Automatic alarm method and system based on distribution line on-line fault detection

Abstract

The invention relates to the technical field of line fault detection, in particular to an automatic alarm method and system based on distribution line online fault detection, and the method comprises the steps: detecting a current environment, obtaining current wind speed data, if a current wind speed value greater than a preset standard wind speed threshold exists in the current wind speed data, obtaining a repair line set based on a plurality of distribution lines, if the current wind speed value larger than the preset standard wind speed threshold value does not exist in the current wind speed data, statistical characteristics of the distribution line are obtained, a physical construction model is obtained, the statistical characteristics are input into the physical construction model, a model prediction value is obtained, fault point positioning operation is executed on a fault electric line, the position of a fault point is obtained, and an automatic alarm mechanism is triggered. And performing fault repair on the fault electric line to obtain a normal electric line set, and completing automatic alarm based on distribution line online fault detection based on the normal electric line set and the repair line set. The reliability and the operation efficiency of the power system can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of line fault detection, and in particular to an automatic alarm method and system based on online fault detection of a power distribution line. Background Art

[0002] Distribution lines are a vital component of the power system, responsible for transporting electricity from substations to individual users. Online fault detection involves real-time monitoring and analysis of the line's operating status during normal operation, promptly identifying potential faults or fault points along the line and accurately determining the fault type and location.

[0003] Traditional fault detection methods rely primarily on simple electrical parameter monitoring, such as abnormal changes in current and voltage. These parameters change when a line fault occurs, but accurately determining the fault type and location based solely on these parameters is difficult. Traditional distribution line fault detection relies primarily on regular manual inspections, which are limited in scope and make it difficult to conduct comprehensive and timely inspections of the entire distribution network. Therefore, improving the reliability and operational efficiency of power systems is an urgent technical challenge. Summary of the Invention

[0004] The present invention provides an automatic alarm method based on online fault detection of distribution lines and a computer-readable storage medium, the main purpose of which is to improve the reliability and operation efficiency of the power system.

[0005] To achieve the above-mentioned purpose, the present invention provides an automatic alarm method based on online fault detection of distribution lines, comprising: identifying a target distribution network, obtaining a current environment based on the target distribution network, wherein the target distribution network comprises: multiple distribution lines; receiving a line fault detection instruction, and detecting the current environment using a pre-built wind speed sensor according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data comprises multiple current wind speed values; if a current wind speed value greater than a preset standard wind speed threshold exists in the current wind speed data, the current wind speed value is used as an abnormal wind speed value, and the abnormal wind speed values are summarized to obtain an abnormal wind speed value set; obtaining the number of abnormal values in the abnormal wind speed value set, and if the number of abnormal values is greater than a preset abnormal value number threshold, obtaining a repair line set based on multiple distribution lines; if a current wind speed value greater than a preset standard wind speed threshold does not exist in the current wind speed data, Then, distribution lines are extracted from multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: statistical features of the distribution lines are obtained, a physical construction model is obtained, the statistical features are input into the physical construction model, a model prediction value is obtained, and the model prediction value is compared with a preset normal prediction value; if the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as a faulty line, and a fault point location operation is performed on the faulty line to obtain the position of the fault point; a pre-built automatic alarm mechanism is triggered according to the position of the fault point, and an alarm file is generated, and the faulty line is repaired according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value to obtain a normal line; the normal lines are summarized to obtain a normal line set, and automatic alarm based on online fault detection of the distribution line is completed based on the normal line set and the repair line set.

[0006] Optionally, obtaining a repair line set based on multiple distribution lines includes: determining whether there is a broken distribution line among the multiple distribution lines; if there is a broken distribution line among the multiple distribution lines, treating the broken distribution line as a broken line, summarizing the broken lines, and obtaining a broken line set; obtaining the number of fractures in the broken line set, and if the number of fractures is greater than a preset fracture number threshold, formulating an optimal fault repair strategy, and performing emergency repairs on the broken line set according to the optimal fault repair strategy to obtain a repair line set; if the number of fractures is less than or equal to the preset fracture number threshold, formulating a fault repair strategy, and repairing the broken line set according to the fault repair strategy to obtain a repair line set.

[0007] Optionally, the formulation of the optimal fault repair strategy includes: determining an initial repair sequence and an initial number of disturbances, obtaining an objective function value according to the initial repair sequence, randomly disturbing the initial repair sequence, and performing an addition operation on the initial number of disturbances to obtain an updated repair sequence and an updated number of disturbances; calculating an updated objective function value of the updated repair sequence, obtaining a function difference value according to the objective function value and the updated objective function value, wherein the function difference value is the absolute difference between the updated objective function value and the objective function value; determining whether to accept the updated objective function value according to the pre-constructed Boltzmann probability formula and the function difference value; and if the updated objective function value is accepted, determining whether to update the number of disturbances. The updated number of disturbances is less than the preset maximum number of disturbances. If the updated number of disturbances is less than the preset maximum number of disturbances, the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the step of randomly disturbing the initial repair order is returned; if the updated number of disturbances is greater than or equal to the preset maximum number of disturbances, the updated repair order corresponding to the updated number of disturbances that is less than the preset maximum number of disturbances is used as the optimal fault repair strategy; if the updated objective function value is not accepted, the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the step of randomly disturbing the initial repair order is returned until the updated objective function value is accepted.

[0008] Optionally, obtaining the objective function value according to the initial emergency repair sequence includes: obtaining an initial sequence line set according to the initial emergency repair sequence, calculating the repair time and load power of each initial sequence line in the initial sequence line set to obtain a repair time set and a load power set, accumulating the repair time set and the load power set to obtain a comprehensive repair time and a comprehensive load power, wherein the initial sequence line set includes multiple initial sequence lines, the comprehensive repair time includes multiple repair times, and the comprehensive load power includes multiple load powers, wherein the initial sequence lines correspond to the repair time and the load power in a one-to-one manner; and calculating the objective function value of the initial sequence line set according to a pre-constructed objective function, the comprehensive repair time, and the comprehensive load power, wherein the objective function is as follows: ,in, represents the objective function value, Represents all symbols, represents the initial sequence line set, represents the repair time of the initial sequence line, Indicates the index of the preset unbroken line, The index representing the sequence in the initial sequence line set, and Both represent preset binary variables. and Both represent the load power of the initial sequence line, Indicates the The repair time of the initial sequence line, Indicates the comprehensive repair time, Indicates the comprehensive load power, represents the number index of the initial sequence line set, Indicates taking the minimum value.

[0009] Optionally, obtaining the statistical characteristics of the distribution line includes: using pre-built intelligent sensors and a preset sampling frequency to collect electrical parameters of the distribution line to obtain electrical parameters, wherein the intelligent sensors include: current sensors and voltage sensors, wherein the electrical parameters include: current data and voltage data, wherein the current data includes multiple current values, and the voltage data includes multiple voltage values; performing analog-to-digital conversion operations on the electrical parameters to obtain digital electrical parameters, filtering the digital electrical parameters to obtain filtered electrical parameters, wherein the filtered electrical parameters include: filtered voltage data and filtered current data; and calculating the statistical characteristics of the filtered electrical parameters.

[0010] Optionally, the calculating of the statistical characteristics of the filter electrical parameters includes: calculating the filter voltage standard deviation and the filter voltage mean according to the filter voltage data, and calculating the filter voltage skewness and the filter voltage kurtosis according to the filter voltage standard deviation and the filter voltage mean, wherein the calculation formulas of the filter voltage skewness and the filter voltage kurtosis are as follows: , ,in, Indicates the filter voltage skewness, Indicates the total number of filtered voltage data, Indicates the The filtered voltage value, represents the mean value of the filtered voltage, represents the standard deviation of the filtered voltage, represents the filtered voltage peak, Represents the index of the filtered voltage data; obtains the filtered current skewness and filtered current kurtosis based on the filtered current data, and uses the filtered voltage skewness, filtered voltage kurtosis, filtered current skewness and filtered current kurtosis as statistical features.

[0011] Optionally, the physical construction model is as follows: , among which, among which, represents the physical construction model, Indicates the detection time is Current data on the distribution line, Indicates the inductance of the preset power distribution line, Indicates the resistance of the preset distribution line, Indicates the capacitance of the preset distribution line, represents the rate of change of current, Indicates the weight of the preset filter voltage skewness, represents the weight of the preset filtered voltage peak, Indicates the preset detection time.

[0012] Optionally, performing a fault point location operation on the faulty electrical line to obtain the fault point location includes: dividing the faulty electrical line to obtain a line segment group, wherein the line segment group includes multiple line segments, and the line segments include: a front-end segment breakpoint and a rear-end segment breakpoint; extracting line segments from the line segment group in sequence, and performing the following operations on each of the extracted line segments: obtaining a power supply breakpoint inductance and a power supply breakpoint capacitance based on pre-established power supply points and rear-end segment breakpoints, and calculating a rear-end breakpoint impedance of the rear-end segment breakpoint in the line segment based on the power supply breakpoint inductance and the power supply breakpoint capacitance, wherein the calculation formula is as follows: ,in, Represents the back-end breakpoint impedance, Indicates the preset initial impedance, represents the preset imaginary unit, represents pi, Indicates the preset power frequency, Indicates the power breakpoint inductance, represents the power breakpoint capacitance; obtain the impedance difference based on the back-end breakpoint impedance and the initial impedance, and determine whether the impedance difference is within a preset standard impedance range; if the impedance difference is not within the preset standard impedance range, extract the inductance and capacitance from the impedance difference, and calculate the fault point location based on the inductance and capacitance; if the impedance difference is within the preset standard impedance range, return to the step of sequentially extracting line segments from the line segment group until the line segment group is an empty set.

[0013] Optionally, triggering a pre-built automatic alarm mechanism according to the fault point location and generating an alarm file includes: obtaining a blank file, obtaining a fault level according to the fault point location, obtaining a first-level threshold and a second-level threshold, comparing the fault level with the first-level threshold, and comparing the fault level with the second-level threshold; if the fault level is greater than the first level, the automatic alarm mechanism generates an orange alarm, imports the orange alarm and the fault point location into the blank file, and obtains a first alarm file; if the fault level is less than or equal to the first level and the fault level is greater than the second-level threshold, the automatic alarm mechanism generates a red alarm, imports the red alarm and the fault point location into the blank file, and obtains a second alarm file; if the fault level is less than or equal to the second-level threshold, the automatic alarm mechanism generates a yellow alarm, imports the yellow alarm and the fault point location into the blank file, and obtains a third alarm file; obtaining an alarm file based on the first alarm file, the second alarm file, and the third alarm file, wherein when the fault level is greater than the first level, the alarm file is the first alarm file, when the fault level is less than or equal to the first level and the fault level is greater than the second-level threshold, the alarm file is the second alarm file, and when the fault level is less than or equal to the second-level threshold, the alarm file is the third alarm file.

[0014] To achieve the above-mentioned purpose, the present invention also provides an automatic alarm system based on online fault detection of distribution lines, comprising: a line environment detection module, for identifying a target distribution network, and obtaining a current environment based on the target distribution network, wherein the target distribution network comprises: multiple distribution lines, receiving a line fault detection instruction, and detecting the current environment using a pre-built wind speed sensor according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data comprises multiple current wind speed values, and if there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, the current wind speed value is taken as an abnormal wind speed value, the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained, and if the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines; a line fault detection module, for, if there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, Then, distribution lines are extracted from multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: statistical features of the distribution lines are obtained, a physical construction model is obtained, the statistical features are input into the physical construction model, a model prediction value is obtained, the model prediction value is compared with a preset normal prediction value, if the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as a faulty line, a fault point location operation is performed on the faulty line, and the fault point location is obtained; a line fault repair module is used to trigger a pre-built automatic alarm mechanism according to the fault point location, and generate an alarm file, and perform fault repair on the faulty line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value to obtain a normal line; a fault alarm completion module is used to summarize the normal lines to obtain a normal line set, and complete the automatic alarm based on the online fault detection of the distribution line based on the normal line set and the repair line set.

[0015] In order to solve the above problem, the present invention further provides an electronic device, comprising: a memory storing at least one instruction; The processor executes the instructions stored in the memory to implement the above-mentioned automatic alarm method based on online fault detection of distribution lines.

[0016] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned automatic alarm method based on online fault detection of distribution lines.

[0017] The present invention is to solve the problems described in the background technology. The present invention identifies the target distribution network and obtains the current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines. The present invention clarifies the target distribution network and its current environment, which helps to focus the fault detection work on a specific area, avoids invalid detection of irrelevant areas, improves the pertinence and efficiency of detection, receives a line fault detection instruction, and uses a pre-built wind speed sensor to detect the current environment according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values. The present invention receives the line fault detection instruction, so that the system can start the fault detection work in time according to actual needs, has strong initiative and flexibility, and uses the wind speed sensor to detect The wind speed data of the current environment can predict the impact of strong winds on the lines in advance by monitoring the wind speed in real time, and take corresponding preventive measures. If the current wind speed data contains a current wind speed value that is greater than the preset standard wind speed threshold, the current wind speed value is used as an abnormal wind speed value, and the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained. If the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines. In the present invention, when the current wind speed data contains a current wind speed value that is greater than the preset standard wind speed threshold, it indicates that the strong wind in the current environment may cause greater damage to the distribution lines. At this time, the repair line set is obtained, and the necessary repair materials can be prepared in advance so that they can be repaired quickly after the strong wind passes. The damaged lines can be repaired quickly to reduce the power outage time and improve the power supply reliability. If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, the distribution lines are extracted from multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: obtain the statistical characteristics of the distribution lines, obtain the physical construction model, input the statistical characteristics into the physical construction model, obtain the model prediction value, and compare the model prediction value with the preset normal prediction value. By comparing the model prediction value with the normal prediction value, the present invention can accurately identify the faulty power line, avoid misjudgment of the normal line, and improve the accuracy of fault detection. If the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as the faulty power line. The present invention can accurately locate the fault point of the fault line so that maintenance personnel can quickly reach the fault site, shorten the fault repair time, reduce the scope and impact of power outages, trigger a pre-built automatic alarm mechanism according to the fault point location, and generate an alarm file. According to the alarm file, the fault line is repaired until the model prediction value is less than or equal to the preset normal prediction value, and a normal line is obtained. The present invention triggers the automatic alarm mechanism according to the fault point location, and can promptly notify the relevant operation and maintenance personnel of the fault information. The automatic alarm can be carried out in a variety of ways such as text messages, emails, and sound and light alarms, ensuring that the operation and maintenance personnel can know the fault situation at the first time, take timely measures to deal with it, and summarize the normal lines.A normal line set is obtained, and based on the normal line set and the repair line set, an automatic alarm based on online fault detection of the distribution line is completed. The present invention aggregates the normal lines to obtain the normal line set, which can fully understand the normal operation of the lines in the target distribution network. This helps to evaluate and manage the operating status of the entire distribution network and provides a reference for subsequent grid planning and maintenance. Therefore, the present invention can improve the reliability and operating efficiency of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of an automatic alarm method based on online fault detection of a power distribution line provided by one embodiment of the present invention; Figure 2 A functional module diagram of an automatic alarm system based on online fault detection of distribution lines provided by one embodiment of the present invention; Figure 3 A schematic structural diagram of an electronic device for implementing the automatic alarm method based on online fault detection of distribution lines provided in one embodiment of the present invention.

[0019] Description of reference numerals: 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0020] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] The embodiment of the present application provides an automatic alarm method based on online fault detection of distribution lines. The execution subject of the automatic alarm method based on online fault detection of distribution lines includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the automatic alarm method based on online fault detection of distribution lines can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0023] Reference Figure 1 FIG2 is a flow chart of an automatic alarm method based on online fault detection of distribution lines according to an embodiment of the present invention. In this embodiment, the automatic alarm method based on online fault detection of distribution lines includes: S1. Identifying a target distribution network and obtaining a current environment based on the target distribution network, wherein the target distribution network includes: a plurality of distribution lines.

[0024] It should be noted that the target distribution network refers to the distribution network for which online fault detection is required. The current environment refers to the current environment of the target distribution network. Distribution lines are important components of the target distribution network, used to transmit and distribute electrical energy.

[0025] S2. Receive a line fault detection instruction, and according to the line fault detection instruction, use a pre-built wind speed sensor to detect the current environment to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values.

[0026] It should be explained that a line fault detection command is initiated by an operator and is used to trigger and direct fault detection operations on distribution lines. A wind speed sensor is a sensor used to measure air velocity. Examples include cup wind speed sensors and ultrasonic wind speed sensors. Wind speed data refers to the air velocity data acquired and recorded by the wind speed sensor during environmental monitoring.

[0027] S3. If there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, the current wind speed value is taken as an abnormal wind speed value, the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained. If the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines.

[0028] It should be noted that the standard wind speed threshold is a pre-set reference value used to measure whether the current ambient wind speed is within a safe range. An abnormal wind speed value refers to a wind speed value when a wind speed value in the current wind speed data exceeds the preset standard wind speed threshold. An abnormal wind speed value set refers to the collection of all abnormal wind speed values. The abnormal value quantity threshold refers to a pre-set number of abnormal wind speed values.

[0029] In detail, the method of obtaining a repair line set based on multiple distribution lines includes: determining whether there is a broken distribution line among the multiple distribution lines; if there is a broken distribution line among the multiple distribution lines, treating the broken distribution line as a broken line, summarizing the broken lines, and obtaining a broken line set; obtaining the number of breaks in the broken line set, and if the number of breaks is greater than a preset break number threshold, formulating an optimal fault repair strategy, and performing emergency repairs on the broken line set according to the optimal fault repair strategy to obtain a repair line set; if the number of breaks is less than or equal to the preset break number threshold, formulating a fault repair strategy, and repairing the broken line set according to the fault repair strategy to obtain a repair line set.

[0030] It should be explained that a broken line refers to a distribution line among multiple distribution lines that is broken due to various reasons (such as strong winds). A broken line set refers to a set consisting of all broken lines. The break number threshold refers to a pre-set value for the number of broken lines. The break number threshold is used to judge the severity of the current distribution line break and then decide what repair strategy to adopt. The emergency repair refers to giving priority to repair plans that can restore power to important user locations as quickly as possible, reducing power outage time and impact range. For example, important users are hospitals, transportation hubs, etc. Repairing the broken line set according to the fault repair strategy refers to obtaining the location of the broken line set and repairing the broken line set according to the location distance.

[0031] In detail, the formulation of the optimal fault repair strategy includes: determining the initial emergency repair sequence and the initial disturbance times, obtaining the objective function value according to the initial emergency repair sequence, randomly disturbing the initial emergency repair sequence, and performing an addition operation on the initial disturbance times to obtain the updated emergency repair sequence and the updated disturbance times; calculating the updated objective function value of the updated emergency repair sequence, obtaining the function difference value according to the objective function value and the updated objective function value, wherein the function difference value is the absolute difference between the updated objective function value and the objective function value; deciding whether to accept the updated objective function value according to the pre-constructed Boltzmann probability formula and the function difference value; if the updated objective function value is accepted, then judging whether to update the disturbance times The updated number of disturbances is less than the preset maximum number of disturbances. If the updated number of disturbances is less than the preset maximum number of disturbances, the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the step of randomly disturbing the initial repair order is returned; if the updated number of disturbances is greater than or equal to the preset maximum number of disturbances, the updated repair order corresponding to the updated number of disturbances that is less than the preset maximum number of disturbances is used as the optimal fault repair strategy; if the updated objective function value is not accepted, the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the step of randomly disturbing the initial repair order is returned until the updated objective function value is accepted.

[0032] It should be explained that the initial repair order refers to the pre-set order of repairing the broken wire set when the optimal fault repair strategy is first formulated. The initial disturbance count refers to the starting value of the number of random adjustments to the initial repair order. For example, the initial disturbance count is 0. Random disturbance refers to a random adjustment operation on the current repair order. The updated repair order refers to the new repair order obtained after a random disturbance operation, which is used to determine whether a better objective function value can be obtained. The updated disturbance count refers to the new disturbance count obtained by adding one to the disturbance count after each random disturbance operation. The Boltzmann probability formula refers to a probability formula used to decide whether to accept the updated objective function value, where the Boltzmann probability formula is as follows: ,in, Indicate whether to accept, and when When , it means accepting the updated objective function value. Indicates that the updated objective function value is not accepted. represents the natural exponential function, represents the function difference value, Indicates the preset control parameters.

[0033] It is understandable that the maximum number of disturbances refers to a pre-set maximum upper limit of the number of random disturbances. The plus-one operation refers to the operation of increasing the current number of disturbances by 1 each time the current emergency repair order is randomly disturbed. The updated objective function value refers to the objective function value calculated based on the updated emergency repair order. The method of calculating the updated objective function value of the updated emergency repair order is the same as the method of obtaining the objective function value based on the initial emergency repair order, and will not be repeated here. The optimal fault repair strategy refers to the updated emergency repair order corresponding to the updated disturbance number that is less than the maximum disturbance number when the updated disturbance number reaches the preset maximum disturbance number after multiple random disturbances and comparisons with the objective function value.

[0034] In detail, obtaining the objective function value according to the initial emergency repair sequence includes: obtaining an initial sequence line set according to the initial emergency repair sequence, calculating the repair time and load power of each initial sequence line in the initial sequence line set to obtain a repair time set and a load power set, accumulating the repair time set and the load power set to obtain a comprehensive repair time and a comprehensive load power, wherein the initial sequence line set includes multiple initial sequence lines, the comprehensive repair time includes multiple repair times, and the comprehensive load power includes multiple load powers, wherein the initial sequence lines correspond to the repair time and the load power in a one-to-one manner; and calculating the objective function value of the initial sequence line set according to the pre-constructed objective function, the comprehensive repair time, and the comprehensive load power, wherein the objective function is as follows: ,in, represents the objective function value, Represents all symbols, represents the initial sequence line set, represents the repair time of the initial sequence line, Indicates the index of the preset unbroken line, The index representing the sequence in the initial sequence line set, and Both represent preset binary variables. and Both represent the load power of the initial sequence line, Indicates the The repair time of the initial sequence line, Indicates the comprehensive repair time, Indicates the comprehensive load power, represents the number index of the initial sequence line set, Indicates taking the minimum value.

[0035] It should be explained that the initial sequence line set refers to the set of lines that need to be repaired according to the initial repair sequence. Load power refers to the power load carried by the line. A binary variable is a variable that includes two states, wherein the two states include an unbroken state or a broken state. The index of the sequence in the initial sequence line set refers to the order of the lines in the initial repair sequence. For example, when When , it represents the line ranked first in the initial sequence line set. The number index of the initial sequence line set is the index used to number the lines in the initial sequence line set. For example, there are 5 lines in the line set. It can take values from 1 to 5, corresponding to these 5 different lines.

[0036] S4. If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, then extract distribution lines from multiple distribution lines in sequence, and perform the following operations on the extracted distribution lines: obtain statistical characteristics of the distribution lines.

[0037] In detail, the obtaining of statistical characteristics of the distribution line includes: using pre-built intelligent sensors and preset sampling frequencies to collect electrical parameters of the distribution line to obtain electrical parameters, wherein the intelligent sensors include: current sensors and voltage sensors, wherein the electrical parameters include: current data and voltage data, wherein the current data includes multiple current values, and the voltage data includes multiple voltage values; performing analog-to-digital conversion operations on the electrical parameters to obtain digital electrical parameters, filtering the digital electrical parameters to obtain filtered electrical parameters, wherein the filtered electrical parameters include: filtered voltage data and filtered current data; and calculating the statistical characteristics of the filtered electrical parameters.

[0038] It should be explained that the sampling frequency refers to the number of samples collected per unit time when discrete sampling of a continuous analog signal is performed at a predetermined frequency. For example, the sampling frequency is 0.01 seconds. The analog-to-digital conversion operation refers to the operation of converting a continuous signal into a discrete digital signal. The filtering of the digital electrical parameters refers to filtering the digital electrical parameters using a filtering algorithm. For example, the filtering algorithm may be a median filter, a mean filter, or the like. The filtered electrical parameters refer to the parameters obtained after filtering the digital electrical parameters.

[0039] In detail, the statistical characteristics of the filter electrical parameters are calculated, including: calculating the filter voltage standard deviation and the filter voltage mean according to the filter voltage data, and calculating the filter voltage skewness and the filter voltage kurtosis according to the filter voltage standard deviation and the filter voltage mean, wherein the calculation formulas of the filter voltage skewness and the filter voltage kurtosis are as follows: , ,in, Indicates the filter voltage skewness, Indicates the total number of filtered voltage data, Indicates the The filtered voltage value, represents the mean value of the filtered voltage, represents the standard deviation of the filtered voltage, represents the filtered voltage peak, Represents the index of the filtered voltage data; obtains the filtered current skewness and filtered current kurtosis based on the filtered current data, and uses the filtered voltage skewness, filtered voltage kurtosis, filtered current skewness and filtered current kurtosis as statistical features.

[0040] It should be explained that the filtered voltage mean refers to the average value of the filtered voltage data. The filtered voltage standard deviation measures the degree of dispersion of the filtered voltage data relative to the filtered voltage mean. The steps for calculating the filtered voltage standard deviation are prior art and will not be repeated here. The filtered voltage skewness is used to describe the degree of asymmetry of the filtered voltage data distribution. The larger the filtered voltage skewness, the more concentrated the filtered voltage data is on the right side of the filtered voltage mean. The filtered voltage kurtosis refers to the flatness of the filtered voltage data distribution. The larger the filtered voltage kurtosis, the more serious the degree to which the distribution of the filtered voltage data deviates from the normal distribution. The method for obtaining the filtered current skewness and filtered current kurtosis based on the filtered current data is the same as the method for calculating the filtered voltage skewness and filtered voltage kurtosis, wherein the calculation formulas for the filtered current skewness and filtered current kurtosis are as follows: , ,in, Indicates the filter current skewness, Indicates the total number of filtered current data, Indicates the The filter current value, represents the mean value of the filtered current, Indicates the standard deviation of the filter current, represents the peak value of the filter current, Indicates the index of filtered current data.

[0041] It should be explained that the filtered current mean refers to the average value of the filtered current data. The filtered current standard deviation measures the degree of dispersion of the filtered current data relative to the filtered current mean. The steps for calculating the filtered current standard deviation are prior art and will not be repeated here. The filtered current skewness is used to describe the degree of asymmetry of the filtered voltage data distribution. The larger the filtered current skewness, the more concentrated the filtered current data is to the right of the filtered current mean. The filtered current kurtosis refers to the flatness of the filtered current data distribution. The larger the filtered current kurtosis, the more serious the deviation of the filtered current data distribution from the normal distribution.

[0042] S5. Obtain a physical construction model, input the statistical features into the physical construction model, obtain a model prediction value, and compare the model prediction value with a preset normal prediction value.

[0043] It should be explained that the steps of inputting statistical features into the physical construction model to obtain the model prediction value are: inputting the filtered voltage skewness and the filtered voltage kurtosis into the physical construction model to obtain the model voltage prediction value, inputting the filtered current skewness and the filtered current kurtosis into the physical construction model to obtain the model current prediction value, and confirming the sum of the model voltage prediction value and the model current prediction value as the model prediction value.

[0044] In detail, the physical construction model is as follows: ,in, represents the physical construction model, Indicates the detection time is Current data on the distribution line, Indicates the inductance of the preset power distribution line, Indicates the resistance of the preset distribution line, Indicates the capacitance of the preset distribution line, represents the rate of change of current, Indicates the weight of the preset filter voltage skewness, represents the weight of the preset filtered voltage peak, Indicates the preset detection time.

[0045] It should be explained that the weight of the filtered voltage skewness refers to the weight that measures the degree of asymmetry in the distribution of the filtered voltage data. The greater the weight of the filtered voltage skewness, the greater the impact of the filtered voltage skewness on the physical construction model. The greater the weight of the filtered voltage kurtosis, the greater the impact of the filtered voltage kurtosis on the physical construction model. The detection time refers to the pre-set time used to detect the current or voltage on the distribution line. The physical construction model of the model current prediction value is as follows: ,in, A physically constructed model representing the predicted values of the model current, Indicates the detection time is Voltage data on the distribution line at this time, Indicates the detection time is Current data on the distribution line, Indicates the weight of the preset filter current skewness, In the embodiment of the present invention, when calculating the model voltage prediction value and the model current prediction value, only the numerical value is substituted into the physical construction model without the unit, because the model prediction value needs to be compared with the normal prediction value.

[0046] S6. If the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as a faulty line, and a fault point location operation is performed on the faulty line to obtain the fault point position.

[0047] In detail, performing a fault point location operation on a faulty electrical line to obtain the fault point location includes: dividing the faulty electrical line to obtain a line segment group, wherein the line segment group includes multiple line segments, and the line segments include: a front-end dividing breakpoint and a rear-end dividing breakpoint; extracting line segments from the line segment group in sequence, and performing the following operations on each of the extracted line segments: obtaining a power breakpoint inductance and a power breakpoint capacitance based on pre-established power points and rear-end dividing breakpoints, and calculating a rear-end breaking point impedance of the rear-end dividing breakpoint in the line segment based on the power breakpoint inductance and the power breakpoint capacitance, wherein the calculation formula is as follows: ,in, Represents the back-end breakpoint impedance, Indicates the preset initial impedance, represents the preset imaginary unit, represents pi, Indicates the preset power frequency, Indicates the power breakpoint inductance, represents the power breakpoint capacitance; obtain the impedance difference based on the back-end breakpoint impedance and the initial impedance, and determine whether the impedance difference is within a preset standard impedance range; if the impedance difference is not within the preset standard impedance range, extract the inductance and capacitance from the impedance difference, and calculate the fault point location based on the inductance and capacitance; if the impedance difference is within the preset standard impedance range, return to the step of sequentially extracting line segments from the line segment group until the line segment group is an empty set.

[0048] It should be explained that the division of the faulty electrical line refers to the division of the faulty electrical line using a preset division length. The division length refers to a pre-set length. The line segment group refers to a set consisting of all line segments. The front-end division breakpoint and the rear-end division breakpoint refer to the starting endpoint of the line segment as the front-end division breakpoint and the ending endpoint as the rear-end division breakpoint, respectively. For example, starting from the power point and dividing the line in sequence, the starting point of the first line segment is the front-end division breakpoint, and the end point is the rear-end division breakpoint. The starting point of the second line segment is the rear-end division breakpoint of the previous line segment, and its end point is the new rear-end division breakpoint.

[0049] Importantly, the power breakpoint inductance refers to the inductance from the power point to the back-end dividing breakpoint. The power breakpoint capacitance refers to the capacitance from the power point to the back-end dividing breakpoint. The step of obtaining the power breakpoint inductance and power breakpoint capacitance based on the pre-established power point and back-end dividing breakpoint is: obtaining the length of the line segment, and calculating the inductance per unit length and the capacitance per unit length based on the length of the line segment, wherein the calculation formula is as follows: , ,in, represents the inductance per unit length, Indicates the distance between the preset fault lines. Indicates the equivalent radius of the preset fault line, represents the capacitance per unit length, represents the preset vacuum dielectric constant, Represents a logarithmic function.

[0050] The power breakpoint inductance is calculated based on the line segment length and the inductance per unit length. The fault line spacing refers to the distance between the faulty line and adjacent faulty lines. The equivalent radius of the faulty line and the spacing between the faulty lines are obtained from the technical manual for the line. The power breakpoint inductance is the product of the line segment length and the inductance per unit length. The vacuum dielectric constant refers to the ability of a dielectric to polarize in an electric field.

[0051] It should be explained that the power frequency refers to the frequency of the power supply in the power system. The power supply point refers to the point where power is output from the power generation equipment to the faulty power line. Obtaining the impedance difference based on the rear-end breakpoint impedance and the initial impedance means subtracting the initial impedance from the rear-end breakpoint impedance to obtain the impedance difference. The standard impedance range refers to a pre-set range. The calculation formula for calculating the fault point location based on inductance and capacitance is as follows: ,in, Indicates the location of the fault point.

[0052] S7. Trigger a pre-built automatic alarm mechanism according to the fault point location and generate an alarm file. Repair the faulty power line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value, and a normal power line is obtained.

[0053] In detail, the method triggers a pre-built automatic alarm mechanism according to the fault point location and generates an alarm file, including: obtaining a blank file, obtaining a fault level according to the fault point location, obtaining a first-level threshold and a second-level threshold, comparing the fault level with the first-level threshold, and comparing the fault level with the second-level threshold; if the fault level is greater than the first level, the automatic alarm mechanism generates an orange alarm, imports the orange alarm and the fault point location into the blank file, and obtains a first alarm file; if the fault level is less than or equal to the first level and the fault level is greater than the second-level threshold, the automatic alarm mechanism generates a red alarm, imports the red alarm and the fault point location into the blank file, and obtains a second alarm file; if the fault level is less than or equal to the second-level threshold, the automatic alarm mechanism generates a yellow alarm, imports the yellow alarm and the fault point location into the blank file, and obtains a third alarm file; and obtaining an alarm file based on the first alarm file, the second alarm file, and the third alarm file, wherein, when the fault level is greater than the first level, the alarm file is the first alarm file, when the fault level is less than or equal to the first level and the fault level is greater than the second-level threshold, the alarm file is the second alarm file, and when the fault level is less than or equal to the second-level threshold, the alarm file is the third alarm file.

[0054] It should be explained that determining the fault severity based on the location of the fault point refers to determining the fault severity based on the impact and hazard level of the fault point location. For example, if the fault point is located near a key hub substation or on a power supply line at an important load center, the fault severity is Level 1. The Level 1 and Level 2 thresholds are pre-set thresholds for classifying fault severity. An automatic alarm mechanism is a mechanism that automatically triggers corresponding alarm actions based on fault information (such as the fault point location and fault severity). A blank file is a pre-prepared file containing no content. An alarm file is a file created by importing generated alarm information (such as orange, red, and yellow alarms) and the fault point location into a blank file after the automatic alarm mechanism is triggered. The method for repairing a faulty power line based on an alarm file is similar to the steps for repairing a broken line set based on a fault repair strategy and will not be further described here. The first alarm file is the file generated by the automatic alarm mechanism to generate an orange alarm when the fault severity is greater than the Level 1 threshold. The second alarm file is the file generated by the automatic alarm mechanism to generate a red alarm when the fault severity is less than or equal to the Level 1 threshold and greater than the Level 2 threshold. The third alarm file refers to a file generated by the automatic alarm mechanism as a yellow alarm when the fault level is less than or equal to the level 2 threshold. In the embodiment of the present invention, if the fault level is greater than level 1, a first alarm file is generated; if the fault level is less than or equal to level 1 and the fault level is greater than the level 2 threshold, a second alarm file is generated; and if the fault level is less than or equal to the level 2 threshold, a third alarm file is generated. The first, second, and third alarm files are all generated at different fault levels. Therefore, an alarm file refers to an alarm file identified from the first, second, and third alarm files based on the fault level.

[0055] S8. Summarize the normal power lines to obtain a normal power line set, and complete automatic alarm based on online fault detection of the distribution line based on the normal power line set and the repaired line set.

[0056] It should be explained that a normal power line refers to a line whose model-predicted value is less than or equal to the preset normal predicted value after a series of fault repair operations. A normal power line set refers to the set of all normal power lines. A repaired power line set refers to the set of all repaired power lines.

[0057] The present invention is to solve the problems described in the background technology. The present invention identifies the target distribution network and obtains the current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines. The present invention clarifies the target distribution network and its current environment, which helps to focus the fault detection work on a specific area, avoids invalid detection of irrelevant areas, improves the pertinence and efficiency of detection, receives a line fault detection instruction, and uses a pre-built wind speed sensor to detect the current environment according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values. The present invention receives the line fault detection instruction, so that the system can start the fault detection work in time according to actual needs, has strong initiative and flexibility, and uses the wind speed sensor to detect The wind speed data of the current environment can predict the impact of strong winds on the lines in advance by monitoring the wind speed in real time, and take corresponding preventive measures. If the current wind speed data contains a current wind speed value that is greater than the preset standard wind speed threshold, the current wind speed value is used as an abnormal wind speed value, and the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained. If the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines. In the present invention, when the current wind speed data contains a current wind speed value that is greater than the preset standard wind speed threshold, it indicates that the strong wind in the current environment may cause greater damage to the distribution lines. At this time, the repair line set is obtained, and the necessary repair materials can be prepared in advance so that they can be repaired quickly after the strong wind passes. The damaged lines can be repaired quickly to reduce the power outage time and improve the power supply reliability. If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, the distribution lines are extracted from multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: obtain the statistical characteristics of the distribution lines, obtain the physical construction model, input the statistical characteristics into the physical construction model, obtain the model prediction value, and compare the model prediction value with the preset normal prediction value. By comparing the model prediction value with the normal prediction value, the present invention can accurately identify the faulty power line, avoid misjudgment of the normal line, and improve the accuracy of fault detection. If the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as the faulty power line. The present invention can accurately locate the fault point of the fault line so that maintenance personnel can quickly reach the fault site, shorten the fault repair time, reduce the scope and impact of power outages, trigger a pre-built automatic alarm mechanism according to the fault point location, and generate an alarm file. According to the alarm file, the fault line is repaired until the model prediction value is less than or equal to the preset normal prediction value, and a normal line is obtained. The present invention triggers the automatic alarm mechanism according to the fault point location, and can promptly notify the relevant operation and maintenance personnel of the fault information. The automatic alarm can be carried out in a variety of ways such as text messages, emails, and sound and light alarms, ensuring that the operation and maintenance personnel can know the fault situation at the first time, take timely measures to deal with it, and summarize the normal lines.A normal line set is obtained, and based on the normal line set and the repair line set, an automatic alarm based on online fault detection of the distribution line is completed. The present invention aggregates the normal lines to obtain the normal line set, which can fully understand the normal operation of the lines in the target distribution network. This helps to evaluate and manage the operating status of the entire distribution network and provides a reference for subsequent grid planning and maintenance. Therefore, the present invention can improve the reliability and operating efficiency of the power system.

[0058] like Figure 2 , which is a functional module diagram of an automatic alarm system based on online fault detection of distribution lines provided by an embodiment of the present invention.

[0059] The automatic alarm system 100 for online fault detection of power distribution lines described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the automatic alarm system 100 can include a line environment detection module 101, a line fault detection module 102, a line fault repair module 103, and a fault alarm completion module 104. The module described in the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device; the line environment detection module 101 is used to confirm the target distribution network and obtain the current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines, receiving a line fault detection instruction, and using a pre-built wind speed sensor to detect the current environment according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values. If there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, the current wind speed value is used as an abnormal wind speed value, the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained. If the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines; the line fault detection module 102 is used to, if there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, The current wind speed value of the standard wind speed threshold is set, and the distribution lines are extracted from the multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: obtain the statistical characteristics of the distribution lines, obtain the physical construction model, input the statistical characteristics into the physical construction model, obtain the model prediction value, compare the model prediction value with the preset normal prediction value, if the model prediction value is greater than the preset normal prediction value, then the distribution line corresponding to the model prediction value is confirmed as a faulty line, and the fault point location operation is performed on the faulty line to obtain the fault point location; the line fault repair module 103 is used to trigger the pre-built automatic alarm mechanism according to the fault point location, and generate an alarm file, and perform fault repair on the faulty line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value to obtain a normal line; the fault alarm completion module 104 is used to summarize the normal lines to obtain a normal line set, and complete the automatic alarm based on the online fault detection of the distribution line based on the normal line set and the repair line set.

[0060] In detail, the modules in the automatic alarm system 100 based on online fault detection of distribution lines in the embodiment of the present invention are used in the same manner as above. Figure 1 The automatic alarm method based on online fault detection of distribution lines is the same technical means as described in , and can produce the same technical effects, so it will not be repeated here.

[0061] like Figure 31 is a schematic structural diagram of an electronic device for implementing an automatic alarm method based on online fault detection of a power distribution line provided by an embodiment of the present invention.

[0062] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an automatic alarm method program based on online fault detection of a distribution line.

[0063] The memory 11 includes at least one type of readable storage medium, including flash memory, a removable hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in removable hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 11 includes both the internal storage unit of the electronic device 1 and external storage devices. The memory 11 can be used not only to store application software installed in the electronic device 1 and various data, such as the code of an automatic alarm method program based on online fault detection of distribution lines, but also to temporarily store data that has been output or is about to be output.

[0064] In some embodiments, the processor 10 may be comprised of an integrated circuit, such as a single packaged integrated circuit or a combination of multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting the various components of the electronic device using various interfaces and circuits. It executes programs or modules stored in the memory 11 (e.g., an automatic alarm method program based on online fault detection of distribution lines) and accesses data stored in the memory 11 to perform various functions and process data.

[0065] The bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to enable communication between the memory 11 and at least one processor 10.

[0066] Figure 3 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the electronic device 1 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0067] For example, although not shown, the electronic device 1 may further include a power supply (e.g., a battery) to power various components. Preferably, the power supply may be logically connected to the at least one processor 10 via a power management device, thereby enabling functions such as charge management, discharge management, and power consumption management via the power management device. The power supply may further include any components such as one or more DC or AC power supplies, a recharging device, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not further described here.

[0068] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0069] Optionally, the electronic device 1 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device 1 and to display a visual user interface.

[0070] The automatic alarm method program based on online fault detection of distribution lines stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve: identifying the target distribution network, obtaining the current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines; receiving a line fault detection instruction, and according to the line fault detection instruction, using a pre-built wind speed sensor to detect the current environment to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values; if there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, then the current wind speed value is used as an abnormal wind speed value, and the abnormal wind speed values are summarized to obtain an abnormal wind speed value set; obtaining the number of abnormal values in the abnormal wind speed value set, and if the number of abnormal values is greater than the preset abnormal value number threshold, then obtaining a repair line set based on multiple distribution lines; if there is no current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, then The current wind speed value of the standard wind speed threshold is obtained, and the distribution lines are extracted from the multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: statistical characteristics of the distribution lines are obtained, a physical construction model is obtained, the statistical characteristics are input into the physical construction model, a model prediction value is obtained, and the model prediction value is compared with a preset normal prediction value; if the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as a faulty line, and a fault point location operation is performed on the faulty line to obtain the fault point location; a pre-built automatic alarm mechanism is triggered according to the fault point location, and an alarm file is generated, and the fault line is repaired according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value to obtain a normal line; the normal lines are summarized to obtain a normal line set, and automatic alarm based on online fault detection of the distribution line is completed based on the normal line set and the repair line set.

[0071] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0072] Furthermore, if the modules / units integrated into the electronic device 1 are implemented as software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. The computer-readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0073] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can achieve the following: identifying a target distribution network, obtaining a current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines; receiving a line fault detection instruction, and according to the line fault detection instruction, using a pre-built wind speed sensor to detect the current environment to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values; if there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, then the current wind speed value is used as an abnormal wind speed value, and the abnormal wind speed values are summarized to obtain an abnormal wind speed value set; obtaining the number of abnormal values in the abnormal wind speed value set, and if the number of abnormal values is greater than a preset abnormal value number threshold, then obtaining a repair line set based on multiple distribution lines; if there is no current wind speed value greater than a preset standard wind speed threshold in the current wind speed data If the current wind speed value is greater than the quasi-wind speed threshold, the distribution lines are extracted from the multiple distribution lines in sequence, and the following operations are performed on the extracted distribution lines: obtain the statistical characteristics of the distribution lines, obtain the physical construction model, input the statistical characteristics into the physical construction model, obtain the model prediction value, and compare the model prediction value with the preset normal prediction value; if the model prediction value is greater than the preset normal prediction value, the distribution line corresponding to the model prediction value is confirmed as a faulty line, and the fault point location operation is performed on the faulty line to obtain the fault point location; according to the fault point location, a pre-built automatic alarm mechanism is triggered, and an alarm file is generated, and the fault line is repaired according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value to obtain a normal line; the normal lines are summarized to obtain a normal line set, and the automatic alarm based on the online fault detection of the distribution line is completed based on the normal line set and the repair line set.

[0074] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only exemplary, and actual implementations may have other division methods.

[0075] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0076] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0077] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. 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.

Claims

1. An automatic alarm method based on online fault detection of distribution lines, characterized in that: The method includes: identifying a target distribution network, obtaining a current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines; receiving a line fault detection instruction, and detecting the current environment using a pre-built wind speed sensor according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values; if there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, then taking the current wind speed value as an abnormal wind speed value, summarizing the abnormal wind speed values, and obtaining an abnormal wind speed value set; obtaining the number of abnormal values in the abnormal wind speed value set, and if the number of abnormal values is greater than a preset abnormal value number threshold, obtaining a repair line set based on multiple distribution lines; if there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, then extracting distribution lines from the multiple distribution lines in sequence. The method comprises the following steps: obtaining statistical features of the distribution lines, obtaining a physical construction model, inputting the statistical features into the physical construction model, obtaining a model prediction value, and comparing the model prediction value with a preset normal prediction value; if the model prediction value is greater than the preset normal prediction value, confirming the distribution line corresponding to the model prediction value as a faulty line, performing a fault point location operation on the faulty line, and obtaining the position of the fault point; triggering a pre-built automatic alarm mechanism according to the position of the fault point, generating an alarm file, and repairing the faulty line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value, and obtaining a normal line; summarizing the normal lines to obtain a normal line set, and completing an automatic alarm based on online fault detection of the distribution line based on the normal line set and the repair line set.

2. The automatic alarm method based on online fault detection of distribution lines according to claim 1, characterized in that: The method of obtaining a repair line set based on multiple distribution lines includes: determining whether there is a broken distribution line among the multiple distribution lines; if there is a broken distribution line among the multiple distribution lines, treating the broken distribution line as a broken line, summarizing the broken lines, and obtaining a broken line set; obtaining the number of breaks in the broken line set, and if the number of breaks is greater than a preset break number threshold, formulating an optimal fault repair strategy, and performing emergency repair on the broken line set according to the optimal fault repair strategy to obtain a repair line set; if the number of breaks is less than or equal to the preset break number threshold, formulating a fault repair strategy, and repairing the broken line set according to the fault repair strategy to obtain a repair line set.

3. The automatic alarm method based on online fault detection of distribution lines according to claim 2, characterized in that: The formulation of the optimal fault repair strategy includes: determining an initial repair sequence and an initial disturbance number, obtaining an objective function value according to the initial repair sequence, randomly disturbing the initial repair sequence, and performing an addition operation on the initial disturbance number to obtain an updated repair sequence and an updated disturbance number; calculating an updated objective function value of the updated repair sequence, obtaining a function difference value according to the objective function value and the updated objective function value, wherein the function difference value is the absolute difference between the updated objective function value and the objective function value; determining whether to accept the updated objective function value according to the pre-constructed Boltzmann probability formula and the function difference value; if the updated objective function value is accepted, then determining whether the updated disturbance number is If the updated disturbance number is less than the preset maximum disturbance number, then the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the process returns to the step of randomly disturbing the initial repair order; if the updated disturbance number is greater than or equal to the preset maximum disturbance number, then the updated repair order corresponding to the updated disturbance number that is less than the preset maximum disturbance number is used as the optimal fault repair strategy; if the updated objective function value is not accepted, then the updated repair order corresponding to the updated objective function value is used as the initial repair order, and the process returns to the step of randomly disturbing the initial repair order until the updated objective function value is accepted.

4. The automatic alarm method based on online fault detection of distribution lines according to claim 3, characterized in that: The obtaining of the objective function value according to the initial emergency repair sequence includes: obtaining an initial sequence line set according to the initial emergency repair sequence, calculating the repair time and load power of each initial sequence line in the initial sequence line set to obtain a repair time set and a load power set, accumulating the repair time set and the load power set to obtain a comprehensive repair time and a comprehensive load power, wherein the initial sequence line set includes multiple initial sequence lines, the comprehensive repair time includes multiple repair times, and the comprehensive load power includes multiple load powers, wherein the initial sequence lines correspond to the repair time and the load power in a one-to-one manner; and calculating the objective function value of the initial sequence line set according to a pre-constructed objective function, the comprehensive repair time, and the comprehensive load power, wherein the objective function is as follows: ,in, represents the objective function value, Represents all symbols, represents the initial sequence line set, represents the repair time of the initial sequence line, Indicates the index of the preset unbroken line, The index representing the sequence in the initial sequence line set, and Both represent preset binary variables. and Both represent the load power of the initial sequence line, Indicates the The repair time of the initial sequence line, Indicates the comprehensive repair time, Indicates the comprehensive load power, represents the number index of the initial sequence line set, Indicates taking the minimum value.

5. The automatic alarm method based on online fault detection of distribution lines according to claim 4, characterized in that: The obtaining of statistical characteristics of the distribution line includes: using pre-built intelligent sensors and a preset sampling frequency to collect electrical parameters of the distribution line to obtain electrical parameters, wherein the intelligent sensors include: current sensors and voltage sensors, wherein the electrical parameters include: current data and voltage data, wherein the current data includes multiple current values, and the voltage data includes multiple voltage values; performing analog-to-digital conversion operations on the electrical parameters to obtain digital electrical parameters, filtering the digital electrical parameters to obtain filtered electrical parameters, wherein the filtered electrical parameters include: filtered voltage data and filtered current data; and calculating the statistical characteristics of the filtered electrical parameters.

6. The automatic alarm method based on online fault detection of distribution lines according to claim 5, characterized in that: The statistical characteristics of the filter electrical parameters are calculated, including: calculating the filter voltage standard deviation and the filter voltage mean according to the filter voltage data, and calculating the filter voltage skewness and the filter voltage kurtosis according to the filter voltage standard deviation and the filter voltage mean, wherein the calculation formulas of the filter voltage skewness and the filter voltage kurtosis are as follows: , ,in, Indicates the filter voltage skewness, Indicates the total number of filtered voltage data, Indicates the The filtered voltage value, represents the mean value of the filtered voltage, represents the standard deviation of the filtered voltage, represents the filtered voltage peak, Represents the index of the filtered voltage data; obtains the filtered current skewness and filtered current kurtosis based on the filtered current data, and uses the filtered voltage skewness, filtered voltage kurtosis, filtered current skewness and filtered current kurtosis as statistical features.

7. The automatic alarm method based on online fault detection of distribution lines according to claim 6, characterized in that: The physical construction model is as follows: ,in, represents the physical construction model, Indicates the detection time is Current data on the distribution line, Indicates the inductance of the preset power distribution line, Indicates the resistance of the preset distribution line, Indicates the capacitance of the preset distribution line, represents the rate of change of current, Indicates the weight of the preset filter voltage skewness, represents the weight of the preset filtered voltage peak, Indicates the preset detection time.

8. The automatic alarm method based on online fault detection of distribution lines according to claim 7, characterized in that: The performing of a fault point location operation on the faulty electrical line to obtain the fault point position includes: dividing the faulty electrical line to obtain a line segment group, wherein the line segment group includes a plurality of line segments, and the line segments include: a front-end segment breakpoint and a rear-end segment breakpoint; sequentially extracting line segments from the line segment group, and performing the following operations on each of the extracted line segments: obtaining a power breakpoint inductance and a power breakpoint capacitance based on pre-established power points and rear-end segment breakpoints, and calculating a rear-end breakpoint impedance of the rear-end segment breakpoint in the line segment based on the power breakpoint inductance and the power breakpoint capacitance, wherein the calculation formula is as follows: ,in, Represents the back-end breakpoint impedance, Indicates the preset initial impedance, represents the preset imaginary unit, represents pi, Indicates the preset power frequency, Indicates the power breakpoint inductance, represents the power breakpoint capacitance; obtain the impedance difference based on the back-end breakpoint impedance and the initial impedance, and determine whether the impedance difference is within a preset standard impedance range; if the impedance difference is not within the preset standard impedance range, extract the inductance and capacitance from the impedance difference, and calculate the fault point location based on the inductance and capacitance; if the impedance difference is within the preset standard impedance range, return to the step of sequentially extracting line segments from the line segment group until the line segment group is an empty set.

9. The automatic alarm method based on online fault detection of distribution lines according to claim 8, characterized in that: The method triggering a pre-built automatic alarm mechanism according to the fault point location and generating an alarm file includes: obtaining a blank file, obtaining a fault level according to the fault point location, obtaining a first level threshold and a second level threshold, comparing the fault level with the first level threshold, and comparing the fault level with the second level threshold; if the fault level is greater than the first level, the automatic alarm mechanism generates an orange alarm, imports the orange alarm and the fault point location into the blank file to obtain a first alarm file; if the fault level is less than or equal to the first level and the fault level is greater than the second level threshold, the automatic alarm mechanism generates a red alarm, imports the red alarm and the fault point location into the blank file to obtain a second alarm file; if the fault level is less than or equal to the second level threshold, the automatic alarm mechanism generates a yellow alarm, imports the yellow alarm and the fault point location into the blank file to obtain a third alarm file; and obtaining an alarm file based on the first alarm file, the second alarm file, and the third alarm file, wherein when the fault level is greater than the first level, the alarm file is the first alarm file; when the fault level is less than or equal to the first level and the fault level is greater than the second level threshold, the alarm file is the second alarm file; and when the fault level is less than or equal to the second level threshold, the alarm file is the third alarm file.

10. An automatic alarm system based on online fault detection of distribution lines, characterized in that: The system includes: a line environment detection module, which is used to confirm the target distribution network and obtain the current environment based on the target distribution network, wherein the target distribution network includes: multiple distribution lines, receives a line fault detection instruction, and uses a pre-built wind speed sensor to detect the current environment according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data includes multiple current wind speed values. If there is a current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, the current wind speed value is used as an abnormal wind speed value, the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, and the number of abnormal values in the abnormal wind speed value set is obtained. If the number of abnormal values is greater than the preset abnormal value number threshold, a repair line set is obtained based on multiple distribution lines; a line fault detection module is used to extract distribution lines from multiple distribution lines in sequence if there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data. The extracted distribution lines are all subjected to the following operations: obtaining statistical features of the distribution lines, obtaining a physical construction model, inputting the statistical features into the physical construction model, obtaining a model prediction value, comparing the model prediction value with a preset normal prediction value, and if the model prediction value is greater than the preset normal prediction value, confirming the distribution line corresponding to the model prediction value as a faulty line, performing a fault point location operation on the faulty line, and obtaining the position of the fault point; a line fault repair module is used to trigger a pre-built automatic alarm mechanism according to the position of the fault point, and generate an alarm file, and perform fault repair on the faulty line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value, thereby obtaining a normal line; a fault alarm completion module is used to summarize the normal lines to obtain a normal line set, and complete the automatic alarm based on the online fault detection of the distribution line based on the normal line set and the repair line set.

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