Power grid fault intelligent diagnosis and analysis system

Abstract

The invention relates to the technical field of fault analysis, in particular to a power grid fault intelligent diagnosis and analysis system which comprises a fault signal detection module, a propagation path analysis module, a fault positioning calculation module, a fault type analysis module and a fault influence analysis module. According to the invention, by monitoring the voltage transient data of the plurality of nodes of the power grid in real time, the instantaneous offset and the time sequence difference of the voltage can be accurately calculated, so that the voltage mutation exceeding the preset threshold value can be quickly identified in the continuous time window, the early identification of the power grid fault is quicker, the risk of false alarm is reduced, and the accuracy of the early identification is improved. By analyzing the propagation path and speed of the sudden change quantity along the power grid, the fault positioning precision is improved, rapid and accurate fault source tracing is realized, and by careful analysis of the current waveform of a fault point and combination of real-time tripping current data, the fault type can be identified more accurately, the fault handling strategy can be optimized, and the fault handling efficiency is improved. And the power grid fault processing efficiency and safety are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault analysis, and in particular to an intelligent diagnosis and analysis system for power grid faults. Background Art

[0002] The field of fault analysis technology encompasses power system fault detection, grid operation status monitoring, fault location and analysis, and power quality assessment. The core content of this technical field includes fault detection methods based on grid topology, power equipment status parameter acquisition and analysis, adaptive setting of relay protection devices, intelligent identification and diagnosis of grid disturbance events, and grid stability assessment and prediction. Existing technologies employ methods such as fault identification based on synchronized phasor measurements, power waveform time-frequency analysis, fault feature extraction based on wavelet transforms, fault classification and prediction based on neural networks, and fault location using the current traveling wave method to monitor, analyze, and diagnose grid faults. Development directions in this technical field encompass multi-source information fusion diagnosis, high-dimensional grid data analysis, fault prediction model optimization based on artificial intelligence, and intelligent grid fault operation and maintenance management.

[0003] The intelligent power grid fault diagnosis and analysis system refers to a system used to detect the power grid's operating status, diagnose the type of power grid fault, locate the location of the fault, and perform fault mode analysis. The technical aspects covered by this system include power grid operating status assessment based on phasor measurement unit data, fault waveform feature extraction based on time-frequency transformation, fault type identification based on deep neural networks, fault location methods based on traveling wave propagation characteristics, a fault alarm mechanism based on adaptive threshold setting, and fault handling strategy optimization based on a decision tree algorithm. The system primarily acquires power system operating data by constructing a data acquisition module, extracts characteristic parameters using time-frequency analysis methods, employs an intelligent classification algorithm to determine the fault type, and calculates the fault point location based on the power grid topology, providing data support for power grid fault handling.

[0004] Traditional analysis systems rely on synchronized phasor measurements and set thresholds, limiting the dynamic adaptability and real-time response speed of fault detection. Lacking efficient real-time data analysis capabilities, traditional systems are unable to accurately determine the nature or location of faults in the early stages of a fault, resulting in delayed fault response and high misjudgment rates. Traditional systems are unable to quickly and accurately locate fault points in complex grid environments, impacting the timeliness and accuracy of fault repair. When grid conditions are complex or data volumes are large, traditional system status analysis is unable to process data in real time, impacting the timeliness and accuracy of fault diagnosis, extending fault recovery time, and increasing the risks and costs of grid operation. This can lead to misjudgments of grid operating status, increasing the risks and maintenance costs of grid operations. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent diagnosis and analysis system for power grid faults.

[0006] In order to achieve the above-mentioned object, the present invention adopts the following technical solution: an intelligent diagnosis and analysis system for power grid faults, the system comprising: The fault signal detection module obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage transient offset, screens points where the change exceeds the set voltage mutation threshold, extracts transient characteristic values, calculates the evolution trend of the mutation amount over time, and establishes a short-term voltage mutation sequence; The propagation path analysis module analyzes the main direction of the mutation along the line based on the short-term voltage mutation sequence, obtains the propagation rate of the voltage mutation point, calls the power grid topology information, screens the mutation propagation path, and establishes fault propagation path mapping information; The fault location calculation module calls the fault propagation path mapping information, obtains the node sequence on the main propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the voltage phase offset ratios between adjacent nodes, determines the fault source based on the maximum ratio, and establishes the fault tracing point location information; The fault type analysis module calls the fault tracing point location information, calls the tripping current data recorded by the relay protection device, compares the harmonic components in the current signal, screens the waveform pattern that matches the known fault characteristics, extracts the corresponding fault type parameters, and obtains the fault category judgment information.

[0007] The present invention has the following improvements: the short-time voltage mutation sequence includes the mutation amplitude, mutation time distribution, mutation gradient change rate and mutation propagation direction; the fault propagation path mapping information includes the propagation path node sequence, main propagation path direction, branch propagation distribution and key node timing relationship; the fault tracing point location information is specifically the coordinates of the fault starting node, fault propagation distance, adjacent node phase difference and propagation path weight coefficient; the fault category determination information includes the fault current mutation rate, harmonic amplitude distribution, fault type weight and relay protection triggering status.

[0008] The present invention is improved in that the fault signal detection module includes: The voltage transient calculation submodule obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage mean of each monitoring point within a continuous time window, calls the voltage mean difference between time windows, calculates the voltage transient offset of the monitoring point in the same time window, calls the set voltage transient threshold, limits the range of the voltage transient offset of the monitoring point, filters out the values within the threshold range, retains the data exceeding the threshold, and obtains the transient offset; The mutation point screening submodule establishes a time series for the voltage transient data of the monitoring point based on the transient offset, calls the set voltage mutation threshold, compares the voltage changes at adjacent time points in the time series, screens the monitoring points whose changes exceed the threshold, calculates the voltage change rate of the mutation point in the adjacent time period, and extracts the transient characteristic value of the mutation point based on the mean voltage change offset of the mutation point in each time period to obtain the key morphological features; The short-term sequence construction submodule establishes a time series for the voltage change rate of the mutation point based on the key morphological features, calculates the voltage change trend of the mutation point, calls the short-term time window, segments the trend data, calculates the trend change rate in each time period, and obtains the short-term voltage mutation sequence.

[0009] The present invention is improved in that the propagation path parsing module includes: The mutation quantity sorting submodule obtains the short-time voltage mutation sequence, arranges the mutation quantities of the monitoring points in chronological order, calculates the voltage mutation time difference between adjacent measuring points, and sorts the time differences according to their spatial positions to obtain a mutation quantity time series sequence; The propagation rate calculation submodule calculates the spatial spacing between adjacent measuring points based on the mutation time series, calls the voltage mutation time difference of the measuring points, compares the mutation time series relationship of adjacent measuring points, calculates the propagation rate of the mutation between the measuring points, analyzes the main propagation direction of the mutation along the line, and obtains the mutation propagation rate; The fault path mapping submodule calls the grid topology information based on the mutation propagation rate, screens the mutation propagation path, identifies key nodes of the substation bus and trunk line, calculates the propagation attenuation degree of the mutation in the transmission line branch, and establishes fault propagation path mapping information.

[0010] The present invention is improved in that the formula for calculating the propagation attenuation degree in the transmission line branch is: ; in, Representative Node The degree of attenuation of the mutation propagation, Representative Node Relative to adjacent nodes The voltage mutation amplitude, Representative Node To adjacent nodes The mutation propagation time, Representatives and Nodes The number of directly connected adjacent nodes, Representative Node The power flow value at represents the average power flow value of the node, Represents the number of nodes on a transmission line branch.

[0011] The present invention is improved in that the fault location calculation module includes: The propagation path node extraction submodule calls the fault propagation path mapping information, extracts the node sequence on the main propagation path, calculates the temporal variation trend of the node mutation amount, screens the path segments with continuously distributed mutation amounts, eliminates isolated and randomly fluctuating nodes, matches the site numbers of the monitoring points based on the power grid topology data, and obtains the key nodes of the propagation path; The voltage phase offset calculation submodule calls the key nodes of the propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the phase change amplitude of adjacent nodes, calculates the voltage phase offset ratio between the nodes, screens the phase offset mutation area, and obtains the phase offset characteristic value; The fault source determination submodule calls the phase offset characteristic value, selects the node with the largest offset ratio based on the phase offset ratio of adjacent nodes, matches the power grid topology, determines the source of fault propagation, and establishes the location information of the fault tracing point.

[0012] The present invention is improved in that the fault type analysis module includes: The current waveform acquisition submodule calls the fault tracing point location information, obtains the current waveform data of the fault point, calculates the current amplitude mutation rate in a short period of time, screens the waveform segments whose mutation rate exceeds the set current mutation threshold, extracts the maximum amplitude variation range of the mutation segment, and obtains the current mutation amount parameter; The harmonic characteristic calculation submodule calls the current mutation parameter, obtains the tripping current data recorded by the relay protection device, calculates the harmonic amplitude distribution of the current signal, compares the energy proportions of multiple harmonic components, screens the waveform pattern that matches the known fault characteristics, and obtains the fault harmonic characteristic value; The fault type determination submodule calls the fault harmonic characteristic value, matches the current signal characteristics of the known fault mode, calculates the matching degree of the known mode, screens the fault type with the highest matching degree, extracts the corresponding fault classification parameters, and establishes fault category determination information.

[0013] The present invention is improved in that the formula for calculating the matching degree of the known pattern is: ; in, Represents the matching degree of the pattern, Representative The measured fault characteristic value of each harmonic, Representative The harmonic characteristic value corresponding to the known fault mode, Representative The weight of the harmonic features, Represents the total harmonics.

[0014] The present invention is improved in that the system further comprises: The fault impact analysis module calls the fault category determination information and the fault tracing point location information, calculates the power fluctuation rate of adjacent branches, selects branches whose power changes exceed the short-term power imbalance threshold, determines the fault propagation impact range, and obtains the fault impact range information; The fault impact range information includes the affected branch number, power fluctuation range, load stability parameter and adjacent node current coupling coefficient.

[0015] The present invention is improved in that the fault impact analysis module includes: The power fluctuation calculation submodule calls the fault category determination information and the fault tracing point location information to obtain the power data of the branches around the fault point, calculates the power change rate in adjacent time periods, and uses the power fluctuation rate of the branch to compare the power fluctuation trends between adjacent branches to obtain the branch power fluctuation rate; The branch screening submodule calls the short-term power imbalance threshold based on the branch power fluctuation rate, compares the relationship between the branch power fluctuation rate and the threshold, screens the branches whose power changes exceed the threshold, calculates the power change duration of the screened branches, and obtains the power abnormal branches; The impact range determination submodule calculates the topological distribution of the fault point and the abnormal branch based on the power abnormal branch, determines the spatial propagation of the power fluctuation, analyzes the branch coverage range affected by the power fluctuation, calculates the grid load offset in the affected area, and obtains the fault impact range information.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by real-time monitoring of voltage transient data of multiple nodes in the power grid, the instantaneous offset and time series difference of the voltage can be accurately calculated, so that voltage mutations exceeding a predetermined threshold can be quickly identified in a continuous time window, thereby optimizing the speed and accuracy of fault diagnosis, making early identification of power grid faults faster, and reducing the risk of false alarms. By analyzing the path and rate of propagation of mutations along the power grid, the accuracy of fault location is improved. By comparing the voltage phase change rate, the location of the fault source can be more accurately determined, and fast and accurate fault source tracing can be achieved. Through detailed analysis of the current waveform at the fault point, combined with real-time tripping current data, the fault type can be more accurately identified, the fault handling strategy can be optimized, the efficiency and safety of power grid fault handling are improved, the intelligence level of power grid operation and maintenance is enhanced, and the guarantee of power grid stability is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system flow chart of the present invention; Figure 2 Schematic diagram of the system framework of the present invention; Figure 3 This is a flow chart of the fault signal detection module of the present invention; Figure 4 This is a flow chart of the propagation path parsing module of the present invention; Figure 5 This is a flow chart of the fault location calculation module of the present invention; Figure 6 This is a flow chart of the fault type analysis module of the present invention; Figure 7 This is a flow chart of the fault impact analysis module of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operate in a specific direction, and therefore should not be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0020] See also Figure 1 The present invention provides a technical solution: an intelligent diagnosis and analysis system for power grid faults, the system comprising: The fault signal detection module obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage transient offset, performs differential operations on the voltage mean within a continuous time window, establishes a time series, screens points where the change exceeds the set voltage mutation threshold, extracts transient characteristic values, calculates the evolution trend of the mutation amount over time, and establishes a short-term voltage mutation sequence; The propagation path analysis module arranges the mutations of monitoring points in chronological order based on the short-term voltage mutation sequence, calculates the voltage mutation time difference between adjacent measuring points, analyzes the main direction of mutation propagation along the line, obtains the propagation rate of the voltage mutation point, calls the grid topology information, screens the mutation propagation path, identifies the key propagation nodes on the substation bus and trunk line, analyzes the attenuation degree of the mutation in the transmission line branch, and establishes fault propagation path mapping information; The fault location calculation module uses fault propagation path mapping information to obtain the node sequence on the main propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the voltage phase offset ratios between adjacent nodes, determines the fault source based on the maximum ratio, and establishes the location information of the fault tracing point; The fault type analysis module uses the fault tracing point location information to obtain the current waveform data of the fault point, calculates the current amplitude mutation rate in a short period of time, uses the tripping current data recorded by the relay protection device, compares the harmonic components in the current signal, screens the waveform pattern that matches the known fault characteristics, extracts the corresponding fault type parameters, and obtains the fault category determination information; The fault impact analysis module calls the fault category determination information and the fault tracing point location information, calculates the power fluctuation rate of adjacent branches, screens the branches whose power changes exceed the short-term power imbalance threshold, determines the fault propagation impact range, and obtains the fault impact range information.

[0021] The short-time voltage mutation sequence includes the mutation amplitude, mutation time distribution, mutation gradient change rate and mutation propagation direction. The fault propagation path mapping information includes the propagation path node sequence, main propagation path direction, branch propagation distribution and key node timing relationship. The fault tracing point location information specifically includes the coordinates of the fault starting node, fault propagation distance, adjacent node phase difference and propagation path weight coefficient. The fault category determination information includes the fault current mutation rate, harmonic amplitude distribution, fault type weight and relay protection triggering status. The fault impact range information includes the affected branch number, power fluctuation range, load stability parameter and adjacent node current coupling coefficient.

[0022] See also Figure 2 ,The fault signal detection module includes a voltage transient calculation submodule, a mutation point screening submodule, and a short time sequence construction submodule; The voltage transient calculation submodule obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage mean of each monitoring point within a continuous time window, calls the voltage mean difference between time windows, calculates the voltage transient offset of the monitoring point in the same time window, calls the set voltage transient threshold, limits the range of the voltage transient offset of the monitoring point, filters out the values within the threshold range, retains the data exceeding the threshold, and obtains the transient offset; The voltage transient calculation submodule is based on the voltage transient data collected by multiple monitoring points of the power grid. It counts the voltage of each monitoring point in a continuous time window, extracts the voltage value in each time window, calculates the voltage mean in the time window, and performs differential operation on the voltage mean of adjacent time windows during the window sliding process to obtain the voltage change between time windows. For each monitoring point, within the same time window, the voltage transient offset of the monitoring point is obtained. Specifically, for each monitoring point, within the time window range, the local maximum and local minimum values of the voltage transient data are selected, the difference is calculated, and the difference is normalized. The normalization uses the set maximum voltage fluctuation range, which is recorded as and minimum voltage fluctuation range , the calculation formula is as follows: ; in, The voltage transient range is set. This value is determined based on the maximum voltage fluctuation range obtained from the long-term monitoring data of the power grid system. For example, in an industrial power grid, the voltage fluctuation range in the past 30 days was between 190V and 250V, so the voltage transient range is set. To ensure that the calculated transient offset can cover the historical fluctuation range of the power grid, if the local maximum voltage value of a monitoring point is 220V and the local minimum voltage value is 200V within a specific time window, the transient offset is calculated as: ; Recall the set voltage transient threshold , to determine whether the transient offset exceeds the threshold range. The threshold is set based on the stable range of voltage changes during normal operation of the power grid. For example, the steady-state voltage fluctuation of the industrial power grid is generally within the range of ±5V, so the threshold is set That is, if the offset exceeds 0.167, it is considered that the voltage has transiently changed and the data needs to be retained. Otherwise, it is discarded. If it exceeds the threshold, the data is retained as the transient offset. For example, if the calculated value 0.33 exceeds the threshold 0.167, the data is retained and the transient offset is finally obtained.

[0023] The mutation point screening submodule creates a time series for the voltage transient data of the monitoring point based on the transient offset, calls the set voltage mutation threshold, compares the voltage changes at adjacent time points in the time series, screens the monitoring points whose changes exceed the threshold, calculates the voltage change rate of the mutation point in the adjacent time period, and extracts the transient characteristic value of the mutation point based on the mean voltage change offset of the mutation point in each time period to obtain the key morphological features; The mutation point screening submodule constructs the voltage transient time series of the monitoring point based on the transient offset. For adjacent time points in the time series, the voltage change is calculated. The specific calculation method is: take the current time point and the previous time point Voltage value and , calculate the voltage change as follows: ; Call the set voltage mutation threshold , to determine the voltage change. The threshold is set based on the voltage change rate of the power grid within the normal fluctuation range. Generally, a voltage change rate of less than 0.5V / s is considered normal, so the threshold is set to In the time interval of 1s, if the voltage change between adjacent time points is greater than 0.5V, it is judged as a mutation point. , then the monitoring point is screened as a mutation point, the timestamp of the mutation point is recorded, and then the voltage change rate of the mutation point in the adjacent time period is calculated. The calculation method is: ; in, is the interval between two time points. If the interval is 5 seconds, then for a certain monitoring point, The voltage value at is 210V. If the voltage at the point is 200V, the rate of change is calculated as ; Then, the mean voltage change deviation of the mutation point in each time period is calculated, that is, the mean change rate of all mutation points is calculated within the set time window, and the weighted average method is used for calculation: ; in, The weight is set according to the influence of the mutation amplitude on the voltage stability. Generally speaking, the higher the rate of change, the greater the impact on the power grid. Therefore, the weight is set Proportional to the mutation rate, e.g. , if the change rate of a monitoring point in three time windows is 2V / s, 3V / s and 5V / s respectively, and the corresponding weights are 0.2, 0.3 and 0.5 respectively, then the weighted mean is calculated as: ; Finally, the transient characteristic values of the mutation points are extracted to obtain the key morphological features.

[0024] The short-term sequence construction submodule establishes a time series for the voltage change rate of the mutation point based on key morphological features, calculates the voltage change trend of the mutation point, calls the short-term time window, segments the trend data, calculates the trend change rate in each time period, and obtains the short-term voltage mutation sequence.

[0025] The short-time series construction submodule constructs the voltage change rate time series of the mutation point based on the key morphological features, extracts the trend characteristics of the time series, segments the trend data within the short time window, and calculates the trend change rate of each time period. The specific calculation method is: select the change rate data sequence within the time window , the calculated change trend is: ; in, The short-term time window is set according to the typical duration of voltage mutation. For example, the voltage mutation of a certain power grid is usually restored within 5 seconds, so the short-term time window is set according to the typical duration of voltage mutation. To ensure that the trend change of short-term mutations can be captured, if the short-term time window is set to 10 seconds, then for a certain mutation point, the change rate at the starting point of the time window is 1V / s, and the change rate at the end point is 4V / s, then the change trend is calculated as: ; Call the set short-term trend change threshold The threshold value is set based on the normal trend change rate of the grid sudden recovery process. Generally, the short-term voltage trend change rate is relatively stable below 0.2V / s2, so it is set , the time period where the trend change rate exceeds the threshold is screened, and finally the short-term voltage mutation sequence is obtained.

[0026] See also Figure 3 ,The propagation path parsing module includes a mutation amount sorting submodule, a propagation rate calculation submodule, and a fault path mapping submodule; The mutation quantity sorting submodule obtains the short-time voltage mutation sequence, arranges the mutation quantities of the monitoring points in chronological order, calculates the voltage mutation time difference between adjacent measuring points, and sorts the time differences according to their spatial positions to obtain the mutation quantity time series sequence; The mutation sorting submodule obtains the short-time voltage mutation sequence, arranges the mutations of the monitoring points in chronological order, reads the occurrence time of the mutation for each monitoring point, and arranges them in ascending order of time to construct a time series. For adjacent monitoring points, the time difference of the mutation occurrence is calculated. The time difference calculation method is: suppose the current monitoring point The mutation time is , adjacent monitoring points The mutation time is , then the voltage mutation time difference of adjacent monitoring points is calculated as: ; For example, if the time for sudden changes at monitoring points A, B, and C on a certain line is 10.2s, 10.5s, and 11.0s respectively, calculate the time difference of sudden changes between adjacent monitoring points: , ,Then, the calculated time difference is sorted according to the spatial position of the ,monitoring point.,First, the monitoring points are arranged in physical space order to obtain the ,spatial distribution order of the mutation amount.,For example, if monitoring points A, B, and C are distributed at 10km, 15km, and 20km, ,then the mutation amount time series sequence after sorting by time difference is A (10.2s), B (10.5s), and C (11.0s), ,and finally the mutation amount time series sequence is obtained.

[0027] The propagation rate calculation submodule calculates the spatial distance between adjacent measuring points based on the mutation time series, calls the voltage mutation time difference of the measuring points, compares the mutation time series relationship of adjacent measuring points, calculates the propagation rate of the mutation between the measuring points, analyzes the main propagation direction of the mutation along the line, and obtains the mutation propagation rate; The propagation rate calculation submodule calculates the spatial distance between adjacent measuring points based on the mutation time series, calls the voltage mutation time difference of the measuring points, compares the mutation time series relationship of adjacent measuring points, calculates the propagation rate of the mutation between the measuring points, and sets the adjacent measuring points to be and The physical distance between , the propagation rate is calculated as follows: ; in, Representative monitoring points To the monitoring point The spatial spacing is set according to the actual layout of the power grid monitoring points. For example, in a high-voltage transmission line, the distance between adjacent monitoring points is usually between 3km and 10km. Here, the distances between the three monitoring points A, B, and C are set to be 5km and 5km respectively. Then, the propagation rate is calculated. If , , the propagation rate is calculated as: ; Similarly, if , ,but ; Compare the time series relationship of the mutations at adjacent measuring points, analyze the main propagation direction of the mutations along the line, and determine whether the propagation rate shows a decreasing trend. If the mutation propagation rate decreases with the position of the measuring point, it indicates that the mutation may be attenuated due to the grid impedance or load distribution. For example, in this example, This indicates that the propagation speed has slowed down, and the mutation propagation rate is finally obtained.

[0028] The fault path mapping submodule uses the grid topology information based on the mutation propagation rate, screens the mutation propagation path, identifies key nodes on the substation bus and trunk line, calculates the propagation attenuation of the mutation in the transmission line branch, and establishes fault propagation path mapping information; The formula for calculating the propagation attenuation in a transmission line branch is: ; in, Representative Node The degree of attenuation of the mutation propagation, Representative Node Relative to adjacent nodes The voltage mutation amplitude, Representative Node To adjacent nodes The mutation propagation time, Representatives and Nodes The number of directly connected adjacent nodes, Representative Node The power flow value at represents the average power flow value of the node, Represents the number of nodes on a transmission line branch.

[0029] The fault path mapping submodule uses the grid topology information based on the mutation propagation rate, screens the mutation propagation path, analyzes the mutation propagation path along the transmission line, identifies key nodes on the substation bus and trunk line, reads the grid topology information, obtains the connection relationship between each node, and calculates the propagation attenuation degree of the mutation in the transmission line branch. The calculation method is as follows: ; in, Representative Node The mutation propagation attenuation degree is used to measure the attenuation trend of the mutation between power grid nodes. If the value is high, it means that the mutation attenuation near the node is strong. Representative Node Relative to adjacent nodes The voltage mutation amplitude is obtained by calculating the voltage change before and after the mutation at adjacent measuring points. For example, if the voltage before and after the mutation at measuring points A and B are 220V and 210V respectively, then , Representative Node To adjacent nodes The mutation propagation time, Representatives and Nodes The number of directly connected adjacent nodes, Representative Node The power flow value at represents the average power flow value of the node, Represents the number of nodes on the transmission line branch, where the node power flow value Based on SCADA monitoring data, for example, if the power flow of a transmission line is between 100MW and 150MW, and the power flows at monitoring points A, B, and C are 120MW, 130MW, and 110MW respectively, then the average power flow value is calculated as: ; Calculate the power fluctuation degree of the transmission line branch: ; If node i is directly connected to 3 adjacent nodes, and the measured 8V, 12V, 15V respectively, corresponding to the propagation time If the time intervals are 0.4s, 0.5s, and 0.6s respectively, the degree of attenuation of the mutation propagation is calculated as follows: ; Establish fault propagation path mapping information.

[0030] See also Figure 4 ,The fault location calculation module includes a propagation path node extraction submodule, a voltage phase offset calculation submodule, and a fault source determination submodule; The propagation path node extraction submodule calls the fault propagation path mapping information, extracts the node sequence on the main propagation path, calculates the temporal variation trend of the node mutation amount, selects the path segments with continuously distributed mutation amounts, eliminates isolated and randomly fluctuating nodes, and matches the site numbers of the monitoring points based on the power grid topology data to obtain the key nodes of the propagation path; The propagation path node extraction submodule calls the fault propagation path mapping information, extracts the node sequence on the main propagation path, reads all the node information on the fault propagation path, and screens the continuously distributed mutation nodes according to the mutation propagation rate and propagation direction, calculates the temporal change trend of the mutation of each node, and for each node , record the time when the mutation occurs , adjacent nodes The time of mutation occurrence , calculate the time difference of the mutation amount of adjacent nodes: ; Path segments with continuous distribution of mutations are screened, and isolated and randomly fluctuating nodes are eliminated. Nodes that experience mutations alone and have no adjacent nodes that conform to the propagation trend are determined to be isolated points, and the node data is deleted. For example, if on a certain transmission line, nodes A, B, C, D, and E experience mutations at 10.2s, 10.5s, 11.0s, 12.0s, and 15.0s, respectively, and the time difference between A, B, and C is less than 1s, while the time difference between D and C exceeds 1s, and the time difference between E and D exceeds 3s, then A, B, and C are considered to constitute a continuous propagation path, while D and E are randomly fluctuating nodes and should be eliminated. Based on the power grid topology data, the site numbers of the monitoring points are matched, the corresponding relationship between the monitoring points and substations or lines is found, and the key nodes of the propagation path are obtained.

[0031] The voltage phase offset calculation submodule calls the key nodes of the propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the phase change amplitude of adjacent nodes, calculates the voltage phase offset ratio between nodes, screens the phase offset mutation area, and obtains the phase offset characteristic value; The voltage phase offset calculation submodule calls the key nodes of the propagation path and calculates the voltage phase change rate of the node in the propagation path. For each key node, the voltage phase data before and after the mutation occurs are extracted. Set the node Before the mutation occurs, the phase is , the phase after the mutation occurs is , calculate the phase change: ; Compare the phase change amplitudes of adjacent nodes and calculate the voltage phase shift ratio between nodes. and The phase changes are and , the phase shift ratio is calculated as follows: ; Screen the phase shift mutation area and set the phase shift ratio threshold The threshold is set according to the steady-state phase fluctuation range of the power grid. For example, in steady-state operation, the phase offset ratio of adjacent nodes is usually less than 1.2, so the threshold is set If the calculated ratio of an adjacent node is greater than 1.2, the area is determined to be a phase mutation area. If the phase changes of nodes A, B, C, and D are 2.5°, 2.7°, 3.0°, and 6.0°, respectively, the phase offset ratio is calculated: ; ; ; in, Far less than the set threshold , so there is a phase mutation at node D, and finally the phase offset characteristic value is obtained.

[0032] The fault source determination submodule calls the phase offset characteristic value, selects the node with the largest offset ratio based on the phase offset ratio of adjacent nodes, matches the power grid topology, determines the source of fault propagation, and establishes the location information of the fault tracing point.

[0033] The fault source determination submodule calls the phase offset characteristic value, selects the node with the largest offset ratio according to the phase offset ratio of adjacent nodes, obtains all nodes on the mutation propagation path, calculates the phase offset ratio of each node, sorts the ratio values of all nodes, and sets the node The phase shift ratio is , then find , match the grid topology, find the line or substation where the node with the maximum offset ratio is located, and determine the source of fault propagation. This determination is based on the direction of mutation propagation and the mutation trend of phase offset. For example, if the phase offset ratio of a node is significantly higher than that of the adjacent nodes and is located on the load side of the grid or at the end of the branch, it may be the fault point. For example, if the phase offset ratios of nodes A, B, C, D, and E are 0.93, 0.9, 0.5, 2.5, and 1.8 respectively, the maximum ratio appears at node D, that is, , then match the grid topology, find the line information connected to the D node, determine that the node may be the fault propagation source, and finally establish the fault tracing point location information.

[0034] See also Figure 5 ,The fault type analysis module includes a current waveform acquisition submodule, a harmonic feature calculation submodule, and a fault type determination submodule; The current waveform acquisition submodule calls the fault tracing point location information to obtain the current waveform data of the fault point, calculates the current amplitude mutation rate in a short period of time, selects waveform segments with mutation rates exceeding the set current mutation threshold, extracts the maximum amplitude variation range of the mutation segment, and obtains the current mutation amount parameter; The current waveform acquisition submodule calls the fault tracing point location information, obtains the current waveform data of the fault point, reads the short-term current data stream recorded by the monitoring equipment, extracts the current waveform sequence during the fault period, calculates the current amplitude mutation rate in a short period of time, and sets the calculation time window. And perform differential processing on the current amplitude within this window, set the time point The current value at , time point The current value at , the current mutation rate is calculated as follows: ; Set the current mutation threshold To filter waveform segments whose mutation rate exceeds the set threshold. The threshold is set according to the normal load fluctuation range of the power grid. For example, under steady-state conditions, the current mutation rate usually does not exceed 100A / ms. If a fault may cause the mutation rate to far exceed this value, then the threshold is set. In order to screen the mutation area, if a waveform data suddenly increases from 500A to 900A within 1ms, the mutation rate is calculated as follows: ; because If the current exceeds the set threshold of 200A / ms, the segment is judged as a sudden change waveform segment, the maximum amplitude change range of the sudden change segment is extracted, and the maximum current change is calculated. If the maximum current during a fault is 1200A and the minimum current is 400A, the maximum amplitude variation range is calculated as follows: ; Get the current mutation parameter.

[0035] The harmonic characteristic calculation submodule uses the current mutation parameter to obtain the tripping current data recorded by the relay protection device, calculates the harmonic amplitude distribution of the current signal, compares the energy proportions of various harmonic components, screens the waveform pattern that matches the known fault characteristics, and obtains the fault harmonic characteristic value; The harmonic characteristic calculation submodule calls the current mutation parameter, obtains the tripping current data recorded by the relay protection device, reads the current signal before and after the fault is triggered, compares the amplitude changes of the harmonic components of different frequencies, calculates the harmonic amplitude distribution of the current signal, and calculates the harmonic amplitude distribution of the signal sequence. , extract its fundamental component And each harmonic component , calculate its energy proportion as follows: ; in, Representative The energy proportion of subharmonics, Representative The amplitude of the subharmonic, setting the threshold of harmonic energy ratio To filter the waveform pattern that matches the known fault characteristics, the threshold is obtained based on historical fault data statistics. For example, in the case of short circuit fault, the proportion of the third harmonic usually exceeds 15%, so the threshold is set. To screen possible matching fault features, if the 3rd harmonic energy ratio of a current signal is calculated as: ; because If the calculated 5th harmonic ratio reaches 20%, it meets a certain known harmonic fault characteristic, and finally the fault harmonic characteristic value is obtained.

[0036] The fault type determination submodule calls the fault harmonic characteristic value, matches the current signal characteristics of the known fault mode, calculates the matching degree of the known mode, selects the fault type with the highest matching degree, extracts the corresponding fault classification parameters, and establishes the fault category determination information; The formula for calculating the matching degree of a known pattern is: ; in, Represents the matching degree of the pattern, Representative The measured fault characteristic value of each harmonic, Representative The harmonic characteristic value corresponding to the known fault mode, Representative The weight of the harmonic features, represents the total harmonic number; The fault type determination submodule calls the fault harmonic characteristic value, matches the current signal characteristics of the known fault mode, calculates the matching degree of the known mode, and sets the measured harmonic characteristic value to be , the characteristic value of the known failure mode is , the corresponding weight is , the matching degree is calculated as follows: ; in, Represents the matching degree and sets the matching degree threshold To filter the fault type with the highest matching degree, the threshold is set according to the fault judgment accuracy. For example, historical data statistics show that when When the fault type matching rate is high, set To screen possible fault types, if the measured value of the third harmonic of a current signal is 50A, the third harmonic characteristic value corresponding to the known fault mode is 45A, and the corresponding weight is set to 2, the matching degree is calculated as follows: ; because If the signal is greater than the set threshold of 0.85, the signal matches the known fault mode, and the fault type is screened out, the corresponding fault classification parameters are extracted, and finally the fault category judgment information is established.

[0037] See also Figure 6,The fault impact analysis module includes a power fluctuation calculation submodule, a branch screening submodule, and an impact range determination submodule; The power fluctuation calculation submodule uses the fault category determination information and the fault tracing point location information to obtain the power data of the branches around the fault point, calculate the power change rate in adjacent time periods, and use the power fluctuation rate of the branch to compare the power fluctuation trends between adjacent branches to obtain the branch power fluctuation rate; The power fluctuation calculation submodule calls the fault category determination information and the fault tracing point location information to obtain the power data of the branches around the fault point and read the active power of the fault point and its adjacent branches. and reactive power Data, in the set time window Calculate the power change rate of adjacent time periods, set the time point and The power values at and , the power change rate is calculated as follows: ; Set the power change rate calculation interval If a branch road is The power value is 50MW. The power value at this time is 55MW, and the power change rate is calculated as follows: ; Using the power fluctuation rate of the branch, compare the power fluctuation trend between adjacent branches and calculate the power fluctuation trend of adjacent branches. and The power change rate difference: ; If the adjacent branch The power change rates are 5MW / s and 3MW / s respectively, and the difference in power change rates is calculated as follows: ; Get the branch power fluctuation rate.

[0038] The branch screening submodule uses the short-term power imbalance threshold based on the branch power fluctuation rate, compares the relationship between the branch power fluctuation rate and the threshold, screens branches with power changes exceeding the threshold, calculates the power change duration of the screened branches, and obtains branches with abnormal power. The branch screening submodule calls the short-term power imbalance threshold based on the branch power fluctuation rate, compares the relationship between the branch power fluctuation rate and the threshold, and sets the short-term power imbalance threshold. The threshold is set according to the steady-state load fluctuation of the power grid. For example, within the normal load fluctuation range, the power change rate difference between adjacent branches usually does not exceed 1.5MW / s, so the threshold is set , filter the branches that exceed the threshold, if the power change rate difference between a branch and the adjacent branches is calculated If the threshold exceeds 1.5MW / s, the branch is judged as an abnormal power branch. The power change duration of the screening branch is calculated and the power change rate in the time interval is extracted. Internal Satisfaction Duration If the branch power change rate exceeds 1.5MW / s for 10s, the power change duration of the branch is recorded. ,Finally, the power abnormal branch is obtained.

[0039] The impact range determination submodule calculates the topological distribution of the fault point and the abnormal branch based on the power abnormal branch, determines the spatial propagation of the power fluctuation, analyzes the branch coverage affected by the power fluctuation, calculates the grid load offset in the affected area, and obtains the fault impact range information.

[0040] The impact range determination submodule is based on the abnormal power branch, calculates the topological distribution of the fault point and the abnormal branch, extracts the node relationship between the fault point and its adjacent branches in the power grid topology, determines the spatial propagation of power fluctuations, and calculates the correlation degree of power fluctuations between branches. If the power change rate between adjacent branches meets Then determine whether there is a power fluctuation propagation path between branches, construct the branch coverage affected by power fluctuation, screen the topological distribution of the affected branches, calculate the grid load offset of the affected area, and set the total system load The power before the fault is , the power after the fault is , the load offset is calculated as follows: ; If the total system load before the fault was 500MW and dropped to 450MW after the fault, the load offset is calculated as follows: ; Get information about the fault's impact range.

[0041] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. The intelligent diagnosis and analysis system for power grid faults is characterized by: The system comprises: The fault signal detection module obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage transient offset, screens points where the change exceeds the set voltage mutation threshold, extracts transient characteristic values, calculates the evolution trend of the mutation amount over time, and establishes a short-term voltage mutation sequence; The propagation path analysis module analyzes the main direction of the mutation along the line based on the short-term voltage mutation sequence, obtains the propagation rate of the voltage mutation point, calls the power grid topology information, screens the mutation propagation path, and establishes fault propagation path mapping information; The fault location calculation module calls the fault propagation path mapping information, obtains the node sequence on the main propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the voltage phase offset ratios between adjacent nodes, determines the fault source based on the maximum ratio, and establishes the fault tracing point location information; The fault type analysis module calls the fault tracing point location information, calls the tripping current data recorded by the relay protection device, compares the harmonic components in the current signal, screens the waveform pattern that matches the known fault characteristics, extracts the corresponding fault type parameters, and obtains the fault category judgment information.

2. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The short-time voltage mutation sequence includes the mutation amplitude, mutation time distribution, mutation gradient change rate and mutation propagation direction; the fault propagation path mapping information includes the propagation path node sequence, main propagation path direction, branch propagation distribution and key node timing relationship; the fault tracing point location information is specifically the coordinates of the fault starting node, fault propagation distance, adjacent node phase difference and propagation path weight coefficient; the fault category determination information includes the fault current mutation rate, harmonic amplitude distribution, fault type weight and relay protection triggering status.

3. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The fault signal detection module includes: The voltage transient calculation submodule obtains voltage transient data from multiple monitoring points in the power grid, calculates the voltage mean of each monitoring point within a continuous time window, calls the voltage mean difference between time windows, calculates the voltage transient offset of the monitoring point in the same time window, calls the set voltage transient threshold, limits the range of the voltage transient offset of the monitoring point, filters out the values within the threshold range, retains the data exceeding the threshold, and obtains the transient offset; The mutation point screening submodule establishes a time series for the voltage transient data of the monitoring point based on the transient offset, calls the set voltage mutation threshold, compares the voltage changes at adjacent time points in the time series, screens the monitoring points whose changes exceed the threshold, calculates the voltage change rate of the mutation point in the adjacent time period, and extracts the transient characteristic value of the mutation point based on the mean voltage change offset of the mutation point in each time period to obtain the key morphological features; The short-term sequence construction submodule establishes a time series for the voltage change rate of the mutation point based on the key morphological features, calculates the voltage change trend of the mutation point, calls the short-term time window, segments the trend data, calculates the trend change rate in each time period, and obtains the short-term voltage mutation sequence.

4. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The propagation path parsing module includes: The mutation quantity sorting submodule obtains the short-time voltage mutation sequence, arranges the mutation quantities of the monitoring points in chronological order, calculates the voltage mutation time difference between adjacent measuring points, and sorts the time differences according to their spatial positions to obtain a mutation quantity time series sequence; The propagation rate calculation submodule calculates the spatial spacing between adjacent measuring points based on the mutation time series, calls the voltage mutation time difference of the measuring points, compares the mutation time series relationship of adjacent measuring points, calculates the propagation rate of the mutation between the measuring points, analyzes the main propagation direction of the mutation along the line, and obtains the mutation propagation rate; The fault path mapping submodule calls the grid topology information based on the mutation propagation rate, screens the mutation propagation path, identifies key nodes of the substation bus and trunk line, calculates the propagation attenuation degree of the mutation in the transmission line branch, and establishes fault propagation path mapping information.

5. The intelligent diagnosis and analysis system for power grid faults according to claim 4, characterized in that: The formula for calculating the propagation attenuation degree in the transmission line branch is: ； in, Representative Node The degree of mutation propagation attenuation, Representative Node Relative to adjacent nodes The voltage mutation amplitude, Representative Node To adjacent nodes The mutation propagation time, Representatives and Nodes The number of directly connected adjacent nodes, Representative Node The power flow value at represents the average power flow value of the node, Represents the number of nodes on a transmission line branch.

6. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The fault location calculation module includes: The propagation path node extraction submodule calls the fault propagation path mapping information, extracts the node sequence on the main propagation path, calculates the temporal variation trend of the node mutation amount, screens the path segments with continuously distributed mutation amounts, eliminates isolated and randomly fluctuating nodes, matches the site numbers of the monitoring points based on the power grid topology data, and obtains the key nodes of the propagation path; The voltage phase offset calculation submodule calls the key nodes of the propagation path, calculates the voltage phase change rate of the node in the propagation path, compares the phase change amplitude of adjacent nodes, calculates the voltage phase offset ratio between the nodes, screens the phase offset mutation area, and obtains the phase offset characteristic value; The fault source determination submodule calls the phase offset characteristic value, selects the node with the largest offset ratio based on the phase offset ratio of adjacent nodes, matches the power grid topology, determines the source of fault propagation, and establishes the location information of the fault tracing point.

7. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The fault type analysis module includes: The current waveform acquisition submodule calls the fault tracing point location information, obtains the current waveform data of the fault point, calculates the current amplitude mutation rate in a short period of time, screens the waveform segments whose mutation rate exceeds the set current mutation threshold, extracts the maximum amplitude variation range of the mutation segment, and obtains the current mutation amount parameter; The harmonic characteristic calculation submodule calls the current mutation parameter, obtains the tripping current data recorded by the relay protection device, calculates the harmonic amplitude distribution of the current signal, compares the energy proportions of multiple harmonic components, screens the waveform pattern that matches the known fault characteristics, and obtains the fault harmonic characteristic value; The fault type determination submodule calls the fault harmonic characteristic value, matches the current signal characteristics of the known fault mode, calculates the matching degree of the known mode, screens the fault type with the highest matching degree, extracts the corresponding fault classification parameters, and establishes fault category determination information.

8. The intelligent diagnosis and analysis system for power grid faults according to claim 7, characterized in that: The formula for calculating the matching degree of a known pattern is: ； in, Represents the matching degree of the pattern, Representative The measured fault characteristic value of each harmonic, Representative The harmonic characteristic value corresponding to the known fault mode, Representative The weight of the harmonic features, Represents the total harmonics.

9. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The system further comprises: The fault impact analysis module calls the fault category determination information and the fault tracing point location information, calculates the power fluctuation rate of adjacent branches, selects branches whose power changes exceed the short-term power imbalance threshold, determines the fault propagation impact range, and obtains the fault impact range information; The fault impact range information includes the affected branch number, power fluctuation range, load stability parameter and adjacent node current coupling coefficient.

10. The intelligent diagnosis and analysis system for power grid faults according to claim 1, characterized in that: The fault impact analysis module includes: The power fluctuation calculation submodule calls the fault category determination information and the fault tracing point location information to obtain the power data of the branches around the fault point, calculates the power change rate in adjacent time periods, and uses the power fluctuation rate of the branch to compare the power fluctuation trends between adjacent branches to obtain the branch power fluctuation rate; The branch screening submodule calls the short-term power imbalance threshold based on the branch power fluctuation rate, compares the relationship between the branch power fluctuation rate and the threshold, screens the branches whose power changes exceed the threshold, calculates the power change duration of the screened branches, and obtains the power abnormal branches; The impact range determination submodule calculates the topological distribution of the fault point and the abnormal branch based on the power abnormal branch, determines the spatial propagation of the power fluctuation, analyzes the branch coverage range affected by the power fluctuation, calculates the grid load offset in the affected area, and obtains the fault impact range information.

Images