rights of the whole system are domestically produced, autonomous, secure, and controllable. The fault database stores fault types, fault characteristics, and fault diagnosis models to support the formulation of subsequent self-healing recovery strategies. In step S2, the terminal of the Dianhong operating system wirelessly connects to all Dianhong sensors in the box-type substation, and through all Dianhong sensors, it collects the operation data and environmental monitoring data of key parts of the box-type substation in real time, monitors all data, conducts data analysis and data comprehensive superposition diagnosis, and quickly locates the fault data. In step S3, the terminal of the Dianhong operating system performs preprocessing on the fault data, such as data cleaning, data conversion, and data dimensionality reduction. Then, based on the eigenvalue extraction method of machine learning (such as the principal component analysis method), the most useful features are selected from the preprocessed data, useless features or noise are excluded, the extraction of fault eigenvalue is realized, and then the extracted fault eigenvalue is compared with the fault diagnosis model in the fault database, so as to quickly judge the fault type and accurately locate the fault position. In step S4, the terminal of the Dianhong operating system, according to the diagnosed fault type and fault position, simulates the possible faults during the operation of the box-type substation, thereby can anticipate equipment faults in advance and formulate corresponding self-healing recovery strategies. For example, when the diagnosed fault is that the transformer is overloaded until the temperature reaches the over-temperature threshold, the terminal of the Dianhong operating system formulates a self-healing recovery strategy of "automatically cutting off the transformer output and automatically healing the transformer operation after the temperature drops". In step S5, the terminal of the Dianhong operating system can generate self-healing recovery instructions according to the self-healing recovery strategy, send the self-healing recovery instructions to the corresponding protection and measurement control unit of the box-type substation, and the protection and measurement control unit executes the self-healing recovery instructions. For minor faults such as overcurrent and over-temperature, the terminal of the Dianhong operating system can perform self-healing operations by itself. For complex faults such as abnormal vibration, abnormal discharge, water ingress, and excessive smoke of the transformer, manual shutdown and maintenance are required in time. After the terminal of the Dianhong operating system passes the self-check, the power supply is self-healed and restored, thus realizing the self-healing recovery power supply of the box-type substation, reducing the power outage time, and reducing the irreversible damage of the equipment caused by the continuous deterioration of the fault, achieving the role of preventing equipment damage in advance.

[0007] As a preferred embodiment of the present invention, in step S1, common fault types are pre-imported into the fault database, and new fault types and corresponding fault characteristics that occur during the operation of the box-type substation are gradually imported into the fault database to continuously improve the fault types and fault diagnosis models in the fault database. Among them, common fault types include temperature over-limit, current overload, etc., and new fault types include discharge type, abnormal vibration of the transformer, etc.

[0008] As a preferred embodiment of the present invention, the box-type substation includes a ring main unit, a transformer room, and a low-voltage cabinet; in step S2, a variety of the electric Hong sensors are deployed inside and around the ring main unit, the transformer room, and the low-voltage cabinet, and these electric Hong sensors can collect ring main unit data, transformer data, low-voltage cabinet data, and environmental monitoring data in real time. Specifically, the electric Hong sensors deployed inside the ring main unit can collect ring main unit data such as SF6 density monitoring, gas tank visualization, partial discharge monitoring, RFID temperature monitoring, etc.; the electric Hong sensors deployed inside the transformer room can collect transformer data such as partial discharge monitoring, vibration monitoring, core grounding current monitoring, winding temperature monitoring, fan monitoring, infrared thermal imaging monitoring, etc.; the electric Hong sensors deployed inside the low-voltage cabinet can collect low-voltage room data such as display terminals, RFID incoming and outgoing line temperature monitoring, etc.; the electric Hong sensors deployed in the surrounding environment of the ring main unit, the transformer room, and the low-voltage cabinet can collect data such as high-voltage room door status monitoring, transformer room temperature and humidity, water immersion, smoke detection monitoring, high-voltage room temperature and humidity, water immersion, smoke detection monitoring, transformer room door status monitoring, low-voltage room door status monitoring, low-voltage room temperature and humidity, water immersion, smoke detection monitoring, etc.

[0009] As a preferred embodiment of the present invention, in step S2, at the initial state of the box-type substation, the electric Hong operating system terminal collects the data of all electric Hong sensors as standard basic data; after the box-type substation runs, the electric Hong operating system terminal collects the data of all electric Hong sensors in real time in a multi-threaded and multi-dimensional manner for data analysis and processing, compares it with the normal factory data to find abnormalities, and if abnormal data is still found after multiple analysis and verification, it is judged as fault data.

[0010] As a preferred embodiment of the present invention, in step S3, the preprocessing process of the fault data by the electric Hong operating system terminal includes: (1) Data cleaning: checking for outliers, missing values, duplicate values, etc. in the fault data; (2) Data conversion: performing operations such as standardization and normalization of the fault data; (3) Data dimensionality reduction: reducing high-dimensional data to a low-dimensional space through methods such as principal component analysis and factor analysis to reduce the computational complexity.

[0011] As a preferred embodiment of the present invention, in step S1, a control center is set up and connected to the terminal of the DHOS (Digital Hydraulic Operating System) through network communication. The control center can collect and integrate fault information, provide data for big data analysis, manually review the rationality of the self-healing strategy, and remotely control through manual intervention, etc.

[0012] As a further preferred embodiment of the present invention, in step S3, if the extracted fault characteristic value cannot be compared to a corresponding fault diagnosis model in the fault database, the DHOS terminal will continue to generate a fault diagnosis model from the fault characteristic value and store it in the fault database. At the same time, it will be uploaded to the control center through the network, and the control center will remotely control the self-healing recovery to achieve rapid power restoration. Thus, the fault characteristics and fault diagnosis models in the fault database can be continuously improved, and when an unknown fault occurs, manual intervention can be timely for remote control to better ensure the stability of power supply.

[0013] As a further preferred embodiment of the present invention, in step S5, the DHOS terminal also uploads the self-healing recovery strategy to the control center through the network, and the control center remotely controls the self-healing recovery to achieve rapid power restoration. The DHOS terminal uploads the self-healing recovery strategy to the control center through the network to achieve remote visual double confirmation, with strong real-time information interaction with the control center, improving the reliability of power supply guarantee.

[0014] Compared with the prior art, the present invention has the following advantages: (1) This application uses the DHOS terminal as the basis and radiates a variety of DHOS wireless sensors deployed in the high-voltage chamber, transformer chamber, and low-voltage chamber of the box substation. The DHOS terminal monitors, analyzes, and diagnoses data in real time through multi-threading and multi-dimensions, realizes comprehensive data superposition diagnosis, can autonomously and quickly identify faults, remotely visualize double confirmation, and at the same time establish a fault database, improve fault characteristics and models, improve the speed and accuracy of fault diagnosis of the box substation, support the formulation of self-healing recovery strategies, predict equipment faults in advance, realize the self-healing recovery of the box substation, and reduce power outage time; (2) This application uses the domestic autonomous, secure and controllable DHOS, as well as the DHOS sensors that support plug-and-play and wireless communication, deeply integrates wireless communication, fast fault diagnosis, self-healing recovery methods and Internet of Things technologies, constructs a "cloud-edge-end" collaborative architecture, effectively improves the equipment monitoring accuracy and fault warning ability, improves the operation and maintenance response efficiency, achieves the digital goals of intelligent primary equipment, equipment maintenance in a state-based manner, networked secondary equipment, as well as digitalization of all-station information, networked communication platform, and standardization of information sharing; (3) This application belongs to the technological innovation of traditional box-type substations. It can not only accelerate the evolution of traditional box-type substations towards intelligence, greenness, and diversification, but also achieve value chain reconstruction through technological integration and scientific and technological innovation, improve the work efficiency and service quality of operation and maintenance personnel, enhance operation and maintenance efficiency, reduce costs, ensure the stability of the power grid and the power supply system, and provide strong technical support for building a more intelligent, green, and efficient power infrastructure in the future. Brief Description of the Drawings

[0015] Figure 1 It is the system topology diagram of the method for rapid fault diagnosis and self-healing recovery of box-type substations provided by the preferred embodiment of the present invention.

[0016] Figure 2 It is the control flow chart of the terminal of the Dianhong operation system in the preferred embodiment of the present invention. Detailed Embodiment

[0017] As Figure 1 - Figure 2 shown, this method for rapid fault diagnosis and self-healing recovery of box-type substations based on the Dianhong system includes the following steps: S1. Set up the terminal 1 of the Dianhong operation system and the fault database 2, deploy a variety of Dianhong sensors 3 inside the box-type substation, and wirelessly communicate the terminal 1 of the Dianhong operation system with all Dianhong sensors 3; S2. The terminal 1 of the Dianhong operation system collects the operation data and environmental monitoring data of each key part of the box-type substation in real time through all Dianhong sensors 3, and monitors, analyzes, and diagnoses these data to determine the fault data 11; S3. The terminal 1 of the Dianhong operation system preprocesses the fault data 11 and extracts the fault feature values 12, and compares them with the fault diagnosis models in the fault database 2 to determine the fault type and accurately locate the fault position; S4. The terminal 1 of the Dianhong operation system formulates corresponding self-healing recovery strategies according to the diagnosed fault type and fault position; S5. The terminal 1 of the Dianhong operation system generates self-healing recovery instructions according to the self-healing recovery strategies, and then issues them to the corresponding protection and measurement control unit of the box-type substation, and the protection and measurement control unit executes the self-healing recovery instructions to achieve rapid power supply restoration.

[0018] In this embodiment, in step S1, common fault types are pre-imported into the fault database 2, and new fault types and corresponding fault features that occur during the operation of the box-type substation are gradually imported into the fault database 2 to continuously improve the fault types and fault diagnosis models in the fault database 2. Among them, common fault types include temperature overlimit, current overload, etc., and new fault types include discharge type, abnormal vibration of the transformer, etc.

[0019] In this embodiment, the box-type substation includes a ring main unit 21, a transformer chamber 22, and a low-voltage cabinet 23. In step S2, a variety of electric eel sensors 3 are deployed inside and around the ring main unit 21, the transformer chamber 22, and the low-voltage cabinet 23. These electric eel sensors 3 can collect the ring main unit data 210, the transformer data 220, the low-voltage cabinet data 230, and the environmental monitoring data in real time. Specifically, the electric eel sensors 3 deployed in the ring main unit 21 can collect ring main unit data 210 such as SF6 density monitoring, gas tank visualization, partial discharge monitoring, RFID temperature monitoring, etc.; the electric eel sensors 3 deployed in the transformer chamber 22 can collect transformer data 220 such as partial discharge monitoring, vibration monitoring, core grounding current monitoring, winding temperature monitoring, fan monitoring, infrared thermal imaging monitoring, etc.; the electric eel sensors 3 deployed in the low-voltage cabinet 23 can collect low-voltage chamber data such as display terminals, RFID incoming and outgoing line temperature monitoring, etc.; the electric eel sensors 3 deployed in the surrounding environment of the ring main unit 21, the transformer chamber 22, and the low-voltage cabinet 23 can collect data such as high-voltage chamber door status monitoring, temperature and humidity in the transformer chamber 22, water immersion, smoke detection monitoring, high-voltage chamber temperature and humidity, water immersion, smoke detection monitoring, transformer chamber 22 door status monitoring, low-voltage chamber door status monitoring, low-voltage chamber temperature and humidity, water immersion, smoke detection monitoring, etc.

[0020] In this embodiment, in step S2, in the initial state of the box-type substation, the electric eel operation system terminal 1 collects the data of all the electric eel sensors 3 as standard basic data; after the box-type substation runs, the electric eel operation system terminal 1 collects the data of all the electric eel sensors 3 in a multi-threaded and multi-dimensional manner in real time for data analysis and processing, compares it with the normal data at the time of factory shipment, and if abnormalities are found after multiple analyses and verifications, the abnormal data is judged as fault data 11.

[0021] In this embodiment, in step S1, a control center 5 is also set, and the control center 5 is connected to the electric eel operation system terminal 1 through network communication. The control center 5 can play roles such as collecting and integrating fault information, providing big data analysis, manually reviewing the rationality of the self-healing strategy, and manually intervening in remote control.

[0022] In this embodiment, in step S3, if the extracted fault feature value 12 cannot be compared to the corresponding fault diagnosis model in the fault database 2, the electric eel operation system terminal 1 will continue to generate a fault diagnosis model for the fault feature value 12 and store it in the fault database 2, and at the same time upload it to the control center 5 through the network. The control center 5 remotely controls the self-healing recovery to achieve rapid power restoration. Thus, the fault features and fault diagnosis models in the fault database 2 can be continuously improved, and when an unknown fault occurs, manual intervention in remote control can be carried out in a timely manner to better ensure the stability of power supply.

[0023] In this embodiment, in step S5, the terminal 1 of the Dianhong operating system also uploads the self-healing recovery strategy to the control center 5 through the network, and the control center 5 remotely controls the self-healing recovery to achieve rapid power supply restoration. The terminal 1 of the Dianhong operating system uploads the self-healing recovery strategy to the control center 5 through the network to achieve remote visual double confirmation, with strong real-time information interaction with the control center 5, and improves the reliability of power supply guarantee.

[0024] In addition, it should be noted that for the specific embodiments described in this specification, the names of their respective parts and the like can be different. Any equivalent or simple changes made according to the structure, features, and principles of the inventive concept of this invention patent are included in the protection scope of this invention patent. Those skilled in the technical field to which this invention pertains can make various modifications, supplements, or use similar methods to substitute for the specific embodiments described, as long as they do not deviate from the structure of this invention or exceed the scope defined by this claim book, they should all fall within the protection scope of this invention.

Claims

1. A method for rapid fault diagnosis and self-healing recovery of box-type substations based on the electric Hong system, characterized in that It includes the following steps: S1. Set up the terminal of the Dianhong operating system and the fault database, deploy a variety of Dianhong sensors inside the box-type substation, and wirelessly communicate and connect the terminal of the Dianhong operating system with all Dianhong sensors; S2. The terminal of the Dianhong operating system collects the operation data and environmental monitoring data of the box-type substation in real time through all Dianhong sensors, and monitors, analyzes and diagnoses these data to judge the fault data; S3. The terminal of the Dianhong operating system preprocesses the fault data and extracts the fault feature values, and compares them with the fault diagnosis models in the fault database to judge the fault type and accurately locate the fault position; S4. The terminal of the Dianhong operating system formulates corresponding self-healing and recovery strategies according to the diagnosed fault type and fault position; S5. The terminal of the Dianhong operating system generates self-healing and recovery instructions according to the self-healing and recovery strategies, and then issues them to the corresponding protection and measurement control unit of the box-type substation, and the protection and measurement control unit executes the self-healing and recovery instructions to achieve rapid power supply restoration.

2. A method for rapid fault diagnosis and self-healing recovery of a box-type substation based on an electric eel system according to claim 1, characterized in that: In step S1, the common fault types are pre-imported into the fault database, and the new fault types and corresponding fault features that appear during the operation of the box-type substation are gradually imported into the fault database to continuously improve the fault types and fault diagnosis models in the fault database.

3. A rapid fault diagnosis and self-healing recovery method for a box-type substation based on an electric Hong system according to claim 1, characterized in that: The box-type substation includes a ring main unit, a transformer room and a low-voltage cabinet; in step S2, a variety of the Dianhong sensors are deployed inside and around the ring main unit, the transformer room and the low-voltage cabinet, and these Dianhong sensors can collect the ring main unit data, transformer data, low-voltage cabinet data and environmental monitoring data in real time.

4. A rapid fault diagnosis and self-healing recovery method for box-type substations based on the electric hong system according to claim 1, characterized in that: In step S2, in the initial state of the box-type substation, the terminal of the Dianhong operating system collects the data of all Dianhong sensors as standard basic data; after the box-type substation runs, the terminal of the Dianhong operating system collects the data of all Dianhong sensors in real time in a multi-threaded and multi-dimensional manner for data analysis and processing, compares them with the normal data at the time of factory, and if any abnormality is found after multiple analysis and verification, the abnormal data is judged as fault data.

5. A method for rapid fault diagnosis and self-healing recovery of a box-type substation based on an electric power system according to claim 1, characterized in that: In step S3, the preprocessing process of the fault data by the terminal of the Dianhong operating system includes: (1) data cleaning: checking for outliers, missing values and duplicate values in the fault data; (2) data conversion: performing standardization and normalization operations on the fault data; (3) data dimensionality reduction: reducing the high-dimensional data to a low-dimensional space through principal component analysis and factor analysis methods to reduce the computational complexity.

6. A method for rapid fault diagnosis and self-healing recovery of a box-type transformer based on an electric power system according to claim 1, characterized in that: In step S1, a control center is set up, and the control center is connected to the terminal of the Dianhong operating system through network communication.

7. A rapid fault diagnosis and self-healing recovery method for a box-type substation based on an electric Hong system according to claim 6, characterized in that: In step S3, if the extracted fault feature values cannot be compared with the corresponding fault diagnosis models in the fault database, the terminal of the Dianhong operating system will continue to generate a fault diagnosis model for the fault feature values and store them in the fault database, and at the same time upload them to the control center through the network, and the control center remotely controls the self-healing and recovery to achieve rapid power supply restoration.

8. A method for rapid fault diagnosis and self-healing recovery of a box-type substation based on the DH system according to claim 6, characterized in that: In the step S5, the terminal of the Dianhong operating system also uploads the self-healing recovery policy to the control center through the network, and the control center remotely controls the self-healing recovery to achieve a rapid power supply recovery.

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