A distribution line status online monitoring system and grounding fault diagnosis method

Abstract

The present application relates to an online monitoring system for the status of a distribution line and a method for diagnosing ground faults. The system includes a signal acquisition module, a collection preprocessing module, and an analysis main station. The signal acquisition module is used to obtain the status and environmental data of the distribution line and send the collected data to the collection preprocessing module; the collection preprocessing module is used to receive, store, and process the data sent by the signal acquisition module, and actively or passively upload the data to the analysis main station based on the data processing results; the analysis main station is used to receive or call for data stored in each collection preprocessing module to perform line status assessment and fault location diagnosis. The present application can use existing monitoring equipment to monitor the operating status of distribution network feeders in real time and identify potential hidden dangers. It can quickly locate the fault location after a fault occurs, which helps to quickly troubleshoot the fault and restore power supply.

Description

Technical Field

[0001] The present application relates to the field of detection, and in particular to an online status monitoring system and a fault diagnosis method for distribution lines in a new power system. Background Art

[0002] The distribution network is an electric power network that receives electric energy from the transmission network or regional power plants and distributes it to users locally or step by step through distribution facilities. It plays an important role in distributing electric energy in the power grid.

[0003] Improving the reliability of distribution network power supply has long been a core priority, with key measures requiring rapid and accurate fault diagnosis and further identification of line defects. Single-phase ground faults account for over 80% of all distribution network faults, easily causing power outages, electric shocks, and electrical fires. However, cost-effective technical means are still lacking for detecting and diagnosing single-phase ground faults, making this a key area of focus for provincial power companies. Due to the high proportion of cabled lines in current distribution networks, neutral point operation often utilizes a neutral point grounding system (resonant grounding system) via arc suppression coils to offset cable capacitive currents, suppress arcing during ground faults, and thus reduce the risk of system overvoltage and fault duration. While this neutral point operation method allows low-current grounded distribution networks to operate with faults for one to two hours, the influence of the arc suppression coils prevents the use of steady-state electrical quantities to identify ground faults.

[0004] In contrast, transient electrical quantities contain rich information and can overcome the interference of arc suppression coils on fault detection. For example, transient voltage and current change more dramatically at the moment of a fault, with amplitudes several to dozens of times higher than their steady-state values, and their frequency characteristics are not significantly affected by arc suppression coils. Therefore, analyzing transient electrical quantities can accurately reflect the electrical state at the time of the fault, facilitating rapid and accurate fault line selection and location. However, existing methods for ground fault analysis based on transient electrical quantities have the following difficulties:

[0005] 1. Complex fault determination criteria. Ground fault determination involves multiple transient electrical quantities, especially for low-current single-phase ground faults, such as faults. The selection and proper combination of effective transient electrical quantities directly determines the accuracy of fault determination. However, with such a diverse set of characteristic quantities, selecting and combining the optimal determination criteria is highly complex, increasing the difficulty of fault determination.

[0006] 2. Data collection is difficult and lacks unified standards. The sheer number of monitoring devices and the resulting volume of collected data are enormous. However, because the wave recording monitoring equipment deployed in the distribution network comes from different manufacturers, the recording triggering standards are inconsistent. The lack of standardized regulations for the fault recording trigger amplitude and duration for different devices complicates data utilization and integration. This inconsistency in standards impacts the accuracy of data analysis and the reliability of fault diagnosis.

[0007] 3. Insufficient sensitivity to weak fault signals. Current fault indicators and line selection technologies primarily rely on obvious current and voltage changes, making it difficult to promptly capture and identify weak fault signals, such as high-resistance single-phase grounding faults. Furthermore, under abnormal operating conditions (e.g., differences in system operation mode, fault location, transition impedance, and fault timing), feature quantities are susceptible to significant interference, increasing the difficulty of feature identification.

[0008] 4. High real-time and computing resource requirements. As the scale of power systems expands, the number of monitoring points and the amount of data increase dramatically. Data uploads are subject to delays and missed transmissions, and processing large amounts of high-frequency sampled data requires powerful computing resources. This can prevent fault analysis algorithms from running effectively and in real time. This impacts the timeliness of fault detection and location, making it impossible to meet the power system's rapid response requirements.

[0009] Currently, most fault analysis methods and models based on transient electrical quantities theoretically address the theoretical basis for ground fault determination, which is challenge 1. These include the first half-wave method, the transient zero-sequence current amplitude and phase ratio method, and the transient energy method, as well as the more widely studied time-frequency analysis, waveform similarity, and traveling wave methods. However, significant room for improvement remains in challenges 2, 3, and 4. Regarding challenges 2 and 4, existing patents such as CN109683062B, CN205787050U, and CN219552575U rely on the development and widespread installation of highly accurate fault indicators as the sole data acquisition device, failing to integrate and utilize existing distribution automation terminals within the distribution network. Consequently, these methods can only locate the fault zone for purely overhead lines, ignoring the situation involving purely cable lines and mixed overhead cable lines within the distribution network. Furthermore, effective implementation methods for addressing challenge 3, high-resistance ground faults, remain limited in practical analysis.

[0010] On the other hand, enhancing the distribution network's capacity to handle new energy elements is a key task in the current transformation and upgrading of the power system, and this also requires monitoring the volatility and uncertainty of new energy sources. With the continuous emergence and large-scale integration of diverse loads such as distributed power sources, electric vehicles, energy storage, and smart microgrids, the function and form of the distribution network are undergoing significant changes, gradually evolving from a one-way flow to a two-way flow, exhibiting increasingly complex "multi-source" characteristics. Relying solely on the monitoring of electrical quantities is insufficient to provide sufficient monitoring data support for the reliability and security of the distribution network after the integration of new energy. Greater consideration should be given to collecting non-electrical quantity data, such as environmental parameters and meteorological information, alongside monitoring electrical quantity data. Active monitoring of this multi-source data will lay the data foundation for the optimized regulation and control of the new distribution network. Summary of the Invention

[0011] The purpose of the embodiments of the present application is to provide an online monitoring system for the status of distribution lines and a grounding fault diagnosis method, which can use existing monitoring equipment to monitor the operating status of distribution network feeders in real time and identify potential hidden dangers, and can quickly locate the fault position after a fault occurs, which helps to quickly troubleshoot the fault and restore power supply.

[0012] To achieve the above objectives, this application provides the following technical solutions:

[0013] In a first aspect, an embodiment of the present application provides a distribution line status monitoring system, comprising a signal acquisition module, a collection pre-processing module, and an analysis master station.

[0014] The signal acquisition module is used to obtain the distribution line status and environmental data, and send the collected data to the aggregation preprocessing module;

[0015] The aggregation pre-processing module is used to receive, store and process the data sent by the signal acquisition module, and actively or passively upload the data to the analysis main station according to the data processing results;

[0016] The analysis master station is used to receive or call for data stored in each aggregation pre-processing module to perform line status evaluation and fault location diagnosis.

[0017] The signal acquisition module collects the voltage waveform, current waveform, temperature, image and ambient temperature and humidity data of the line equipment in real time through the online terminal monitoring equipment installed in the distribution network, and transmits the data to the aggregation preprocessing module. Each signal acquisition module is only responsible for signal acquisition at one monitoring point. The online terminal monitoring equipment includes a fault indicator, an infrared camera, and a temperature and humidity sensor.

[0018] The aggregation and preprocessing module includes a data aggregation unit, a data preprocessing unit and a communication unit. The data aggregation unit aggregates the data collected by a signal acquisition module and stores it locally. The data preprocessing unit calculates the zero-sequence voltage and zero-sequence current based on the stored three-phase voltage and three-phase current data. When the amplitude of the zero-sequence voltage or zero-sequence current exceeds the safety threshold and the duration exceeds the set value T, all data are actively uploaded to the analysis main station through the communication unit. Each aggregation and preprocessing module receives, stores, preprocesses and uploads the data of a collection module to the analysis main station.

[0019] The aggregation preprocessing module forms a wireless communication network with the signal acquisition module and the analysis main station through a communication unit using a time-division multiplexing wireless communication method. The communication unit of the aggregation preprocessing module uses GPS or Beidou timing to achieve precise time synchronization with the signal acquisition module and the analysis main station.

[0020] The analysis master station receives and calls for data uploaded from the aggregation preprocessing module. The analysis master station also reserves an interface to receive the distribution automation terminal recording data such as the station terminal DTU, feeder terminal FTU, and primary and secondary fusion switch transmitted by the external system.

[0021] The analysis master station first synchronizes the data collection time of each monitoring point according to the timestamp of the global positioning system or the Beidou satellite navigation system. Subsequently, the master station performs time alignment and truncation processing on the three-phase voltage and three-phase current waveform data received from each monitoring point of the distribution network, and removes redundant data at unaligned time points to ensure that the length and time points of all waveform data are consistent. On this basis, the master station superimposes the preprocessed data through the vector sum method to calculate the zero-sequence voltage and zero-sequence current of each monitoring point, and extracts steady-state and transient signals therefrom respectively. The analysis master station further calculates the characteristic values of these signals, and calculates the zero-sequence active power and zero-sequence reactive power of each monitoring point based on this. By comparing the waveform similarity and polarity of the current signal and reactive power of each monitoring point, the faulty and non-faulty lines and further fault location are confirmed.

[0022] In a second aspect, an embodiment of the present application provides a method for diagnosing a ground fault in a distribution network line, comprising the following specific steps:

[0023] S1, real-time capture of electric field and current data, generating accurate transient waveform recordings;

[0024] S2, the fault triggers the judgment criteria at the moment, and all terminal data of the bus are sent synchronously;

[0025] S3, the algorithm combines topology data to achieve fault line selection and location;

[0026] S4, rapid notification and guidance of emergency repairs;

[0027] S5, optimize and adjust the monitoring point locations according to the fault statistics results.

[0028] In step S1, the on-site fault indicator, station terminal DTU, feeder terminal FTU, and primary and secondary integrated switch distribution automation terminal record the voltage and current of the distribution network line in real time to generate a transient recording file;

[0029] In step S2, when a fault occurs, based on the preset threshold: the zero-sequence current I0 exceeds 200A or the zero-sequence voltage U0 exceeds 28V, and the duration T exceeds 0.02s, the judgment is triggered successfully, and the aggregation preprocessing module and distribution automation terminal here send the recording to the analysis master station. At the same time, the analysis master station calls for the voltage and current recording data of all remaining station terminals DTU, feeder terminals FTU, primary and secondary fusion switches under the same bus according to the line topology.

[0030] In step S3, the analysis master station performs time alignment and truncation processing on the received and called recording files, removes redundant data at unaligned time points, and calculates the zero-sequence voltage and zero-sequence current of each monitoring point. The steady-state and transient signals are extracted from them respectively, and the characteristic values of these signals are calculated. The fault line selection and position are realized according to the positioning judgment principle of ground fault.

[0031] In step S4, by analyzing the ground fault location conclusion given by the master station, the emergency repair personnel are guided to rush to the scene quickly to carry out emergency repairs and power supply;

[0032] In step S5, based on the on-site verification of the ground fault analysis accuracy, according to the formula , k is the 10kV voltage transformer ratio, v is the arc suppression coil transition compensation coefficient, U N is the rated phase voltage, R g Transition resistance: When the safety threshold of zero-sequence current I0 is 200A, if there are many cases of missed ground faults in on-site statistics, the safety threshold and duration T of zero-sequence voltage U0 will be reduced, and the corresponding transition resistance value will be increased, thereby reducing the number of missed ground faults.

[0033] Compared with existing technologies, the present invention offers the following advantages: It proactively monitors distribution network lines and their diverse loads in multiple dimensions, providing decision support for new distribution networks to cope with the massive influx of distributed power sources. By developing unified ground fault criteria, it addresses the inability of traditional monitoring systems to comprehensively process heterogeneous data from multiple sources, enabling accurate diagnosis and rapid location of ground faults, thereby enhancing the reliability and safety of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 This is the block diagram of the distribution line status monitoring system;

[0036] Figure 2 This is the schematic diagram of the distribution line status monitoring system;

[0037] Figure 3 To collect the working mode flow chart of the pre-processing module;

[0038] Figure 4 This is a flow chart of the ground fault diagnosis method;

[0039] Figure 5 The principle of ground fault line selection and location is shown. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings. It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0041] The terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0042] The terms "first," "second," etc. are only used to distinguish one entity or operation from another entity or operation, and are not to be understood as indicating or implying relative importance, nor are they to be understood as requiring or implying any actual relationship or order between these entities or operations.

[0043] like Figure 1 、 Figure 2 and Figure 5As shown in the figure, the system consists of a signal acquisition module, a collection and pre-processing module, and an analysis master station. The signal acquisition module is used to obtain distribution line status and environmental data and send the collected data to the collection and pre-processing module. The collection and pre-processing module is used to receive, store, and process the data sent by the signal acquisition module and actively or passively upload the data to the analysis master station based on the data processing results. The analysis master station is used to receive or call the data stored by each collection and pre-processing module to perform line status assessment and fault location diagnosis.

[0044] The signal acquisition module at each monitoring point includes the following equipment:

[0045] 1) Fault indicator: real-time monitoring of current and voltage waveforms to detect abnormal signals in the line;

[0046] 2) Infrared camera: provides real-time images of line equipment for identifying equipment status;

[0047] 3) Temperature and humidity sensor: monitors the environmental conditions of the power distribution line and assists in fault diagnosis.

[0048] The aggregation preprocessing module is responsible for receiving the data transmitted by the signal acquisition module and storing and processing it.

[0049] like Figure 3 As shown, the working mode of the aggregation preprocessing module is: when there is no fault in the distribution network line, that is, the zero-sequence voltage and current amplitude are within the normal range, the aggregation preprocessing module only stores the data of all monitoring points locally but does not automatically upload them to the analysis master station through the communication module. It only uploads the specified time period and collected data as required when the analysis master station calls for testing; when an abnormality occurs in the distribution network line, that is, the line zero-sequence voltage and current amplitude exceed the normal range, causing any online terminal monitoring device to upload abnormal or fault data, the aggregation preprocessing module uploads the data collected by all monitoring devices in the abnormal or fault period to the analysis master station through the communication unit.

[0050] The aggregation preprocessing module includes the following units:

[0051] 1) Data collection unit: receives data from the signal acquisition module and stores it locally.

[0052] 2) Data pre-processing unit: Calculates zero-sequence voltage (U0) and zero-sequence current (I0) based on stored voltage and current data, and determines whether they exceed the set safety threshold, such as zero-sequence current exceeding 200A and lasting for more than 0.02s, or zero-sequence voltage (secondary) exceeding 28V and lasting for more than 0.02s.

[0053] 3) Communication unit: The processed data is transmitted to the analysis main station through time-division multiplexing wireless communication, and precise time synchronization between modules is achieved through GPS or Beidou timing.

[0054] like Figure 3 As shown, corresponding to the operating mode of the aggregation preprocessing module, the operating mode of the analysis master station is as follows: when the distribution network line is not faulty, the analysis master station does not receive information from the aggregation preprocessing module. However, it can manually select voltage waveforms, current waveforms, temperature, images, and ambient temperature and humidity data within a certain time period to be viewed. It then uses wireless communication to call for data stored in the aggregation preprocessing module, providing data for identifying hidden dangers. When a distribution network line fault occurs, the analysis master station receives data uploaded by the signal acquisition module at a monitoring point via wireless communication. Based on the line topology, it calls for data such as voltage waveforms, current waveforms, temperature, images, and ambient temperature and humidity data from all monitoring points on the feeders under the same busbar, performs analysis, and achieves fault line selection and location.

[0055] The functions of the analysis master station include the following aspects:

[0056] 1) Data Reception and Processing: The master station not only receives and monitors data uploaded by the aggregation preprocessing module but also has interfaces for receiving waveform data from distribution automation terminals (DTUs), feeder FTUs, and primary / secondary fusion switches) transmitted from external systems. This data is then reconstructed and integrated, including synchronizing data collection times at each monitoring point using timestamps from the Global Positioning System (GPS) or Beidou satellite navigation system. The master station then time-aligns and truncates the three-phase voltage and current waveform data received from each monitoring point in the distribution network, removing redundant data at misaligned time points to ensure consistent length and timing across all waveform data.

[0057] 2) Fault Diagnosis and Location: The master station superimposes the preprocessed data using the vector sum method to calculate the zero-sequence voltage and current at each monitoring point, extracting steady-state and transient signals from these signals. The analysis master station further calculates the characteristic values of these signals, such as amplitude, average, differential, integral, and their combinations, and uses these to calculate the zero-sequence active power and reactive power at each monitoring point. By comparing the waveform similarity and polarity of the current and reactive power signals at each monitoring point, faulty and non-faulty lines can be identified and further fault location can be achieved.

[0058] 3) Review and repair: Once the fault is located at the ground fault point, the analysis master station will provide a manual review mechanism to confirm the fault point and display the fault location on the Geographic Information System (GIS) map, such as Figure 2 As shown, the fault point is located between monitoring point 10 and monitoring point 11. The analysis master station also supports sending ground fault signals to the signal acquisition module via a time-division multiplexing wireless communication network to help on-site personnel quickly locate the fault point.

[0059] In particular, when a ground fault occurs in the distribution network line, Figure 4 The 5 steps to achieve ground fault line selection and accurate location. Figure 4 As shown:

[0060] Step S1: Real-time capture of electric field and current data to generate accurate transient waveforms

[0061] Monitoring terminals in the distribution network (such as fault indicators, DTUs, FTUs, and primary / secondary fusion switches) are responsible for collecting real-time data on distribution line voltage, current, temperature, and humidity, and generating accurate transient waveform recordings. This monitoring data serves as a basis for line status evaluation and provides a key foundation for subsequent fault analysis. Real-time data collection requires high accuracy to ensure that the data accurately reflects the operating status and transient changes of the distribution line.

[0062] Step S2: The fault triggers the judgment criteria and all the terminal data of the bus are sent synchronously.

[0063] When a ground fault occurs, the system automatically triggers a fault alarm based on the set criteria.

[0064] During the transient process of a single-phase grounding fault, the relationship between the zero-sequence voltage (secondary) U0, the zero-sequence current I0 and the transition resistance Rg is: , where k is the 10kV voltage transformer ratio, which is 1:100 ; v is the arc suppression coil transition compensation coefficient, take -10%; U N is the rated phase voltage, take 10 / kV. The magnitude of the transition resistance Rg when a ground fault occurs directly affects the accuracy of ground fault location. Unifying the value of the transition resistance is an important way and basis for different distribution automation terminals to cooperate with each other in zero-sequence protection. Currently, the distribution network's transition resistance is generally required to be greater than 2000Ω. Usually, the capacitive current of the arc suppression coil grounding system is generally around 150A, and the maximum does not exceed 200A. The zero-sequence current safety threshold can be set to 200A. The zero-sequence voltage (secondary side) safety threshold can be between 23V and 0.15U N The value changes between the two levels to adjust the transition resistance capability of ground fault diagnosis, improve the line selection accuracy and further identify potential line grounding defects.

[0065] When the transition resistance Rg is set to 2000Ω, the safety threshold of the zero-sequence current is 200A, and the zero-sequence voltage (secondary) U0 can be calculated to be approximately 28V.

[0066] The specific criteria are: when the zero-sequence current I0 exceeds 200A or the zero-sequence voltage (secondary side) U0 exceeds 28V and persists for more than 0.02 seconds, the system determines a fault has occurred and triggers an alarm. At this point, all pre-processing modules and distribution automation terminals simultaneously upload the relevant data to the analysis master station.

[0067] At the same time, the analysis master station activates the call test function based on the line topology data of the distribution network, and obtains the recorded data of other terminals under the fault bus in real time to ensure that comprehensive data is obtained to support fault analysis.

[0068] Step S3: The algorithm is combined with topology data to achieve fault line selection and location.

[0069] The analysis master station then time-aligns and truncates the received recorded data to remove redundant data and ensure accuracy. The master station then uses proprietary algorithms to analyze the zero-sequence voltage and current, extracting steady-state and transient signals and evaluating their characteristic values (such as amplitude and average). These characteristic values are used for subsequent fault line screening and location.

[0070] like Figure 3 Specifically, the fault location method is as follows:

[0071] 1) Transient zero-sequence current amplitude and polarity comparison method: The high-frequency transient zero-sequence current amplitudes of the non-fault line and the fault line are different and the polarities are opposite. The polarities of the high-frequency transient zero-sequence currents before and after the fault point on the fault line are different.

[0072] 2) Transient zero-sequence power direction method: The actual direction of the capacitive reactive power in the non-fault line is from the busbar to the line, and the actual direction of the capacitive reactive power in the fault line is from the line to the busbar. The capacitive reactive power before and after the fault point on the fault line is opposite.

[0073] For example Figure 2 In the figure, when the ground fault occurs between monitoring points 10 and 11, the directions of the transient zero-sequence current and capacitive reactive power at monitoring points 7, 8, and 10 are from the line to the bus, while the directions of the transient zero-sequence current and capacitive reactive power at the remaining monitoring points are from the bus to the line. Based on this, it can be confirmed that the fault path is 7>8>10, and the fault point is located after monitoring point 10 and before 11.

[0074] Step S4: Quickly notify and guide emergency repairs

[0075] Once the analysis master station completes fault diagnosis, the system transmits the ground fault location results to on-site repair personnel in real time via the communication network. Based on the fault location and type information provided by the master station, repair personnel can quickly begin repair work, shortening the power outage and ensuring that power is restored to the faulty line as soon as possible.

[0076] Step S5: Optimize and adjust the monitoring point location based on the fault statistics results

[0077] By analyzing the statistics of all previous fault data, the analysis master station can evaluate the coverage of existing monitoring points and optimize the layout of the monitoring points and the basis for grounding judgment based on the results. The accuracy of fault location depends on the layout and installation interval of the on-site monitoring points. If the actual grounding faults of a certain line occur frequently and the fault location range is too large, the operation and maintenance personnel can optimize it by adjusting the layout of the monitoring points and adding monitoring points, thereby improving the accuracy of fault location and the efficiency of emergency repairs. If the statistical results of the analysis master station are inconsistent with the actual situation, such as frequent missed grounding faults, the safety threshold of the zero-sequence voltage (secondary) U0 can be manually reduced (23V to 0.15U N The corresponding transition resistance value increases, thereby reducing the possibility of missed ground faults and improving the overall diagnostic capability and fault response speed of the system.

[0078] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for diagnosing ground faults in a distribution network, characterized in that: The specific steps include: S1, real-time capture of voltage and current data, generating accurate transient waveforms; S2, the fault triggers the judgment criteria at the moment, and all terminal data of the bus are sent synchronously; S3, the algorithm combines topology data to achieve fault line selection and location; S4, rapid notification and guidance of emergency repairs; S5, optimize and adjust the monitoring point location according to the fault statistics results; In step S1, the on-site fault indicator, station terminal DTU, feeder terminal FTU, and primary and secondary integrated switch distribution automation terminal record the voltage and current of the distribution network line in real time to generate a transient recording file; In step S2, when a fault occurs, based on the preset thresholds: zero-sequence current I0 exceeds 200A or zero-sequence voltage U0 exceeds 28V, and the duration T exceeds 0.02s, the judgment is triggered successfully. The aggregation pre-processing module and distribution automation terminal at this location send the recorded waveform to the analysis master station. At the same time, the analysis master station calls for the voltage and current recorded waveform data of all remaining distribution automation terminals under the same bus, such as station terminals DTUs, feeder terminals FTUs, and primary and secondary fusion switches, based on the line topology. In step S3, the analysis master station performs time alignment and truncation processing on the received and called recording files, removes redundant data at unaligned time points, and calculates the zero-sequence voltage and zero-sequence current of each monitoring point. The steady-state and transient signals are extracted from them, and the characteristic values of these signals are calculated. The fault line is selected and the position is located according to the ground fault location determination principle. In step S4, by analyzing the ground fault location conclusion given by the master station, the emergency repair personnel are guided to rush to the scene quickly to carry out emergency repairs and power supply; In step S5, based on the on-site verification of the ground fault analysis accuracy, according to the formula , k is the 10kV voltage transformer ratio, v is the arc suppression coil transition compensation coefficient, U N is the rated phase voltage, R g For the transition resistance, when the safety threshold of the zero-sequence current I0 is 200A, if there are many cases of missed ground faults in the on-site statistics, the safety threshold and duration T of the zero-sequence voltage U0 will be reduced, and the corresponding transition resistance value will be increased, thereby reducing the cases of missed ground faults.

2. A distribution line status monitoring system for implementing the method according to claim 1, characterized in that: Including signal acquisition module, collection pre-processing module and analysis main station, The signal acquisition module is used to obtain the status and environmental data of the distribution line and send the collected data to the aggregation preprocessing module; The aggregation pre-processing module is used to receive, store and process the data sent by the signal acquisition module, and actively or passively upload the data to the analysis main station according to the data processing results; The analysis master station is used to receive or call for data stored in each aggregation pre-processing module to perform line status evaluation and fault location diagnosis.

3. The power distribution line status monitoring system according to claim 2, characterized in that: The signal acquisition module collects the voltage waveform, current waveform, temperature, image and ambient temperature and humidity data of the line equipment in real time through the online terminal monitoring equipment installed in the distribution network, and transmits the data to the aggregation preprocessing module. Each signal acquisition module is only responsible for signal acquisition at one monitoring point. The online terminal monitoring equipment includes a fault indicator, an infrared camera, and a temperature and humidity sensor.

4. The power distribution line status monitoring system according to claim 2, characterized in that: The aggregation and preprocessing module includes a data aggregation unit, a data preprocessing unit and a communication unit. The data aggregation unit aggregates the data collected by a signal acquisition module and stores it locally. The data preprocessing unit calculates the zero-sequence voltage and zero-sequence current based on the stored three-phase voltage and three-phase current data. When the amplitude of the zero-sequence voltage or zero-sequence current exceeds the safety threshold and the duration exceeds the set value T, all data are actively uploaded to the analysis main station through the communication unit. Each aggregation and preprocessing module receives, stores, preprocesses and uploads the data of a collection module to the analysis main station.

5. The power distribution line status monitoring system according to claim 2, characterized in that: The aggregation preprocessing module forms a wireless communication network with the signal acquisition module and the analysis main station through a communication unit using a time-division multiplexing wireless communication method. The communication unit of the aggregation preprocessing module uses GPS or Beidou timing to achieve precise time synchronization with the signal acquisition module and the analysis main station.

6. The distribution line status monitoring system according to claim 2, characterized in that: The analysis master station receives and calls for data uploaded from the aggregation preprocessing module. The analysis master station also reserves an interface to receive the distribution automation terminal recording data such as the station terminal DTU, feeder terminal FTU, and primary and secondary fusion switch transmitted by the external system.

7. The power distribution line status monitoring system according to claim 2, characterized in that: The analysis master station first synchronizes the data collection time of each monitoring point according to the timestamp of the global positioning system or the Beidou satellite navigation system. Subsequently, the master station performs time alignment and truncation processing on the three-phase voltage and three-phase current waveform data received from each monitoring point of the distribution network, and removes redundant data at unaligned time points to ensure that the length and time points of all waveform data are consistent. On this basis, the master station superimposes the preprocessed data through the vector sum method to calculate the zero-sequence voltage and zero-sequence current of each monitoring point, and extracts steady-state and transient signals therefrom respectively. The analysis master station further calculates the characteristic values of these signals, and calculates the zero-sequence active power and zero-sequence reactive power of each monitoring point based on this. By comparing the waveform similarity and polarity of the current signal and reactive power of each monitoring point, the faulty and non-faulty lines and further fault location are confirmed.

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