Digital power distribution station house safety management and control system based on cloud edge collaboration

Abstract

The invention discloses a digital power distribution station house safety management and control system based on cloud-side cooperation, which relates to the technical field of power distribution station houses and comprises a data acquisition module, a cloud-side cooperation processing module, an alarm module and a panoramic visualization module. According to the digital power distribution station house safety management and control system based on cloud edge collaboration, the data processing and response speed is greatly improved, so that the system can quickly identify potential safety hazards in a power distribution station house and trigger a corresponding alarm mechanism, and the time from data detection to alarm sending is remarkably shortened; and when the system detects the potential safety hazard, secondary modeling can be quickly performed on the related area of the position of the potential safety hazard, visual potential hazard display is provided for management personnel, a scientific decision-making basis is provided for the management personnel in cooperation with a decision-making support module, and the fault response time is shortened to the greatest extent.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution station, in particular to a digital power distribution station safety management and control system based on cloud-edge collaboration. BACKGROUND

[0002] The power distribution station, also known as a power distribution substation, is a key facility in the power system for distributing electric energy. It usually contains transformers, switches, cables and other key power equipment, and can be divided into substations, distribution stations, switching stations, etc. according to different functions. The power distribution station is at the end of the power grid and is responsible for delivering electric energy to power equipment or user end, including switching stations, ring sites, distribution rooms, box-type substations and other forms. These stations play a key role in the backbone of the power grid and the blood vessels in the power network, ensuring stable and reliable transmission of electric energy.

[0003] The safe operation of the power distribution station is of great significance to the reliability of the entire power grid. In the prior art, real-time monitoring of the power distribution station is usually achieved by using related systems, which collect various data in the station in real time and analyze and process them to discover potential safety hazards and prevent accidents. With the continuous development of technology, existing systems have been able to integrate with other technologies, making their functions more comprehensive and achieving better safety monitoring results. For example, the patent document with publication number CN117422849A discloses a power distribution station panoramic visualization digital management system, method and storage medium. The system can realize three-dimensional modeling of the structure information and object position information of the power distribution station through the data acquisition module and the panoramic visualization module, and obtain the three-dimensional space model of the power distribution station. It also has a model interaction module for responding to triggered operations to transform the three-dimensional space model and display the real-time state of the power equipment and control the power equipment. The above technical solution uses 3D modeling to more intuitively display the equipment state and environmental information inside and outside the power distribution station, and realizes data monitoring of the power distribution station environment. In addition, the system also includes an alarm module for determining power distribution station alarm information based on the state information of the power distribution station, and an information push module for pushing the alarm information to the current user, which, in combination with other modules, achieves a safety warning effect.

[0004] Although the existing power distribution station system of the above-mentioned application has a safety warning function, and the three-dimensional space model of the power distribution station can provide intuitive display when the management personnel investigates problems, in the actual use process, due to the poor data processing and response speed of the existing system, the general three-dimensional space model can only provide the approximate hidden danger or fault condition, and the management personnel often needs to spend a lot of time to locate the problem, and due to the lack of relevant data support, it is difficult for the management personnel to make a quick decision when the accident occurs, thereby delaying the emergency response time, causing the accident to expand, and being not conducive to the safe, reliable and efficient operation of the power distribution station.

[0005] Therefore, it is urgent to improve this defect, and the present application is researched and improved in view of the existing technology and deficiencies, and provides a digital power distribution station safety management and control system based on cloud edge collaboration. SUMMARY

[0006] The present application aims to provide a digital power distribution station safety management and control system based on cloud edge collaboration to solve the problems raised in the background art.

[0007] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0008] A digital power distribution station safety management and control system based on cloud edge collaboration, comprising a data acquisition module for acquiring various data in the power distribution station, including environmental data, equipment data, and running state data, and further comprising a cloud edge collaborative processing module, an alarm module and a panoramic visualization module;

[0009] The cloud edge collaborative processing module is used for receiving the data transmitted by the data acquisition module, rapidly analyzing and processing the data by using cloud computing and edge computing technology, and identifying potential safety hazards;

[0010] The alarm module is used for sending alarm information to the management personnel when the cloud edge collaborative processing module discovers potential safety hazards, and triggering the panoramic visualization module through the internal interface of the system;

[0011] The panoramic visualization module is used for establishing a three-dimensional space model of the power distribution station according to the power distribution station data, performing secondary modeling on the position with safety hazards, and displaying the hazard condition and regional details; the panoramic visualization module specifically comprises the following sub-modules:

[0012] Panoramic modeling sub-module: according to the actual layout and equipment configuration of the power distribution station, a three-dimensional space model is constructed by using three-dimensional modeling software and panoramic visualization technology to display the equipment distribution and running state in the power distribution station, and the model is continuously updated and improved, and the three-dimensional space model is continuously regenerated according to the latest data to cover the original model;

[0013] Local modeling submodule: when receiving alarm information, locate the hidden danger area in the three-dimensional model of the power distribution station according to the location information of the hidden danger, and expand secondary modeling combined with the content of the hidden danger to generate a three-dimensional model of the hidden danger area, and show the details of the hidden danger and the area;

[0014] Simulation modeling submodule: support managers to perform simulation operations in a virtual scene, accept and analyze the simulation operation instructions of managers, and generate corresponding three-dimensional models based on the instruction content to show the instruction operation effect, discover potential risks and problems, and adjust and optimize the instructions in time.

[0015] Further, the cloud-edge collaborative processing module specifically includes the following processing steps:

[0016] S1, data preprocessing: the edge computing device receives the raw data from the sensor and performs preliminary data cleaning, format conversion and compression;

[0017] S2, data uploading: after the preprocessed data is encrypted, it is transmitted to the cloud computing center through high-speed network;

[0018] S3, cloud computing analysis: the cloud computing center receives data from the edge computing device and performs deep analysis and mining on the data to identify abnormal data or potential security risks;

[0019] S4, result feedback: the cloud computing center feeds back the analysis result to the edge computing device, and if potential security risks are found, the alarm module will be triggered and the emergency response mechanism will be started at the same time.

[0020] Further, the system further includes:

[0021] The decision support module is used to provide data support for managers to help them make decisions to minimize fault response time;

[0022] The remote control module is used to provide a remote control interface to allow managers to remotely control the power distribution station through the system;

[0023] The emergency response module is used to automatically trigger and execute a series of emergency measures when the remote control module cannot respond or handle security risks in time;

[0024] The update checking module is used to check whether there is an update in the power distribution station according to the latest power distribution station data, and sends the update information to the panoramic visualization module to build the latest three-dimensional space model of the power distribution station.

[0025] Further, the cloud computing center uses a distributed storage system to receive and store data from the edge computing device, and performs data backup and disaster recovery processing while storing data;

[0026] The cloud computing center uses a big data processing engine to perform in-depth analysis and mining of the stored data. Specifically, the cloud computing center uses machine learning algorithms to build predictive models and uses these models to identify potential security risks. These machine learning algorithms include, but are not limited to, support vector machines, decision trees, and neural networks.

[0027] Furthermore, the data backup specifically includes:

[0028] Local backup: A copy of the data is stored on each node of the distributed storage system;

[0029] Off-site backup: Backing up data to a backup center located geographically far away to prevent data loss due to force majeure.

[0030] Furthermore, the disaster recovery process specifically includes:

[0031] Fault detection and recovery: The distributed storage system has a fault detection mechanism that can promptly detect and locate faulty nodes. Once a fault is detected, the system will automatically trigger a data recovery process to recover data from other nodes.

[0032] Data migration: Regularly migrate data from nodes with high failure rates to more reliable nodes to avoid the risk of single points of failure and data loss;

[0033] Disaster Recovery Plan: The cloud computing center develops a detailed disaster recovery plan, including data recovery processes, recovery time targets, and recovery point targets, to ensure that business operations can be quickly restored in the event of a disaster.

[0034] Furthermore, the alarm module sends alarm information to management personnel via SMS, email, telephone, APP push, and instant messaging software. The alarm information includes at least the location of the hazard, time information, and information of the equipment affected by the hazard. The alarm module uses natural language processing technology to automatically classify and summarize the alarm information, and combines it with voice recognition technology to realize voice alarms, so that management personnel can receive and process alarm information in a timely manner even when they cannot check their mobile phones or computers.

[0035] Furthermore, the decision support module includes the following functions: displaying a 3D model and related data of the potential hazard area to help managers understand the hazard situation, providing analysis reports based on historical and real-time data to provide decision-making basis for managers, and supporting managers to conduct simulation operations in the system to evaluate the effectiveness of different decision-making schemes.

[0036] Furthermore, the emergency response module specifically includes the following sub-modules:

[0037] The timeout judgment submodule is used for monitoring the processing situation of the remote control module on the security risks, and setting a response time threshold to judge whether there is an unprocessed timeout situation;

[0038] The mechanism matching submodule is used for matching the corresponding emergency response mechanism according to the type and severity of the security risks;

[0039] The automatic response submodule is used for automatically executing the corresponding emergency measures after determining the emergency response mechanism;

[0040] The response recording submodule is used for recording the execution situation of the emergency response module in real time by using the system internal log recording and database functions, and providing query and report functions.

[0041] Further, the implementation mode of the update checking module: periodically or on demand, the data of the power distribution station is updated and checked, through comparing historical data and real-time data, the equipment update or layout adjustment is identified, and the update information is sent to the panoramic visualization module, to build the latest three-dimensional space model.

[0042] The application provides a digital power distribution station safety management and control system based on cloud edge collaboration, which has the following beneficial effects:

[0043] The application adopts cloud edge collaboration technology, which combines the advantages of edge computing devices and cloud computing centers, greatly improves the data processing and response speed, enables the system to quickly analyze and process various data in the power distribution station, thereby quickly identifying potential safety hazards in the power distribution station, and triggering the corresponding alarm mechanism, significantly shortening the time from data detection to alarm issuance. When the system detects a safety hazard, in combination with the three-dimensional space model of the power distribution station established by the panoramic visualization technology, the related area of the hazard location can be quickly modeled again. This not only shortens the time to obtain the three-dimensional model, but also provides a visual hazard display for the management personnel, and provides scientific decision-making basis for the management personnel with the decision support module, which helps the management personnel to make quick and accurate decisions in emergency situations, thereby greatly reducing the fault response time, and is beneficial to the safe, reliable and efficient operation of the power distribution station.

[0044] In addition, during the safety hazard processing process, the management personnel can refer to the hazard area situation displayed by the local modeling submodule and use the simulation modeling submodule to simulate the instruction running. Through simulation running, the management personnel can understand the execution effect of the instruction without contacting the actual equipment, thereby avoiding potential safety risks, and can evaluate the advantages and disadvantages of different instructions by observing the effect of simulation running, thereby selecting the best operation and maintenance strategy, and further avoiding equipment damage and maintenance costs caused by incorrect instructions or improper operation. BRIEF DESCRIPTION OF DRAWINGS

[0045] Fig. 1 This is a logical architecture diagram of a cloud-edge collaborative digital power distribution room safety management and control system according to the present invention.

[0046] Fig. 2 This is a schematic diagram of the operation process of a panoramic visualization module of a cloud-edge collaborative digital power distribution station safety management and control system according to the present invention.

[0047] Fig. 3 This is a schematic diagram of the operation process of the emergency response module of a cloud-edge collaborative digital power distribution station safety management system according to the present invention. Detailed Implementation

[0048] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0049] like Figs. 1-3 As shown, a digital power distribution station safety management and control system based on cloud-edge collaboration includes a data acquisition module, a cloud-edge collaborative processing module, an alarm module, a panoramic visualization module, a decision support module, a remote control module, an emergency response module, and an update and inspection module.

[0050] Data acquisition module: Collects various data within the power distribution room, including environmental data (such as temperature and humidity), equipment data (such as voltage, current, and power factor), and operating status data. In this embodiment, the data acquisition module collects data in real time through various sensors, monitoring devices, and smart meters installed in the power distribution room, and transmits the data to the system via wired or wireless means.

[0051] The cloud-edge collaborative processing module receives data transmitted from the data acquisition module, and uses cloud computing and edge computing technologies to quickly analyze and process the data, identifying potential security risks. Specifically, it includes the following processing steps:

[0052] S1, data preprocessing: the edge computing device receives raw data from sensors and performs preliminary data cleaning (deleting redundant, erroneous and missing data), format conversion (the edge computing device converts data into a unified standard format such as JSON, XML, etc. to facilitate subsequent data processing and analysis, and for complex data structures, the edge computing device will perform necessary conversion such as flattening nested data structures into flat structures or converting data into formats suitable for specific analysis algorithms), and compression (to save storage space and transmission bandwidth, data is lossless compressed or lossy compressed. For scenarios where data integrity needs to be maintained, the edge computing device will use lossless compression algorithms such as gzip, zip, etc. to significantly reduce data volume without losing original data information. For scenarios where data quality is not high or a certain degree of data loss is allowed, the edge computing device will use lossy compression algorithms to reduce data volume to a greater extent, but at the expense of certain data quality); in this embodiment, by deploying edge computing devices near power distribution stations, preliminary processing of data is performed to make data more easily transmitted and analyzed, reduce the burden on the cloud computing center, and improve response speed;

[0053] S2, data upload: according to the sensitivity and transmission requirements of the data, symmetric encryption (such as AES algorithm), asymmetric encryption (such as RSA algorithm) or hybrid encryption is selected to encrypt the preprocessed data, and then transmitted to the cloud computing center through high-speed network;

[0054] S3, cloud computing analysis: the cloud computing center receives data from the edge computing device and performs deep analysis and mining on the data to identify abnormal data or potential security risks;

[0055] S4, result feedback: the cloud computing center feeds back the analysis result to the edge computing device, and if potential security risks are found, the alarm module will be triggered and the emergency response mechanism will be started at the same time.

[0056] In this embodiment, the cloud computing center uses a distributed storage system to receive and store data from the edge computing device, and at the same time of data storage, data backup and disaster recovery processing are performed;

[0057] 1) Data backup specifically includes:

[0058] Local backup: a copy of the data is stored on each node of the distributed storage system to ensure that the data can be recovered in the event of node failure;

[0059] Off-site backup: backup the data to a backup center that is geographically far apart to prevent data loss caused by natural disasters and other irresistible factors;

[0060] 2) Disaster recovery processing specifically includes:

[0061] Fault detection and recovery: The distributed storage system has a fault detection mechanism that can promptly detect and locate faulty nodes. Once a fault is detected, the system will automatically trigger a data recovery process to recover data from other nodes.

[0062] Data migration: Regularly migrate data from nodes with high failure rates to more reliable nodes to avoid the risk of single points of failure and data loss;

[0063] Disaster Recovery Plan: The cloud computing center develops a detailed disaster recovery plan, including data recovery processes, recovery time objectives (RTO), and recovery point objectives (RPO), to ensure that business operations can be quickly restored in the event of a disaster.

[0064] In this embodiment, the cloud computing center utilizes big data processing engines such as Apache Spark and Hadoop to perform deep analysis and mining of stored data. Specifically, the cloud computing center uses machine learning algorithms to build predictive models and identify potential security vulnerabilities. These machine learning algorithms include, but are not limited to, support vector machines, decision trees, and neural networks. The specific process is as follows: In the cloud computing center, big data analysis algorithms are used to extract features from preprocessed data, identifying features useful for anomaly detection and security alerts. Then, machine learning algorithms, combined with historical data and the feature extraction results, are used to train a predictive model for anomaly detection and security alerts. During subsequent use, the cloud computing center receives data from edge computing devices in real time and uses the trained predictive model to perform online data detection. Furthermore, the predictive model is continuously optimized based on new data and user feedback.

[0065] Alarm Module: When the cloud-edge collaborative processing module detects potential security risks, it immediately sends alarm information to the administrators and triggers the panoramic visualization module through the system's internal interface. In this embodiment, the alarm module sends alarm information to the administrators through various alarm methods such as SMS, email, telephone, APP push, and instant messaging software, ensuring that they can receive and handle the alarms in a timely manner. The alarm information includes at least the location of the risk, the time information, and the equipment information affected by the risk. The alarm module uses natural language processing technology to automatically classify and summarize the alarm information, helping the administrators to understand the alarm situation more quickly. It also combines voice recognition technology to realize voice alarms, enabling the administrators to receive and handle alarm information in a timely manner even when they cannot check their mobile phones or computers.

[0066] Panoramic Visualization Module: This module builds a 3D spatial model of the substation based on substation data and performs secondary modeling for locations with potential safety hazards when necessary, to display the hazard situation and regional details in detail. This module specifically includes the following sub-modules:

[0067] The panoramic modeling submodule receives the actual layout, equipment configuration, and running state of the power distribution station, and then uses a three-dimensional modeling software to construct a three-dimensional space model of the power distribution station according to the collected data, accurately reflecting the position, shape, and running state of the equipment and other information. Whenever new equipment is added or the layout changes, the submodule needs to regenerate the three-dimensional space model according to the latest data and replace the original model to reflect the latest changes in the power distribution station, ensuring the accuracy and timeliness of the model.

[0068] The local modeling submodule receives alarm information from the alarm module, including the location, type, and severity of the hidden danger, and then locates the hidden danger area in the three-dimensional model of the power distribution station according to the location information in the alarm information. Then, combined with the hidden danger content, the hidden danger area is modeled again to generate a detailed three-dimensional model that accurately reflects the structure, equipment layout, and specific situation of the hidden danger area. The application of this module not only helps users quickly locate and understand the situation of the hidden danger area, but also provides strong support for subsequent fault handling and maintenance work. Through this module, users can more intuitively understand the structure and equipment layout of the hidden danger area, and thus more accurately develop maintenance plans and implement maintenance work.

[0069] The simulation modeling submodule supports managers to perform simulation operations in a virtual scene, receives and analyzes the simulation operation instructions of managers, and generates corresponding three-dimensional models based on the instruction content to display the instruction operation effect. Managers can evaluate the feasibility and safety of the instructions by observing these effects, and can discover potential risks and problems such as equipment conflicts and environmental abnormalities during the simulation operation, and timely adjust and optimize the instructions to avoid these risks before the formal issuance of the instructions, ensuring the safe operation of the power distribution station. Workflow: This submodule first receives simulation operation instructions from managers and analyzes them, then generates corresponding three-dimensional models based on the instruction content using three-dimensional modeling technology, and displays the instruction operation effect. Managers can evaluate the feasibility and safety of the instructions by observing the generated three-dimensional models and operation effects. If potential risks and problems such as equipment conflicts and environmental abnormalities are found, managers can timely adjust and optimize the instructions to ensure the safe operation of the power distribution station.

[0070] In this embodiment, when potential safety hazards are found, the cooperation of the panoramic modeling submodule and the local modeling submodule can effectively simplify the three-dimensional modeling process of the hazard area, so as to quickly obtain the hazard situation and the details of the area, thereby helping to accelerate the efficiency of hazard processing. During the processing process, the management personnel can refer to the hazard area situation displayed by the local modeling submodule and use the simulation modeling submodule to simulate the operation of the instruction; through the simulation operation, the management personnel can understand the execution effect of the instruction without contacting the actual equipment, thereby avoiding potential safety risks, and can evaluate the pros and cons of different instructions by observing the effect of the simulation operation, so as to select the best operation and maintenance strategy, and further avoid equipment damage and maintenance costs caused by incorrect or improper operation of the instruction.

[0071] The three modules closely cooperate with each other and jointly constitute the core function of the panoramic visualization module. The panoramic modeling submodule provides a basic three-dimensional space model for the power distribution station, the local modeling submodule provides a detailed hazard area model when an alarm is given, and the simulation modeling submodule supports the management personnel to perform simulation operations in a virtual scene to evaluate the feasibility and safety of the instruction. The cooperation among them is reflected in that the three modules share the relevant data of the power distribution station and update the model according to the latest data to ensure the accuracy and timeliness of the model. Moreover, the functions are complementary, the panoramic modeling submodule provides an overall three-dimensional space model, the local modeling submodule provides a detailed hazard area model, and the simulation modeling submodule supports the management personnel to perform simulation operations. The three modules complement each other in function and jointly meet the demand of panoramic visualization of the power distribution station. Through the cooperation of the three modules, the management personnel can more intuitively understand the running state of the power distribution station, the hazard situation and the instruction operation effect, so as to more accurately make decisions and implement maintenance work.

[0072] The decision support module provides data support for the management personnel to help them make decisions to minimize the fault response time; the functions of this module include: displaying the three-dimensional model of the hazard area and related data such as temperature, humidity, current, etc., helping the management personnel to understand the hazard situation, and providing analysis reports based on historical data and real-time data to provide decision basis for the management personnel, while supporting the management personnel to perform simulation operations in the system to evaluate the effects of different decision schemes;

[0073] The remote control module provides a remote control interface to allow the management personnel to remotely control the power distribution station through the system, such as shutting down dangerous equipment, starting the standby power supply, etc.;

[0074] The emergency response module automatically triggers and executes a series of emergency measures when the remote control module cannot respond or handle the safety hazard in time; this module specifically includes the following submodules:

[0075] The timeout judgment submodule monitors the processing of the remote control module on the security risks, and sets a response time threshold to determine whether there is an unprocessed timeout condition;

[0076] The mechanism matching submodule matches the corresponding emergency response mechanism according to the type and severity of the security risks. The submodule pre-sets multiple emergency response mechanisms, such as shutting down dangerous equipment, starting a backup power supply, starting a fire extinguishing system, etc. When triggered, the system internal logic and rule engine are used to automatically match the most suitable emergency response mechanism according to the specific information of the security risks (such as type, location, severity, etc.);

[0077] The automatic response submodule automatically executes the corresponding emergency measures after the mechanism matching submodule determines the emergency response mechanism. Specifically, through the system internal interface and the remote control protocol, the automatic response submodule automatically controls the related equipment in the power distribution station, such as shutting down dangerous equipment, starting a backup power supply, etc. If necessary, through integration with other systems (such as a fire extinguishing system, a monitoring system, etc.), more complex emergency response operations can be achieved.

[0078] The response recording submodule uses the system internal log recording and database function to record the execution of the emergency response module in real time, including the triggering time, the executed emergency measures, the execution result, etc. The response recording submodule also provides query and report functions to facilitate management personnel to view and analyze the execution history of the emergency response module.

[0079] The update checking module checks whether there is an update in the power distribution station according to the latest power distribution station data, such as equipment update, layout adjustment, etc. The update checking module sends the update information to the panoramic visualization module to build the latest three-dimensional space model of the power distribution station. In this embodiment, the implementation of the update checking module is as follows: the data of the power distribution station is periodically or on-demand updated and checked. By comparing the historical data and the real-time data, the update information such as equipment update or layout adjustment is identified and sent to the panoramic visualization module to build the latest three-dimensional space model.

[0080] Embodiments of the present application are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the application to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. Embodiments are chosen and described in order to best explain the principles of the application and its practical application, and to enable others skilled in the art to understand the application for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A cloud-edge collaboration-based digital power distribution station safety management and control system, comprising a data acquisition module, the data acquisition module is used for acquiring various data in the power distribution station, including environmental data, equipment data, running state data, characterized in that, Also include cloud edge collaborative processing module, alarm module and panoramic visualization module; The cloud edge collaborative processing module is used for receiving data transmitted by the data acquisition module, using cloud computing and edge computing technology to quickly analyze and process data, and identifying potential security risks; The alarm module is used for sending alarm information to the management personnel when the cloud edge collaborative processing module discovers potential security risks, and triggering the panoramic visualization module through the internal interface of the system; The panoramic visualization module is used for establishing a power distribution station three-dimensional space model according to power distribution station data, and performing secondary modeling on the position with security risks to show the risk situation and regional details; The panoramic visualization module specifically Comprise the following sub-modules: Panoramic modeling submodule: according to the actual layout and equipment configuration of the power distribution station, a three-dimensional space model is constructed by using three-dimensional modeling software and panoramic visualization technology to show the equipment distribution and running state in the power distribution station, and the model is continuously updated and improved, and the three-dimensional space model is regenerated according to the latest data to cover the original model; Local modeling submodule: when receiving the alarm information, the hidden danger area is located in the three-dimensional model of the power distribution station according to the hidden danger position information, and the three-dimensional model of the hidden danger area is generated by expanding secondary modeling combined with the hidden danger content, and the hidden danger situation and regional details are displayed in detail; Simulation modeling submodule: support management personnel to perform simulation operation in virtual scene, accept and analyze simulation operation instructions of management personnel, and generate corresponding three-dimensional model based on instruction content, show instruction operation effect, find potential risks and problems, and timely adjust and optimize instructions.

2. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 1, characterized in that, The cloud edge collaborative processing module specifically comprises the following processing steps: S1, data preprocessing: the edge computing device receives the original data from the sensor, and performs preliminary data cleaning, format conversion and compression; S2, data uploading: after the preprocessed data is encrypted, it is transmitted to the cloud computing center through high-speed network; S3, cloud computing analysis: the cloud computing center receives data from the edge computing device, and performs deep analysis and mining on the data to identify abnormal data or potential security risks; S4, result feedback: the cloud computing center feeds back the analysis result to the edge computing device, and if potential security risks are found, the alarm module is triggered, and the emergency response mechanism is started at the same time.

3. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 1, characterized in that, The system further comprises: Decision support module, for providing data support for management personnel to help them make decisions to minimize fault response time; Remote control module, for providing a remote control interface to allow management personnel to remotely control the power distribution station through the system; Emergency response module, for automatically triggering and executing a series of emergency measures when the remote control module cannot respond or process security risks in time; Update checking module, for checking whether there is an update in the power distribution station according to the latest power distribution station data, and sending the update information to the panoramic visualization module to build the latest power distribution station three-dimensional space model.

4. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 1, characterized in that, The cloud computing center uses a distributed storage system to receive and store data from the edge computing device, and performs data backup and disaster recovery processing while storing data; The cloud computing center utilizes a big data processing engine to conduct deep analysis and mining on the stored data. Specifically, the cloud computing center constructs a prediction model by running a machine learning algorithm, and identifies potential security risks by using the model. The machine learning algorithm includes, but is not limited to, support vector machine, decision tree, and neural network.

5. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 4, characterized in that, The data backup specifically includes: Local backup: storing a copy of the data on each node of the distributed storage system; Remote backup: backing up the data to a backup center that is geographically far away to prevent data loss caused by force majeure factors.

6. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 4, characterized in that, The disaster recovery process specifically includes: Fault detection and recovery: the distributed storage system has a fault detection mechanism that can timely detect and locate faulty nodes. Once a fault is detected, the system automatically triggers a data recovery process to recover data from other nodes; Data migration: periodically migrating data from nodes with high failure rates to more reliable nodes to avoid single point of failure and data loss risks; Disaster recovery plan: the cloud computing center formulates a detailed disaster recovery plan, including data recovery process, recovery time objective, and recovery point objective, to ensure that business operations can be quickly restored in the event of a disaster.

7. The cloud-edge collaboration based digital power distribution station safety management and control system according to claim 1, characterized in that, The alarm module sends alarm information to the management personnel through the ways of SMS, email, phone, APP push, and instant messaging software. The alarm information at least includes the location of the hidden danger, time information, and equipment information affected by the hidden danger. The alarm module uses natural language processing technology to automatically classify and summarize the alarm information, and combines voice recognition technology to realize voice alarm, so that the management personnel can also receive and process alarm information in time without checking mobile phones or computers.

8. The cloud-edge collaboration-based digital power distribution station safety management and control system according to claim 3, characterized in that, The decision support module has the following functions: displaying a three-dimensional model of the hidden danger area and related data to help the management personnel understand the hidden danger situation, and providing analysis reports based on historical data and real-time data to provide decision basis for the management personnel, while supporting the management personnel to perform simulation operations in the system to evaluate the effects of different decision schemes.

9. The cloud-edge collaboration based digital power distribution station safety management and control system according to claim 3, characterized in that, The emergency response module specifically includes the following sub-modules: Timeout judgment sub-module: used to monitor the processing of the remote control module on the security risk, and set a response time threshold to determine whether there is a timeout situation; Mechanism matching sub-module: used to match the corresponding emergency response mechanism according to the type and severity of the security risk; Automatic response sub-module: used to automatically execute the corresponding emergency measures after determining the emergency response mechanism; Response record sub-module: used to record the execution of the emergency response module in real time by using the system internal log record and database function, and provide query and report functions.

10. The cloud-edge collaboration based digital power distribution station safety management and control system according to claim 3, characterized in that, The implementation of the update checking module: periodically or on demand, the data of the power distribution station is checked for updates, by comparing historical data and real-time data, identifying equipment updates or layout adjustments, and sending the update information to the panoramic visualization module to build the latest three-dimensional space model.

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