Multi-side collaborative diagnosis and positioning method for single-phase earth fault of power distribution network

Abstract

The invention relates to the technical field of power system diagnosis, in particular to a power distribution network single-phase earth fault multilateral collaborative diagnosis and positioning method, which comprises the following steps: S1, collecting current and voltage signals in a power distribution network in real time through a sensor network; s2, preprocessing the current and voltage signals; s3, analyzing the unbalance degree of the current and the abrupt change point of the voltage, and identifying whether a single-phase earth fault occurs or not; s4, calculating the propagation time difference of the fault signal by using a time difference of arrival method, and preliminarily estimating the position of the fault; s5, correcting a fault position to locate a specific fault point; s6, generating a fault positioning report; and S7, according to a fault positioning result, triggering a processing measure to send a maintenance instruction to related personnel. According to the invention, through combination of multi-data source analysis and a power grid topological structure, an accurate fault positioning and automatic processing flow is provided, the fault detection precision and the processing efficiency are effectively improved, and stable operation of a power grid is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power system diagnosis, and in particular to a method for multilateral collaborative diagnosis and positioning of single-phase grounding faults in a distribution network. Background Art

[0002] With the continuous expansion of the scale of power grids and the increase in complexity, single-phase grounding faults in distribution networks have become a common type of fault that affects the safe and stable operation of power systems. Such faults are usually caused by aging of power grid lines, external environmental impacts or equipment damage. When a fault occurs, it will cause current imbalance, line short circuit, and even cause large-scale power outages. Therefore, how to quickly and accurately detect and locate single-phase grounding faults is a key link in ensuring power grid safety and reducing power outage time. Traditional fault detection methods mostly rely on manual inspections or single sensors to collect data, which is not only inefficient, but also has poor accuracy, making it difficult to detect and repair faults in a timely manner.

[0003] In the existing technology, although some automated equipment and systems have been introduced for fault detection, these methods are often limited by insufficient equipment coverage and limited data processing capabilities, resulting in inaccurate fault location. In addition, existing methods usually ignore the effective use of power grid topology and historical fault data, and cannot provide intelligent fault analysis and processing mechanisms. Therefore, it is particularly necessary to develop a fault diagnosis and location method based on power grid topology that combines multiple data sources. Summary of the invention

[0004] Based on the above objectives, the present invention provides a method for multilateral collaborative diagnosis and positioning of single-phase grounding faults in distribution networks.

[0005] The method for multi-lateral collaborative diagnosis and location of single-phase grounding fault in distribution network includes the following steps:

[0006] S1: collect current and voltage signals in the distribution network in real time through the sensor network, and transmit the collected data to the data processing unit;

[0007] S2: preprocessing the current and voltage signals transmitted to the data processing unit, wherein the preprocessing includes noise removal and outlier removal to generate standard data;

[0008] S3: Based on standard data, analyze the current imbalance and voltage mutation point, and use the fault detection algorithm to identify whether a single-phase grounding fault occurs;

[0009] S4: If a single-phase grounding fault is detected, the data at different sampling points will be analyzed in time series, and the propagation time difference of the fault signal will be calculated using the arrival time difference method to preliminarily estimate the location of the fault;

[0010] S5: Based on the preliminary location estimation, combined with historical fault data and grid topology, the fault location is corrected using a regression analysis algorithm to locate the specific fault point;

[0011] S6: Generate a fault location report, which includes the specific line, location and time of the fault;

[0012] S7: According to the fault location result, trigger the processing measures and send maintenance instructions to relevant personnel.

[0013] Optionally, the S1 specifically includes:

[0014] S11: arranging current and voltage sensors at predetermined nodes of the distribution network to collect three-phase current and voltage signals in real time;

[0015] S12: performing preliminary data packaging on the collected current and voltage signals, wherein the packaging includes adding a timestamp and a sampling point location label to each sampling signal;

[0016] S13: Transmitting the packaged current and voltage data to a data processing unit via a communication network, wherein the communication network adopts optical fiber or 5G communication technology;

[0017] S14: During the data transmission process, TCP / IP protocol is used for data packaging and transmission to ensure data integrity.

[0018] Optionally, the S2 specifically includes:

[0019] S21: After receiving the current and voltage signals transmitted to the data processing unit, the data is first filtered, and a frequency domain filtering algorithm based on fast Fourier transform is used to remove high-frequency noise and interference signals in the signal;

[0020] S22: performing outlier detection on the filtered current and voltage signals, using a statistically based outlier elimination algorithm to identify and eliminate abnormal data points that exceed the normal range by calculating the mean and standard deviation of the signals;

[0021] S23: performing data smoothing processing on the signal after removing noise and outliers, and using a sliding average algorithm to smooth the signal to reduce short-term fluctuations in the signal;

[0022] S24: normalize the current and voltage signals processed by S23, and convert the numerical range of the signals into a standardized interval through a linear normalization algorithm, so as to ensure that data in different measurement units can be processed uniformly and finally generate standard data.

[0023] Optionally, the S3 specifically includes:

[0024] S31: Based on the standardized current data, calculate the unbalance degree of the three-phase current, analyze the difference between the three-phase currents, and determine whether there is an obvious current unbalance phenomenon by comparing the amplitude and phase of the current of each phase;

[0025] S32: Perform mutation point detection on the voltage signal, identify the rapid drop or sudden rise of the voltage value by real-time monitoring the change trend of each phase voltage, and mark the time and amplitude of these changes for subsequent fault judgment;

[0026] S33: combining the change of current unbalance degree with the time and amplitude of the voltage mutation point, and using a fault detection algorithm to comprehensively analyze the features to determine whether it is a single-phase grounding fault. The fault detection algorithm is based on a preset feature threshold and compares the current current and voltage features with feature data during normal operation to identify whether it meets the typical features of a single-phase grounding fault;

[0027] S34: If the characteristic analysis result in S33 meets the characteristics of a single-phase grounding fault, the time point, location and related data are recorded and marked as a fault point.

[0028] Optionally, the S33 specifically includes:

[0029] S331: synchronously collect the change of current unbalance and the change rate of voltage, and calculate a comprehensive fault characteristic parameter by assigning different weights to current and voltage characteristics and combining the changes of the two;

[0030] S332: Setting a threshold for fault identification, when the calculated fault characteristic parameter exceeds the threshold, determining that the current state is a single-phase grounding fault;

[0031] S333: Analyze the changes of current and voltage characteristics in combination with the time dimension, and observe the abnormal duration of the characteristics. When the characteristic values ​​of current and voltage remain abnormal for a preset period of time, it is confirmed that a single-phase grounding fault has occurred.

[0032] S334: Based on the fault characteristic parameters and time analysis results, record the time, location and related characteristic information of the fault.

[0033] Optionally, the S4 specifically includes:

[0034] S41: when a single-phase grounding fault is detected, data of sampling points at different locations are collected to obtain the time point at which the fault signal is received at each location;

[0035] S42: Perform time series analysis on the data at different sampling points to determine the exact time t at which each sampling point receives the fault signal i , and by comparing the time point t iThe time difference with other sampling points, records the time difference of receiving the signal at each sampling point;

[0036] S43: Use the arrival time difference method to make a preliminary estimate of the fault location. Assuming that the propagation speed of the fault signal in the conductor is v, the distance difference Δd between the fault point and the sampling point is ij Calculated by the following formula: Δd ij =v×Δt ij , where Δd ij is the propagation distance difference of the fault signal between different sampling points, v is the propagation speed of the fault signal, Δt ij is the time difference between different sampling points, and the relative distance between the fault location and each sampling point is preliminarily estimated through the calculated distance difference;

[0037] S44: Combine the distance difference between different sampling points and use the triangulation method to calculate the approximate location of the fault;

[0038] S45: Compare the fault location calculated in S44 with the geographical location information of the distribution network to preliminarily determine the specific location range of the fault.

[0039] Optionally, the S44 specifically includes:

[0040] S441: first determine the known position coordinates of multiple sampling points in the distribution network, and determine the relative distance difference between each pair of sampling points and the fault point according to the distance difference of the fault signal propagation calculated in S43;

[0041] S442: Based on the known positions and distance differences of the sampling points, multiple sets of position equations are established to represent the distance relationship between each sampling point and the fault point;

[0042] S443: A set of equations is formed using data from multiple sampling points, and the approximate location of the fault point is solved by analyzing the equations using the least square method.

[0043] Optionally, the S5 specifically includes:

[0044] S51: Collecting historical fault data, where the historical fault data includes the location, time and related electrical characteristics of single-phase grounding faults that occurred in the past;

[0045] S52: Analyze the length and impedance characteristics of each line in combination with the grid topology data;

[0046] S53: applying a multivariate regression analysis algorithm to correct the fault location, and establishing a regression model based on the impedance analysis results in step S52 and historical fault data;

[0047] S54: Based on the calculation result of the regression model, the initially estimated fault location is corrected to ensure that the final positioning result is consistent with the actual power grid topology.

[0048] Optionally, the S6 specifically includes:

[0049] S61: Collect and integrate fault location data, the data including the specific location of the fault point, the corresponding line number, the fault detection time and related electrical parameters;

[0050] S62: Compare the fault location with the power grid geographic information system to confirm on which specific line the fault location is located, and based on the known distribution network topology, the location report will list the specific line number where the fault occurs;

[0051] S63: Record the fault occurrence time of the fault detection mark. If there are multiple time records, take the earliest time point as the fault occurrence time;

[0052] S64: Generate a fault location report.

[0053] Optionally, the S7 specifically includes:

[0054] S71: According to the fault location result, a maintenance instruction generation program is automatically triggered to generate a maintenance task instruction according to the fault location, line number and occurrence time recorded in the fault report. The maintenance task includes a detailed description of the fault location and the maintenance or repair operation to be performed;

[0055] S72: Send the generated maintenance instruction to relevant maintenance personnel, and the maintenance personnel information is automatically assigned through a pre-configured task management platform to ensure that the maintenance team closest to the fault location receives the maintenance task.

[0056] Beneficial effects of the present invention:

[0057] The present invention collects current and voltage signals in real time, analyzes current imbalance and voltage mutation points, and uses regression analysis and triangulation to accurately calculate the fault location, thereby effectively improving the accuracy of fault detection. Compared with traditional fault detection methods, it can quickly locate the fault point, reduce the fault response time, and avoid long power outages and unnecessary manual intervention.

[0058] The present invention integrates historical fault data and power grid topology to automatically generate maintenance instructions and adjust power distribution after a fault occurs, ensuring that the scope of fault impact is minimized. This not only improves fault handling efficiency, but also enhances the stability and security of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 A schematic diagram of a method for multilateral collaborative fault diagnosis and location according to an embodiment of the present invention;

[0061] Figure 2 The figure is a schematic diagram of a judgment flow of using a fault detection algorithm according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0063] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0064] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0065] like Figure 1-Figure 2 As shown, the method for multi-lateral collaborative diagnosis and location of single-phase grounding fault in distribution network includes the following steps:

[0066] S1: collect current and voltage signals in the distribution network in real time through the sensor network, and transmit the collected data to the data processing unit;

[0067] S2: preprocessing the current and voltage signals transmitted to the data processing unit, the preprocessing includes noise removal and outlier removal, and generating standard data;

[0068] S3: Based on standard data, analyze the current imbalance and voltage mutation point, and use the fault detection algorithm to identify whether a single-phase grounding fault occurs;

[0069] S4: If a single-phase grounding fault is detected, the data at different sampling points will be analyzed in time series, and the propagation time difference of the fault signal will be calculated using the arrival time difference method to preliminarily estimate the location of the fault;

[0070] S5: Based on the preliminary location estimation, combined with historical fault data and grid topology, the fault location is corrected using a regression analysis algorithm to locate the specific fault point;

[0071] S6: Generate a fault location report, which includes the specific line, location and time of the fault;

[0072] S7: According to the fault location result, trigger the processing measures to send maintenance instructions to relevant personnel to reduce the impact of the fault on the operation of the power grid.

[0073] S1 specifically includes:

[0074] S11: Current and voltage sensors are arranged at predetermined nodes of the distribution network to collect three-phase current and voltage signals in real time, wherein the collection frequency is a fixed high frequency to ensure that dynamic changes of the power grid are captured;

[0075] S12: performing preliminary data packaging on the collected current and voltage signals, wherein the packaging includes adding a timestamp and a sampling point location label to each sampling signal to ensure that each data packet contains accurate spatiotemporal information;

[0076] S13: The packaged current and voltage data are transmitted to the data processing unit through a low-latency, high-bandwidth communication network. The communication network uses optical fiber or 5G communication technology to ensure the stability and real-time performance of data transmission, and the transmission delay does not exceed the set millisecond level;

[0077] S14: During the data transmission process, a data transmission protocol is used to ensure lossless data transmission. The protocol specifically uses the TCP / IP protocol for data packaging and transmission to ensure data integrity. Through the above steps, efficient real-time collection and transmission of current and voltage signals in the distribution network can be achieved, ensuring the accuracy and timeliness of the data, and providing reliable basic data support for subsequent fault analysis and positioning.

[0078] The preprocessing in S2 specifically includes:

[0079] S21: After receiving the current and voltage signals transmitted to the data processing unit, the data is first filtered by using a frequency domain filtering algorithm based on fast Fourier transform (FFT) to remove high-frequency noise and interference signals in the signal and retain the main frequency band information related to fault diagnosis; the transformation formula of FFT is:

[0080] Among them, X(f) is the result of the frequency domain signal, x(n) is the value of the time domain signal, N is the total number of sampling points, f is the frequency, and n is the sampling point number of the signal. By setting the threshold in the frequency domain, the signal that exceeds the set noise frequency range can be removed;

[0081] S22: Perform outlier detection on the filtered current and voltage signals, and use a statistically based outlier elimination algorithm to identify and eliminate abnormal data points that exceed the normal range by calculating the mean and standard deviation of the signal; the outlier elimination algorithm formula is: |x i -μ x |>3σ x , where x i is a single data point in the signal, μ x is the data mean, σ x is the data standard deviation, and signal data outside this range will be considered abnormal and eliminated;

[0082] S23: Perform data smoothing on the signal after removing noise and outliers, and use a sliding average algorithm to smooth the signal to reduce short-term fluctuations in the signal. The formula for using the sliding average algorithm is: Among them, y i is the signal value after smoothing, x i+k is the current signal point x i and the average of the subsequent M data points, where M is the length of the sliding window;

[0083] S24: Normalize the current and voltage signals processed by S23, and convert the numerical range of the signals into a standardized interval through a linear normalization algorithm to ensure that data in different measurement units can be processed uniformly, and finally generate standard data as the basis for subsequent fault analysis.

[0084] S3 specifically includes:

[0085] S31: Based on the standardized current data, calculate the unbalance degree of the three-phase current, analyze the difference between the three-phase currents, and determine whether there is obvious current unbalance by comparing the amplitude and phase of each phase current; the unbalance degree is determined by the following formula: Among them, ΔI is the unbalance degree of three-phase current, I max is the maximum value among the three-phase currents, I minis the minimum value among the three-phase currents, I avg is the average value of the three-phase current; when ΔI exceeds the set threshold, it indicates that there is an obvious current imbalance phenomenon, indicating that the amplitude difference between the three-phase currents is large;

[0086] S32: Perform mutation point detection on the voltage signal, identify the rapid drop or sudden rise of the voltage value by real-time monitoring the change trend of each phase voltage, and mark the time and amplitude of these changes for subsequent fault judgment; specifically, identify the rapid change of voltage through the following formula: Where ΔV is the voltage change rate, V(t1) and V(t2) are the voltage values ​​at time points t1 and t2 respectively, and t2-t1 is the time difference between two samplings. When ΔV exceeds the preset mutation threshold, it means that the voltage has dropped or risen rapidly, and these change points are marked for subsequent fault analysis.

[0087] S33: combining the change of current unbalance degree with the time and amplitude of the voltage mutation point, and using the fault detection algorithm to comprehensively analyze the features to determine whether it is a single-phase grounding fault. The fault detection algorithm is based on a preset feature threshold and compares the current current and voltage features with the feature data during normal operation to identify whether it meets the typical features of a single-phase grounding fault;

[0088] S34: If the characteristic analysis result in S33 meets the characteristics of a single-phase grounding fault, the time point, location and related data are recorded and marked as the fault point to facilitate subsequent fault location.

[0089] The fault detection algorithm in S33 specifically includes:

[0090] S331: synchronously collect the change of current unbalance and the change rate of voltage, and calculate a comprehensive fault characteristic parameter by assigning different weights to the current and voltage characteristics and combining the change of the two, so as to judge the possibility of the fault;

[0091] S332: Setting a threshold for fault identification. When the calculated fault characteristic parameter exceeds the threshold, the current state is determined to be a single-phase grounding fault. The threshold is set based on historical fault data and the actual operating environment to ensure that it accurately reflects the characteristics of the fault.

[0092] S333: Analyze the changes of current and voltage characteristics in combination with the time dimension, and observe the abnormal duration of the characteristics. When the characteristic values ​​of current and voltage remain abnormal for a preset period of time, it is confirmed that a single-phase grounding fault has occurred. This time analysis ensures the stability and reliability of the detection process.

[0093] S334: Based on the fault characteristic parameters and time analysis results, the time, location and related characteristic information of the fault are recorded for subsequent fault location and repair operations; through the above steps, the fault detection algorithm can accurately identify single-phase grounding faults in the distribution network by comprehensively analyzing the current imbalance and voltage change characteristics.

[0094] The specific operation steps of the fault detection algorithm are as follows:

[0095] The change of current unbalance ΔI and voltage change rate ΔV are collected synchronously, and these characteristic data are compared with the set threshold value. The fault characteristic parameter F is calculated by the following formula: F = αΔI + βΔV, where F is the fault characteristic parameter, ΔI is the change of current unbalance, ΔV is the voltage change rate, α and β are weight coefficients, which represent the influence weight of current and voltage characteristics on the fault, and the weight value is set according to the actual operation situation;

[0096] Set the fault identification threshold F threshold When the fault characteristic parameter F meets the following conditions, it is judged as a single-phase grounding fault. The condition formula is: F ≥ F threshold , where F threshold It is a preset fault identification threshold, which is adjusted according to historical fault data and actual operating environment. When F exceeds this threshold, it means that the current current and voltage characteristics meet the characteristics of a single-phase grounding fault.

[0097] According to the changing trend of the fault characteristic parameter F, combined with the analysis of the time dimension, the duration of the current and voltage characteristics is observed. If the characteristic value exceeds the set threshold for a period of time T, it is confirmed that a single-phase grounding fault has occurred. The set time threshold condition is: t duration ≥T, where t duration is the duration of abnormal current unbalance and voltage mutation point, T is the set minimum duration threshold; if the time condition is met, the fault identification result will be confirmed;

[0098] Finally, combined with the above analysis results, the time, location, characteristic parameter F and other information when the fault occurs are recorded and used for subsequent fault location and repair.

[0099] The preliminary estimation of the fault location in S4 specifically includes:

[0100] S41: When a single-phase grounding fault is detected, data from sampling points at different locations are collected. The sampling points are distributed at multiple nodes of the power grid and can record the changing moments of current and voltage signals in real time. By collecting the fault signal at each sampling point, the time point when the fault signal is received at each location is obtained.

[0101] S42: Perform time series analysis on the data at different sampling points to determine the exact time t at which each sampling point receives the fault signal i , and by comparing the time point t i The time difference with other sampling points, record the time difference Δt of each sampling point receiving the signal ij , where i and j represent different sampling points, the formula is: Δt ij =t j -t i ;

[0102] S43: Use the arrival time difference method to make a preliminary estimate of the fault location. Assuming that the propagation speed of the fault signal in the conductor is v, the distance difference Δd between the fault point and the sampling point is ij Calculated by the following formula: Δd ij =v×Δt ij , where Δd ij is the propagation distance difference of the fault signal between different sampling points, v is the propagation speed of the fault signal, Δt ij is the time difference between different sampling points, and the relative distance between the fault location and each sampling point is preliminarily estimated through the calculated distance difference;

[0103] S44: Combine the distance difference between different sampling points and use the triangulation method to calculate the approximate location of the fault;

[0104] S45: Compare the fault location calculated by S44 with the geographical location information of the distribution network to preliminarily determine the specific location range of the fault, providing a basis for subsequent precise positioning; by performing timing analysis on the fault signals at different sampling points and combining the arrival time difference method, this method can quickly and accurately preliminarily estimate the location of the fault, significantly improving the efficiency and accuracy of fault positioning.

[0105] S44 specifically includes:

[0106] S441: first determine the known position coordinates of multiple sampling points in the distribution network, and determine the relative distance difference between each pair of sampling points and the fault point according to the distance difference of the fault signal propagation calculated in S43. This step is determined according to the time difference of each sampling point receiving the fault signal;

[0107] S442: Based on the known positions and distance differences of the sampling points, multiple sets of position equations are established to represent the distance relationship between each sampling point and the fault point. These equations represent the relative distance difference between the fault point and multiple sampling points. The specific position of the fault point can be further determined by these equations.

[0108] S443: A set of equations is formed using data from multiple sampling points. By analyzing these equations, the approximate position of the fault point is solved using the least squares method. This step ensures that even if the number of sampling points is large or there are certain errors in the signal, accurate positioning can still be performed using multiple sets of data. By applying the triangulation positioning method combined with the least squares method, the specific position of the fault point can be calculated quickly and accurately, greatly improving the accuracy of fault location and ensuring the efficiency of subsequent maintenance work.

[0109] The steps to use triangulation to calculate the approximate location of the fault are as follows:

[0110] First determine the position coordinates of multiple sampling points (x i ,y i ), where i represents different sampling points, x i and i is the known coordinate of the sampling point in the distribution network; the distance difference Δd of the fault signal propagation is calculated according to the time difference in step S43 ij , represents the distance difference between two sampling points and the fault point;

[0111] Then, according to the known positions and distance differences of different sampling points, a triangulated positioning equation group is established; specifically, for each sampling point i and j, the position (x, y) of the fault point satisfies the following relationship:

[0112] Among them, (x, y) is the unknown coordinates of the fault point, (x i ,y i ) and (x j ,y j ) are the known coordinates of sampling points i and j, Δd ij is the distance difference calculated based on the propagation time difference;

[0113] Then, the distance difference Δd of multiple sets of sampling points is ij Form multiple equations and construct a linear system of equations, the expression is: The least square method is used to solve the equations, and the approximate position of the fault point (x, y) is finally obtained;

[0114] Finally, the solved fault location is compared with the geographical location information of the power grid to further verify the calculation results and ensure the rationality and accuracy of the fault point location.

[0115] S5 specifically includes:

[0116] S51: Collect historical fault data, which includes the location, time and related electrical characteristics of single-phase grounding faults that occurred in the past. These data will be used to analyze the similarity between the characteristics of the current fault and the historical faults.

[0117] S52: Analyze the length and impedance characteristics of each line in combination with the grid topology data; assume that the impedance of the grid line is Z, and the specific formula is: Z=R+jX, where R is the resistance of the line, X is the reactance of the line, and Z is the total impedance of the line; calculate the total impedance of each line by combining the length L of the line and its impedance Z, and determine the impact of each line on signal propagation; lines with lower impedance and close to the preliminary position are more likely to fail;

[0118] S53: Apply the multivariate regression analysis algorithm to correct the fault location. According to the impedance analysis results in step S52 and the historical fault data, a regression model is established. The fault location L is set to be related to multiple characteristic variables x1, x2, ..., x n There is a linear relationship, then the expression of the fault location L is: L = β0 + β1x1 + β2x2 + ... + β n x n , where x1,x2,…,x n are the electrical characteristics of the line (such as impedance, load, current, etc.), β0, β1, …, β n is the regression coefficient, and the regression model is trained through historical data;

[0119] S54: Based on the calculation results of the regression model, the initially estimated fault location is corrected to ensure that the final positioning result is consistent with the actual power grid topology. After the regression model is trained with historical data, it can provide a more accurate prediction value for the current fault location. The initially estimated location will be adjusted according to the fault location output by the model. The specific process is as follows: according to the impedance characteristics and historical fault modes of each line, the initially estimated location is corrected to make it more consistent with the physical characteristics of the actual power grid operation and match the mode of historical fault occurrence, so as to obtain a more accurate fault point location. Through the above steps, combined with historical fault data, the topological structure of the power grid and the calculation results of the regression model, the initially estimated fault location can be effectively corrected to improve the accuracy of fault location.

[0120] S6 specifically includes:

[0121] S61: Collect and integrate fault location data, including the specific location of the fault point, the corresponding line number, the fault detection time and related electrical parameters (such as current, voltage, etc.). These data will serve as basic information for generating a fault report;

[0122] S62: Compare the fault location with the power grid geographic information system (GIS) to confirm on which specific line the fault location is located, and based on the known distribution network topology, the location report will list the specific line number where the fault occurs;

[0123] S63: Record the fault occurrence time of the fault detection mark. If there are multiple time records, take the earliest time point as the fault occurrence time;

[0124] S64: Generate a fault location report, which includes:

[0125] The specific line name and number where the fault occurred;

[0126] The geographical location where the fault occurred, including longitude and latitude or the specific node in the distribution network;

[0127] The time when the fault occurred, accurate to the second level;

[0128] Relevant electrical characteristic data, such as current and voltage at the time of fault, for subsequent analysis.

[0129] S7 specifically includes:

[0130] S71: According to the fault location result, a maintenance instruction generation program is automatically triggered to generate a maintenance task instruction according to the fault location, line number and occurrence time recorded in the fault report. The maintenance task includes a detailed description of the fault location and the maintenance or repair operation to be performed;

[0131] S72: The generated maintenance instructions are sent to relevant maintenance personnel. The maintenance personnel information is automatically assigned through a pre-configured task management platform to ensure that the maintenance team closest to the fault location receives the maintenance task. The maintenance instructions should list in detail the specific line where the fault occurred; the exact geographical location of the fault; the expected fault type (such as a single-phase grounding fault); the maintenance tools and equipment that need to be carried; and the recommended maintenance time window.

[0132] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0133] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for multi-lateral collaborative diagnosis and location of single-phase grounding faults in distribution networks, characterized in that: The following steps are involved: S1: collect current and voltage signals in the distribution network in real time through the sensor network, and transmit the collected data to the data processing unit; S2: preprocessing the current and voltage signals transmitted to the data processing unit, wherein the preprocessing includes noise removal and outlier removal to generate standard data; S3: Based on standard data, analyze the current imbalance and voltage mutation point, and use the fault detection algorithm to identify whether a single-phase grounding fault occurs; S4: If a single-phase grounding fault is detected, the data at different sampling points will be analyzed in time series, and the propagation time difference of the fault signal will be calculated using the arrival time difference method to preliminarily estimate the location of the fault; S5: Based on the preliminary location estimation, combined with historical fault data and grid topology, the fault location is corrected using a regression analysis algorithm to locate the specific fault point; S6: Generate a fault location report, which includes the specific line, location and time of the fault; S7: According to the fault location result, trigger the processing measures and send maintenance instructions to relevant personnel.

2. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1 is characterized in that: The S1 specifically includes: S11: arranging current and voltage sensors at predetermined nodes of the distribution network to collect three-phase current and voltage signals in real time; S12: performing preliminary data packaging on the collected current and voltage signals, wherein the packaging includes adding a timestamp and a sampling point location label to each sampling signal; S13: Transmitting the packaged current and voltage data to a data processing unit via a communication network, wherein the communication network adopts optical fiber or 5G communication technology; S14: During the data transmission process, TCP / IP protocol is used for data packaging and transmission to ensure data integrity.

3. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1 is characterized in that: The S2 specifically includes: S21: After receiving the current and voltage signals transmitted to the data processing unit, the data is first filtered, and a frequency domain filtering algorithm based on fast Fourier transform is used to remove high-frequency noise and interference signals in the signal; S22: performing outlier detection on the filtered current and voltage signals, using a statistically based outlier elimination algorithm to identify and eliminate abnormal data points that exceed the normal range by calculating the mean and standard deviation of the signals; S23: performing data smoothing processing on the signal after removing noise and outliers, and using a sliding average algorithm to smooth the signal to reduce short-term fluctuations in the signal; S24: normalize the current and voltage signals processed by S23, and convert the numerical range of the signals into a standardized interval through a linear normalization algorithm, so as to ensure that data in different measurement units can be processed uniformly and finally generate standard data.

4. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1, characterized in that: The S3 specifically includes: S31: Based on the standardized current data, calculate the unbalance degree of the three-phase current, analyze the difference between the three-phase currents, and determine whether there is an obvious current unbalance phenomenon by comparing the amplitude and phase of the current of each phase; S32: Detect the mutation point of the voltage signal, identify the rapid drop or sudden rise of the voltage value by real-time monitoring the change trend of each phase voltage, and mark the time and amplitude of these changes for subsequent fault judgment; S33: combining the change of current unbalance degree with the time and amplitude of the voltage mutation point, and using a fault detection algorithm to comprehensively analyze the features to determine whether it is a single-phase grounding fault. The fault detection algorithm is based on a preset feature threshold and compares the current current and voltage features with feature data during normal operation to identify whether it meets the typical features of a single-phase grounding fault; S34: If the characteristic analysis result in S33 meets the characteristics of a single-phase grounding fault, the time point, location and related data are recorded and marked as a fault point.

5. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 4 is characterized in that: The S33 specifically includes: S331: synchronously collect the change of current unbalance and the change rate of voltage, and calculate a comprehensive fault characteristic parameter by assigning different weights to current and voltage characteristics and combining the changes of the two; S332: Setting a threshold for fault identification, when the calculated fault characteristic parameter exceeds the threshold, determining that the current state is a single-phase grounding fault; S333: Analyze the changes of current and voltage characteristics in combination with the time dimension, and observe the abnormal duration of the characteristics. When the characteristic values ​​of current and voltage remain abnormal for a preset period of time, it is confirmed that a single-phase grounding fault has occurred. S334: Based on the fault characteristic parameters and time analysis results, record the time, location and related characteristic information of the fault.

6. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1, characterized in that: The S4 specifically includes: S41: when a single-phase grounding fault is detected, data of sampling points at different locations are collected to obtain the time point at which the fault signal is received at each location; S42: Perform time series analysis on the data at different sampling points to determine the exact time t at which each sampling point receives the fault signal i , and by comparing the time point t i The time difference with other sampling points, records the time difference of receiving the signal at each sampling point; S43: Use the arrival time difference method to make a preliminary estimate of the fault location. Assuming that the propagation speed of the fault signal in the conductor is v, the distance difference Δd between the fault point and the sampling point is ij Calculated by the following formula: Δd ij =v×Δt ij , where Δd ij is the propagation distance difference of the fault signal between different sampling points, v is the propagation speed of the fault signal, Δt ij is the time difference between different sampling points, and the relative distance between the fault location and each sampling point is preliminarily estimated through the calculated distance difference; S44: Combine the distance difference between different sampling points and use the triangulation method to calculate the approximate location of the fault; S45: Compare the fault location calculated in S44 with the geographical location information of the distribution network to preliminarily determine the specific location range of the fault.

7. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 6, characterized in that: The S44 specifically includes: S441: first determine the known position coordinates of multiple sampling points in the distribution network, and determine the relative distance difference between each pair of sampling points and the fault point according to the distance difference of the fault signal propagation calculated in S43; S442: Based on the known positions and distance differences of the sampling points, multiple sets of position equations are established to represent the distance relationship between each sampling point and the fault point; S443: A set of equations is formed using data from multiple sampling points, and the approximate location of the fault point is solved by analyzing the equations using the least square method.

8. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1, characterized in that: The S5 specifically includes: S51: Collecting historical fault data, where the historical fault data includes the location, time and related electrical characteristics of single-phase grounding faults that occurred in the past; S52: Analyze the length and impedance characteristics of each line in combination with the grid topology data; S53: applying a multivariate regression analysis algorithm to correct the fault location, and establishing a regression model based on the impedance analysis results in step S52 and historical fault data; S54: Based on the calculation result of the regression model, the initially estimated fault location is corrected to ensure that the final positioning result is consistent with the actual power grid topology.

9. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1, characterized in that: The S6 specifically includes: S61: Collect and integrate fault location data, the data including the specific location of the fault point, the corresponding line number, the fault detection time and related electrical parameters; S62: Compare the fault location with the power grid geographic information system to confirm on which specific line the fault location is located, and based on the known distribution network topology, the location report will list the specific line number where the fault occurs; S63: Record the fault occurrence time of the fault detection mark. If there are multiple time records, take the earliest time point as the fault occurrence time; S64: Generate a fault location report.

10. The method for multilateral collaborative diagnosis and location of single-phase grounding fault in distribution network according to claim 1, characterized in that: The S7 specifically includes: S71: According to the fault location result, a maintenance instruction generation program is automatically triggered to generate a maintenance task instruction according to the fault location, line number and occurrence time recorded in the fault report. The maintenance task includes a detailed description of the fault location and the maintenance or repair operation to be performed; S72: Send the generated maintenance instruction to relevant maintenance personnel, and the maintenance personnel information is automatically assigned through a pre-configured task management platform to ensure that the maintenance team closest to the fault location receives the maintenance task.

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