Automatic alarm method and system based on power distribution line online fault detection

Abstract

The application relates to the technical field of line fault detection, and relates to an automatic alarm method and system based on power distribution line online fault detection, which comprises the following steps: detecting a current environment to obtain current wind speed data; if there is a current wind speed value greater than a preset standard wind speed threshold value in the current wind speed data, a line repair set is obtained based on multiple power distribution lines; if there is no current wind speed value greater than the preset standard wind speed threshold value in the current wind speed data, statistical characteristics of the power distribution lines are obtained, a physical construction model is obtained, the statistical characteristics are input into the physical construction model, model prediction values are obtained, fault point positioning operation is performed on a fault power line, a fault point position is obtained, an automatic alarm mechanism is triggered, fault repair is performed on the fault power line, a normal power line set is obtained, and automatic alarm based on power distribution line online fault detection is completed based on the normal power line set and the repair line set. The application can improve the reliability and operation efficiency of a power system.

Description

Technical Field

[0001] This invention relates to the field of line fault detection technology, and in particular to an automatic alarm method and system based on online fault detection of power distribution lines. Background Technology

[0002] Power distribution lines are a crucial component of the power system, responsible for transmitting electricity from substations to various user terminals. Online fault detection refers to the real-time monitoring and analysis of the operating status of power distribution lines during normal operation, promptly identifying potential faults or fault points in the lines, and accurately determining the type and location of the fault.

[0003] Traditional fault detection methods primarily rely on monitoring simple electrical parameters, such as abnormal changes in current and voltage. While these parameters change when a fault occurs in a line, it's difficult to accurately determine the type and location of the fault based solely on these parameters. Traditional power distribution line fault detection mainly depends on periodic manual inspections, but the scope of manual inspections is limited, making it difficult to conduct a comprehensive and timely check of the entire power distribution network. Therefore, improving the reliability and operational efficiency of power systems is an urgent technical problem that needs to be solved. Summary of the Invention

[0004] This invention provides an automatic alarm method and a computer-readable storage medium based on online fault detection of power distribution lines, with the main purpose of improving the reliability and operating efficiency of power systems.

[0005] To achieve the above objectives, the present invention provides an automatic alarm method based on online fault detection of power distribution lines, comprising:

[0006] The target power distribution network is identified, and the current environment is obtained based on the target power distribution network. The target power distribution network includes multiple power distribution lines.

[0007] Receive a line fault detection command, and according to the line fault detection command, use a pre-built wind speed sensor to detect the current environment and obtain the current wind speed data, which includes multiple current wind speed values;

[0008] If there is a current wind speed value in the current wind speed data that is greater than the preset standard wind speed threshold, then the current wind speed value is taken as an abnormal wind speed value, and the abnormal wind speed values ​​are summarized to obtain an abnormal wind speed value set.

[0009] Obtain the number of outliers in the abnormal wind speed value set. If the number of outliers exceeds the preset outlier threshold, obtain a set of repair lines based on multiple power distribution lines.

[0010] If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, then extract the power distribution lines sequentially from multiple power distribution lines, and perform the following operations on each extracted power distribution line:

[0011] Obtain the statistical characteristics of the power distribution line, 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.

[0012] If the model prediction value is greater than the preset normal prediction value, the power distribution line corresponding to the model prediction value is identified as a faulty power line, and a fault point location operation is performed on the faulty power line to obtain the fault point location.

[0013] The pre-built automatic alarm mechanism is triggered based on the location of the fault point, and an alarm file is generated. The faulty circuit is repaired based on the alarm file until the model prediction value is less than or equal to the preset normal prediction value, and a normal circuit is obtained.

[0014] The normal power lines are summarized to obtain a set of normal power lines. Based on the set of normal power lines and the set of repaired power lines, an automatic alarm is completed based on the online fault detection of power distribution lines.

[0015] Optionally, the step of obtaining a set of repair lines based on multiple power distribution lines includes:

[0016] Determine if there is a broken power distribution line among multiple power distribution lines;

[0017] If there are broken distribution lines among multiple distribution lines, then the broken distribution lines are considered as broken lines, and the broken lines are summarized to obtain a broken line set.

[0018] The number of breaks in the broken line set is obtained. If the number of breaks is greater than the preset break number threshold, the optimal fault repair strategy is formulated. The broken line set is then repaired urgently according to the optimal fault repair strategy to obtain the repaired line set.

[0019] If the number of breaks is less than or equal to the preset break number threshold, a fault repair strategy is formulated, and the broken line set is repaired according to the fault repair strategy to obtain the repaired line set.

[0020] Optionally, the step of formulating the optimal fault repair strategy includes:

[0021] Determine the initial emergency repair sequence and the initial number of disturbances, obtain the objective function value based on the initial emergency repair sequence, randomly disturb the initial emergency repair sequence, and increment the initial number of disturbances to obtain the updated emergency repair sequence and the updated number of disturbances.

[0022] Calculate the updated objective function value for updating the emergency repair order, and obtain the function difference value based on the objective function value and the updated objective function value. The function difference value is the absolute difference between the updated objective function value and the objective function value.

[0023] The decision to accept the updated objective function value is based on the pre-constructed Boltzmann probability formula and the function difference value.

[0024] If the updated objective function value is accepted, it is determined whether the number of updates and disturbances is less than the preset maximum number of disturbances. If the number of updates and disturbances is less than the preset maximum number of disturbances, the updated emergency repair order corresponding to the updated objective function value is used as the initial emergency repair order, and the step of randomly disturbing the initial emergency repair order is returned.

[0025] If the number of update disturbances is greater than or equal to the preset maximum number of disturbances, then the update repair sequence corresponding to the number of update disturbances less than the preset maximum number of disturbances will be used as the optimal fault repair strategy.

[0026] If the updated objective function value is not accepted, the updated emergency repair order corresponding to the updated objective function value is used as the initial emergency repair order, and the process returns to the step of randomly perturbing the initial emergency repair order until the updated objective function value is accepted.

[0027] Optionally, obtaining the objective function value according to the initial repair sequence includes:

[0028] The initial sequence line set is obtained based on the initial emergency repair sequence. The repair time and load power of each initial sequence line in the initial sequence line set are calculated to obtain the repair time set and load power set. The load power sets are accumulated to obtain the comprehensive load power. The initial sequence line set includes multiple initial sequence lines, and the comprehensive load power includes multiple load powers. The initial sequence lines correspond one-to-one with the repair time and load power.

[0029] The objective function value of the initial sequence line set is calculated based on the pre-constructed objective function, the repair time set, and the comprehensive load power. The objective function is shown below:

[0030] ,in, Represents the objective function value. Representing all symbols, This represents the initial sequential set of routes. This indicates the repair time for the initial sequence of lines. Indicates the index of the preset unbroken line. The index representing the order of the initial sequence of the lines. and Both represent pre-defined binary variables. and Both represent the load power of the initial sequence lines. Indicates the first Repair time for the initial sequence of lines Indicates the total load power. Indicates the index of the initial sequential line set. This indicates taking the minimum value. This represents the total number of broken lines in the initial sequence line set.

[0031] Optionally, obtaining the statistical characteristics of the power distribution line includes:

[0032] Electrical parameters of power distribution lines are collected using pre-built smart sensors and preset sampling frequencies. The smart sensors include current sensors and voltage sensors. The electrical parameters include current data and voltage data. The current data includes multiple current values, and the voltage data includes multiple voltage values.

[0033] The electrical parameters are converted from analog to digital to obtain digital electrical parameters. The digital electrical parameters are then filtered to obtain filtered electrical parameters, which include filtered voltage data and filtered current data.

[0034] Calculate the statistical characteristics of the filter's electrical parameters.

[0035] Optionally, the statistical characteristics of the calculated filter electrical parameters include:

[0036] The standard deviation and mean of the filter voltage are calculated based on the filter voltage data. The skewness and kurtosis of the filter voltage are then calculated based on these values. The formulas for calculating the skewness and kurtosis are shown below:

[0037] , ,in, Indicates the filter voltage skewness. This indicates the total number of filtered voltage data. Indicates the first Each filter voltage value, This represents the average value of the filtered voltage. Indicates the standard deviation of the filter voltage. Indicates the kurtosis of the filtered voltage. The index represents the filtered voltage data; the filtered current skewness and kurtosis are obtained based on the filtered current data, and the filtered voltage skewness, filtered voltage kurtosis, filtered current skewness, and filtered current kurtosis are used as statistical features.

[0038] Optionally, the physical construction model is as follows:

[0039] ,in, Represents the physical construction model, Indicates the detection time is Current data on power distribution lines This indicates the inductance of the pre-defined power distribution line. This indicates the resistance of the preset power distribution line. This indicates the capacitance of the pre-set power distribution line. Indicates the rate of change of current. This indicates the weight of the preset filter voltage bias or the weight of the preset filter current bias. This indicates the weight of the preset filter voltage kurtosis or the weight of the preset filter current skewness. This indicates a preset detection time. Optionally, the fault point location operation for the faulty line to obtain the fault point location includes: dividing the faulty line into line segment groups, wherein the line segment group includes multiple line segments, and the line segment includes: a front-end breakpoint and a rear-end breakpoint; sequentially extracting line segments from the line segment group, and performing the following operations on each extracted line segment: obtaining the power breakpoint inductance and power breakpoint capacitance based on the pre-constructed power point and the rear-end breakpoint, and calculating the rear-end breakpoint impedance of the rear-end breakpoint in the line segment based on the power breakpoint inductance and power breakpoint capacitance, wherein the calculation formula is as follows: ,in, Indicates the impedance at the end of the circuit. This represents the preset initial impedance. This indicates the preset imaginary unit. Represents pi (π). This indicates the preset power frequency. Indicates the inductance at the power supply break point. This indicates the capacitor at the power supply breakpoint; based on the impedance at the breakpoint and the initial impedance, the impedance difference is obtained, and it is determined whether the impedance difference is within the preset standard impedance range.

[0040] If the impedance difference is not within the preset standard impedance range, the inductance and capacitance are extracted from the impedance difference, and the location of the fault point is calculated based on the inductance and capacitance.

[0041] If the impedance difference is within the preset standard impedance range, then return to the step of sequentially extracting line segments from the line segment group until the line segment group is an empty set.

[0042] Optionally, the step of triggering a pre-built automatic alarm mechanism based on the location of the fault point and generating an alarm file includes:

[0043] Obtain a blank file, determine the fault level based on the fault location, obtain the first-level threshold and the second-level threshold, compare the fault level with the first-level threshold, and compare the fault level with the second-level threshold.

[0044] If the fault level is greater than level one, the automatic alarm mechanism generates an orange alarm, and imports the orange alarm and the fault location into a blank file to obtain the first alarm file.

[0045] If the fault level is less than or equal to level one and the fault level is greater than the level two threshold, the automatic alarm mechanism generates a red alarm, imports the red alarm and the fault location into a blank file, and obtains the second alarm file.

[0046] If the fault level is less than or equal to the second-level threshold, the automatic alarm mechanism generates a yellow alarm. The yellow alarm and the fault location are then imported into a blank file to obtain the third alarm file.

[0047] Alarm files are obtained based on the first alarm file, the second alarm file, and the third alarm file. 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 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.

[0048] To achieve the above objectives, the present invention also provides an automatic alarm system based on online fault detection of power distribution lines, comprising:

[0049] The line environment detection module is used to identify the target power distribution network, obtain the current environment based on the target power distribution network, wherein the target power distribution network includes multiple power distribution lines, receive line fault detection instructions, and detect the current environment using pre-built wind speed sensors according to the line fault detection instructions 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 in the current wind speed data that is greater than a preset standard wind speed threshold, then the current wind speed value is regarded 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 a preset abnormal value number threshold, then a repair line set is obtained based on the multiple power distribution lines.

[0050] The line fault detection module is used to extract power distribution lines sequentially from multiple power distribution lines if there is no current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, and to perform the following operations on the extracted power distribution lines: obtain the statistical characteristics of the power distribution line, obtain the physical construction model, input the statistical characteristics into the physical construction model to 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 power distribution line corresponding to the model prediction value is identified as a faulty power distribution line, and the fault point location operation is performed on the faulty power distribution line to obtain the fault point location;

[0051] The line fault repair module is used to trigger a pre-built automatic alarm mechanism based on the location of the fault point and generate an alarm file. Based on the alarm file, the faulty 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.

[0052] The fault alarm completion module is used to summarize normal power lines to obtain a set of normal power lines, and to complete automatic alarm based on the set of normal power lines and the set of repaired power lines, based on the online fault detection of power distribution lines.

[0053] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0054] Memory, storing at least one instruction;

[0055] The processor executes the instructions stored in the memory to implement the automatic alarm method based on online fault detection of power distribution lines described above.

[0056] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned automatic alarm method based on online fault detection of power distribution lines.

[0057] To address the problems described in the background section, this invention identifies the target power distribution network and obtains the current environment based on it. The target power distribution network includes multiple power distribution lines. This invention clearly defines the target power distribution network and its current environment, helping to focus fault detection on specific areas, avoiding ineffective detection of irrelevant areas, and improving the targeting and efficiency of detection. It receives line fault detection commands and, based on these commands, uses a pre-built wind speed sensor to detect the current environment and obtain current wind speed data. This current wind speed data includes multiple current wind speed values. This invention's receipt of line fault detection commands allows the system to promptly initiate fault detection based on actual needs, exhibiting strong initiative and flexibility. The use of wind speed sensors for detection... By monitoring wind speed in real time, the impact of strong winds on power lines can be predicted in advance, allowing for the implementation of corresponding preventative measures. If a wind speed value exceeding a preset standard threshold exists in the current wind speed data, this value is considered an abnormal wind speed. These abnormal wind speed values ​​are then aggregated to obtain an abnormal wind speed value set. The number of abnormal values ​​in this set is then determined. If the number of abnormal values ​​exceeds a preset threshold, a repair line set is obtained based on multiple power distribution lines. This invention addresses the issue that when a wind speed value exceeding the preset standard threshold exists in the current wind speed data, it indicates that strong winds in the current environment may cause significant damage to power distribution lines. Obtaining a repair line set in this situation allows for the preparation of necessary repair materials in advance, enabling rapid repair after the strong winds subside. The system rapidly repairs damaged power lines to reduce power outage time and improve power supply reliability. If no current wind speed value exceeding a preset standard wind speed threshold exists in the current wind speed data, power distribution lines are sequentially extracted from multiple distribution lines. The following operations are performed on each extracted line: statistical characteristics of the distribution line are obtained, a physical model is constructed, the statistical characteristics are input into the physical model to obtain model predictions, and the model predictions are compared with preset normal predictions. This invention accurately identifies faulty power lines by comparing model predictions and normal predictions, avoiding misjudgments of normal lines and improving the accuracy of fault detection. If the model prediction is greater than the preset normal prediction, the power distribution line corresponding to the model prediction is confirmed as the faulty line. This invention performs fault location operations on faulty power lines to obtain the fault location. Accurate fault location allows maintenance personnel to quickly reach the fault site, shortening repair time and reducing the scope and impact of power outages. Based on the fault location, a pre-built automatic alarm mechanism is triggered, generating an alarm file. Fault repair is then performed on the faulty power line according to the alarm file until the model's predicted value is less than or equal to the preset normal predicted value, thus identifying a normal power line. This invention's automatic alarm mechanism, triggered by the fault location, can promptly notify relevant maintenance personnel of fault information. Automatic alarms can be sent via SMS, email, audible and visual alarms, etc., ensuring that maintenance personnel are informed of the fault situation immediately and can take timely measures to handle it, thus compiling a list of normal power lines.This invention obtains a set of normal power lines and, based on this set and the set of repaired power lines, completes automatic alarms based on online fault detection of distribution lines. By summarizing the normal power lines to obtain a set of normal power lines, this invention provides a comprehensive understanding of the normally operating lines in the target distribution network. This facilitates the assessment and management of the entire distribution network's operational status and provides a reference for subsequent power grid planning and maintenance. Therefore, this invention can improve the reliability and operational efficiency of the power system. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating an automatic alarm method based on online fault detection of power distribution lines according to an embodiment of the present invention.

[0059] Figure 2 This is a functional block diagram of an automatic alarm system based on online fault detection of power distribution lines provided in an embodiment of the present invention;

[0060] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the automatic alarm method based on online fault detection of power distribution lines, according to an embodiment of the present invention.

[0061] Explanation of reference numerals in the attached figures:

[0062] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0063] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0064] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0065] This application provides an automatic alarm method based on online fault detection of power distribution lines. The executing entity of the automatic alarm method based on online fault detection of power distribution lines includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the automatic alarm method based on online fault detection of power 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.

[0066] Reference Figure 1 The diagram shown is a flowchart illustrating an automatic alarm method based on online fault detection of power distribution lines according to an embodiment of the present invention. In this embodiment, the automatic alarm method based on online fault detection of power distribution lines includes:

[0067] S1. Identify the target distribution network and obtain the current environment based on the target distribution network. The target distribution network includes multiple distribution lines.

[0068] It should be explained that the target distribution network refers to a distribution network that requires online fault detection. The current environment refers to the environment in which the target distribution network exists at the present moment. Distribution lines are an important component of the target distribution network, used for transmitting and distributing electrical energy.

[0069] S2. Receive line fault detection command, and according to the line fault detection command, use a pre-built wind speed sensor to detect the current environment and obtain the current wind speed data, which includes multiple current wind speed values.

[0070] It should be explained that the line fault detection command is initiated by the operator and is used to trigger and guide the fault detection operation of the power distribution line. A wind speed sensor is a sensor used to measure the speed of airflow. Examples include cup anemometers and ultrasonic anemometers. Wind speed data refers to the data about airflow speed acquired and recorded by the wind speed sensor during the detection of the current environment.

[0071] S3. If there is a current wind speed value in the current wind speed data that is greater than the preset standard wind speed threshold, then 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, then a repair line set is obtained based on multiple power distribution lines.

[0072] It should be explained 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 the wind speed value when a certain wind speed value in the current wind speed data exceeds the pre-set standard wind speed threshold. The abnormal wind speed value set is the collection obtained by summing up all abnormal wind speed values. The outlier count threshold is a pre-set value regarding the number of abnormal wind speed values.

[0073] Specifically, the acquisition of the repair line set based on multiple power distribution lines includes:

[0074] Determine if there is a broken power distribution line among multiple power distribution lines;

[0075] If there are broken distribution lines among multiple distribution lines, then the broken distribution lines are considered as broken lines, and the broken lines are summarized to obtain a broken line set.

[0076] The number of breaks in the broken line set is obtained. If the number of breaks is greater than the preset break number threshold, the optimal fault repair strategy is formulated. The broken line set is then repaired urgently according to the optimal fault repair strategy to obtain the repaired line set.

[0077] If the number of breaks is less than or equal to the preset break number threshold, a fault repair strategy is formulated, and the broken line set is repaired according to the fault repair strategy to obtain the repaired line set.

[0078] It should be explained that a broken line refers to a power distribution line that has broken due to various reasons (such as strong winds) among multiple power distribution lines. A broken line set is a collection of all broken lines. The broken line number threshold is a pre-set numerical value regarding the number of broken lines. The broken line number threshold is used to determine the severity of the current power distribution line breakage and thus decide on the appropriate repair strategy. Emergency repair refers to prioritizing repair plans that can restore power to important user locations as quickly as possible, minimizing power outage time and impact. For example, important users include hospitals and transportation hubs. Repairing the broken line set according to the fault repair strategy means obtaining the location of the broken line set and repairing it based on the distance to the location.

[0079] In detail, the formulation of the optimal fault repair strategy includes:

[0080] Determine the initial emergency repair sequence and the initial number of disturbances, obtain the objective function value based on the initial emergency repair sequence, randomly disturb the initial emergency repair sequence, and increment the initial number of disturbances to obtain the updated emergency repair sequence and the updated number of disturbances.

[0081] Calculate the updated objective function value for updating the emergency repair order, and obtain the function difference value based on the objective function value and the updated objective function value. The function difference value is the absolute difference between the updated objective function value and the objective function value.

[0082] The decision to accept the updated objective function value is based on the pre-constructed Boltzmann probability formula and the function difference value.

[0083] If the updated objective function value is accepted, it is determined whether the number of updates and disturbances is less than the preset maximum number of disturbances. If the number of updates and disturbances is less than the preset maximum number of disturbances, the updated emergency repair order corresponding to the updated objective function value is used as the initial emergency repair order, and the step of randomly disturbing the initial emergency repair order is returned.

[0084] If the number of update disturbances is greater than or equal to the preset maximum number of disturbances, then the update repair sequence corresponding to the number of update disturbances less than the preset maximum number of disturbances will be used as the optimal fault repair strategy.

[0085] If the updated objective function value is not accepted, the updated emergency repair order corresponding to the updated objective function value is used as the initial emergency repair order, and the process returns to the step of randomly perturbing the initial emergency repair order until the updated objective function value is accepted.

[0086] It should be explained that the initial repair sequence refers to the pre-set order in which the broken wire set is repaired when the optimal fault repair strategy is initially formulated. The initial perturbation count refers to the initial count of random adjustments to the initial repair sequence. For example, the initial perturbation count is 0. Random perturbation refers to randomly adjusting the current repair sequence. Updated repair sequence refers to the new repair sequence obtained after one random perturbation operation, used to determine whether a better objective function value can be obtained. Updated perturbation count refers to the new perturbation count obtained by incrementing the perturbation count after each random perturbation operation. The Boltzmann probability formula is a probabilistic formula used to determine whether to accept the updated objective function value, as shown below:

[0087] ,in, Indicate whether or not to accept, and when This indicates that the objective function value is being updated. This indicates that updating the objective function value is not accepted. This represents the natural exponential function. Indicates the difference value of the function. This indicates the preset control parameters.

[0088] Understandably, the maximum number of disturbances refers to a pre-set upper limit for the maximum number of random disturbances. The "increment by one" operation refers to the operation of incrementing the current disturbance count by 1 after each random disturbance to the current repair sequence. The updated objective function value refers to the objective function value calculated based on the updated repair sequence. The method for calculating the updated objective function value of the updated repair sequence is the same as the method for obtaining the objective function value based on the initial repair sequence, and will not be repeated here. The optimal fault repair strategy refers to the updated repair sequence corresponding to the updated disturbance count that is less than the maximum disturbance count, determined after multiple random disturbances and comparisons with the objective function value, when the number of updated disturbances reaches the pre-set maximum number of disturbances.

[0089] Specifically, obtaining the objective function value based on the initial repair sequence includes:

[0090] The initial sequence line set is obtained based on the initial emergency repair sequence. The repair time and load power of each initial sequence line in the initial sequence line set are calculated to obtain the repair time set and load power set. The load power sets are accumulated to obtain the comprehensive load power. The initial sequence line set includes multiple initial sequence lines, and the comprehensive load power includes multiple load powers. The initial sequence lines correspond one-to-one with the repair time and load power.

[0091] The objective function value of the initial sequence line set is calculated based on the pre-constructed objective function, the repair time set, and the comprehensive load power. The objective function is shown below:

[0092] ,in, Represents the objective function value. Representing all symbols, This represents the initial sequential set of routes. This indicates the repair time for the initial sequence of lines. Indicates the index of the preset unbroken line. The index representing the order of the initial sequence of the lines. and Both represent pre-defined binary variables. and Both represent the load power of the initial sequence lines. Indicates the first Repair time for the initial sequence of lines Indicates the total load power. Indicates the index of the initial sequential line set. This indicates taking the minimum value. This represents the total number of broken lines in the initial sequence line set.

[0093] It needs to be explained that the initial sequence line set refers to the set of lines that need to be repaired according to the initial emergency repair sequence. Load power refers to the electrical load carried by the line. A binary variable is a variable that includes two states, namely, an unbroken state or a broken state. The index of the sequence in the initial sequence line set refers to the order in which the lines are repaired in the initial emergency repair sequence. For example, when... When the initial sequence number is 1, it represents the route that is ranked first in the initial sequence route set. The index of the initial sequence route set is used to number the routes in the initial sequence route set. For example, if there are 5 routes in the route set... The values ​​can be taken from 1 to 5, each corresponding to one of the 5 different lines.

[0094] 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 the power distribution lines from multiple power distribution lines in sequence, and perform the following operation on the extracted power distribution lines: obtain the statistical characteristics of the power distribution lines.

[0095] Specifically, the acquisition of statistical characteristics of the power distribution lines includes:

[0096] Electrical parameters of power distribution lines are collected using pre-built smart sensors and preset sampling frequencies. The smart sensors include current sensors and voltage sensors. The electrical parameters include current data and voltage data. The current data includes multiple current values, and the voltage data includes multiple voltage values.

[0097] The electrical parameters are converted from analog to digital to obtain digital electrical parameters. The digital electrical parameters are then filtered to obtain filtered electrical parameters, which include filtered voltage data and filtered current data.

[0098] Calculate the statistical characteristics of the filter's electrical parameters.

[0099] It should be explained that the sampling frequency refers to the number of samples collected per unit time when discretely sampling a continuous analog signal. For example, a sampling frequency of 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 digital electrical parameters refers to filtering digital electrical parameters using a filtering algorithm. For example, the filtering algorithm is median filtering, mean filtering, etc. The filtered electrical parameters are the parameters obtained after filtering the digital electrical parameters.

[0100] In detail, the statistical characteristics of the calculated filter electrical parameters include:

[0101] The standard deviation and mean of the filter voltage are calculated based on the filter voltage data. The skewness and kurtosis of the filter voltage are then calculated based on these values. The formulas for calculating the skewness and kurtosis are shown below:

[0102] , ,in, Indicates the filter voltage skewness. This indicates the total number of filtered voltage data. Indicates the first Each filter voltage value, This represents the average value of the filtered voltage. Indicates the standard deviation of the filter voltage. Indicates the kurtosis of the filtered voltage. The index represents the filtered voltage data; the filtered current skewness and kurtosis are obtained based on the filtered current data, and the filtered voltage skewness, filtered voltage kurtosis, filtered current skewness, and filtered current kurtosis are used as statistical features.

[0103] It should be explained that the mean of the filter voltage refers to the average value of the filter voltage data. The standard deviation of the filter voltage measures the dispersion of the filter voltage data relative to the mean of the filter voltage. The step of calculating the standard deviation of the filter voltage is existing technology and will not be described in detail here. The skewness of the filter voltage describes the degree of asymmetry in the distribution of the filter voltage data. The larger the skewness of the filter voltage, the more concentrated the filter voltage data is to the right of the mean of the filter voltage. The kurtosis of the filter voltage refers to the flatness of the distribution of the filter voltage data. The larger the kurtosis of the filter voltage, the more serious the deviation of the distribution of the filter voltage data from the normal distribution. The method for obtaining the skewness and kurtosis of the filter current based on the filter current data is the same as the method for calculating the skewness and kurtosis of the filter voltage, wherein the calculation formulas for the skewness and kurtosis of the filter current are as follows:

[0104] , ,in, Indicates the filter current skewness. This indicates the total number of filtered current data. Indicates the first Each filter current value, This represents the average value of the filtered current. Indicates the standard deviation of the filter current. Indicates the kurtosis of the filter current. Indicates the index of the filtered current data.

[0105] It should be explained that the mean of the filter current refers to the average value of the filter current data. The standard deviation of the filter current measures the dispersion of the filter current data relative to the mean of the filter current. The steps for calculating the standard deviation of the filter current are existing technology and will not be described in detail here. The skewness of the filter current describes the degree of asymmetry in the distribution of the filter voltage data. The larger the skewness of the filter current, the more concentrated the filter current data is to the right of the mean of the filter current. The kurtosis of the filter current refers to the flatness of the distribution of the filter current data. The larger the kurtosis of the filter current, the more severely the distribution of the filter current data deviates from a normal distribution.

[0106] S5. Obtain the physical construction model, input the statistical features into the physical construction model, obtain the model prediction value, and compare the model prediction value with the preset normal prediction value.

[0107] It should be explained that the step of inputting statistical features into the physical model to obtain the model prediction value is as follows: inputting the filter voltage skewness and filter voltage kurtosis into the physical model to obtain the model voltage prediction value, inputting the filter current skewness and filter current kurtosis into the physical 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.

[0108] In detail, the physical construction model is as follows:

[0109] ,in, Represents the physical construction model, Indicates the detection time is Current data on power distribution lines This indicates the inductance of the pre-defined power distribution line. This indicates the resistance of the preset power distribution line. This indicates the capacitance of the pre-set power distribution line. Indicates the rate of change of current. This indicates the weight of the preset filter voltage skewness. This indicates the preset weight of the filter voltage kurtosis. This indicates the preset detection time.

[0110] It should be explained that the weight of the filtered voltage skewness refers to the weight used to measure the degree of asymmetry in the distribution of the filtered voltage data. The larger the weight of the filtered voltage skewness, the greater its impact on the physical model. Similarly, the larger the weight of the filtered voltage kurtosis, the greater its impact on the physical model. Detection time refers to the pre-set time used to detect the current or voltage on the distribution line. The physical model for the predicted current value is shown below:

[0111] ,in, The physical model representing the predicted current values ​​of the model is constructed. Indicates the detection time is Voltage data on power distribution lines Indicates the detection time is Current data on power distribution lines This indicates the weight of the preset filter current skewness. This indicates the weight of the preset filter current kurtosis. In this embodiment of the invention, when calculating the model voltage prediction value and the model current prediction value, only the numerical values ​​are substituted into the physical model without units, because it is necessary to compare the model prediction value with the normal prediction value.

[0112] S6. If the model prediction value is greater than the preset normal prediction value, the power distribution line corresponding to the model prediction value is identified as a faulty power line, and a fault point location operation is performed on the faulty power line to obtain the fault point location.

[0113] Specifically, the step of performing a fault location operation on the faulty power line to obtain the fault location includes:

[0114] The faulty power line is divided into line segment groups, which include multiple line segments and include: front-end segmentation points and rear-end segmentation points.

[0115] Extract line segments sequentially from the line segment group, and perform the following operations on each extracted line segment:

[0116] Based on the pre-constructed power supply point and the subsequent breakpoint, obtain the power supply breakpoint inductance and capacitance. Then, calculate the subsequent breakpoint impedance in the line segment based on the power supply breakpoint inductance and capacitance. The calculation formula is shown below:

[0117] ,in, Indicates the impedance at the end of the circuit. This represents the preset initial impedance. This indicates the preset imaginary unit. Represents pi (π). This indicates the preset power frequency. Indicates the inductance at the power supply break point. Indicates the capacitor at the power supply break point;

[0118] The impedance difference is obtained based on the back-end breakpoint impedance and the initial impedance. It is then determined whether the impedance difference is within the preset standard impedance range.

[0119] If the impedance difference is not within the preset standard impedance range, the inductance and capacitance are extracted from the impedance difference, and the location of the fault point is calculated based on the inductance and capacitance.

[0120] If the impedance difference is within the preset standard impedance range, then return to the step of sequentially extracting line segments from the line segment group until the line segment group is an empty set.

[0121] It should be explained that the division of the faulty power line refers to dividing the faulty power line using a preset division length. The division length is a pre-defined length. A line segment group refers to a set composed of all line segments. The front end division point and the back end division point refer to the starting endpoint of the line segment as the front end division point and the ending endpoint as the back end division point, respectively. For example, starting from the power source point and dividing the line sequentially, the starting point of the first line segment is the front end division point, and the ending point is the back end division point. The starting point of the second line segment is the back end division point of the previous line segment, and its ending point is a new back end division point.

[0122] Importantly, the power supply breakpoint inductance refers to the inductance at the point of breakage from the power supply point to the downstream end. The power supply breakpoint capacitance refers to the capacitance at the point of breakage from the power supply point to the downstream end. The steps for obtaining the power supply breakpoint inductance and capacitance based on the pre-constructed power supply point and downstream breakpoint are as follows: obtain the length of the line segment, and calculate the inductance and capacitance per unit length based on the length of the line segment, wherein the calculation formula is as follows:

[0123] , ,in, Inductance per unit length This indicates the pre-defined spacing of faulty power lines. This represents the equivalent radius of the pre-defined faulty circuit. Capacitance per unit length This represents the preset vacuum permittivity. Represents a logarithmic function.

[0124] The inductance at the power supply break point is obtained based on the length of the line segment and the inductance per unit length. The spacing between faulty lines refers to the distance between adjacent faulty lines. The equivalent radius and spacing of the faulty lines are obtained from the circuit's technical manual. The inductance at the power supply break point is the product of the length of the line segment and the inductance per unit length. The vacuum permittivity refers to the ability of a dielectric to polarize in an electric field.

[0125] It should be explained that the power supply frequency refers to the frequency of the power source in the power system. The power supply point refers to the connection point where power is output from the generating equipment to the faulty line. Obtaining the impedance difference based on the downstream breakpoint impedance and the initial impedance means subtracting the initial impedance from the downstream breakpoint impedance. The standard impedance range refers to a pre-defined range. The calculation formula in the step of calculating the fault location based on inductance and capacitance is as follows:

[0126] ,in, S7. Based on the location of the fault point, trigger the pre-built automatic alarm mechanism and generate an alarm file. Based on the alarm file, repair the faulty circuit until the model prediction value is less than or equal to the preset normal prediction value, and obtain the normal circuit.

[0127] Specifically, the step of triggering a pre-built automatic alarm mechanism based on the location of the fault and generating an alarm file includes:

[0128] Obtain a blank file, determine the fault level based on the fault location, obtain the first-level threshold and the second-level threshold, compare the fault level with the first-level threshold, and compare the fault level with the second-level threshold.

[0129] If the fault level is greater than level one, the automatic alarm mechanism generates an orange alarm, and imports the orange alarm and the fault location into a blank file to obtain the first alarm file.

[0130] If the fault level is less than or equal to level one and the fault level is greater than the level two threshold, the automatic alarm mechanism generates a red alarm, imports the red alarm and the fault location into a blank file, and obtains the second alarm file.

[0131] If the fault level is less than or equal to the second-level threshold, the automatic alarm mechanism generates a yellow alarm. The yellow alarm and the fault location are then imported into a blank file to obtain the third alarm file.

[0132] Alarm files are obtained based on the first alarm file, the second alarm file, and the third alarm file. 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 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.

[0133] It should be explained that obtaining the fault level based on the fault location refers to obtaining the fault level based on the degree of impact and harm caused by the fault location. For example, if the fault point is located near a critical hub substation or on a power supply line of an important load center, the fault level is Level 1. The Level 1 and Level 2 thresholds are pre-set boundary values ​​used to classify fault levels. An automatic alarm mechanism is a mechanism that can automatically trigger corresponding alarm actions based on fault information (such as fault location, fault level, etc.). A blank file is a pre-prepared file without any content. An alarm file is a file formed after the automatic alarm mechanism is triggered, by importing the generated alarm information (such as orange alarm, red alarm, yellow alarm) and fault location into the blank file. The method for repairing faulty lines based on alarm files is the same as the steps for repairing broken line sets based on fault repair strategies, and will not be repeated here. The first alarm file is the file that the automatic alarm mechanism generates when the fault level is greater than the Level 1 threshold, resulting in an orange alarm. The second alarm file is the file that the automatic alarm mechanism generates when the fault level is less than or equal to the Level 1 threshold but greater than the Level 2 threshold, resulting in a red alarm. The third alarm file refers to the file generated by the automatic alarm mechanism when the fault level is less than or equal to the second-level threshold. In this embodiment of the invention, if the fault level is greater than the first level, a first alarm file is generated; if the fault level is less than or equal to the first level and greater than the second-level threshold, a second alarm file is generated; and if the fault level is less than or equal to the second-level threshold, a third alarm file is generated. The first, second, and third alarm files are all generated under 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.

[0134] S8. Summarize the normal power lines to obtain the normal power line set, and complete the automatic alarm based on the normal power line set and the repaired power line set based on the online fault detection of the power distribution line.

[0135] It should be explained that a normal power line refers to a power line whose model prediction value is less than or equal to the preset normal prediction value after a series of fault repair operations. The normal power line set refers to the set of all normal power lines. The repaired power line set refers to the set of all repaired power lines.

[0136] To address the problems described in the background section, this invention identifies the target power distribution network and obtains the current environment based on it. The target power distribution network includes multiple power distribution lines. This invention clearly defines the target power distribution network and its current environment, helping to focus fault detection on specific areas, avoiding ineffective detection of irrelevant areas, and improving the targeting and efficiency of detection. It receives line fault detection commands and, based on these commands, uses a pre-built wind speed sensor to detect the current environment and obtain current wind speed data. This current wind speed data includes multiple current wind speed values. This invention's receipt of line fault detection commands allows the system to promptly initiate fault detection based on actual needs, exhibiting strong initiative and flexibility. The use of wind speed sensors for detection... By monitoring wind speed in real time, the impact of strong winds on power lines can be predicted in advance, allowing for the implementation of corresponding preventative measures. If a wind speed value exceeding a preset standard threshold exists in the current wind speed data, this value is considered an abnormal wind speed. These abnormal wind speed values ​​are then aggregated to obtain an abnormal wind speed value set. The number of abnormal values ​​in this set is then determined. If the number of abnormal values ​​exceeds a preset threshold, a repair line set is obtained based on multiple power distribution lines. This invention addresses the issue that when a wind speed value exceeding the preset standard threshold exists in the current wind speed data, it indicates that strong winds in the current environment may cause significant damage to power distribution lines. Obtaining a repair line set in this situation allows for the preparation of necessary repair materials in advance, enabling rapid repair after the strong winds subside. The system rapidly repairs damaged power lines to reduce power outage time and improve power supply reliability. If no current wind speed value exceeding a preset standard wind speed threshold exists in the current wind speed data, power distribution lines are sequentially extracted from multiple distribution lines. The following operations are performed on each extracted line: statistical characteristics of the distribution line are obtained, a physical model is constructed, the statistical characteristics are input into the physical model to obtain model predictions, and the model predictions are compared with preset normal predictions. This invention accurately identifies faulty power lines by comparing model predictions and normal predictions, avoiding misjudgments of normal lines and improving the accuracy of fault detection. If the model prediction is greater than the preset normal prediction, the power distribution line corresponding to the model prediction is confirmed as the faulty line. This invention performs fault location operations on faulty power lines to obtain the fault location. Accurate fault location allows maintenance personnel to quickly reach the fault site, shortening repair time and reducing the scope and impact of power outages. Based on the fault location, a pre-built automatic alarm mechanism is triggered, generating an alarm file. Fault repair is then performed on the faulty power line according to the alarm file until the model's predicted value is less than or equal to the preset normal predicted value, thus identifying a normal power line. This invention's automatic alarm mechanism, triggered by the fault location, can promptly notify relevant maintenance personnel of fault information. Automatic alarms can be sent via SMS, email, audible and visual alarms, etc., ensuring that maintenance personnel are informed of the fault situation immediately and can take timely measures to handle it, thus compiling a list of normal power lines.This invention obtains a set of normal power lines and, based on this set and the set of repaired power lines, completes automatic alarms based on online fault detection of distribution lines. By summarizing the normal power lines to obtain a set of normal power lines, this invention provides a comprehensive understanding of the normally operating lines in the target distribution network. This facilitates the assessment and management of the entire distribution network's operational status and provides a reference for subsequent power grid planning and maintenance. Therefore, this invention can improve the reliability and operational efficiency of the power system.

[0137] like Figure 2 The diagram shown is a functional block diagram of an automatic alarm system based on online fault detection of power distribution lines provided in an embodiment of the present invention.

[0138] The automatic alarm system 100 based on online fault detection of power distribution lines described in this invention can be installed in electronic devices. Depending on the functions implemented, the automatic alarm system 100 based on online fault detection of power distribution lines may 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 this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0139] The line environment detection module 101 is used to identify the target power distribution network, obtain the current environment based on the target power distribution network, wherein the target power distribution network includes: multiple power distribution lines, receive line fault detection instructions, and detect the current environment using a pre-built wind speed sensor according to the line fault detection instructions 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 in the current wind speed data that is greater than a preset standard wind speed threshold, then 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 a preset abnormal value number threshold, then a repair line set is obtained based on the multiple power distribution lines;

[0140] The line fault detection module 102 is used to extract power distribution lines sequentially from multiple power distribution lines if there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, and to perform the following operations on the extracted power distribution lines: obtain the statistical characteristics of the power distribution line, obtain the physical construction model, input the statistical characteristics into the physical construction model to 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 confirm the power distribution line corresponding to the model prediction value as a faulty power distribution line, and perform a fault point location operation on the faulty power distribution line to obtain the fault point location;

[0141] The line fault repair module 103 is used to trigger a pre-built automatic alarm mechanism based on the location of the fault point, generate an alarm file, and repair the faulty line according to the alarm file until the model prediction value is less than or equal to the preset normal prediction value, thus obtaining a normal line.

[0142] The fault alarm completion module 104 is used to summarize normal power lines to obtain a set of normal power lines, and to complete an automatic alarm based on the set of normal power lines and the set of repaired power lines based on online fault detection of power distribution lines.

[0143] In detail, the modules in the automatic alarm system 100 based on online fault detection of power distribution lines described in this embodiment of the invention employ the same methods as described above. Figure 1 The method used here is the same as the automatic alarm method based on online fault detection of power distribution lines, and can produce the same technical effect, so it will not be repeated here.

[0144] like Figure 3 The diagram shown is a structural schematic of an electronic device for implementing an automatic alarm method based on online fault detection of power distribution lines, according to an embodiment of the present invention.

[0145] 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 power distribution lines.

[0146] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard. Furthermore, the memory 11 includes both internal and external storage units of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of an automatic alarm method program based on online fault detection of power distribution lines, but also to temporarily store data that has been output or will be output.

[0147] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., an automatic alarm method program based on online fault detection of power distribution lines) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0148] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0149] Figure 3 Only electronic devices with components are shown; those skilled in the art will understand 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, or combine certain components, or have different component arrangements.

[0150] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0151] 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 typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0152] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or 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, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0153] The automatic alarm method program based on online fault detection of power distribution lines stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0154] The target power distribution network is identified, and the current environment is obtained based on the target power distribution network. The target power distribution network includes multiple power distribution lines.

[0155] Receive a line fault detection command, and according to the line fault detection command, use a pre-built wind speed sensor to detect the current environment and obtain the current wind speed data, which includes multiple current wind speed values;

[0156] If there is a current wind speed value in the current wind speed data that is greater than the preset standard wind speed threshold, then the current wind speed value is taken as an abnormal wind speed value, and the abnormal wind speed values ​​are summarized to obtain an abnormal wind speed value set.

[0157] Obtain the number of outliers in the abnormal wind speed value set. If the number of outliers exceeds the preset outlier threshold, obtain a set of repair lines based on multiple power distribution lines.

[0158] If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, then extract the power distribution lines sequentially from multiple power distribution lines, and perform the following operations on each extracted power distribution line:

[0159] Obtain the statistical characteristics of the power distribution line, 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.

[0160] If the model prediction value is greater than the preset normal prediction value, the power distribution line corresponding to the model prediction value is identified as a faulty power line, and a fault point location operation is performed on the faulty power line to obtain the fault point location.

[0161] The pre-built automatic alarm mechanism is triggered based on the location of the fault point, and an alarm file is generated. The faulty circuit is repaired based on the alarm file until the model prediction value is less than or equal to the preset normal prediction value, and a normal circuit is obtained.

[0162] The normal power lines are summarized to obtain a set of normal power lines. Based on the set of normal power lines and the set of repaired power lines, an automatic alarm is completed based on the online fault detection of power distribution lines.

[0163] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0164] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can 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 portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0165] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0166] The target power distribution network is identified, and the current environment is obtained based on the target power distribution network. The target power distribution network includes multiple power distribution lines.

[0167] Receive a line fault detection command, and according to the line fault detection command, use a pre-built wind speed sensor to detect the current environment and obtain the current wind speed data, which includes multiple current wind speed values;

[0168] If there is a current wind speed value in the current wind speed data that is greater than the preset standard wind speed threshold, then the current wind speed value is taken as an abnormal wind speed value, and the abnormal wind speed values ​​are summarized to obtain an abnormal wind speed value set.

[0169] Obtain the number of outliers in the abnormal wind speed value set. If the number of outliers exceeds the preset outlier threshold, obtain a set of repair lines based on multiple power distribution lines.

[0170] If there is no current wind speed value greater than the preset standard wind speed threshold in the current wind speed data, then extract the power distribution lines sequentially from multiple power distribution lines, and perform the following operations on each extracted power distribution line:

[0171] Obtain the statistical characteristics of the power distribution line, 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.

[0172] If the model prediction value is greater than the preset normal prediction value, the power distribution line corresponding to the model prediction value is identified as a faulty power line, and a fault point location operation is performed on the faulty power line to obtain the fault point location.

[0173] The pre-built automatic alarm mechanism is triggered based on the location of the fault point, and an alarm file is generated. The faulty circuit is repaired based on the alarm file until the model prediction value is less than or equal to the preset normal prediction value, and a normal circuit is obtained.

[0174] The normal power lines are summarized to obtain a set of normal power lines. Based on the set of normal power lines and the set of repaired power lines, an automatic alarm is completed based on the online fault detection of power distribution lines.

[0175] In the embodiments provided by this 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 merely illustrative, and actual implementations may have other classification methods.

[0176] The modules described as separate components may or may not be physically separate. 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 units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0177] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0178] 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.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for automatic alarm based on on-line fault detection of power distribution lines, characterized in that, The method comprises: Confirming a target power distribution network, and acquiring a current environment based on the target power distribution network, wherein the target power distribution network comprises a plurality of power distribution lines; Receiving a line fault detection instruction, and detecting the current environment by using a pre-constructed wind speed sensor according to the line fault detection instruction to obtain current wind speed data, wherein the current wind speed data comprises a plurality of current wind speed values; If there is a current wind speed value greater than a preset standard wind speed threshold value 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; Acquiring the number of abnormal values of the abnormal wind speed value set, and if the number of abnormal values is greater than a preset number of abnormal value threshold value, a repaired line set is acquired based on the plurality of power distribution lines; If there is no current wind speed value greater than the preset standard wind speed threshold value in the current wind speed data, a power distribution line is sequentially extracted from the plurality of power distribution lines, and the following operations are performed on the extracted power distribution line: Acquiring statistical characteristics of the power distribution line, acquiring a physical construction model, inputting the statistical characteristics into the physical construction model to obtain 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, the power distribution line corresponding to the model prediction value is confirmed as a fault power line, a fault point positioning operation is performed on the fault power line to obtain a fault point position; An automatically pre-constructed alarm mechanism is triggered according to the fault point position, and an alarm file is generated, the fault power line is repaired 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; The normal power lines are summarized to obtain a normal power line set, and the automatic alarm based on the online fault detection of the power distribution line is completed based on the normal power line set and the repaired line set.

2. The automatic alarm method based on power line online fault detection as claimed in claim 1, wherein, The method comprises: Judging whether there is a broken power distribution line in the plurality of power distribution lines; If there is a broken power distribution line in the plurality of power distribution lines, the broken power distribution line is taken as a broken line, and the broken lines are summarized to obtain a broken line set; Acquiring the number of broken lines of the broken line set, if the number of broken lines is greater than a preset number of broken line threshold value, an optimal fault repair strategy is formulated, the broken line set is repaired according to the optimal fault repair strategy, and a repaired line set is obtained; If the number of broken lines is less than or equal to the preset number of broken line threshold value, a fault repair strategy is formulated, the broken line set is repaired according to the fault repair strategy, and a repaired line set is obtained.

3. The automatic alarm method based on power line online fault detection as claimed in claim 2, wherein, The method comprises: Determining an initial repair order and an initial disturbance number, acquiring a target function value according to the initial repair order, performing random disturbance on the initial repair order, and performing plus one operation on the initial disturbance number to obtain an updated repair order and an updated disturbance number; Calculating an updated target function value of the updated repair order, and acquiring a function difference value according to the target function value and the updated target function value, wherein the function difference value is an absolute difference value between the updated target function value and the target function value; According to the pre-constructed Boltzmann probability formula and the function difference value, it is determined whether to accept the updated target function value. If the updated target function value is accepted, it is determined whether the number of updated perturbations is less than a preset maximum number of perturbations, and if the number of updated perturbations is less than the preset maximum number of perturbations, the updated repair sequence corresponding to the updated target function value is taken as an initial repair sequence, and the step of randomly perturbing the initial repair sequence is returned to. If the number of updated perturbations is greater than or equal to the preset maximum number of perturbations, the updated repair sequence corresponding to the number of updated perturbations less than the preset maximum number of perturbations is taken as an optimal fault repair strategy. If the updated target function value is not accepted, the updated repair sequence corresponding to the updated target function value is taken as an initial repair sequence, and the step of randomly perturbing the initial repair sequence is returned to until the updated target function value is accepted.

4. The automatic alarm method based on power line online fault detection as claimed in claim 3, wherein, The target function value is obtained according to the initial repair sequence, including: An initial sequence line set is obtained according to the initial repair sequence, repair time and load power of each initial sequence line in the initial sequence line set are calculated, a repair time set and a load power set are obtained, the load power set is accumulated to obtain a comprehensive load power, wherein the initial sequence line set includes a plurality of initial sequence lines, and the comprehensive load power includes a plurality of load powers, wherein the initial sequence line corresponds to the repair time and the load power one by one. The target function value of the initial sequence line set is calculated according to a pre-constructed target function, the repair time set and the comprehensive load power, wherein the target function is as follows: wherein, denotes the objective function value, denotes all symbols, denotes the initial sequence line set, denotes the repair time of the initial sequence line, denotes the index of the preset unbroken line, denotes the index of the sequence in the initial sequence line set, and both denote the preset binary variable, and both denote the load power of the initial sequence line, denotes the repair time of the initial sequence line, denotes the repair time of the initial sequence line, denotes the comprehensive load power, denotes the number index of the initial sequence line set, denotes the minimum value, denotes the total number of broken lines in the initial sequence line set.

5. The automatic alarm method based on power line online fault detection as claimed in claim 4, wherein, The statistical characteristics of the distribution line are obtained, including: The electrical parameters of the distribution line are collected by using a pre-constructed intelligent sensor and a preset sampling frequency to obtain electrical parameters, wherein the intelligent sensor includes a current sensor and a voltage sensor, and the electrical parameters include current data and voltage data, wherein the current data includes a plurality of current values, and the voltage data includes a plurality of voltage values. An analog-to-digital conversion operation is performed on the electrical parameters to obtain digital electrical parameters, and the digital electrical parameters are filtered to obtain filtered electrical parameters, wherein the filtered electrical parameters include filtered voltage data and filtered current data. The statistical characteristics of the filtered electrical parameters are calculated.

6. The automatic alarm method based on power line online fault detection as claimed in claim 5, wherein, The statistical characteristics of the filtered electrical parameters are calculated, including: The filtered voltage standard deviation and the filtered voltage mean value are calculated according to the filtered voltage data, and the filtered voltage skewness and the filtered voltage kurtosis are calculated according to the filtered voltage standard deviation and the filtered voltage mean value, wherein the calculation formulas of the filtered voltage skewness and the filtered voltage kurtosis are as follows: , , wherein, represents a filtered voltage skew, represents a total number of filtered voltage data, represents a filtered voltage value, of the filtered voltage value, represents a filtered voltage mean, represents a filtered voltage standard deviation, represents a filtered voltage kurtosis, represents an index of the filtered voltage data; The filtered current skewness and the filtered current kurtosis are obtained based on the filtered current data, and the filtered voltage skewness, the filtered voltage kurtosis, the filtered current skewness and the filtered current kurtosis are taken as the statistical characteristics.

7. The automatic alarm method based on power line online fault detection as claimed in claim 6, wherein, The physical construction model is as follows: wherein, represents a physical construction model, represents a detection time as current data on the power distribution line at represents a preset inductance of the power distribution line, represents a preset resistance of the power distribution line, represents a preset capacitance of the power distribution line, represents a rate of change of the current, represents a preset weight of filtering voltage skewness, represents a preset weight of filtering voltage kurtosis, represents a preset detection time.

8. The automatic alarm method based on power line online fault detection as claimed in claim 7, wherein, The fault point positioning operation is performed on the fault line to obtain the fault point position, including: The fault line is divided to obtain a line segment group, wherein the line segment group includes a plurality of line segments, and each line segment includes a front-end division breakpoint and a rear-end division breakpoint. The line segments are extracted from the line segment group in turn, and the following operations are performed on the extracted line segments: According to the pre-constructed power supply point and the back-end division breakpoint, a power supply breakpoint inductance and a power supply breakpoint capacitance are obtained, and a back-end breakpoint impedance of the back-end division breakpoint in the line section is calculated according to the power supply breakpoint inductance and the power supply breakpoint capacitance, wherein the calculation formula is as follows: wherein, represents the back-end break impedance, represents the preset initial impedance, represents the preset imaginary unit, represents the circular constant, represents the preset power supply frequency, represents the power supply break inductance, represents the power supply break capacitance; According to the back-end breakpoint impedance and the initial impedance, an impedance difference is obtained, and it is judged whether the impedance difference is located in a preset standard impedance interval; If the impedance difference is not located in the preset standard impedance interval, inductance and capacitance are extracted from the impedance difference, and a fault point position is calculated according to the inductance and the capacitance; If the impedance difference is located in the preset standard impedance interval, the step of sequentially extracting the line section from the line section group is returned until the line section group is an empty set.

9. The automatic alarm method based on power line online fault detection as claimed in claim 8, wherein, The pre-constructed automatic alarm mechanism is triggered according to the fault point position, and an alarm file is generated, including: A blank file is obtained, a fault level is obtained according to the fault point position, a first level threshold and a second level threshold are obtained, the fault level is compared with the first level threshold, and the fault level is compared with the second level threshold; If the fault level is greater than the first level, the automatic alarm mechanism generates an orange alarm, the orange alarm and the fault point position are imported into the blank file to obtain a first alarm file; If the fault level is less than or equal to the first level and greater than the second level threshold, the automatic alarm mechanism generates a red alarm, the red alarm and the fault point position are imported 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, the yellow alarm and the fault point position are imported into the blank file to obtain a third alarm file; Based on the first alarm file, the second alarm file and the third alarm file, an alarm file is obtained, 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 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 on-line fault detection of power distribution lines, characterized in that, The system comprises: A line environment detection module is used to confirm a target power distribution network, obtain a current environment based on the target power distribution network, wherein the target power distribution network comprises a plurality of power distribution lines, receive a line fault detection instruction, and obtain current wind speed data by using a pre-constructed wind speed sensor according to the line fault detection instruction, wherein the current wind speed data comprises a plurality of 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 taken as an abnormal wind speed value, the abnormal wind speed values are summarized to obtain an abnormal wind speed value set, the number of abnormal values of the abnormal wind speed value set is obtained, and if the number of abnormal values is greater than a preset number of abnormal value threshold, a repair line set is obtained based on the plurality of power distribution lines. The line fault detection module is configured to: if there is no current wind speed value greater than a preset standard wind speed threshold in the current wind speed data, sequentially extract power distribution lines from the plurality of power distribution lines, and perform the following operations on each of the extracted power distribution lines: obtaining a statistical feature of the power distribution line, obtaining a physical construction model, inputting the statistical feature into the physical construction model to obtain a model prediction value, 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 power distribution line corresponding to the model prediction value as a fault power line, performing a fault point positioning operation on the fault power line to obtain a fault point position; The line fault repair module is configured to trigger a pre-constructed automatic alarm mechanism according to the fault point position, and generate an alarm file, and perform fault repair on the fault power 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 power line; The fault alarm completion module is configured to: aggregate the normal power lines to obtain a normal power line set, and complete automatic alarm based on power distribution line online fault detection based on the normal power line set and the repaired line set.

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