Feeder terminal unit fault positioning method based on ranging principle

Abstract

The invention provides a feeder terminal unit fault positioning method based on a ranging principle. According to the method, node information of corresponding monitoring nodes is obtained through each feeder terminal unit, the node information is sent to a server to form a node information set, then the server determines a first feature monitoring node and a second feature monitoring node according to the node information set and a power distribution network topological structure, and the first feature monitoring node and the second feature monitoring node are monitored. A to-be-positioned fault line is determined according to the first feature monitoring node and the second feature monitoring node, and then a fault distance is determined according to first node information corresponding to the first feature monitoring node, second node information corresponding to the second feature monitoring node and line physical parameters of the to-be-positioned fault line. And the fault area is positioned from the fault line to be positioned according to the first characteristic monitoring node and the fault distance, so that the positioning of the fault area is realized, clear fault position information is provided for maintenance personnel, and the reliability and the stability of a power supply system are improved.

Description

Technical Field

[0001] The present application relates to data processing technology, and in particular to a method for locating a feeder terminal unit fault based on the distance measurement principle. Background Art

[0002] With the continuous development of power systems, the scale and complexity of distribution networks are increasing, and the requirements for fault location are becoming higher and higher. Traditional fault location methods often rely on manual inspections and simple fault indicators. These methods have problems such as slow positioning speed and low accuracy, and it is difficult to meet the needs of modern power systems for rapid response and precise positioning of faults. Especially in large-scale distribution networks, the fault point may be hidden in a complex line structure. Traditional positioning methods often have difficulty in quickly and accurately finding the fault location, resulting in long power outages and high repair costs.

[0003] In recent years, with the rapid development of communication technology, data processing technology and intelligent algorithms, by real-time collection of voltage and current signals of each monitoring node in the distribution network, and utilizing the characteristic changes of these signals combined with the topological structure of the distribution network, fault location at the line level can be achieved. Then, the fault location cannot be further located. Summary of the invention

[0004] The present application provides a feeder terminal unit fault location method based on the ranging principle to locate the fault area, which not only provides maintenance personnel with clear fault location information, but also greatly shortens the time for fault investigation and repair, and improves the reliability and stability of the power supply system.

[0005] In a first aspect, the present application provides a feeder terminal unit fault location method based on the ranging principle, which is applied to a distribution network fault location system; the distribution network fault location system comprises: a distribution network topology structure, a feeder terminal unit set and a server, the distribution network topology structure comprises a monitoring node set and a line for connecting each monitoring node in the monitoring node set, each feeder terminal unit in the feeder terminal unit set is correspondingly arranged on each monitoring node in the monitoring node set, and is communicatively connected with the server; the method comprises:

[0006] Acquire node information of a corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set, and send the node information to the server to form a node information set, wherein the node information includes a voltage monitoring signal and a current monitoring signal;

[0007] The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine a fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node;

[0008] The server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located;

[0009] The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

[0010] In the above scheme, by constructing a comprehensive system including a distribution network topology, a feeder terminal unit set and a server, the fault area of ​​the distribution network is located. The system architecture makes full use of communication technology and data processing capabilities to centrally process information scattered in various monitoring nodes of the distribution network, thereby improving the efficiency and accuracy of fault location. In addition, through each feeder terminal unit in the feeder terminal unit set, the voltage monitoring signal and current monitoring signal of the corresponding monitoring node are obtained in real time, and the information is sent to the server. This process realizes comprehensive monitoring of the operating status of the distribution network and provides a rich data basis for subsequent fault location. At the same time, the communication connection between the feeder terminal unit and the server ensures the real-time and accuracy of the information. Then, the server identifies the first characteristic monitoring node and the second characteristic monitoring node based on the received node information set and the distribution network topology. These two characteristic monitoring nodes show significant changes before and after the fault occurs, which is crucial for determining the fault line to be located. Through intelligent recognition technology, the fault-related area can be accurately and quickly locked, reducing unnecessary search range. Based on the information of the first characteristic monitoring node and the second characteristic monitoring node, the server can accurately determine the fault line to be located. This process not only relies on the identification of characteristic monitoring nodes, but also makes full use of the prior knowledge of the topological structure of the distribution network to ensure the accuracy and reliability of the fault line determination. Then, the server accurately calculates the fault distance through the calculation model based on the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located. This process fully considers the propagation characteristics of the voltage and current signals on the fault line and the physical parameters of the line to ensure the accuracy of the fault distance calculation. Finally, the server accurately locates the fault area from the fault line to be located based on the first characteristic monitoring node and the calculated fault distance. This process not only provides maintenance personnel with clear fault location information, but also greatly shortens the time for fault detection and repair, and improves the reliability and stability of the power supply system.

[0011] Optionally, the server determines the fault distance according to first node information corresponding to the first characteristic monitoring node, second node information corresponding to the second characteristic monitoring node, and line physical parameters of the fault line to be located, including:

[0012] The server uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding first voltage frequency domain signals and first current frequency domain signals, and converts the second voltage monitoring signal and the second current monitoring signal corresponding to the second characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding second voltage frequency domain signals and second current frequency domain signals;

[0013] The server determines the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal.

[0014] In the above technical solution, the voltage and current monitoring signals in the time domain are converted into frequency domain signals through Fourier transform. This process not only retains all the information of the signal, but also makes the signal easier to analyze and process in the frequency domain. Through Fourier transform, the server can efficiently convert the voltage and current monitoring signals of the first characteristic monitoring node and the second characteristic monitoring node from the time domain to the frequency domain, which provides convenience for subsequent calculations. In the frequency domain, the characteristics of the signal are more intuitive and easy to understand. For example, when a fault occurs, the voltage and current signals will produce obvious changes at a specific frequency. Through the voltage frequency domain signal and the current frequency domain signal obtained by Fourier transform, the server can more accurately capture these changes, thereby more accurately determining the fault distance. In addition, frequency domain analysis can also effectively filter out noise interference and improve the accuracy of signal processing. After obtaining the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal and the second current frequency domain signal, the server can use these frequency domain signals to calculate the fault distance. Since the frequency domain signal can more accurately reflect the changes in voltage and current when a fault occurs, the calculation result based on the frequency domain signal is more accurate. This process not only relies on the accuracy of Fourier transform, but also makes full use of the characteristics of frequency domain signals to achieve accurate calculation of fault distance. In addition, by using Fourier transform to convert time domain signals into frequency domain signals and combining frequency domain signals to calculate fault distance, the reliability of fault location can be significantly improved. Frequency domain analysis can more accurately capture the changes in signals when a fault occurs, reducing the possibility of misjudgment due to signal noise or interference. At the same time, accurate fault distance calculation provides strong support for subsequent fault repair work, ensuring the accuracy and effectiveness of fault location.

[0015] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0016] The server determines the characteristic impedance of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the characteristic impedance is used to determine the fault distance.

[0017] In the above scheme, characteristic impedance is an important parameter introduced to describe the electrical characteristics of the transmission line, which reflects the obstruction of the line to current and voltage at different frequencies. By calculating the characteristic impedance of the fault line to be located at each frequency component, the server can more accurately understand the electrical behavior of the line at different frequencies. This information is crucial for the subsequent fault distance calculation based on frequency domain signals, because it can help the server to more accurately interpret the fault characteristics in the frequency domain signal, thereby improving the accuracy of the fault distance calculation. Different line physical parameters (such as conductor material, cross-sectional area, insulation material, etc.) will cause the characteristic impedance of the line to change at different frequencies. By introducing the above characteristic impedance, the server can fully consider the impact of the physical characteristics of the line on the propagation of the fault signal. This helps the server to more accurately simulate the propagation process of the signal on the line during the fault distance calculation process, and reduce the calculation error caused by ignoring the physical characteristics of the line. In addition, in the distribution network, the physical parameters of the lines in different areas may be different. By calculating the characteristic impedance of each fault line to be located, the server can perform customized fault distance calculations based on the physical characteristics of different lines. This highly adaptable calculation method helps the server to achieve accurate fault location in various complex distribution network environments, and improves the universal applicability and reliability of fault location. Incorporating characteristic impedance into the fault distance calculation process helps optimize the performance of the entire fault location system. By more accurately calculating the fault distance, the system can locate the fault area more quickly, reducing the time for troubleshooting and repairing. At the same time, accurate fault location can also reduce the additional maintenance costs and time waste caused by misjudgment, and improve the reliability and economy of the power supply system.

[0018] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0019] The server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the propagation parameters are used to determine the fault distance.

[0020] In the above scheme, propagation parameters are introduced to describe the propagation speed and attenuation characteristics of the signal on the transmission line. These parameters are crucial for accurately calculating the fault distance. By considering the physical parameters of the line (such as wire length, diameter, material, and insulation thickness, etc.), the server can calculate the propagation speed and attenuation rate of the signal at different frequency components. This information enables the server to more accurately simulate the propagation process of the signal on the fault line, thereby improving the accuracy of the fault distance calculation. Among them, the propagation parameters of the signal are usually frequency-dependent, that is, the propagation speed and attenuation rate of signals of different frequencies on the same line may be different. By calculating the propagation parameters of the fault line to be located at each frequency component, the server can fully consider the impact of this frequency dependence on the propagation of the fault signal. This helps the server to more accurately simulate the actual signal propagation situation during the fault distance calculation process and reduce the calculation error caused by ignoring frequency dependence. In the fault location of the distribution network, real-time performance is an important indicator. By pre-calculating and storing the propagation parameters of the fault line to be located, the server can quickly calculate the fault distance after receiving the fault signal without calculating the propagation parameters in real time. This greatly shortens the time for fault location, enhances the real-time nature of fault location, helps to quickly restore power supply, and reduces power outage losses. Accurate calculation of propagation parameters helps the server identify the characteristics of fault signals more accurately, thereby more reliably determining the fault distance. This reduces the possibility of misjudgment due to signal interference, noise, or line parameter changes, and improves the reliability of fault location. At the same time, accurate fault distance calculation provides strong support for subsequent fault repair work, ensuring the accuracy and effectiveness of fault location. Moreover, incorporating the determination of propagation parameters into the fault distance calculation process helps optimize the performance of the entire fault location system. By calculating the fault distance more accurately, the system can lock the fault area more quickly and improve the efficiency of fault troubleshooting and repair. In addition, accurate fault location can also reduce the additional maintenance costs and time waste caused by misjudgment, and improve the overall reliability and economy of the power supply system.

[0021] Optionally, before the server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, the method further includes:

[0022] The server determines the resistance per unit length and the reactance per unit length of the fault line to be located at each frequency component according to the line physical parameters of the fault line to be located, and the resistance per unit length and the reactance per unit length are used to determine the propagation parameter.

[0023] In the above scheme, by introducing unit length resistance and unit length reactance, it directly affects the propagation speed and attenuation rate of the signal on the line. By accurately calculating the unit length resistance and unit length reactance of the fault line to be located at each frequency component, the server can more accurately simulate the propagation process of the signal on the fault line. The accuracy of this basic data provides a strong guarantee for the calculation of subsequent propagation parameters, thereby improving the accuracy of fault distance calculation. Unit length resistance and unit length reactance are usually frequency-dependent, that is, the propagation characteristics of signals of different frequencies on the same line may be different. By calculating the unit length resistance and unit length reactance of the fault line to be located at each frequency component, the server can fully consider the impact of this frequency characteristic on the propagation parameters. This helps the server to more accurately reflect the actual propagation of the signal in subsequent calculations and reduce the calculation error caused by ignoring the frequency characteristics. In the distribution network, the physical parameters of the lines in different areas may be different, resulting in different unit length resistance and unit length reactance. By calculating the unit length resistance and unit length reactance of each fault line to be located, the server can perform customized propagation parameter calculations according to the characteristics of different lines. This enhanced flexibility enables the server to adapt to various complex distribution network environments and improves the universal applicability and accuracy of fault location. The accurate calculation of unit length resistance and unit length reactance provides the basis for the precise determination of propagation parameters, thereby ensuring the accuracy of fault distance calculation.

[0024] Optionally, the server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including:

[0025] The server determines an abnormality index according to a voltage monitoring signal and a current monitoring signal in each node information in the node information set;

[0026] If the server determines that the abnormality index corresponding to the feature monitoring node is greater than or equal to the preset abnormality index threshold, the server determines that the feature monitoring node is an abnormal feature monitoring node; if the server determines that the abnormality index corresponding to the feature monitoring node is less than the preset abnormality index threshold, the server determines that the feature monitoring node is a normal feature monitoring node;

[0027] The server traverses each pending feature monitoring node in the distribution network topology structure to determine the first feature monitoring node and the second feature monitoring node, wherein the first feature monitoring node and the second feature monitoring node are two adjacent monitoring nodes in the distribution network topology structure, the first feature monitoring node is the normal feature monitoring node, and the second feature monitoring node is the abnormal feature monitoring node.

[0028] In the above scheme, by calculating the abnormal index of the voltage monitoring signal and the current monitoring signal in each node information, the server can quantitatively evaluate the abnormal degree of the electrical state of each node. The calculation of the abnormal index enables the server to capture potential fault signs more sensitively and respond even when the signal is weak at the beginning of the fault. This high sensitivity helps to detect and locate faults in a timely manner and reduce the risk of fault propagation. The server compares the abnormal index of the feature monitoring node with the preset abnormal index threshold to accurately distinguish between normal feature monitoring nodes and abnormal feature monitoring nodes. This distinction provides a clear goal for subsequent fault location, that is, focusing on abnormal feature monitoring nodes. By combining the distribution network topology, the server can further lock the adjacent normal feature monitoring nodes and abnormal feature monitoring nodes as the first feature monitoring nodes and the second feature monitoring nodes, thereby narrowing the fault search range and improving the accuracy of fault location. In addition, the process of traversing each pending feature monitoring node in the distribution network topology to determine the first feature monitoring node and the second feature monitoring node makes full use of the topological information of the distribution network. By giving priority to adjacent normal and abnormal feature monitoring node pairs, the server can reduce unnecessary searches and calculations and optimize the process of fault location. This efficiency improvement helps to shorten the time of fault location, speed up the fault repair speed, and reduce the power outage loss. In addition, the characteristic monitoring node determination method based on the node anomaly index and the distribution network topology structure enhances the robustness of fault location. Even in the face of complex distribution network environment and changing fault conditions, the server can accurately identify the fault location by comprehensively analyzing the node information and topology structure, reducing the risk of misjudgment or missed judgment caused by a single data source or simple algorithm, and improving the reliability and stability of fault location. In addition, the above-mentioned characteristic monitoring node determination method reflects the intelligent characteristics of the fault location system. By automatically analyzing node information and using the topology structure for reasoning and judgment, the system can autonomously learn and optimize the fault location strategy. This intelligent development helps to improve the overall performance of the fault location system, enabling it to better adapt to the development needs of the future distribution network and provide a strong guarantee for the stable operation of the power system.

[0029] Optionally, the server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including:

[0030] The server determines a pending characteristic monitoring node combination according to the distribution network topology structure, wherein a first characteristic monitoring node and a second characteristic monitoring node in the pending characteristic monitoring node combination are two adjacent monitoring nodes, and the direction of electric energy transmission in the distribution network topology structure is from the first characteristic monitoring node to the second characteristic monitoring node;

[0031] The server determines a correlation characteristic index according to the first node information and the second node information;

[0032] If the server determines that the correlation feature index is less than a preset correlation feature threshold, it determines that the first feature monitoring node is a normal feature monitoring node and the second feature monitoring node is an abnormal feature monitoring node.

[0033] In the above scheme, the server first determines the combination of pending feature monitoring nodes according to the topological structure of the distribution network. This step makes full use of the physical connection information of the distribution network. By selecting two adjacent monitoring nodes as the pending feature monitoring node combination, the server can quickly narrow the fault search range. Especially in large and complex distribution networks, this topology-based screening method can significantly improve the efficiency of fault location. The server further calculates the correlation feature index based on the first node information and the second node information. This index reflects the degree of association between the two adjacent nodes in terms of electrical state. By comparing the correlation feature index with the preset correlation feature threshold, the server can accurately distinguish between normal feature monitoring nodes and abnormal feature monitoring nodes. The application of the correlation feature index enhances the accuracy of fault identification and can effectively identify fault nodes even in a complex and changeable distribution network environment. When determining the pending feature monitoring node combination, the server pays special attention to the direction of power transmission in the topological structure of the distribution network, that is, the first feature monitoring node points to the second feature monitoring node. This directional information is crucial for understanding the propagation path of the fault in the distribution network. By combining the power transmission direction and the correlation feature index, the server can optimize the fault location strategy, more accurately determine the location of the fault point, and reduce the possibility of misjudgment and missed judgment. Then, through the characteristic monitoring node determination method based on the topological structure and correlation characteristic index, the server can lock the fault area more quickly and improve the real-time performance of fault location. At the same time, since the electrical state correlation and power transmission direction between nodes are comprehensively considered, the reliability of fault location has also been significantly improved. This is of great significance for reducing power outage time and reducing economic losses. In addition, by automatically analyzing the distribution network topology and node information, the server can intelligently determine the characteristic monitoring nodes and locate the fault accordingly. This intelligent development not only improves the efficiency and accuracy of fault location, but also provides possibilities for future fault prediction and preventive maintenance, which will help to further improve the stability and reliability of the power system.

[0034] In a second aspect, the present application provides a distribution network fault location system, comprising: a distribution network topology structure, a feeder terminal unit set and a server, wherein the distribution network topology structure comprises a monitoring node set and a line for connecting each monitoring node in the monitoring node set, each feeder terminal unit in the feeder terminal unit set is correspondingly arranged on each monitoring node in the monitoring node set, and is communicatively connected to the server;

[0035] Acquire node information of a corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set, and send the node information to the server to form a node information set, wherein the node information includes a voltage monitoring signal and a current monitoring signal;

[0036] The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine a fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node, wherein the first characteristic monitoring node and the second characteristic monitoring node are two adjacent monitoring nodes, and there is no abnormal monitoring parameter in the first node information corresponding to the first characteristic monitoring node, and there is an abnormal monitoring parameter in the first node information corresponding to the second characteristic monitoring node;

[0037] The server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located;

[0038] The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

[0039] Optionally, the server determines the fault distance according to first node information corresponding to the first characteristic monitoring node, second node information corresponding to the second characteristic monitoring node, and line physical parameters of the fault line to be located, including:

[0040] The server uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding first voltage frequency domain signals and first current frequency domain signals, and converts the second voltage monitoring signal and the second current monitoring signal corresponding to the second characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding second voltage frequency domain signals and second current frequency domain signals;

[0041] The server determines the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal.

[0042] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0043] The server determines the characteristic impedance of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the characteristic impedance is used to determine the fault distance.

[0044] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0045] The server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the propagation parameters are used to determine the fault distance.

[0046] Optionally, before the server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, the method further includes:

[0047] The server determines the resistance per unit length and the reactance per unit length of the fault line to be located at each frequency component according to the line physical parameters of the fault line to be located, and the resistance per unit length and the reactance per unit length are used to determine the propagation parameter.

[0048] Optionally, the server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including:

[0049] The server determines an abnormality index according to a voltage monitoring signal and a current monitoring signal in each node information in the node information set;

[0050] If the server determines that the abnormality index corresponding to the feature monitoring node is greater than or equal to the preset abnormality index threshold, the server determines that the feature monitoring node is an abnormal feature monitoring node; if the server determines that the abnormality index corresponding to the feature monitoring node is less than the preset abnormality index threshold, the server determines that the feature monitoring node is a normal feature monitoring node;

[0051] The server traverses each pending feature monitoring node in the distribution network topology structure to determine the first feature monitoring node and the second feature monitoring node, wherein the first feature monitoring node and the second feature monitoring node are two adjacent monitoring nodes in the distribution network topology structure, the first feature monitoring node is the normal feature monitoring node, and the second feature monitoring node is the abnormal feature monitoring node.

[0052] Optionally, the server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including:

[0053] The server determines a pending characteristic monitoring node combination according to the distribution network topology structure, wherein a first characteristic monitoring node and a second characteristic monitoring node in the pending characteristic monitoring node combination are two adjacent monitoring nodes, and the direction of electric energy transmission in the distribution network topology structure is from the first characteristic monitoring node to the second characteristic monitoring node;

[0054] The server determines a correlation characteristic index according to the first node information and the second node information;

[0055] If the server determines that the correlation feature index is less than a preset correlation feature threshold, it determines that the first feature monitoring node is a normal feature monitoring node and the second feature monitoring node is an abnormal feature monitoring node.

[0056] In a third aspect, the present application provides an electronic device, including:

[0057] processor; and,

[0058] A memory, configured to store executable instructions of the processor;

[0059] The processor is configured to perform any possible method described in the first aspect by executing the executable instructions.

[0060] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0061] The feeder terminal unit fault location method based on the ranging principle provided in the present application obtains the node information of the corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set, and sends the node information to the server to form a node information set. Then, the server determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the topology of the distribution network, so as to determine the fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node. Then, the server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located. Then, the fault area is located from the fault line to be located according to the first characteristic monitoring node and the fault distance, so as to realize the positioning of the fault area, which not only provides clear fault location information for maintenance personnel, but also greatly shortens the time for fault investigation and repair, and improves the reliability and stability of the power supply system. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings herein are incorporated in and constitute a part of this specification, illustrate aspects consistent with the present application, and together with the description, serve to explain the principles of the present application.

[0063] Figure 1 is a flow chart of a method for locating a feeder terminal unit fault based on the ranging principle according to an exemplary embodiment of the present application;

[0064] Figure 2 is a flow chart of a method for locating a feeder terminal unit fault based on the ranging principle according to another exemplary embodiment of the present application;

[0065] Figure 3 is a structural schematic diagram of a distribution network fault location system according to an exemplary embodiment of the present application;

[0066] Figure 4 It is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application.

[0067] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0068] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0069] In order to solve the above problems, the embodiments provided in this application are

[0070] It is worth noting that the embodiments provided in the present application are applied to a distribution network fault location system, which includes: a distribution network topology structure, a feeder terminal unit set and a server. The distribution network topology structure includes a monitoring node set and lines for connecting each monitoring node in the monitoring node set. Each feeder terminal unit in the feeder terminal unit set is correspondingly arranged on each monitoring node in the monitoring node set and is communicatively connected to the server.

[0071] Specifically, the system is mainly composed of three core parts: distribution network topology, feeder terminal unit set and server. These parts work together to achieve efficient fault location function.

[0072] The distribution network topology is the skeleton of the system, which defines the flow path of electricity in the distribution network. The structure mainly consists of a collection of monitoring nodes and the lines connecting these nodes. Monitoring nodes are key locations in the power network, where feeder terminal units are installed to monitor power parameters. Lines are the medium for power transmission, connecting various monitoring nodes to form a complete power network.

[0073] Monitoring nodes are usually selected at key intersections, branch points or load concentration points of the power network. Each monitoring node has a unique identifier to facilitate system management and data tracking.

[0074] The line is used to connect the monitoring nodes and form a channel for power transmission. The physical parameters of the line (such as length, wire type, resistivity, etc.) have an important impact on the accuracy of fault location, so these parameters need to be accurately entered when the system is initialized.

[0075] The feeder terminal unit set is the perception layer of the system, responsible for real-time collection of power parameters of the monitoring nodes. Each feeder terminal unit is set on a monitoring node in the monitoring node set and establishes a communication connection with the server. The feeder terminal unit is an intelligent device that integrates power parameter monitoring functions such as voltage and current. It can collect voltage monitoring signals and current monitoring signals of the monitoring node in real time, and perform preliminary processing on these signals (such as filtering, denoising, etc.) to improve data quality.

[0076] The feeder terminal unit establishes a connection with the server through wireless communication (such as 4G / 5G, LoRa, NB-IoT, etc.) or wired communication (such as optical fiber, Ethernet, etc.). This connection ensures the transmission of real-time data and the reception of instructions, and is the basis for the system to achieve remote monitoring and fault location.

[0077] The server is the center of the system, responsible for processing data from the feeder terminal unit, executing the fault location algorithm, and sending control instructions. The server is usually deployed in the data center or cloud platform of the power company and has powerful data processing and storage capabilities. The server receives node information from the feeder terminal unit, including voltage monitoring signals and current monitoring signals. The server further processes and analyzes this information to extract fault characteristics. The server has a built-in fault location algorithm based on the ranging principle, which can quickly and accurately locate the fault area based on the processed node information and the distribution network topology. Once the fault is located, the server will send control instructions to relevant personnel or systems to guide fault handling and maintenance work. At the same time, the server is also responsible for auxiliary functions such as recording fault information and generating reports.

[0078] Figure 1 FIG. 1 is a flow chart of a method for locating a feeder terminal unit fault based on the distance measurement principle according to an exemplary embodiment of the present application. Figure 1 As shown, the method provided in this embodiment includes:

[0079] S101. Acquire node information of a corresponding monitoring node through each feeder terminal unit in a feeder terminal unit set.

[0080] In this step, node information of the corresponding monitoring node is acquired through each feeder terminal unit in the feeder terminal unit set, and the node information is sent to the server to form a node information set, where the node information includes a voltage monitoring signal and a current monitoring signal.

[0081] Specifically, each feeder terminal unit collects the voltage and current data of the monitoring node where it is located periodically or in real time. The feeder terminal unit performs preliminary processing on the collected voltage monitoring signal and current monitoring signal, such as filtering and denoising, to improve the data quality. The processed node information is sent to the server through a communication protocol (such as TCP / IP, Modbus, etc.). The server receives the node information from each feeder terminal unit and integrates it to form a node information set.

[0082] S102. The server determines a first characteristic monitoring node and a second characteristic monitoring node according to a node information set and a distribution network topology structure.

[0083] In this step, the server determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine the fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node.

[0084] Specifically, the server determines all possible adjacent monitoring node combinations as pending feature monitoring node combinations based on the topological structure of the distribution network. For each pending feature monitoring node combination, the server obtains its corresponding first node information and second node information. The server calculates the correlation characteristic index between the two nodes in each combination, and the index is calculated based on the voltage and current data of the node information. The server compares the calculated correlation characteristic index with the preset correlation characteristic threshold. If the index is less than the threshold, it is determined that the first node in the combination is a normal feature monitoring node, and the second node is an abnormal feature monitoring node. Among all pending feature monitoring node combinations, the first combination that meets the conditions is selected, wherein the normal feature monitoring node is the first feature monitoring node, and the abnormal feature monitoring node is the second feature monitoring node.

[0085] Then, the server searches for a line connecting the first characteristic monitoring node and the second characteristic monitoring node in the distribution network topology, confirms that the line is a fault line to be located, and marks its starting point and end point.

[0086] S103. The server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located.

[0087] In this step, the server obtains the line physical parameters of the fault line to be located, such as line length, conductor resistivity, etc. For example, the server may use the voltage and current mutation signals in the first node information and the second node information to calculate the time difference between the signal being generated at the fault point and propagating to the two monitoring nodes. Based on the time difference and the propagation speed of the traveling wave in the line (which can be calculated from the line physical parameters), the server calculates the distance from the fault point to the first characteristic monitoring node.

[0088] S104: The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

[0089] In this step, the server compares the calculated fault distance with the total length of the fault line to be located. Based on the comparison result, the server determines the specific location of the fault area on the fault line and marks the area. The server sends the fault area information to relevant personnel or systems for subsequent fault handling and maintenance work.

[0090] In this embodiment, node information of the corresponding monitoring node is obtained through each feeder terminal unit in the feeder terminal unit set, and the node information is sent to the server to form a node information set. Then, the server determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine the fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node. Then, the server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located. Then, the fault area is located from the fault line to be located according to the first characteristic monitoring node and the fault distance, so as to locate the fault area. This not only provides clear fault location information for maintenance personnel, but also greatly shortens the time for fault detection and repair, thereby improving the reliability and stability of the power supply system.

[0091] Figure 2 FIG. 1 is a flow chart of a method for locating a feeder terminal unit fault based on the ranging principle according to another exemplary embodiment of the present application. Figure 2 As shown, the feeder terminal unit fault location method based on the ranging principle provided in this embodiment includes:

[0092] S201. Obtain node information of a corresponding monitoring node through each feeder terminal unit in a feeder terminal unit set.

[0093] In this step, node information of the corresponding monitoring node is acquired through each feeder terminal unit in the feeder terminal unit set, and the node information is sent to the server to form a node information set, where the node information includes a voltage monitoring signal and a current monitoring signal.

[0094] Specifically, each feeder terminal unit collects the voltage and current data of the monitoring node where it is located periodically or in real time. The feeder terminal unit performs preliminary processing on the collected voltage monitoring signal and current monitoring signal, such as filtering and denoising, to improve the data quality. The processed node information is sent to the server through a communication protocol (such as TCP / IP, Modbus, etc.). The server receives the node information from each feeder terminal unit and integrates it to form a node information set.

[0095] S202. The server determines a first characteristic monitoring node and a second characteristic monitoring node according to a node information set and a topological structure of a distribution network.

[0096] In this step, the server determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine the fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node.

[0097] In a possible implementation, the server uses Formula 1 and determines the abnormality index according to the voltage monitoring signal and the current monitoring signal in each node information in the node information set. Formula 1 is:

[0098]

[0099] Among them, K i is the abnormal index corresponding to the i-th feature monitoring node in the node information set, V i is the equivalent voltage value of the i-th characteristic monitoring node, I i is the equivalent current value of the i-th characteristic monitoring node, V avg is the average equivalent voltage of each characteristic monitoring node in the node information set, I avg is the average equivalent current of each characteristic monitoring node in the node information set;

[0100] If the server determines the anomaly index K corresponding to the i-th feature monitoring node i is greater than or equal to the preset abnormal index threshold, the i-th feature monitoring node is determined to be an abnormal feature monitoring node; if the abnormal index K corresponding to the i-th feature monitoring node is determined i If the abnormal index is less than the preset threshold, the i-th feature monitoring node is determined to be a normal feature monitoring node;

[0101] The server traverses each pending feature monitoring node in the distribution network topology structure to determine a first feature monitoring node and a second feature monitoring node, wherein the first feature monitoring node and the second feature monitoring node are two adjacent monitoring nodes in the distribution network topology structure, the first feature monitoring node is a normal feature monitoring node, and the second feature monitoring node is an abnormal feature monitoring node.

[0102] In the above scheme, the server uses Formula 1 to calculate the abnormality index of each feature monitoring node. The index is based on the deviation of the node voltage and current from the overall average voltage and average current, thereby quantifying the voltage and current fluctuations of the node and accurately identifying abnormal features. The calculation method of square root and square root ensures the sensitivity of the abnormality index to the voltage and current deviations, so that even small deviations can be effectively captured. By presetting the abnormality index threshold, the server can quickly distinguish between normal feature monitoring nodes and abnormal feature monitoring nodes. This mechanism reduces the possibility of misjudgment and improves the accuracy of fault location.

[0103] In addition, the server traverses each pending feature monitoring node in the distribution network topology, paying special attention to the comparison of voltage and current characteristics between adjacent nodes. In this way, the server can determine the approximate location of the fault, especially when one adjacent node is normal and the other is abnormal, the fault point is likely to be between the two. This strategy optimizes the path of fault location and reduces unnecessary search range.

[0104] Then, the characteristic monitoring nodes are clearly divided into normal and abnormal categories, providing clear instructions for subsequent fault line location and fault distance calculation. The clear distinction between normal characteristic monitoring nodes and abnormal characteristic monitoring nodes helps to narrow the fault search range and improve the accuracy and efficiency of fault location. The above scheme is applicable to various complex distribution network topologies, including radial, ring, mesh and other topological forms. By traversing all pending characteristic monitoring nodes, the server can flexibly respond to fault location requirements in different network environments, enhancing the adaptability of the system.

[0105] In addition, when calculating the abnormality index, by comprehensively considering multiple factors of voltage and current, it can effectively resist external interference (such as electromagnetic interference, measurement errors, etc.). This anti-interference ability ensures the accuracy and reliability of fault location, and maintains stable performance even in a complex and changeable power grid environment. By quickly determining the first characteristic monitoring node and the second characteristic monitoring node, the server can quickly lock the approximate range of the fault line. This facilitates the subsequent fault distance calculation and fault area location, and shortens the fault handling time. The operation and maintenance personnel can quickly arrive at the scene to troubleshoot and repair the fault based on the fault area information provided by the server. This method reduces the blind search time of the operation and maintenance personnel, improves the operation and maintenance efficiency, and reduces the power outage time and economic losses caused by faults.

[0106] In another possible implementation, the server determines a pending characteristic monitoring node combination according to a distribution network topology structure, wherein a first characteristic monitoring node and a second characteristic monitoring node in the pending characteristic monitoring node combination are two adjacent monitoring nodes, and in the distribution network topology structure, the direction of electric energy transmission is from the first characteristic monitoring node to the second characteristic monitoring node;

[0107] The server uses formula 2 and determines the correlation characteristic index REL1 according to the first node information and the second node information.<F1,F2> , where Formula 2 is:

[0108]

[0109] Where T is the preset monitoring period, V F1,t is the voltage of the first characteristic monitoring node at the tth monitoring time point, V F1,avgis the equivalent voltage average value of the first characteristic monitoring node within the preset monitoring period, V F2,t is the voltage of the second characteristic monitoring node at the tth monitoring time point, V F2,avg is the equivalent voltage average value of the second characteristic monitoring node within the preset monitoring period;

[0110] If the server determines the correlation characteristic index REL1<F1,F2> If it is less than a preset correlation feature threshold, the first feature monitoring node is determined to be a normal feature monitoring node, and the second feature monitoring node is determined to be an abnormal feature monitoring node.

[0111] In the above scheme, the server first determines the combination of pending characteristic monitoring nodes according to the topological structure of the distribution network, ensures that the first characteristic monitoring node and the second characteristic monitoring node are two adjacent monitoring nodes, and the direction of power transmission is from the first characteristic monitoring node to the second characteristic monitoring node, thereby ensuring the directness and correlation of the selected node combination in electrical connection, and providing a reasonable node pair for the subsequent calculation of the correlation characteristic index. In addition, the server uses Formula 2 to calculate the correlation characteristic index between the first characteristic monitoring node and the second characteristic monitoring node. The formula quantifies the synchronization and correlation of voltage changes between nodes by calculating the ratio of the covariance of voltage fluctuations of the two nodes within a preset monitoring period to the product of the standard deviation of their respective voltage fluctuations. It can capture the subtle differences in voltage changes between nodes and provide strong data support for judging the node status.

[0112] By setting a preset correlation characteristic threshold, the server can quickly determine whether the correlation between the first characteristic monitoring node and the second characteristic monitoring node meets the normal standard. If the correlation characteristic index is less than the preset threshold, it indicates that the voltage change synchronization between the two nodes is poor, and there is a high probability of a fault.

[0113] By calculating and judging the correlation characteristic index, the server can quickly determine that the first characteristic monitoring node is a normal characteristic monitoring node and the second characteristic monitoring node is an abnormal characteristic monitoring node. This method avoids the tedious process of checking each node one by one in the traditional method, and improves the accuracy and efficiency of fault location. After determining the abnormal characteristic monitoring node, the server can immediately start the subsequent fault distance calculation and fault area location process. This process optimization reduces the time for fault handling, allowing operation and maintenance personnel to arrive at the site faster to perform fault troubleshooting and repair work, reducing power outage time and economic losses caused by faults.

[0114] In addition, by comprehensively considering the voltage fluctuations within the preset monitoring period when calculating the correlation characteristic index, this method can effectively resist external interference (such as electromagnetic interference, measurement errors, etc.). This anti-interference ability ensures the accuracy and reliability of fault location, and maintains stable performance even in complex and changing power grid environments.

[0115] S203: The server uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals into frequency domain signals.

[0116] In this step, the server uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals to frequency domain signals to generate the corresponding first voltage frequency domain signal and the first current frequency domain signal, and converts the second voltage monitoring signal and the second current monitoring signal corresponding to the second characteristic monitoring node from time domain signals to frequency domain signals to generate the corresponding second voltage frequency domain signal and the second current frequency domain signal.

[0117] S204. The server determines the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal.

[0118] In this step, the server uses Formula 3 and determines the fault distance d according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal. Formula 3 is:

[0119]

[0120] Where N is the number of frequency components of the frequency domain signal, V F1,k is the voltage amplitude of the first voltage frequency domain signal at the kth frequency component, V F2,k is the voltage amplitude of the second voltage frequency domain signal at the kth frequency component, I F2,k is the voltage amplitude of the second current frequency domain signal at the kth frequency component, Z 0,k is the characteristic impedance of the fault line to be located at the kth frequency component, γ k is the propagation parameter of the fault line to be located at the kth frequency component, and l is the preset line length of the fault line to be located.

[0121] In the above scheme, the server converts the voltage and current monitoring signals of the first characteristic monitoring node and the second characteristic monitoring node from the time domain to the frequency domain through Fourier transform. This conversion can capture the characteristics of the signal at different frequency components, making the subsequent analysis more accurate. Fourier transform performs well in processing complex and non-stationary signals, and can effectively separate the characteristic components in the fault signal and improve the accuracy of fault location. By analyzing the converted frequency domain signal, the server can use formula 3 to comprehensively consider the voltage, current and line physical parameters under multiple frequency components to calculate the fault distance. This method avoids the errors that may be caused by the analysis of a single frequency component and improves the accuracy of fault distance calculation. Formula 3 calculates the ratio of the voltage difference between the two characteristic monitoring nodes to the current, the line characteristic impedance and the propagation parameter, and performs weighted summation to finally obtain the fault distance. This method fully considers the electrical characteristics of the line at different frequencies, making the calculation results more in line with the actual situation. In addition, the characteristic impedance and propagation parameters of the fault line to be located are introduced in formula 3. These two parameters are related to the material, structure, length and frequency of the line. By considering these physical parameters, the server can calculate the fault distance more accurately, especially for complex and changeable distribution network environments. In addition, Formula 3 also takes into account the preset line length of the fault line to be located, which helps to correct when there is a difference between the actual line length and the preset length, ensuring the accuracy of the fault distance calculation. Through the calculation of Fourier transform and Formula 3, the server can quickly derive the fault distance and provide timely and accurate fault information to operation and maintenance personnel. This helps to shorten the fault handling time and reduce power outage losses. In addition, this method does not rely on a single monitoring signal or line parameter, but improves the reliability of fault location by comprehensively analyzing the signal characteristics and line physical parameters under multiple frequency components. Even in a complex and changeable power grid environment, it can maintain stable performance.

[0122] Furthermore, before determining the fault distance d according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal and the second current frequency domain signal, the method further includes:

[0123] The server uses formula 4 and determines the characteristic impedance Z of the fault line to be located at the kth frequency component according to the line physical parameters of the fault line to be located. 0,k , Formula 4 is:

[0124]

[0125] Where L0 is the inductance per unit length of the fault line to be located, C0 is the capacitance per unit length of the fault line to be located, and K L is the preset inductance influence factor of the fault line to be located, K C is the preset capacitance influence factor of the fault line to be located, fk is the frequency value of the kth frequency component of the fault line to be located, f c is the cutoff frequency of the fault line to be located.

[0126] In the above scheme, the frequency component is introduced through Formula 4, which reflects the characteristic impedance changing with frequency. This frequency dependence is particularly important for high-frequency signals, because high-frequency signals are more easily affected by the electrical characteristics of the line during transmission. By considering the frequency dependence, the server can more accurately simulate the propagation of the signal on the fault line and improve the accuracy of fault location. The unit length inductance, unit length capacitance, preset inductance influence factor and preset capacitance influence factor of the fault line to be located in Formula 4 can be adjusted according to different line types (such as overhead lines, cables, etc.), so that the server can adapt to the fault location requirements under various line environments. By calculating the characteristic impedance under different frequency components, the server can support multi-frequency component analysis. This analysis method can more comprehensively capture the propagation characteristics of the signal on the fault line and improve the reliability and accuracy of fault location. At the same time, multi-frequency component analysis also helps to identify different types of fault signals and provide strong support for subsequent fault processing. By considering the frequency dependence of the physical parameters of the line and accurately calculating the characteristic impedance, the server can more accurately simulate the actual operating status of the line. This simulation capability enhances the robustness of the system, so that it can still maintain stable performance when facing a complex and changing power grid environment.

[0127] Furthermore, before determining the fault distance d according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal and the second current frequency domain signal, the method further includes:

[0128] The server uses formula 5 and determines the propagation parameter γ of the fault line to be located at the kth frequency component according to the line physical parameters of the fault line to be located. k , Formula 5 is:

[0129]

[0130] Among them, α(f k ) is the attenuation function of the fault line to be located at the kth frequency component, β(f k ) The phase function of the fault line to be located at the kth frequency component, R(f k ) is the resistance per unit length of the fault line to be located at the kth frequency component, X(f k ) is the unit length reactance of the fault line to be located at the kth frequency component, ε ′ (f k ) is the real part of the dielectric constant of the fault line to be located at the kth frequency component, ε″(f k) is the imaginary part of the dielectric constant of the fault line to be located at the kth frequency component, ω(f k ) is the angular frequency of the kth frequency component, ω(f k )=2πf k , c is the speed of light, ε ∞ is the preset high-frequency limiting dielectric constant of the fault line to be located, ε S is the preset static dielectric constant of the fault line to be located, and τ is the preset relaxation time.

[0131] In the above scheme, through Formula 5, the server can calculate the propagation parameters of the fault line to be located under different frequency components, which include attenuation parameters and phase parameters. These parameters directly reflect the propagation characteristics of the signal on the fault line, such as attenuation and phase offset. Accurate calculation of propagation parameters can ensure the accuracy of subsequent fault distance calculation and avoid positioning deviation caused by parameter errors. All parameters in Formula 5 vary with frequency, reflecting the characteristics of propagation parameters varying with frequency. This frequency dependence is particularly important for high-frequency signals, because high-frequency signals are more susceptible to the electrical characteristics of the line during transmission. By considering frequency dependence, the server can more accurately simulate the propagation of the signal on the fault line, thereby improving the accuracy of fault location. The parameters in Formula 5 can be adjusted according to the physical characteristics of different lines. This enables the server to adapt to fault lines of different materials, structures, and lengths, enhancing the adaptability and flexibility of the system. By calculating the propagation parameters under different frequency components, the server can support multi-frequency component analysis. This analysis method can more comprehensively capture the propagation characteristics of the signal on the fault line and improve the reliability and accuracy of fault location. At the same time, multi-frequency component analysis also helps to identify different types of fault signals, providing strong support for subsequent fault processing. In addition, the real and imaginary parts of the dielectric constant are introduced into Formula 5. These parameters reflect the electrical characteristics of the line medium. By considering the dielectric characteristics, the server can more accurately simulate the propagation of signals on the fault line, thereby improving the reliability of fault location.

[0132] Further, the propagation parameter γ of the fault line to be located at the kth frequency component is determined according to the line physical parameters of the fault line to be located. k Previously, it also included:

[0133] The server uses Formula 6 and determines the unit length resistance R (f k ) and unit length reactance X(f k ), Formula 6 is:

[0134]

[0135] Where R0 is the preset low-frequency resistance per unit length of the fault line to be located, K R The influence factor of the preset resistance of the fault line to be located, C(f k ) is the capacitance per unit length of the fault line to be located, L(f k ) is the inductance per unit length of the fault line to be located.

[0136] In the above scheme, the parameters in Formula 6 all take into account the influence of frequency. By introducing the preset resistance influence factor and frequency component, the server can calculate the accurate values ​​of resistance and reactance per unit length at different frequencies. This frequency-dependent consideration is particularly important for high-frequency signals, and can more realistically reflect the propagation characteristics of the signal on the fault line. The parameters in Formula 6 are all based on the physical characteristics of the fault line to be located. By accurately measuring and inputting these parameters, the server can more accurately calculate the resistance and reactance per unit length, providing a reliable basis for the calculation of subsequent propagation parameters and fault distance. In addition, the parameters in Formula 6 can be adjusted according to the physical characteristics of different lines. This enables the server to adapt to fault lines of different materials, structures, and lengths, enhancing the adaptability and flexibility of the system. By calculating the resistance and reactance per unit length under different frequency components, the server can support multi-frequency component analysis. This analysis capability helps to more comprehensively capture the propagation characteristics of the signal on the fault line and improve the reliability and accuracy of fault location.

[0137] S205. The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

[0138] In this step, the server compares the calculated fault distance with the total length of the fault line to be located. Based on the comparison result, the server determines the specific location of the fault area on the fault line and marks the area. The server sends the fault area information to relevant personnel or systems for subsequent fault handling and maintenance work.

[0139] Figure 3 FIG. 1 is a schematic diagram of a distribution network fault location system according to an exemplary embodiment of the present application. Figure 3 As shown, the distribution network fault location system 300 provided in this embodiment includes:

[0140] A distribution network topology structure 310, a feeder terminal unit set 320 and a server 330, wherein the distribution network topology structure 310 includes a monitoring node set and a line for connecting each monitoring node in the monitoring node set, each feeder terminal unit in the feeder terminal unit set 320 is correspondingly arranged on each monitoring node in the monitoring node set, and is communicatively connected with the server 330;

[0141] Acquire node information of a corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set 320, and send the node information to the server 330 to form a node information set, wherein the node information includes a voltage monitoring signal and a current monitoring signal;

[0142] The server 330 determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology 310, so as to determine a fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node, wherein the first characteristic monitoring node and the second characteristic monitoring node are two adjacent monitoring nodes, and there is no abnormal monitoring parameter in the first node information corresponding to the first characteristic monitoring node, and there is an abnormal monitoring parameter in the first node information corresponding to the second characteristic monitoring node;

[0143] The server 330 determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located;

[0144] The server 330 locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

[0145] Optionally, the server 330 determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located, including:

[0146] The server 330 uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding first voltage frequency domain signals and first current frequency domain signals, and converts the second voltage monitoring signal and the second current monitoring signal corresponding to the second characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding second voltage frequency domain signals and second current frequency domain signals;

[0147] The server 330 determines the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal.

[0148] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0149] The server 330 determines the characteristic impedance of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the characteristic impedance is used to determine the fault distance.

[0150] Optionally, before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes:

[0151] The server 330 determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the propagation parameters are used to determine the fault distance.

[0152] Optionally, before the server 330 determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, the method further includes:

[0153] The server 330 determines the resistance per unit length and the reactance per unit length of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the resistance per unit length and the reactance per unit length are used to determine the propagation parameters.

[0154] Optionally, the server 330 determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the distribution network topology structure 310, including:

[0155] The server 330 determines an abnormality index according to a voltage monitoring signal and a current monitoring signal in each node information in the node information set;

[0156] If the server 330 determines that the abnormality index corresponding to the feature monitoring node is greater than or equal to the preset abnormality index threshold, the server 330 determines that the feature monitoring node is an abnormal feature monitoring node; if the server 330 determines that the abnormality index corresponding to the feature monitoring node is less than the preset abnormality index threshold, the server 330 determines that the feature monitoring node is a normal feature monitoring node;

[0157] The server 330 traverses each pending feature monitoring node in the distribution network topology structure 310 to determine the first feature monitoring node and the second feature monitoring node, wherein the first feature monitoring node and the second feature monitoring node are two adjacent monitoring nodes in the distribution network topology structure 310, the first feature monitoring node is the normal feature monitoring node, and the second feature monitoring node is the abnormal feature monitoring node.

[0158] Optionally, the server 330 determines the first characteristic monitoring node and the second characteristic monitoring node according to the node information set and the distribution network topology structure 310, including:

[0159] The server 330 determines a pending characteristic monitoring node combination according to the power distribution network topology structure 310, wherein a first characteristic monitoring node and a second characteristic monitoring node in the pending characteristic monitoring node combination are two adjacent monitoring nodes, and in the power distribution network topology structure 310, the direction of electric energy transmission is from the first characteristic monitoring node to the second characteristic monitoring node;

[0160] The server 330 determines a correlation characteristic index according to the first node information and the second node information;

[0161] If the server 330 determines that the correlation feature index is less than a preset correlation feature threshold, it determines that the first feature monitoring node is a normal feature monitoring node and the second feature monitoring node is an abnormal feature monitoring node.

[0162] Figure 4 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. Figure 4 As shown, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; wherein:

[0163] The memory 402 is used to store computer programs, and the memory may also be a flash memory.

[0164] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. For details, please refer to the relevant description in the above method embodiment.

[0165] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0166] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include:

[0167] The bus 403 is used to connect the memory 402 and the processor 401 .

[0168] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the above-mentioned various implementation modes.

[0169] This embodiment also provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device implements the methods provided in the above various embodiments.

[0170] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0171] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for locating a feeder terminal unit fault based on the ranging principle, characterized in that: Applicable to a distribution network fault location system; the distribution network fault location system comprises: a distribution network topology structure, a feeder terminal unit set and a server, the distribution network topology structure comprises a monitoring node set and a line for connecting each monitoring node in the monitoring node set, each feeder terminal unit in the feeder terminal unit set is correspondingly arranged on each monitoring node in the monitoring node set, and is communicatively connected with the server; the method comprises: Acquire node information of a corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set, and send the node information to the server to form a node information set, wherein the node information includes a voltage monitoring signal and a current monitoring signal; The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine a fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node; The server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located; The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

2. The method for locating a feeder terminal unit fault based on the ranging principle according to claim 1, characterized in that: The server determines the fault distance according to first node information corresponding to the first characteristic monitoring node, second node information corresponding to the second characteristic monitoring node, and line physical parameters of the fault line to be located, including: The server uses Fourier transform to convert the first voltage monitoring signal and the first current monitoring signal corresponding to the first characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding first voltage frequency domain signals and first current frequency domain signals, and converts the second voltage monitoring signal and the second current monitoring signal corresponding to the second characteristic monitoring node from time domain signals to frequency domain signals to generate corresponding second voltage frequency domain signals and second current frequency domain signals; The server determines the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal.

3. The method for locating a feeder terminal unit fault based on the ranging principle according to claim 2, characterized in that: Before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes: The server determines the characteristic impedance of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the characteristic impedance is used to determine the fault distance.

4. The method for locating a feeder terminal unit fault based on the distance measurement principle according to claim 3, characterized in that: Before determining the fault distance according to the first voltage frequency domain signal, the first current frequency domain signal, the second voltage frequency domain signal, and the second current frequency domain signal, the method further includes: The server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, and the propagation parameters are used to determine the fault distance.

5. The method for locating a feeder terminal unit fault based on the distance measurement principle according to claim 4, characterized in that: Before the server determines the propagation parameters of the faulty line to be located at each frequency component according to the line physical parameters of the faulty line to be located, the method further includes: The server determines the resistance per unit length and the reactance per unit length of the fault line to be located at each frequency component according to the line physical parameters of the fault line to be located, and the resistance per unit length and the reactance per unit length are used to determine the propagation parameter.

6. The method for locating a feeder terminal unit fault based on the distance measurement principle according to any one of claims 1 to 5, characterized in that: The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including: The server determines an abnormality index according to a voltage monitoring signal and a current monitoring signal in each node information in the node information set; If the server determines that the abnormality index corresponding to the feature monitoring node is greater than or equal to the preset abnormality index threshold, the server determines that the feature monitoring node is an abnormal feature monitoring node; if the server determines that the abnormality index corresponding to the feature monitoring node is less than the preset abnormality index threshold, the server determines that the feature monitoring node is a normal feature monitoring node; The server traverses each pending feature monitoring node in the distribution network topology structure to determine the first feature monitoring node and the second feature monitoring node, wherein the first feature monitoring node and the second feature monitoring node are two adjacent monitoring nodes in the distribution network topology structure, the first feature monitoring node is the normal feature monitoring node, and the second feature monitoring node is the abnormal feature monitoring node.

7. The method for locating a feeder terminal unit fault based on the distance measurement principle according to any one of claims 1 to 5, characterized in that: The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, including: The server determines a pending characteristic monitoring node combination according to the distribution network topology structure, wherein a first characteristic monitoring node and a second characteristic monitoring node in the pending characteristic monitoring node combination are two adjacent monitoring nodes, and the direction of electric energy transmission in the distribution network topology structure is from the first characteristic monitoring node to the second characteristic monitoring node; The server determines a correlation characteristic index according to the first node information and the second node information; If the server determines that the correlation feature index is less than a preset correlation feature threshold, it determines that the first feature monitoring node is a normal feature monitoring node and the second feature monitoring node is an abnormal feature monitoring node.

8. A distribution network fault location system, characterized in that: include: A distribution network topology structure, a feeder terminal unit set and a server, wherein the distribution network topology structure includes a monitoring node set and a line for connecting each monitoring node in the monitoring node set, each feeder terminal unit in the feeder terminal unit set is correspondingly arranged on each monitoring node in the monitoring node set and is communicatively connected with the server; Acquire node information of a corresponding monitoring node through each feeder terminal unit in the feeder terminal unit set, and send the node information to the server to form a node information set, wherein the node information includes a voltage monitoring signal and a current monitoring signal; The server determines a first characteristic monitoring node and a second characteristic monitoring node according to the node information set and the distribution network topology structure, so as to determine a fault line to be located according to the first characteristic monitoring node and the second characteristic monitoring node, wherein the first characteristic monitoring node and the second characteristic monitoring node are two adjacent monitoring nodes, and there is no abnormal monitoring parameter in the first node information corresponding to the first characteristic monitoring node, and there is an abnormal monitoring parameter in the first node information corresponding to the second characteristic monitoring node; The server determines the fault distance according to the first node information corresponding to the first characteristic monitoring node, the second node information corresponding to the second characteristic monitoring node, and the line physical parameters of the fault line to be located; The server locates the fault area from the fault line to be located according to the first characteristic monitoring node and the fault distance.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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