A distribution network fault line selection perception measurement and control method and system

Abstract

The application discloses a kind of power distribution network fault line selection line sensing control method and system, belong to power grid situation awareness technical field, including obtaining the component line of pre-set power distribution network, in component line, the historical fault occurrence frequency of each line is collected, and the component line is marked and divided based on historical fault occurrence frequency;In the component line, the operation data of each line is collected, and the collected operation data are distinguished according to power distribution network data acquisition and monitoring data end and power distribution geographic information data end;The component line of pre-set power distribution network is divided in the application, when the fault of each line of pre-set power distribution network occurs, other lines possibly affected can be monitored according to the collected data, not only can the fault line object be quickly locked, but also the fault position can be accurately obtained, the sensitivity and accuracy of fault line selection discrimination are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid situation awareness, and in particular to a method for sensing and controlling fault line selection in a distribution network and a system thereof. Background Art

[0002] In recent years, many power grid accidents have occurred in various regions of the world, causing serious economic losses and social harm, and have attracted widespread attention from researchers. One of the research directions is to predict the selection of fault lines. Its core purpose is to quickly and accurately identify the faulty lines in the power system, thereby improving the reliability and operating efficiency of the power grid. This process involves the precise identification and positioning of the faulty lines so that timely measures can be taken to restore power supply, thereby reducing the duration and scope of power outages. In real life, the topology of the distribution network system is complex and the distribution changes are diverse. In order to realize the line selection of the distribution network fault line, the technical application number CN202410260090.1 provides a method and system for online monitoring of power distribution line faults. The technical method of this technical application is to respond to the client, receive the distribution network fault monitoring request, and feedback the fault nodes of each monitored line to the client, so as to achieve high-precision fault node analysis and positioning, improve the timeliness of distribution network operation and maintenance, and thus ensure the operation reliability and safety of the distribution network; and another technical application number CN202111549513.4 provides a distribution network situation awareness method and system suitable for new power systems. The technical method provided is to conduct all-round and visual operation and scheduling of the distribution network operation status, thereby effectively improving the scheduling efficiency of the distribution network, so as to perceive and predict the fault lines to ensure the smooth operation of the distribution network and improve the power supply reliability.

[0003] Existing fault line selection techniques are based on the resistance and reactance characteristics of the power system's conductors. When a fault occurs in the power system, a short circuit is formed. Since the short-circuit current generates a large voltage drop, the fault location can be determined based on the resistance and reactance characteristics of the power grid's conductors by measuring the voltage and current at different locations. In a distribution network, feeders, as branches connected to any distribution network node, are the most common transmission lines in the power system. However, the line selection methods described in the aforementioned technical applications are mostly limited to feeders. When selecting fault lines, various types of conductors, such as transition lines and branch lines, must also be considered. If only feeders are selected for troubleshooting, problems with other conductors will be ignored, leading to errors and delays. Furthermore, the aforementioned technical solutions do not consider the distribution of the resistance of the power grid conductors. Even for conductors of the same type, the resistance of conductors at different locations can vary significantly, making it easy to misjudge the fault location. Summary of the Invention

[0004] In view of the above-mentioned problems existing in the existing technical field of power grid situation awareness, the present invention is proposed.

[0005] Therefore, one of the objects of the present invention is to provide a distribution network fault line selection perception measurement and control method and system thereof, which divides the constituent lines of the preset distribution network, and can monitor other lines that may be affected based on the collected data when a fault occurs in each line of the preset distribution network, and can analyze the operating characteristics of these lines separately, and then, when a fault occurs in the future period, these line objects can be analyzed and checked in time, thereby not only quickly locking the fault line object, but also accurately obtaining the fault location, thereby improving the sensitivity and accuracy of fault line selection judgment.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In one aspect, the present invention provides a method for detecting and controlling a fault line in a distribution network, comprising the following steps:

[0008] Obtaining component lines of a preset power distribution network, collecting the number of historical fault occurrences of each line in the component lines, and marking and dividing the component lines based on the number of historical fault occurrences;

[0009] In the component lines, the operation data of each line is collected, and the collected operation data is divided into distribution network data collection and monitoring data terminals and distribution geographic information data terminals;

[0010] Analyze the correlation characteristics of the operating data changes of each data end in each of the distinguished data ends, and generate a data set, and divide the data set into a training set, a test set, and a validation set based on the distribution network data acquisition and monitoring data end;

[0011] Based on the distribution network data acquisition and monitoring data terminal, the operation data is divided into ▽1, ▽2, ..., ▽ n , where n represents the nth type of operating data, and in each divided operating data, the operating data corresponding to the occurrence of the line fault is collected, and the data characteristics of the operating data are analyzed;

[0012] The divided operation data are divided into safety levels according to the number of historical line faults, and a prediction model is generated.

[0013] As a preferred solution of the present invention, the component lines are marked and divided, including dividing the component lines into lines with a high number of fault occurrences and lines with a low number of fault occurrences, wherein the number of divided lines with a high number of fault occurrences is at least more than half of the total number of the component lines. At the same time, among the lines with a high number of fault occurrences, the lines are divided into main fault lines and secondary fault lines, wherein the secondary fault line is the affected line and the main fault line is the original fault line, and the correlation between the fault characteristics of the main fault line and the secondary fault line is analyzed.

[0014] As a preferred solution of the present invention, wherein: the distribution network data acquisition and monitoring data terminal includes monitoring the bus voltage, line current, active and / or reactive power and electric energy data of the power supply line;

[0015] The power distribution geographic information includes spatial data and non-spatial data, wherein the spatial data includes the geographical location, terrain and / or land features of the preset power distribution network, and the non-spatial data includes environmental parameters, which include natural environmental condition data, and the natural environmental condition data include temperature, humidity, altitude and air pressure.

[0016] As a preferred solution of the present invention, the operating data includes line resistance data, a change characteristic of the resistance data is obtained in the main fault line, and the change characteristic is uploaded to the prediction model. The prediction model is updated, and the change characteristic is divided into a first change characteristic, a second change characteristic, and a third change characteristic. The affected lines under different change characteristics are collected, and the characteristic value of each change characteristic is collected. The data change of the affected line under the characteristic value is calculated. The data change includes voltage and current data changes, which are calculated according to the following formula:

[0017] Z=[(Τ+Α x ×V x )]·Ω; where Z represents the characteristic value of resistance;

[0018] Where, T represents the monitoring time, A x represents the fault current data collected on the affected line at time point x, V x represents the fault voltage data collected at the xth time point of the affected line, wherein both time points include the time point when the fault of the affected line occurs; Ω represents the resistance data corresponding to the fault current data collected at the xth time point and the fault voltage data collected at the xth time point.

[0019] As a preferred solution of the present invention, the data changes of current and voltage in the ten minutes before the time point when the fault of the affected line occurs are collected based on the time point of the affected line fault, and the trend of current and voltage data changes within the ten minutes is analyzed based on the current and voltage data at the time point when the fault occurs. At the same time, the median data of current and voltage are intercepted from the data change trend, and a safety threshold is preset based on the median data. When the main fault line fails in a future period, the current and voltage data changes of the secondary fault line are collected. If the collected current and voltage data changes exceed the safety threshold, it is determined that the fault of the main fault line will cause the collected line to fail, and an early warning is issued. Otherwise, no determination is made.

[0020] As a preferred solution of the present invention, in the secondary fault line, the lines are divided into high-risk impact lines and low-risk impact lines according to the number of times each line is affected, and based on the high-risk impact line, resistance data of different characteristic segments of the line are collected, wherein the different characteristic segments include an ambient temperature segment and an air pressure segment, and in the ambient temperature segment, based on the collected ambient temperature, a temperature data set δ = [δ1, δ2, ..., δ n ], where n represents the nth temperature feature, and the resistance data variation pattern of the high-risk impact line under different temperature features is analyzed, and the correlation pattern with the resistance data of the main fault line is analyzed based on the variation pattern.

[0021] As a preferred solution of the present invention, resistance data when a fault occurs in the high-risk impact line is collected in different temperature characteristics, and the resistance data is sorted in the order before and after the fault occurs. The first 3 to 5 resistance data closest to the resistance data are intercepted from the sorted resistance data. When the resistance change trend of the high-risk impact line in the future time period conforms to the change pattern of the first 3 intercepted resistance data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

[0022] As a preferred solution of the present invention, the resistance change trends of each component line in the high-risk impact line are compared and analyzed, and the same resistance data within at least ten minutes before the fault occurs is collected in the comparison and analysis results. At the same time, the resistance data is calibrated as risk data. When the resistance change data of a line in the high-risk impact line in a future time period is the same as the risk data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

[0023] As a preferred solution of the present invention, the risk data is sampled using the Monte Carlo method, the ambient temperature corresponding to the sampled data is monitored, and the changing trend of the ambient temperature is monitored. When the changing trend of the ambient temperature changes toward the ambient temperature corresponding to the sampled data, the lines matching the sampled data in the high-risk impact lines are monitored; otherwise, they are not monitored.

[0024] In another aspect, the present invention provides a distribution network fault line selection, sensing, measurement and control system, which is applied to the distribution network fault line selection, sensing, measurement and control method according to claim 1, comprising:

[0025] An information acquisition module is used to obtain the constituent lines of a preset power distribution network, collect the number of historical fault occurrences of each line in the constituent lines, and mark and divide the constituent lines based on the number of historical fault occurrences;

[0026] A data acquisition module, in the component lines, for collecting the operating data of each line and distinguishing the collected operating data according to the distribution network data acquisition and monitoring data terminal and the distribution geographic information data terminal;

[0027] A data analysis module, for analyzing correlation characteristics of changes in operating data of each data end in each of the distinguished data ends, and generating a data set, and dividing the data set into a training set, a test set, and a validation set based on the distribution network data acquisition and monitoring data end;

[0028] The data division module is used to divide the operation data into ▽1, ▽2, ..., ▽ based on the distribution network data acquisition and monitoring data terminal. n , where n represents the nth type of operating data, and in each divided operating data, the operating data corresponding to the occurrence of the line fault is collected, and the data characteristics of the operating data are analyzed;

[0029] A data early warning module is used to classify the operation data into safety levels according to the number of historical line faults in each divided operation data, and to generate a prediction model;

[0030] A fault determination module, which responds to the constituent line data of the preset power distribution network acquired by the information acquisition module, and is used to divide the constituent lines into lines with a high number of faults and lines with a low number of faults, and analyze and determine the changing trends of the line current and voltage based on the collected line current and voltage data. At the same time, a safety threshold is preset based on the current and voltage data of the line during safe operation, and a fault warning judgment is performed on the changing trends of the current and voltage based on the safety threshold.

[0031] By dividing the constituent lines of the preset distribution network, the present invention can monitor other lines that may be affected based on the collected data when a fault occurs in each line of the preset distribution network, and can analyze the operating characteristics of these lines separately. Therefore, when a fault occurs in a future period, these line objects can be analyzed and checked in a timely manner, thereby not only quickly locking the fault line object, but also accurately obtaining the fault location, thereby improving the sensitivity and accuracy of fault line selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0033] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention;

[0034] Figure 2 This is a schematic diagram of the modular structure of a distribution network fault line selection, sensing, measurement and control system according to an embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram of the process structure of an embodiment of the present invention;

[0036] Reference numerals in the figure: 110 - information acquisition module; 120 - data acquisition module; 130 - data analysis module; 140 - data warning module; 150 - fault determination module. DETAILED DESCRIPTION

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0038] Because existing line selection methods are mostly limited to feeders, various types of conductors, such as transition lines and branch lines, need to be considered when selecting fault lines. If only feeders are selected for troubleshooting, problems with other conductors will be ignored, leading to errors and delays. At the same time, existing technologies also do not consider the distribution of grid conductor resistance. Even for the same type of conductor, the conductor resistance at different locations can vary significantly, which can easily lead to misjudgment of the fault location.

[0039] Based on this, the present invention proposes a distribution network fault line selection perception measurement and control method and system, which divides the constituent lines of the preset distribution network. When a fault occurs in each line of the preset distribution network, other lines that may be affected can be monitored based on the collected data, and the operating characteristics of these lines can be analyzed separately. When a fault occurs in the future, these line objects can be analyzed and checked in a timely manner, thereby not only quickly locking the fault line object, but also accurately obtaining the fault location, thereby improving the sensitivity and accuracy of fault line selection judgment.

[0040] The present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0041] Reference Figures 1 to 3 , is an embodiment of the present invention, which provides a method for detecting and controlling fault line selection in a distribution network, comprising the following steps:

[0042] S10: Obtain constituent lines of a preset distribution network, collect the number of historical faults occurring on each of the constituent lines, and mark and divide the constituent lines based on the number of historical faults occurring;

[0043] It should be emphasized that in this embodiment, the component lines are marked and divided, including dividing the component lines into lines with a high number of faults and lines with a low number of faults. The number of lines with a high number of faults is at least half of the total number of component lines. At the same time, among the lines with a high number of faults, the lines are divided into primary fault lines and secondary fault lines. The secondary fault line is the affected line, and the primary fault line is the original fault line. The correlation between the fault characteristics of the primary fault line and the secondary fault line is analyzed.

[0044] This embodiment further obtains a change characteristic of resistance data in the main fault line, uploads the change characteristic to the prediction model, updates the prediction model, and divides the change characteristic into a first change characteristic, a second change characteristic, and a third change characteristic. The affected lines under different change characteristics are collected, and the characteristic value of each change characteristic is collected. The data change of the affected line under the characteristic value is calculated. The data change includes the change of voltage and current data, and is calculated according to the following formula:

[0045] Z=[(Τ+Α x ×V x )]·Ω; where Z represents the characteristic value of resistance;

[0046] Where, T represents the monitoring time, A x represents the fault current data collected on the affected line at time point x, V xrepresents the fault voltage data collected at the xth time point of the affected line, where both time points include the time point when the fault of the affected line occurs; Ω represents the resistance data corresponding to the fault current data collected at the xth time point and the fault voltage data collected at the xth time point;

[0047] Based on the above, it is important to emphasize that in this embodiment, based on the time point when the affected line fault occurs, the current and voltage data changes for the ten minutes before that time point are collected. Based on the current and voltage data at the time point when the fault occurs, the current and voltage data change trends within ten minutes are analyzed. At the same time, the median data of the current and voltage are intercepted from the data change trend. A safety threshold is preset based on the median data. When the primary fault line fails in a future time period, the current and voltage data changes of the secondary fault line are collected. If the collected current and voltage data changes exceed the safety threshold, it is determined that the fault of the primary fault line will cause the collected line to fail, and an early warning is issued. Otherwise, no determination is made.

[0048] S20: Collecting the operating data of each line in the component lines, and distinguishing the collected operating data according to the distribution network data collection and monitoring data terminal and the distribution geographic information data terminal;

[0049] Specifically, in this embodiment, the distribution network data acquisition and monitoring data terminal includes monitoring the bus voltage, line current, active and / or reactive power, and electric energy data of the power supply line;

[0050] The power distribution geographic information includes spatial data and non-spatial data, wherein the spatial data includes the geographical location, terrain and / or land features of the preset power distribution network, and the non-spatial data includes environmental parameters, which include natural environmental condition data, including temperature, humidity, altitude and air pressure;

[0051] According to the operation and management of the power grid, the above distinction can be used to collect real-time data on the distribution network, including voltage, current, and power factor, and collect data in segments as needed to more accurately monitor and analyze the line operation status. It should be further explained that the advantage of end-to-end data collection is that it can more accurately locate and analyze problem areas in the distribution network. When a fault occurs in the distribution network, the data collected in segments can help quickly determine the fault location, reduce the scope of the power outage and the time to restore the power supply. In addition, end-to-end data collection can also optimize the operation mode of the distribution network and improve the quality and efficiency of power supply.

[0052] Wherein, the operation data includes line resistance data;

[0053] S30: Analyze the correlation characteristics of the operating data changes of each data end in each of the distinguished data ends, and generate a data set, and divide the data set into a training set, a test set, and a validation set based on the distribution network data collection and monitoring data end;

[0054] S40: Based on the distribution network data collection and monitoring data terminal, the operation data is divided into Wherein, n represents the nth type of operating data, and among the divided operating data, the operating data corresponding to the occurrence of the line fault is collected, and the data characteristics of the operating data are analyzed;

[0055] It should be emphasized in this embodiment that, in the secondary fault line, the lines are divided into high-risk impact lines and low-risk impact lines according to the number of times each line is affected, and based on the high-risk impact line, resistance data of different characteristic segments are collected for the line, where the different characteristic segments include an ambient temperature segment and an air pressure segment. In the ambient temperature segment, based on the collected ambient temperature, a temperature data set δ = [δ1, δ2, ..., δ n ], where n represents the nth temperature feature. Analyze the variation pattern of the resistance data of the high-risk impact line under different temperature features, and analyze the correlation pattern with the resistance data of the main fault line based on the variation pattern.

[0056] Furthermore, based on the above, this embodiment collects resistance data when a fault occurs in a high-risk impact line under different temperature characteristics, sorts the resistance data in the order of the fault occurrence, and extracts the first 3 to 5 resistance data closest to the resistance data from the sorted resistance data. If the resistance change trend of the high-risk impact line in the future period conforms to the change pattern of the first 3 resistance data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

[0057] This embodiment further compares and analyzes the resistance change trends of each component line in the high-risk impact line, and collects the same resistance data at least ten minutes before the fault occurs in the comparison and analysis results. At the same time, the resistance data is marked as risk data. If the resistance change data of a line in the high-risk impact line in the future period is the same as the risk data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

[0058] At the same time, this embodiment also includes using the Monte Carlo method to sample risk data, monitor the ambient temperature corresponding to the sampled data, and monitor the trend of the ambient temperature. When the trend of the ambient temperature changes toward the ambient temperature corresponding to the sampled data, the lines matching the sampled data are monitored among the high-risk impact lines; otherwise, they are not monitored.

[0059] S50: Classifying the divided operating data into safety levels according to the number of historical line faults, and generating a prediction model;

[0060] It should be noted that in this embodiment, the operating data is divided into security levels, including a step-by-step division of the operating data into high-security operating data, medium-security operating data, and low-security operating data. When the operating data of a line with a high number of faults changes from high-security operating data to medium-security operating data, monitoring of the line with a high number of faults is started; otherwise, monitoring is not performed.

[0061] Based on the above, it can be seen that the present application divides the constituent lines of the preset distribution network. When a fault occurs in each line of the preset distribution network, other lines that may be affected can be monitored based on the collected data, and the operating characteristics of these lines can be analyzed separately. When a fault occurs in the future period, these line objects can be analyzed and checked in a timely manner, thereby not only quickly locking the fault line object, but also accurately obtaining the fault location, thereby improving the sensitivity and accuracy of fault line selection.

[0062] In combination with the above-mentioned distribution network fault line selection, sensing, measurement and control method, this embodiment also proposes a working system applied to this method, as follows:

[0063] The information acquisition module 110 is used to obtain the constituent lines of the preset power distribution network, collect the historical fault occurrence counts of each line in the constituent lines, and mark and divide the constituent lines based on the historical fault occurrence counts;

[0064] The data collection module 120 is used to collect the operation data of each line in the component line, and distinguish the collected operation data according to the distribution network data collection and monitoring data terminal and the distribution geographic information data terminal;

[0065] The data analysis module 130 is used to analyze the correlation characteristics of the operating data changes of each data end in each of the distinguished data ends, and generate a data set, and divide the data set into a training set, a test set, and a validation set based on the distribution network data collection and monitoring data end;

[0066] The data division module is used to divide the operation data into ▽1, ▽2, ..., ▽ based on the distribution network data acquisition and monitoring data terminal n ,in, n Indicates the nth type of operating data, and collects the operating data corresponding to the occurrence of the line fault from each divided operating data, and analyzes the data characteristics of the operating data;

[0067] The data warning module 140 is used to classify the operation data into safety levels according to the number of historical line faults in each divided operation data, and generate a prediction model;

[0068] The fault judgment module 150 responds to the constituent line data of the preset power distribution network obtained by the information acquisition module, and is used to divide the constituent lines into lines with a high number of faults and lines with a low number of faults, and analyze and judge the changing trends of the line current and voltage based on the collected line current and voltage data. At the same time, a safety threshold is preset based on the current and voltage data when the line is operating safely, and a fault warning judgment is made on the changing trends of the current and voltage based on the safety threshold.

[0069] In summary, the present invention divides the constituent lines of the preset distribution network, and can monitor other lines that may be affected based on the collected data when a fault occurs in each line of the preset distribution network, and can analyze the operating characteristics of these lines separately, so that when a fault occurs in the future period, these line objects can be analyzed and checked in time, thereby not only quickly locking the fault line object, but also accurately obtaining the fault location, thereby improving the sensitivity and accuracy of fault line selection.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for detecting and controlling fault lines in a distribution network, characterized in that: The following steps are involved: Obtaining component lines of a preset power distribution network, collecting the number of historical fault occurrences of each line in the component lines, and marking and dividing the component lines based on the number of historical fault occurrences; Marking and dividing the component lines, including dividing the component lines into lines with a high number of fault occurrences and lines with a low number of fault occurrences, wherein the number of lines with a high number of fault occurrences is at least more than half of the total number of the component lines; and, among the lines with a high number of fault occurrences, dividing the lines into primary fault lines and secondary fault lines, wherein the secondary fault line is an affected line and the primary fault line is an original fault line, and analyzing the correlation between the fault characteristics of the primary fault line and the secondary fault line; In the component lines, the operation data of each line is collected, and the collected operation data is divided into distribution network data collection and monitoring data terminals and distribution geographic information data terminals; The distribution network data acquisition and monitoring terminal includes monitoring the bus voltage, line current, active and / or reactive power and electric energy data of the power supply line; The power distribution geographic information includes spatial data and non-spatial data, wherein the spatial data includes the geographical location, terrain and / or land features of the preset power distribution network, and the non-spatial data includes environmental parameters, which include natural environmental condition data, including temperature, humidity, altitude and air pressure; The operating data includes line resistance data. A change characteristic of the resistance data is obtained in the main fault line, and the change characteristic is uploaded to the prediction model. The prediction model is updated, and the change characteristic is divided into a first change characteristic, a second change characteristic, and a third change characteristic. The affected lines under different change characteristics are collected, and a characteristic value is collected in each change characteristic. The data change of the affected line under the characteristic value is calculated. The data change includes voltage and current data changes, which are calculated according to the following formula: Z=[(Τ+Α x ×V x )]·Ω; where Z represents the characteristic value of resistance; Where, T represents the monitoring time, A x represents the fault current data collected on the affected line at time point x, V x represents the fault voltage data collected at the xth time point of the affected line, wherein both of the time points include the time point when the fault of the affected line occurs; Ω represents the resistance data corresponding to the fault current data collected at the xth time point and the fault voltage data collected at the xth time point; Analyze the correlation characteristics of the operating data changes of each data end in each of the distinguished data ends, and generate a data set, and divide the data set into a training set, a test set, and a validation set based on the distribution network data acquisition and monitoring data end; Based on the distribution network data acquisition and monitoring data terminal, the operation data is divided into Wherein, n represents the nth type of operating data, and among the divided operating data, the operating data corresponding to the occurrence of the line fault is collected, and the data characteristics of the operating data are analyzed; The divided operation data are divided into safety levels according to the number of historical line faults, and a prediction model is generated.

2. A method for sensing, measuring and controlling fault line selection in a distribution network according to claim 1, characterized in that: Based on the time point when the fault of the affected line occurs, the data changes of current and voltage in the ten minutes before the time point are collected, and based on the current and voltage data at the time point when the fault occurs, the trend of current and voltage data changes within the ten minutes is analyzed. At the same time, the median data of current and voltage are intercepted from the data change trend, and a safety threshold is preset based on the median data. When the main fault line fails in a future time period, the current and voltage data changes of the secondary fault line are collected. If the collected current and voltage data changes exceed the safety threshold, it is determined that the fault of the main fault line will cause the collected line to fail, and an early warning is issued. Otherwise, no determination is made.

3. A method for detecting and controlling faulty lines in a distribution network according to claim 2, characterized in that: In the secondary fault line, the lines are divided into high-risk impact lines and low-risk impact lines according to the number of times each line is affected, and based on the high-risk impact line, resistance data of different characteristic segments of the line are collected, wherein the different characteristic segments include an ambient temperature segment and an air pressure segment. In the ambient temperature segment, based on the collected ambient temperature, a temperature data set δ = [δ1, δ2, ..., δ n ], where n represents the nth temperature feature, and the resistance data variation pattern of the high-risk impact line under different temperature features is analyzed, and the correlation pattern with the resistance data of the main fault line is analyzed based on the variation pattern.

4. A method for detecting and controlling faulty lines in a distribution network according to claim 3, characterized in that: Resistance data when a fault occurs in the high-risk impact line is collected under different temperature characteristics, and the resistance data is sorted in the order before and after the fault occurs. The first 3 to 5 resistance data closest to the resistance data are intercepted from the sorted resistance data. When the resistance change trend of the high-risk impact line in the future time period conforms to the change pattern of the first 3 intercepted resistance data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

5. A method for detecting and controlling faulty lines in a distribution network according to claim 4, characterized in that: The resistance change trends of each component line in the high-risk impact line are compared and analyzed, and the same resistance data within at least ten minutes before the fault occurs is collected in the comparison and analysis results. At the same time, the resistance data is calibrated as risk data. When the resistance change data of a line in the high-risk impact line in a future time period is the same as the risk data, it is determined that the line will fail and an early warning is issued. Otherwise, no determination is made.

6. A method for detecting and controlling faulty lines in a distribution network according to claim 5, characterized in that: The risk data is sampled using a Monte Carlo method, and the ambient temperature corresponding to the sampled data is monitored, as well as the changing trend of the ambient temperature. When the changing trend of the ambient temperature changes toward the ambient temperature corresponding to the sampled data, the lines matching the sampled data in the high-risk impact lines are monitored; otherwise, they are not monitored.

7. A distribution network fault line selection perception measurement and control system, applied to the distribution network fault line selection perception measurement and control method according to claim 1, characterized in that: include: An information acquisition module is used to obtain the constituent lines of a preset power distribution network, collect the number of historical fault occurrences of each line in the constituent lines, and mark and divide the constituent lines based on the number of historical fault occurrences; A data acquisition module, in the component lines, for collecting the operating data of each line and distinguishing the collected operating data according to the distribution network data acquisition and monitoring data terminal and the distribution geographic information data terminal; A data analysis module, for analyzing correlation characteristics of changes in operating data of each data end in each of the distinguished data ends, and generating a data set, and dividing the data set into a training set, a test set, and a validation set based on the distribution network data acquisition and monitoring data end; The data division module is used to divide the operation data into ▽1, ▽2, ..., ▽ based on the distribution network data acquisition and monitoring data terminal. n , where n represents the nth type of operating data, and in each divided operating data, the operating data corresponding to the occurrence of the line fault is collected, and the data characteristics of the operating data are analyzed; A data early warning module is used to classify the operating data into safety levels according to the number of historical line faults in each divided operating data, and to generate a prediction model; a fault judgment module is used to respond to the component line data of the preset power distribution network obtained by the information acquisition module, and to classify the component lines into lines with a high number of faults and lines with a low number of faults, and to analyze and judge the change trend of the line current and voltage based on the collected line current and voltage data, and at the same time preset a safety threshold based on the current and voltage data when the line is operating safely, and to perform fault early warning judgment on the change trend of the current and voltage based on the safety threshold.

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