A method and device for judging power outage areas in low-voltage distribution areas based on edge computing

Abstract

An embodiment of the present invention discloses a method and device for judging power outage areas in low-voltage power distribution areas based on edge computing. The method includes: issuing a data template to be collected according to the power outage situation and current status of each low-voltage power distribution area, and respectively monitoring data on the low-voltage side of the distribution transformer, branch box, and user side according to the data template to be collected; installing edge computing terminal devices on the devices to be monitored according to the order of the equipment inventory of the low-voltage power distribution area; in the edge computing terminal devices, judging power outages according to the collected data, determining power outage equipment and dividing power outage areas. The power outage judgment adopts an "end-to-end" decentralized architecture data model, with "transformer substation-branch box-user" as the data chain level, and an "end-to-end" data transmission method is adopted between the data chain levels; realizing the "end-to-end" data transmission mode can more intuitively obtain data for information transmission and processing, providing strong support for the judgment of power outage areas.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid fault power outage detection, and particularly to a method and device for judging power outage areas in low-voltage substations based on edge computing. Background Art

[0002] Electricity is the basic guarantee for China's urbanization construction and the improvement of basic industrialization. Ensuring the uninterrupted supply of electricity is an issue that cannot be relaxed. In recent years, the power outage time has been too long and the number of power outages has been frequent in each low-voltage substation, resulting in many customer complaints and heavy maintenance work. With the rapid spread of modern information, the social public opinion after a power outage may also deteriorate rapidly. The rapid judgment of power outage areas has thus become an important measure for rapid maintenance, reducing the number and duration of power outages, improving the quality of user use, and reducing social impacts.

[0003] Currently, for the judgment of power outage areas in most parts of the country, data needs to be uploaded to a unified data center, calculated on the cloud, and then the judgment results of power outage areas in low-voltage substations are sent down, and then inspection work orders are sent down for inspection and repair work by inspection personnel. This method has a relatively large data transmission pressure and low processing efficiency. Currently, there is a lack of a fast and accurate judgment method for medium and low-voltage substations, resulting in a high complaint rate, and more power outage times and durations. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method and device for judging power outage areas in low-voltage substations based on edge computing, realizing an "end-to-end" data transmission mode, more intuitively obtaining data for information transmission and processing, and providing strong support for the judgment of power outage areas.

[0005] To achieve the above object, the present application provides a method for judging power outage areas in low-voltage substations based on edge computing, the method comprising:

[0006] According to the power outage situation and current status of each low-voltage substation, a data template to be collected is sent down, and data monitoring is respectively carried out on the low-voltage side of the distribution transformer, the branch box, and the user side according to the data template to be collected;

[0007] Edge computing end devices are installed on the devices to be monitored according to the order of the equipment ledgers of the low-voltage substations;

[0008] In the edge computing end device, power outage judgment is carried out according to the collected data to determine the power outage equipment and divide the power outage area. The power outage judgment adopts an "end-to-end" decentralized architecture data model, with "transformer substation-branch box-user" as the data chain level, and an "end-to-end" data transmission mode is adopted between the data chain levels.

[0009] Optionally, the data monitoring is respectively carried out on the low-voltage side of the distribution transformer, the branch box, and the user side according to the data template to be collected, including:

[0010] Perform any one or more of the following on the low-voltage side of the distribution transformer: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring;

[0011] Perform any one or more of the following on the branch box: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring;

[0012] Perform any one or more of the following on the user side: voltage quality monitoring, voltage anomaly monitoring, cable flow monitoring, cable temperature monitoring, electrical fire risk assessment monitoring, power outage monitoring.

[0013] Optionally, the edge computing terminal device includes: a main terminal installed on the bus voltage transformation device, and sub-terminals installed on other devices;

[0014] The main terminal is used for data collection, monitoring, and research and judgment analysis. The data collection includes but is not limited to three-phase voltage, current, and transformer load data;

[0015] The sub-terminal is used for data collection. The data collection includes but is not limited to three-phase voltage, current, current-carrying capacity, and temperature data;

[0016] Among them, the main terminal is an integrated device, including a chip, an operating system, and data collection and monitoring software; the sub-terminal communicates with the main terminal and transmits the collected data back to the main terminal.

[0017] Optionally, the "end-to-end" decentralized architecture data model includes:

[0018] A data collection module, a data monitoring module, a big data analysis architecture model, a fault data module, and a research and judgment module.

[0019] Optionally, through the data collection module, perform the following functions:

[0020] Based on the low-voltage station equipment ledger, establish an access terminal equipment ledger, which is used to view the data collected by the terminal equipment in real time and view historical data;

[0021] Based on the low-voltage station equipment ledger and the access terminal equipment ledger, establish a data topology diagram, which is used for visual viewing and real-time observation of abnormal data;

[0022] The collected data is performed in a polling manner, with multiple data calls, and data synchronization processing is performed on the collected data.

[0023] Optionally, through the data monitoring module, perform the following functions:

[0024] Within a preset duration after the data anomaly occurs, the master terminal receives the perceived anomaly information, analyzes the situation of the perceived anomaly information, judges the power outage situation, and outputs a specific situation description;

[0025] After an anomaly occurs in the low-voltage distribution area equipment, visually display the affected power outage area and send an alarm notification to the relevant area monitoring personnel.

[0026] Optionally, perform structured processing on all incoming data through the big data analysis architecture model, perform distributed computing, and use the big data stream processing method to speed up the power outage judgment.

[0027] Optionally, through the judgment module, perform the following functions:

[0028] Data transceiver control: Control the transceiver of data affecting the power outage in the low-voltage distribution area, issue control strategies at the "transformer substation - branch box - user" level, use the clustering algorithm and multi-hop forwarding algorithm for data reception and transmission, complete the terminal data transceiver between each level, and realize the data transceiver of the data links of "transformer substation - branch box" and "transformer substation - user";

[0029] Terminal autonomous collaboration: The low-voltage distribution area performs terminal autonomous collaboration through the data links of "transformer substation", "transformer substation - branch box", and "transformer substation - user", decomposes each judgment task, and uses the zero-sequence algorithm to add autonomous judgment;

[0030] Terminal information fusion: Layer all information and perform information fusion through multi-level algorithms.

[0031] Optionally, the terminal autonomous collaboration specifically includes:

[0032] Terminal information interaction: Unify the data resource interface, use the "end-to-end" data transmission method, model and decompose the judgment task in the form of "total - sub - total", and then merge after each sub - task judgment is completed on each edge computing side;

[0033] Simulation modeling: Use the normal data of each device in the low-voltage distribution area to perform simulation data modeling;

[0034] Autonomous judgment: On the edge computing side, use the simulation data after simulation modeling and the collected real-time data, calculate and compare through the zero-sequence algorithm, judge whether there is data beyond the error. If there is such data, determine that the device is powered off, find the powered-off device on the "transformer substation - branch box - user" data chain, and divide the power outage area;

[0035] The terminal information fusion specifically includes:

[0036] Information fusion: The hierarchical device information is divided into three levels for information fusion, including data level, feature level, and decision level;

[0037] Model algorithm: An information fusion model is constructed, and weighted average calculations are performed through information fusion algorithms and intelligent decision-making algorithms;

[0038] Intelligent decision-making: Through the terminal information fusion, autonomous information processing and decision-making are carried out on the edge computing side to make decisions on the judgment and warning of the power outage area in the low-voltage substation area.

[0039] On the other hand, this application also provides a device for judging the power outage area in the low-voltage substation area based on edge computing, including:

[0040] A data acquisition module, a data monitoring module, a big data analysis architecture model, a fault data module, and a judgment module, where:

[0041] The data acquisition module is used to establish an access terminal device ledger based on the low-voltage substation area device ledger. The access terminal device ledger is used to view the data collected by the terminal device in real time and view historical data; based on the low-voltage substation area device ledger and the access terminal device ledger, a data topology map is established. The data topology map is used for visual viewing and real-time observation of abnormal data; the collected data is polled, called multiple times, and data synchronization processing is performed on the collected data;

[0042] The data monitoring module is used to receive the sensed abnormal information by the master terminal within a preset time after the data appears abnormal, analyze the situation of the sensed abnormal information, judge the power outage situation, and output a specific situation description; after the low-voltage substation area device appears abnormal, visualize the affected power outage area and send an alarm notification to the relevant area monitoring personnel;

[0043] The big data analysis architecture model is used to perform structured processing on all incoming data, perform distributed calculations, and use the big data stream processing method to speed up the power outage judgment;

[0044] The fault data module is used to generate a corresponding fault report based on the fault data ledger, and generate a corresponding fault situation analysis and solution;

[0045] The judgment module is used for:

[0046] Data transceiver control: Control the transceiver of the data affecting the power outage in the low-voltage substation area, issue control strategies at the "transformer substation - branch box - user" level, use clustering algorithms and multi-hop forwarding algorithms for data reception and transmission, complete the terminal data transceiver between each level, and realize the data transceiver of the data links of "transformer substation - branch box" and "transformer substation - user";

[0047] Terminal autonomous collaboration: The low-voltage power distribution area conducts terminal autonomous collaboration through the data links of "transformer substation", "transformer substation - branch box", and "transformer substation - user", decomposes each judgment task, and uses the zero-sequence algorithm to add autonomous judgment.

[0048] Terminal information fusion: Stratify all information and perform information fusion through multi-level algorithms.

[0049] On the other hand, this application provides an electronic device, including a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps of the first aspect and any possible implementation manner thereof.

[0050] On the other hand, this application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor is caused to execute each step in the method described in the first aspect.

[0051] This application provides a method and device for judging the power outage area of a low-voltage power distribution area based on edge computing. By relying on the power outage situation and current status of each low-voltage power distribution area, a data template to be collected is issued, and data monitoring is respectively carried out on the low-voltage side of the distribution transformer, the branch box, and the user side according to the data template to be collected; according to the order of the equipment account books of the low-voltage power distribution area, edge computing terminal devices are installed on the devices to be monitored; inside the edge computing terminal devices, power outage judgment is carried out according to the collected data to determine the power outage devices and divide the power outage area. The power outage judgment adopts an "end-to-end" decentralized architecture data model, with "transformer substation - branch box - user" as the data chain level, and an "end-to-end" data transmission mode is adopted between the data chain levels; realizing the "end-to-end" data transmission mode can more intuitively obtain data for information transmission and processing, accurately obtain the power outage situation of the low-voltage power distribution area, provide strong support for the judgment of the power outage area, and each power supply bureau and department can also analyze based on this data to conduct long-term and effective management and control of power outage judgment and alarm, reducing the power outage time and inspection duration. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0053] Among them:

[0054] Figure 1 It is a schematic flowchart of a method for judging the power outage area of a low-voltage power distribution area based on edge computing provided by an embodiment of the present application.

[0055] Figure 2 A schematic diagram of device distribution provided by an embodiment of the present application;

[0056] Figure 3 A schematic diagram of a service process provided by an embodiment of the present application;

[0057] Figure 4 A schematic diagram of a big data analysis architecture model provided by an embodiment of the present application;

[0058] Figure 5 A schematic diagram of a power outage judgment service provided by an embodiment of the present application;

[0059] Figure 6 A schematic diagram of the structure of a power outage area judgment device for a low-voltage power distribution area based on edge computing provided by an embodiment of the present application. Detailed implementation manners

[0060] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0061] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or devices.

[0062] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0063] The edge computing mentioned in the embodiments of this application refers to an open platform that integrates network, computing, storage, and application core capabilities on the side close to the object or the data source, providing the nearest-end services nearby. Its application programs are initiated on the edge side, generating faster network service responses and meeting the basic needs of the industry in aspects such as real-time services, application intelligence, security, and privacy protection. Edge computing is located between physical entities and industrial connections, or at the top of physical entities. And cloud computing can still access the historical data of edge computing.

[0064] The substation transformer (platform transformer) mentioned in the embodiments of this application is composed of a transformer and high-voltage and low-voltage switchgear, mainly used for power transformation and distribution. It can transform the electric energy of the high-voltage power grid into low-voltage electric energy that meets the needs of places such as industrial and mining enterprises, municipal buildings, and scenic spots, thereby meeting the power demand. During peak periods, it can be controlled in a time-sharing and sectional manner according to needs to achieve the purpose of energy conservation and consumption reduction.

[0065] The end-to-end involved in the embodiments of this application is a communication and computing mode, emphasizing the integrity and reliability of the entire system or process. In this mode, each component of the entire system or process is regarded as an endpoint, and they jointly constitute a complete end-to-end system. The concept of end-to-end originally originated from network connections, where regardless of how complex the physical path of data transmission is, the logical connection between the source and the destination is regarded as direct and continuous. In the embodiments of this application, it specifically mainly refers to the communication between the sub-terminal and the main-terminal devices in the edge computing end device.

[0066] The embodiments of this application will be described below with reference to the accompanying drawings in the embodiments of this application.

[0067] A method for judging power outage areas in low-voltage power distribution areas based on edge computing provided by the embodiments of this application mainly includes two major steps, which will be specifically described later:

[0068] The first step is to collect and monitor the device data of the low-voltage power distribution area, which is divided into two small steps: device data monitoring and device data collection.

[0069] The second step is to conduct power outage judgment in the edge computing end device. Using the "end-to-end" decentralized architecture data model, a power outage big data analysis model is constructed, and the data of each branch line under the known pilot power supply bureau is added. It can be divided into five major modules to judge and control the power outage area situation.

[0070] Please refer to Figure 1 , which is a schematic flowchart of a method for judging power outage areas in low-voltage power distribution areas based on edge computing provided by the embodiments of this application. As Figure 1 shown, this method includes:

[0071] 101. According to the power outage situation and current status of each low-voltage substation area, issue a data template to be collected, and conduct data monitoring on the low-voltage side of the distribution transformer, branch box, and user side respectively according to the above data template to be collected.

[0072] In the embodiments of the present application, the execution subject of the method can be a low-voltage substation area power outage area judgment device based on edge computing. Specifically, it can be executed on an electronic device such as a terminal device. In the embodiments of the present application, power outage judgment is mainly executed on the edge computing end device.

[0073] Among them, the above step 101 corresponds to the device data monitoring described above. First, a data template to be collected can be set and issued as needed to collect data according to the template.

[0074] In an optional implementation manner, the above-mentioned data monitoring of the low-voltage side of the distribution transformer, branch box, and user side respectively according to the above data template to be collected includes:

[0075] Perform any one or more of the following on the above low-voltage side of the distribution transformer: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring;

[0076] Perform any one or more of the following on the above branch box: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring;

[0077] Perform any one or more of the following on the above user side: voltage quality monitoring, voltage anomaly monitoring, cable flow monitoring, cable temperature monitoring, electrical fire risk assessment monitoring, power outage monitoring.

[0078] 102. According to the order of the equipment ledger of the low-voltage substation area, install edge computing end devices on the devices to be monitored.

[0079] The above edge computing end device is a terminal device for performing edge computing. The device to be monitored here can be the devices on the low-voltage side of the distribution transformer, branch box, and user side described above.

[0080] Before power outage judgment, identify the equipment ledger of the low-voltage substation area. Through the collaborative operation of the master-slave devices, based on data such as line load current, realize the topology identification of the equipment ledger of the low-voltage substation area and establish the equipment ledger of the low-voltage substation area. The original equipment ledger of the substation area is known and can be directly issued.

[0081] In an optional implementation manner, the above edge computing end device includes: a master terminal installed on the bus voltage transformation device, and slave terminals installed on other devices;

[0082] The above master terminal is used for data collection, monitoring, and analysis and judgment work. The above data collection includes but is not limited to three-phase voltage, current, and transformer load data;

[0083] The above-mentioned sub-terminal is used for data collection work, and the data collection includes but is not limited to three-phase voltage, current, current-carrying capacity, and temperature data;

[0084] Among them, the above-mentioned main terminal is an integrated device, including a chip, an operating system, data collection and monitoring software; the above-mentioned sub-terminal communicates with the above-mentioned main terminal and transmits the collected data back to the above-mentioned main terminal.

[0085] Specifically, in the embodiments of the present application, edge computing terminal devices can be installed on the devices to be monitored according to the order of the low-voltage substation equipment ledger. The terminal installed on the bus voltage transformation equipment is the main terminal, and the terminals installed on other equipment are sub-terminals.

[0086] 1) The main terminal conducts data collection, monitoring, and research and judgment analysis work. The collection includes but is not limited to data such as three-phase voltage, current, and transformer load;

[0087] 2) The sub-terminal only conducts data collection work. The collection includes but is not limited to data such as three-phase voltage, current, current-carrying capacity, and temperature;

[0088] 3) The main terminal can be an integrated device, including a chip, an operating system, data collection and monitoring software, etc. After the sub-terminal finishes data collection, it communicates with the main terminal and transmits the data back to the main terminal to achieve "end-to-end" data transmission, reducing data transmission pressure and computing pressure.

[0089] 103. Inside the above-mentioned edge computing terminal device, power outage research and judgment are carried out based on the collected data to determine the power outage equipment and divide the power outage area. The above-mentioned power outage research and judgment adopts an "end-to-end" decentralized architecture data model, with "substation-transformer box-user" as the data chain level, and an "end-to-end" data transmission method is adopted between the above-mentioned data chain levels.

[0090] Figure 2 This is a schematic diagram of the device distribution provided by the embodiments of the present application. As Figure 2 shown, the data chain includes 3 levels: substation transformer (substation or substation transformer), transformer box (i.e., the above-mentioned transformer box), and user; one substation corresponds to 3 transformer boxes, and one transformer box corresponds to 2 users.

[0091] The "end-to-end" decentralized architecture data model in the embodiments of the present application includes:

[0092] Data acquisition module, data monitoring module, big data analysis architecture model, fault data module, and judgment module. Among them, the data acquisition module and the data monitoring module are respectively used for data acquisition and data monitoring, that is, the parts mentioned in steps 101 and 102; the big data analysis architecture model performs structured processing on all incoming data and conducts distributed fast calculations. At the same time, it uses the big data stream processing method to speed up the abnormal results of power outage judgment, forms a three-layer architecture, and finally obtains a complete data closed-loop; the fault data module mainly includes the record query of fault data and generates a fault report; the judgment module is mainly based on the edge computing strategy, with the data chain level of "transformer station - one or more branch boxes - multiple users", innovatively uses the multi-terminal autonomous collaboration mode, realizes the "end-to-end" data transmission mode between data chain levels, and has a distributed hardware architecture, which can decompose each judgment task and independently judge the power outage of each level in the low-voltage power distribution area or the power outage of each device.

[0093] Please refer to Figure 3 , Figure 3 which is a schematic diagram of a business process provided by an embodiment of this application. As Figure 3 shown, the following is a specific description of each module:

[0094] ① Data acquisition module (terminal device ledger module):

[0095] 1) Based on the low-voltage power distribution area equipment ledger, establish an access terminal device ledger, view the collected data of each device terminal in real time, and view historical data;

[0096] 2) Based on the low-voltage equipment ledger and the access terminal device ledger, establish a data topology diagram for visual viewing and real-time observation of abnormal data;

[0097] 3) The data is collected in a polling manner, with multiple data calls, and data synchronization processing is performed on the collected data.

[0098] ② Data monitoring module:

[0099] 1) Minute-level perception: Within a preset duration (which can be adjusted, such as 1 minute) after the data appears abnormal, the master terminal receives the perceived abnormality, analyzes the situation of the abnormality, judges the power outage situation, and gives a specific situation description;

[0100] 2) Power outage area map: After the low-voltage power distribution area equipment appears abnormal, the affected power outage area is visually displayed, the power outage area is clarified, and an alarm notice is sent to the relevant area monitoring personnel.

[0101] ③ Big data analysis architecture model: (Three-layer architecture)

[0102] Reference can be made to Figure 4 a schematic diagram of a big data analysis architecture model shown in, where:

[0103] 1) Structured data base: Based on the data after data transmission and interaction between the sub-end data acquisition device and the main-end acquisition and calculation device, unify the data template and construct a complete structured data base;

[0104] 2) Real-time algorithm calculation:

[0105] a) Embedded storage database: An embedded database in the main-end device stores structured data;

[0106] b) Distributed computing architecture: One transformer has one main-end device, and a separate distributed computing architecture is used for data operation in the low-voltage power distribution area to process synchronous data in real time;

[0107] c) Stream processing and analysis method: It acts on processing continuous data streams, processes the structured data stored in the database, and quickly detects abnormal conditions within a few milliseconds to a few minutes.

[0108] 3) Data closed-loop: After the data is processed, fault reports and analysis reports are formed, alarms are given for abnormal data, and the message push process is entered.

[0109] ④ Fault data module:

[0110] 1) Fault data ledger: The fault data ledger includes all device fault data, and the fault conditions of each device can be viewed according to year, month, and day;

[0111] 2) Device fault report: Corresponding to the fault data ledger, a corresponding fault report is generated, and corresponding fault condition analysis and solutions can be given.

[0112] ⑤ Judgment module:

[0113] Reference can be made to Figure 5 a schematic diagram of a power outage judgment service shown in the figure, where:

[0114] 1) Data transceiver control: Control the transceiver of data affecting power outages in the low-voltage power distribution area, issue control strategies at the level of "transformer - one or more branch boxes - multiple users", use clustering algorithms and multi-hop forwarding algorithms for data reception and transmission, complete the transceiver of terminal data between each level, and realize the data transceiver of the data links of "transformer - branch box" and "transformer - user";

[0115] 2) Terminal autonomous collaboration: In the low-voltage power distribution area, terminal autonomous collaboration is carried out through the data links of "transformer", "transformer - branch box", and "transformer - user", the judgment tasks are decomposed, and the zero-sequence algorithm is used to add autonomous judgment to reduce the power outage judgment duration and reduce the impact of power outages;

[0116] a) Terminal information interaction: Unify the data resource interface, use "end-to-end" data transmission, and perform modeling decomposition on the research and judgment tasks in the form of "total-sub-total", that is, first integrate and model the research and judgment tasks, then split and decompose the research and judgment tasks. After the decomposition and research and judgment are completed, then merge each sub-task after completing the research and judgment tasks on each edge computing side;

[0117] b) Simulation modeling: Use the normal data of each device in the low-voltage distribution area to perform simulation data modeling. The simulation modeling is not real collected data, and parameters can be designed independently for data simulation calculation;

[0118] c) Independent research and judgment: Use the simulation data after simulation modeling and the currently collected real-time data at the terminal (edge computing side), and perform calculation and comparison through the zero-sequence algorithm to check whether there is data beyond the error. If there is data beyond the error, the device will be powered off, and the powered-off device will be quickly found on the data chain of "transformer substation - branch box - user", and the power-off area will be quickly divided.

[0119] 3) Terminal information fusion: Layer all information and perform information fusion through multi-level algorithms;

[0120] a) Information fusion: Divide the hierarchical device information into three levels for information fusion, namely data level, feature level, and decision level;

[0121] b) Model algorithm: Build an information fusion model and perform weighted average calculation through information fusion algorithms and intelligent decision-making algorithms;

[0122] c) Intelligent decision-making: Through terminal information fusion, perform autonomous information processing and decision-making on the edge computing side, and make quick decisions on the research and judgment and warning of the power-off area in the low-voltage distribution area.

[0123] The research and judgment of the power-off area in the low-voltage distribution area requires a large number of device installations to access for data support, and there are various different situations. Therefore, after obtaining a large amount of data, combined with the research and judgment methods and devices for big data model analysis, the accuracy of the research and judgment is improved to ensure the comprehensiveness and correctness of the results.

[0124] Furthermore, after multi-angle information analysis, the power-off situation of the low-voltage distribution area can be accurately obtained. Then, through long-term and periodic monitoring, continuously analyze the historical monitoring and fault data obtained, and combine the local land use situation to give the research and judgment analysis of the power-off area in the low-voltage distribution area, including the power-off area, duration, etc. Each power supply bureau and department can also conduct long-term and effective management and control of the power-off research and judgment and warning based on this data analysis, reducing the power-off time and inspection duration.

[0125] As a decentralized computing architecture, edge computing can change the original centralized processing method to perform calculations at edge nodes in the network logic. At the same time, it is closer to user terminal devices, can better process information and transmission, and speed up the judgment speed of power outage areas.

[0126] The importance of power supply is reflected in all aspects of human life, whether it is life, production activities, social stability, or technological development. Accelerating the rapid positioning of faulty equipment after a power outage, visually displaying the power outage scope, automatically generating fault reports, issuing fault repair work orders, etc., can better ensure power supply and rapid inspection after a power outage, improve user quality of use, and reduce the complaint rate. Based on this relationship, this invention patent provides a power outage area judgment solution and device based on edge computing, realizing an "end-to-end" data transmission mode, more intuitively obtaining data for information transmission and processing, and providing strong support for the judgment of power outage areas.

[0127] Based on the description of the foregoing method embodiments, this application embodiment also discloses a power outage area judgment device based on edge computing.

[0128] Figure 6 It is a structural schematic diagram of a power outage area judgment device based on edge computing provided by this application embodiment. As Figure 6 shown, the power outage area judgment device 600 based on edge computing may include a data acquisition module 610, a data monitoring module 620, a big data analysis architecture model 630, a fault data module 640, and a judgment module 650, where:

[0129] The above data acquisition module 610 is used to establish an access terminal device ledger based on the low-voltage substation equipment ledger. The above access terminal device ledger is used to view the data collected by the terminal device in real time and view historical data; based on the above low-voltage substation equipment ledger and the above access terminal device ledger, establish a data topology diagram, and the above data topology diagram is used for visual viewing and real-time observation of abnormal data; the above collected data is performed in a polling manner, with multiple data calls, and data synchronization processing is performed on the above collected data;

[0130] The above data monitoring module 620 is used to receive perceived abnormal information by the master terminal within a preset duration after data abnormalities occur, analyze the situation of the above perceived abnormal information, judge the power outage situation, and output a specific situation description; after abnormalities occur in the above low-voltage substation equipment, visually display the affected power outage area and send an alarm notification to relevant area monitoring personnel;

[0131] The above-mentioned big data analysis architecture model 630 is used to perform structured processing on all inflowing data, perform distributed computing, and use big data stream processing to speed up the above-mentioned power outage research and judgment;

[0132] The above-mentioned fault data module 640 is used to generate corresponding fault reports based on the fault data ledger, and generate corresponding fault situation analysis and solutions;

[0133] The above-mentioned research and judgment module 650 is used for:

[0134] Data transceiver control: Perform transceiver control on the data affecting the power outage of the above-mentioned low-voltage substation area, issue control strategies at the "transformer substation - branch box - user" level, use clustering algorithms and multi-hop forwarding algorithms for data reception and transmission, complete the transceiver of terminal data between each level, and realize the data transceiver of the data links of "transformer substation - branch box" and "transformer substation - user";

[0135] Terminal autonomous collaboration: The above-mentioned low-voltage substation area performs terminal autonomous collaboration through the data links of "transformer substation", "transformer substation - branch box", and "transformer substation - user", decomposes each research and judgment task, and uses the zero-sequence algorithm to add autonomous research and judgment;

[0136] Terminal information fusion: Layer all information and perform information fusion through multi-level algorithms.

[0137] It can be understood that the relevant content related to each module in the above device has been described in detail in the foregoing method embodiments, and specifically, reference can be made to the content in the method embodiments; that is, a low-voltage substation area power outage area research and judgment device provided by the present application can execute any steps in the embodiments as shown in Figure 5 and will not be elaborated here.

[0138] In an embodiment of the present application, an electronic device is further proposed. The electronic device may include a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, it will execute any steps in the method embodiments as shown in Figure 1 or Figure 5 The electronic device may further include input / output devices, etc. In a specific implementation manner, the electronic device may be a terminal device, etc.

[0139] In an embodiment, a computer-readable storage medium is further proposed. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor is caused to execute any steps in the above method embodiments.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0141] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0142] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A method for judging power outage areas in low-voltage distribution areas based on edge computing, characterized in that, The method includes: Issuing a data template to be collected based on the power outage situation and current status of each low-voltage power distribution area, and respectively performing data monitoring on the low-voltage side of the distribution transformer, branch box, and user side according to the data template to be collected; Installing edge computing terminal devices for the devices to be monitored according to the order of the equipment account books of the low-voltage power distribution area; the edge computing terminal devices include: a main terminal installed on the bus voltage transformation device, and a sub-terminal installed on the device to be monitored; the main terminal is used for data collection, monitoring, and research and judgment analysis work, and the data collection includes but is not limited to three-phase voltage, current, and transformer load data; the sub-terminal is used for data collection work, and the data collection includes but is not limited to three-phase voltage, current, current-carrying capacity, and temperature data; among them, the main terminal is an integrated device, including a chip, an operating system, and data collection and monitoring software; the sub-terminal communicates with the main terminal and transmits the collected data back to the main terminal; Inside the edge computing terminal device, perform power outage research and judgment based on the collected data to determine the power outage equipment and divide the power outage area. The power outage research and judgment adopts an "end-to-end" decentralized architecture data model, with "transformer substation-branch box-user" as the data chain level, and an "end-to-end" data transmission method is adopted between the data chain levels. The "end-to-end" decentralized architecture data model includes: a data collection module, a data monitoring module, a big data analysis architecture model, a fault data module, and a research and judgment module; Among them, the research and judgment module includes the following functions: Data transceiver control: Control the reception and transmission of data affecting the power outage of the low-voltage power distribution area, issue control strategies at the "transformer substation-branch box-user" level, use clustering algorithms and multi-hop forwarding algorithms for data reception and transmission, complete the data reception and transmission of terminals between each level, and realize the data reception and transmission of the data links of "transformer substation-branch box" and "transformer substation-user"; Terminal autonomous collaboration: The low-voltage power distribution area performs terminal autonomous collaboration through the data links of "transformer substation", "transformer substation-branch box", and "transformer substation-user", decomposes each research and judgment task, and uses the zero-sequence algorithm to add autonomous research and judgment; Terminal information fusion: Layer all information and perform information fusion through multi-level algorithms.

2. The method for judging the power outage area of a low-voltage power distribution area based on edge computing according to claim 1, wherein The data monitoring of the low-voltage side of the distribution transformer, branch box, and user side respectively according to the data template to be collected includes: Performing any one or more of the following on the low-voltage side of the distribution transformer: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring; Performing any one or more of the following on the branch box: three-phase imbalance monitoring, transformer load monitoring, voltage anomaly monitoring; Performing any one or more of the following on the user side: voltage quality monitoring, voltage anomaly monitoring, cable flow monitoring, cable temperature monitoring, electrical fire risk assessment monitoring, power outage monitoring.

3. The method for judging the power outage area of a low-voltage power distribution area based on edge computing according to claim 1, wherein, Through the data collection module, perform the following functions: Establish an access terminal equipment account book based on the equipment account book of the low-voltage power distribution area. The access terminal equipment account book is used to view the data collected by the terminal equipment in real time and view historical data; Based on the low-voltage substation equipment ledger and the access terminal equipment ledger, a data topology map is established for visual inspection and real-time observation of abnormal data. The data collection is carried out in a polling manner with multiple data calls, and data synchronization processing is performed on the collected data.

4. The method for judging the power outage area of a low-voltage substation area based on edge computing according to claim 1, wherein, Through the data monitoring module, the following functions are executed: Within a preset time period after data anomaly occurs, the master terminal receives the perceived anomaly information, analyzes the situation of the perceived anomaly information, judges the power outage situation, and outputs a specific situation description. After an anomaly occurs in the low-voltage substation equipment, the affected power outage area is visually displayed, and an alarm notification is sent to the relevant area monitoring personnel.

5. The method for judging power outage areas in low-voltage distribution areas based on edge computing according to claim 1, characterized in that, All incoming data is structurally processed and distributed computing is performed through the big data analysis architecture model, and at the same time, the big data stream processing method is used to accelerate the power outage judgment.

6. The method for judging the power outage area of the low-voltage substation area based on edge computing according to claim 5, characterized in that, The autonomous collaboration of the terminal specifically includes: Terminal information interaction: Unify the data resource interface, use the "end-to-end" data transmission method, model and decompose the judgment task in the form of "total-subtotal-total", and then merge after each subtask judgment is completed on each edge computing side. Simulation modeling: Use the normal data of each device in the low-voltage substation for simulation data modeling. Autonomous judgment: On the edge computing side, use the simulation data after simulation modeling and the collected real-time data, calculate and compare through the zero-sequence algorithm to determine whether there is data beyond the error. If there is such data, it is determined that the device is powered off, and the powered-off device is found on the "substation-transformer branch box-user" data chain, and the power outage area is divided. The terminal information fusion specifically includes: Information fusion: Divide the hierarchical device information into three levels for information fusion, including data level, feature level, and decision level. Model algorithm: Construct an information fusion model and perform weighted average calculation through information fusion algorithms and intelligent decision-making algorithms. Intelligent decision-making: Through the terminal information fusion, autonomous information processing and decision-making are carried out on the edge computing side to make decisions on the judgment and alarm of the power outage area in the low-voltage substation.

7. A power outage area judgment device for low-voltage power distribution areas based on edge computing, characterized in that, It includes a data collection module, a data monitoring module, a big data analysis architecture model, a fault data module, and a judgment module, where: The data collection module is used to establish an access terminal equipment ledger based on the low-voltage substation equipment ledger. The access terminal equipment ledger is used to view the data collected by the terminal equipment in real time and view historical data. The data monitoring module is used for the master terminal to receive the perceived anomaly information within a preset time period after data anomaly occurs, analyze the situation of the perceived anomaly information, judge the power outage situation, and output a specific situation description. The big data analysis architecture model is used to structurally process all incoming data and perform distributed computing, and at the same time, use the big data stream processing method to accelerate the power outage judgment. The fault data module is used to generate a corresponding fault report according to the fault data ledger, and generate a corresponding fault situation analysis and solution. The judgment module is used for: Data transceiver control: Perform transceiver control on the data affecting power outage in the low-voltage distribution area, issue control strategies at the "substation-transformer - branch box - user" level, use clustering algorithms and multi-hop forwarding algorithms for data reception and transmission, complete the transceiver of terminal data between each level, and achieve data transceiver of the data links of "substation-transformer - branch box" and "substation-transformer - user"; Terminal autonomous collaboration: The low-voltage distribution area performs terminal autonomous collaboration through the data links of "substation-transformer", "substation-transformer - branch box", and "substation-transformer - user", decomposes each judgment task, and uses the zero-sequence algorithm to add autonomous judgment; Terminal information fusion: Layer all information and perform information fusion through multi-level algorithms.

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