Power distribution network single-phase fault identification method and device, electronic equipment and storage medium

Abstract

The invention discloses a power distribution network single-phase fault identification method and device, electronic equipment and a storage medium, and belongs to the technical field of power system relay protection, and the method comprises the steps: obtaining the zero-sequence voltage time sequence data of a to-be-detected bus of a power distribution network, and the current time sequence data of each to-be-detected feed line monitoring node; determining a first mutation frequency according to the zero-sequence voltage time sequence data; determining a second mutation frequency according to the negative sequence current time sequence data; determining whether the power distribution network is abnormal or not according to the first sudden change times and the second sudden change times; under the condition that the power distribution network is abnormal, calculating a three-phase current asymmetry degree sequence of each feeder tail end node according to the current time sequence data; and determining the abnormality type of the power distribution network according to the three-phase current asymmetry degree sequence and the current time sequence data. According to the invention, the problem that the single-phase fault identification of the power distribution network is not accurate enough in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system relay protection, and in particular to a method, device, electronic equipment and storage medium for identifying single-phase faults in a distribution network. Background Art

[0002] During the operation of the distribution network, single-phase faults are a common abnormal operating condition. A single-phase fault generally refers to an abnormal connection between a phase conductor in a distribution line and the ground or other conductors due to insulation aging, external damage, or equipment defects, thereby disrupting the normal power supply state and affecting the stable operation of the power grid. Based on the specific manifestation of the fault, single-phase faults can generally be divided into two categories: single-phase grounding faults and single-phase line break faults. A single-phase grounding fault refers to a short circuit or contact between a phase conductor and the ground, usually accompanied by significant fluctuations in zero-sequence voltage and current. A single-phase line break fault refers to a physical break in a phase conductor, forming a breakpoint, which causes the current in that phase to be interrupted or significantly attenuated, often manifesting as an abnormal negative-sequence current.

[0003] Prior art techniques typically rely on obtaining phase voltage information from each feeder to identify these single-phase fault types. By analyzing the changes in phase voltage before and after the fault occurs, single-phase grounding or disconnection faults can be identified, which can achieve fault location to a certain extent. However, in actual distribution networks, it is often impossible to obtain stable three-phase voltage information at feeder terminals or intermediate nodes, limiting the accuracy of single-phase fault identification in distribution networks. Summary of the Invention

[0004] The embodiments of the present invention provide a method, device, electronic device and storage medium for identifying single-phase faults in a distribution network, which can solve the problem of inaccurate identification of single-phase faults in the distribution network in the prior art.

[0005] An embodiment of the present invention provides a method for identifying a single-phase fault in a distribution network, comprising:

[0006] Obtain zero-sequence voltage time series data of a busbar to be tested in a distribution network, and current time series data of monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; and the current time series data include negative-sequence current time series data, zero-sequence current time series data, and positive-sequence current time series data;

[0007] Determine the first mutation number of the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data; determine the second mutation number of the negative-sequence current of each feeder to be measured according to the negative-sequence current time series data;

[0008] Determining whether there is an abnormality in the distribution network according to the first mutation number and the second mutation number;

[0009] In the event of an abnormality in the distribution network, a three-phase current asymmetry degree sequence at each feeder terminal node is calculated based on the current time series data;

[0010] The abnormality type of the power distribution network is determined according to the three-phase current asymmetry degree sequence and the current time series data.

[0011] Furthermore, determining the first number of sudden changes in the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data includes:

[0012] Extracting a zero-sequence voltage amplitude sequence of the bus to be measured from the zero-sequence voltage time series data;

[0013] Dividing the zero-sequence voltage amplitude sequence into a plurality of zero-sequence voltage amplitude subsequences according to a preset number of first sampling points;

[0014] Calculating the average value of the zero-sequence voltage amplitude in each zero-sequence voltage amplitude subsequence to generate a corresponding zero-sequence voltage amplitude mean value;

[0015] generating a dynamic voltage threshold corresponding to each zero-sequence voltage amplitude subsequence according to the zero-sequence voltage amplitude mean;

[0016] For each zero-sequence voltage amplitude subsequence, the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence is calculated to generate a first forward difference of the current zero-sequence voltage amplitude subsequence; the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the next zero-sequence voltage amplitude subsequence is calculated to generate a first backward difference of the current zero-sequence voltage amplitude subsequence; and the absolute difference between the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence and the next zero-sequence voltage amplitude subsequence is calculated to generate a first opposite direction difference of the current zero-sequence voltage amplitude subsequence.

[0017] determining whether the first forward difference, the first backward difference, and the first opposite difference are all less than a dynamic voltage threshold of a current zero-sequence voltage amplitude subsequence; if so, determining that the current zero-sequence voltage amplitude subsequence is in a stable state; if not, determining that the current zero-sequence voltage amplitude subsequence is in a sudden change state;

[0018] The first mutation number of the zero-sequence voltage of the bus to be measured is determined according to the number of zero-sequence voltage amplitude subsequences in the mutation state.

[0019] Further, determining the second mutation number of the negative sequence current of each feeder to be tested according to the negative sequence current time series data includes:

[0020] Repeat the negative-sequence current state determination operation until all feeder monitoring nodes to be tested have undergone negative-sequence current state determination, and determine a negative-sequence current amplitude subsequence in a stable state and a negative-sequence current amplitude subsequence in a sudden change state for each feeder monitoring node to be tested;

[0021] Combine the sudden-change feeder monitoring nodes to be tested on the same feeder to generate a plurality of feeder groups; wherein the sudden-change feeder monitoring nodes to be tested are feeder monitoring nodes to be tested that have a negative-sequence current amplitude subsequence in a sudden state;

[0022] For each feeder group, the number of negative sequence current amplitude subsequences in the mutation state in the current feeder group is calculated, and recorded as the mutation number of the current feeder group; the quotient of the mutation number of the current feeder group and the number of monitoring nodes of the feeder to be tested with mutation in the current feeder group is calculated, and the result is recorded as the second mutation number of the negative sequence current of the feeder to be tested corresponding to the current feeder group;

[0023] The second mutation number corresponding to the feeder to be tested that does not have a mutation feeder monitoring node to be tested is recorded as zero;

[0024] The negative sequence current state determination operation includes:

[0025] The current feeder monitoring node to be tested is recorded as the target node; wherein the initial feeder monitoring node to be tested is any feeder monitoring node to be tested for which the negative sequence current state has not been determined;

[0026] Extracting the corresponding negative-sequence current amplitude sequence from the negative-sequence current time series data of the target node;

[0027] Dividing the negative-sequence current amplitude sequence into a plurality of negative-sequence current amplitude subsequences according to a preset number of second sampling points;

[0028] Calculating an average value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence to generate a mean value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence;

[0029] generating a dynamic current threshold value for each negative-sequence current amplitude subsequence according to the negative-sequence current amplitude mean value of each negative-sequence current amplitude subsequence and a preset minimum current threshold value;

[0030] For each negative-sequence current amplitude subsequence, the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence is calculated to generate a second forward difference of the current negative-sequence current amplitude subsequence; the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the next negative-sequence current amplitude subsequence is calculated to generate a second backward difference of the current negative-sequence current amplitude subsequence; and the absolute difference between the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence and the next negative-sequence current amplitude subsequence is calculated to generate a second opposite direction difference of the current negative-sequence current amplitude subsequence.

[0031] determining whether the second forward difference, the second backward difference, and the second opposite difference are all less than the dynamic current threshold of the current negative-sequence current amplitude subsequence; if so, determining that the current negative-sequence current amplitude subsequence is in a stable state; if not, determining that the current negative-sequence current amplitude subsequence is in a sudden change state;

[0032] If there is still a feeder monitoring node to be tested whose negative sequence current state has not been determined, any feeder monitoring node to be tested whose negative sequence current state has not been determined is selected and updated as the current feeder monitoring node to be tested.

[0033] Furthermore, determining the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data includes:

[0034] Extracting the negative sequence current amplitude sequence of each feeder monitoring node to be tested from the negative sequence current time series data;

[0035] Extracting the zero-sequence current amplitude sequence of each feeder monitoring node to be tested from the zero-sequence current time series data;

[0036] Adding the negative-sequence current amplitude in the negative-sequence current amplitude sequence of each feeder monitoring node to be measured to the negative-sequence current amplitude set;

[0037] Adding the zero-sequence current amplitude in the zero-sequence current amplitude sequence of each feeder monitoring node to be measured to the zero-sequence current amplitude set;

[0038] Adding the three-phase current asymmetry degree in the three-phase current asymmetry degree sequence of each feeder terminal node to the three-phase current asymmetry degree set;

[0039] If any zero-sequence current amplitude in the zero-sequence current amplitude set is greater than a preset zero-sequence current threshold, and any three-phase current asymmetry degree in the three-phase current asymmetry degree set does not exceed a preset symmetry degree threshold, it is determined that a single-phase grounding fault exists in the distribution network;

[0040] If any negative-sequence current amplitude in the negative-sequence current amplitude set is greater than the preset negative-sequence current threshold, and the three-phase current asymmetry degree in the three-phase current asymmetry degree set is greater than the preset symmetry degree threshold, it is determined that a single-phase line break fault exists in the distribution network.

[0041] Furthermore, the monitoring node also includes a feeder head end node;

[0042] After determining that a single-phase grounding fault exists in the distribution network, the following steps are also required:

[0043] The moment when the zero-sequence voltage time series data exceeds the preset reference voltage is regarded as the fault moment, and the first fault moment is regarded as the fault start moment;

[0044] Add the zero-sequence current time series data of each feeder head end node in one cycle after the fault initiation moment to the zero-sequence current waveform set to be analyzed;

[0045] Based on a preset ground fault sensitivity coefficient and according to a zero-sequence current waveform set to be analyzed, the fault type of the single-phase ground fault and the fault line of the single-phase ground fault are determined.

[0046] Furthermore, the method of determining the fault type of the single-phase grounding fault and the fault line of the single-phase grounding fault according to the zero-sequence current waveform set to be analyzed based on a preset grounding fault sensitivity coefficient includes:

[0047] sequentially calculating the cosine similarity between each zero-sequence current time series data in the zero-sequence current waveform set to be analyzed, generating an inter-feeder cosine similarity set, and constructing a correlation matrix based on the inter-feeder cosine similarity set;

[0048] Calculating the cumulative value of each row element in the correlation matrix to generate the sum of feeder similarities corresponding to each feeder to be tested;

[0049] Determine whether the difference between the second smallest value in the sum of the feeder similarities and the minimum value in the sum of the feeder similarities is less than a preset ground fault sensitivity coefficient; if so, determine that the single-phase ground fault type is a busbar ground fault; if not, determine that the fault type is a feeder ground fault;

[0050] When the fault type of the single-phase grounding fault is a busbar grounding fault, the busbar is regarded as the fault line of the single-phase grounding fault;

[0051] When the fault type of the single-phase grounding fault is a feeder grounding fault, based on a preset feeder similarity threshold and according to the sum of feeder similarities corresponding to each feeder to be tested, the fault line of the feeder grounding fault is determined.

[0052] Furthermore, when the fault type of the single-phase grounding fault is a feeder grounding fault, after determining the fault line of the feeder grounding fault based on the sum of the feeder similarities corresponding to each feeder to be tested based on a preset feeder similarity threshold, the method further includes:

[0053] The fault line of the feeder grounding fault is recorded as the target fault feeder;

[0054] Based on the zero-sequence current time series data of each monitoring node corresponding to the target fault feeder, the zero-sequence current cosine similarity between adjacent monitoring nodes of the target fault feeder is calculated to generate a zero-sequence current similarity set of adjacent nodes;

[0055] From the zero-sequence current similarity set of adjacent nodes, the minimum cosine similarity of zero-sequence current is selected as the target similarity;

[0056] Determine whether the target similarity is less than the preset section location coefficient. If so, determine that the two monitoring nodes corresponding to the target similarity are fault nodes, and the section between the fault nodes is the fault feeder section;

[0057] If not, it is determined that the end section after the end node of the faulty line of the single-phase grounding fault is the faulty feeder section.

[0058] Based on the above method embodiments, the present invention provides corresponding device embodiments.

[0059] An embodiment of the present invention provides a single-phase fault identification device for a power distribution network, comprising: a data acquisition module, an abnormality monitoring module, a current asymmetry degree calculation module, and an abnormality type identification module;

[0060] The data acquisition module is used to obtain the zero-sequence voltage time series data of the busbar to be tested in the distribution network, and the current time series data of the monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; the current time series data includes negative sequence current time series data, zero sequence current time series data and positive sequence current time series data;

[0061] The abnormality monitoring module is configured to determine a first mutation number of the zero-sequence voltage of the bus to be measured based on the zero-sequence voltage time series data; determine a second mutation number of the negative-sequence current of each feeder to be measured based on the negative-sequence current time series data; and determine whether there is an abnormality in the distribution network based on the first mutation number and the second mutation number;

[0062] The current asymmetry degree calculation module is used to calculate the three-phase current asymmetry degree sequence of each feeder terminal node based on the current time series data when an abnormality occurs in the distribution network;

[0063] The abnormality type identification module is used to determine the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data.

[0064] Based on the above method embodiment, the present invention provides a corresponding electronic device embodiment.

[0065] An embodiment of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the method for identifying single-phase faults in a distribution network as described in any one of the above-mentioned method embodiments is implemented.

[0066] Based on the above method embodiment, the present invention provides a corresponding storage medium embodiment.

[0067] An embodiment of the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the distribution network single-phase fault identification method described in any one of the above method embodiments.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] Embodiments of the present invention provide a method, apparatus, electronic device, and storage medium for identifying single-phase faults in a distribution network. The method obtains zero-sequence voltage time-series data for a busbar to be tested, as well as current time-series data for multiple monitoring nodes in each feeder to be tested, where the current data includes positive-sequence, negative-sequence, and zero-sequence currents. By analyzing the first number of sudden changes in the busbar zero-sequence voltage and the second number of sudden changes in the negative-sequence current of each feeder, a preliminary determination is made as to whether an abnormality exists in the distribution network. After detecting an abnormality, a three-phase current asymmetry degree sequence is constructed based on the current time-series data at the feeder terminal nodes, and combined with the aforementioned current characteristics, the specific single-phase fault type in the distribution network is identified.

[0070] Compared to traditional solutions that rely on feeder voltage information, this solution leverages the sequence component characteristics and mutation behavior inherent in current data, circumventing the difficulty in obtaining stable feeder phase voltages. Furthermore, by integrating busbar zero-sequence voltage with current monitoring data from multiple feeder terminals, it enables accurate identification of single-phase fault types in the distribution network, improving the accuracy of single-phase fault identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 The present invention provides a flow chart of a method for identifying a single-phase fault in a distribution network according to an embodiment of the present invention.

[0072] Figure 2 The present invention is a schematic structural diagram of a single-phase fault identification device for a distribution network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0074] like Figure 1 As shown, in order to solve the problem that the single-phase fault identification of the distribution network is not accurate enough in the prior art, an embodiment of the present invention provides a single-phase fault identification method for the distribution network, which includes at least the following steps:

[0075] Step S1, obtaining zero-sequence voltage time series data of a busbar to be tested in a distribution network, and current time series data of monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; the current time series data include negative-sequence current time series data, zero-sequence current time series data, and positive-sequence current time series data;

[0076] In this solution, the busbar to be tested refers to the distribution network busbar currently being monitored and analyzed. As the convergence node of multiple feeders, its operating status changes can fully reflect the overall characteristics of the system, especially the fluctuation of zero-sequence voltage is often closely related to single-phase faults; the feeders to be tested are multiple distribution lines directly connected to the busbar, and their current characteristics are crucial for fault location; the monitoring nodes are sampling points deployed on the feeders to collect current data, including the feeder head end node, the feeder terminal middle section node and the feeder end node, so as to obtain current signals with more significant fault effects; the current time series data includes negative sequence current time series data, zero sequence current time series data and positive sequence current time series data, all of which are obtained by calculating the original three-phase current signal collected by the distribution network monitoring node through the symmetrical component method. The symmetrical component method is a classic and widely used technical means for power system analysis. It can decompose any asymmetrical three-phase current signal into three independent components: positive sequence current time series data, negative sequence current time series data and zero sequence current time series data. Among them, positive-sequence current time series data reflects the main current components of the system under normal, symmetrical operation; negative-sequence current time series data reveals current anomalies caused by load imbalance or faults; and zero-sequence current time series data represents the superposition of three-phase currents in the same phase and direction, which is often closely related to ground faults. Using this method to process the raw current data, it is possible to extract typical time series features closely related to the fault type.

[0077] This step can provide an accurate and reliable data basis for subsequent anomaly detection and fault type identification.

[0078] Step S2: determining the first mutation number of the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data; determining the second mutation number of the negative-sequence current of each feeder to be measured according to the negative-sequence current time series data;

[0079] Specifically, determining the first mutation number of the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data includes:

[0080] Extracting a zero-sequence voltage amplitude sequence of the bus to be measured from the zero-sequence voltage time series data;

[0081] Dividing the zero-sequence voltage amplitude sequence into a plurality of zero-sequence voltage amplitude subsequences according to a preset number of first sampling points;

[0082] Calculating the average value of the zero-sequence voltage amplitude in each zero-sequence voltage amplitude subsequence to generate a corresponding zero-sequence voltage amplitude mean value;

[0083] generating a dynamic voltage threshold corresponding to each zero-sequence voltage amplitude subsequence according to the zero-sequence voltage amplitude mean;

[0084] For each zero-sequence voltage amplitude subsequence, the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence is calculated to generate a first forward difference of the current zero-sequence voltage amplitude subsequence; the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the next zero-sequence voltage amplitude subsequence is calculated to generate a first backward difference of the current zero-sequence voltage amplitude subsequence; and the absolute difference between the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence and the next zero-sequence voltage amplitude subsequence is calculated to generate a first opposite direction difference of the current zero-sequence voltage amplitude subsequence.

[0085] determining whether the first forward difference, the first backward difference, and the first opposite difference are all less than a dynamic voltage threshold of a current zero-sequence voltage amplitude subsequence; if so, determining that the current zero-sequence voltage amplitude subsequence is in a stable state; if not, determining that the current zero-sequence voltage amplitude subsequence is in a sudden change state;

[0086] The first mutation number of the zero-sequence voltage of the bus to be measured is determined according to the number of zero-sequence voltage amplitude subsequences in the mutation state.

[0087] In an optional embodiment, first, a zero-sequence voltage amplitude sequence of the bus to be measured is extracted from the zero-sequence voltage time series data. The zero-sequence voltage amplitude sequence is composed of the zero-sequence voltage amplitude at each moment in the time series, which reflects the changing trend of the zero-sequence voltage in the distribution network. Then, according to the preset number of first sampling points (i.e., the granularity of dividing the time series), the zero-sequence voltage amplitude sequence is divided into a plurality of zero-sequence voltage amplitude subsequences. Each zero-sequence voltage amplitude subsequence contains a certain amount of zero-sequence voltage amplitude data, which represents the fluctuation characteristics of the zero-sequence voltage signal over a certain period of time.

[0088] Next, the average of the zero-sequence voltage amplitudes in each zero-sequence voltage amplitude subsequence is calculated to generate the corresponding zero-sequence voltage amplitude mean. The zero-sequence voltage amplitude mean is the average of all zero-sequence voltage amplitudes within the subsequence and represents the overall level of zero-sequence voltage variation over that period. Based on the zero-sequence voltage amplitude mean, the corresponding dynamic voltage threshold is generated. The setting of the dynamic voltage threshold takes into account the real-time and fluctuation characteristics of voltage changes and can help accurately determine whether the voltage has undergone a sudden change.

[0089] For each zero-sequence voltage amplitude subsequence, the difference between it and the adjacent subsequences is further calculated to determine the stability of the voltage change. By comparing these differences, it is possible to further confirm whether the voltage change is stable. If the first forward difference, the first backward difference, and the first opposite difference are all less than the dynamic voltage threshold of the current zero-sequence voltage amplitude subsequence, the zero-sequence voltage amplitude subsequence is determined to be in a stable state, indicating that the voltage change is stable. If any of the differences exceeds the dynamic voltage threshold, it is determined to be in a sudden change state, indicating that the voltage has suddenly changed, possibly indicating a fault or other abnormal condition. Finally, by counting all zero-sequence voltage amplitude subsequences in a sudden change state, the first sudden change number of the zero-sequence voltage of the bus under test is determined, providing basic data for subsequent fault analysis.

[0090] Preferably, the dynamic voltage threshold of the zero-sequence voltage amplitude subsequence is calculated by the following formula:

[0091]

[0092] Among them, T m is the dynamic voltage threshold of the mth zero-sequence voltage amplitude subsequence; is the mean value of the zero-sequence voltage amplitude of the mth zero-sequence voltage amplitude subsequence; T min is the preset minimum voltage threshold; α is the preset voltage threshold proportional coefficient.

[0093] Specifically, determining the second mutation number of the negative sequence current of each feeder to be tested according to the negative sequence current time series data includes:

[0094] Repeat the negative-sequence current state determination operation until all feeder monitoring nodes to be tested have undergone negative-sequence current state determination, and determine a negative-sequence current amplitude subsequence in a stable state and a negative-sequence current amplitude subsequence in a sudden change state for each feeder monitoring node to be tested;

[0095] Combine the sudden-change feeder monitoring nodes to be tested on the same feeder to generate a plurality of feeder groups; wherein the sudden-change feeder monitoring nodes to be tested are feeder monitoring nodes to be tested that have a negative-sequence current amplitude subsequence in a sudden state;

[0096] For each feeder group, the number of negative sequence current amplitude subsequences in the mutation state in the current feeder group is calculated, and recorded as the mutation number of the current feeder group; the quotient of the mutation number of the current feeder group and the number of monitoring nodes of the feeder to be tested with mutation in the current feeder group is calculated, and the result is recorded as the second mutation number of the negative sequence current of the feeder to be tested corresponding to the current feeder group;

[0097] The second mutation number corresponding to the feeder to be tested that does not have a mutation feeder monitoring node to be tested is recorded as zero;

[0098] The negative sequence current state determination operation includes:

[0099] The current feeder monitoring node to be tested is recorded as the target node; wherein the initial feeder monitoring node to be tested is any feeder monitoring node to be tested for which the negative sequence current state has not been determined;

[0100] Extracting the corresponding negative-sequence current amplitude sequence from the negative-sequence current time series data of the target node;

[0101] Dividing the negative-sequence current amplitude sequence into a plurality of negative-sequence current amplitude subsequences according to a preset number of second sampling points;

[0102] Calculating an average value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence to generate a mean value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence;

[0103] generating a dynamic current threshold value for each negative-sequence current amplitude subsequence according to the negative-sequence current amplitude mean value of each negative-sequence current amplitude subsequence and a preset minimum current threshold value;

[0104] For each negative-sequence current amplitude subsequence, the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence is calculated to generate a second forward difference of the current negative-sequence current amplitude subsequence; the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the next negative-sequence current amplitude subsequence is calculated to generate a second backward difference of the current negative-sequence current amplitude subsequence; and the absolute difference between the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence and the next negative-sequence current amplitude subsequence is calculated to generate a second opposite direction difference of the current negative-sequence current amplitude subsequence.

[0105] determining whether the second forward difference, the second backward difference, and the second opposite difference are all less than the dynamic current threshold of the current negative-sequence current amplitude subsequence; if so, determining that the current negative-sequence current amplitude subsequence is in a stable state; if not, determining that the current negative-sequence current amplitude subsequence is in a sudden change state;

[0106] If there is still a feeder monitoring node to be tested whose negative sequence current state has not been determined, any feeder monitoring node to be tested whose negative sequence current state has not been determined is selected and updated as the current feeder monitoring node to be tested.

[0107] In an optional embodiment, the negative-sequence current state determination operation is first repeated until the negative-sequence current state of all feeder monitoring nodes to be tested is determined. At this point, each feeder monitoring node to be tested is determined to be in a stable state or a sudden change state. A stable state refers to a relatively gentle fluctuation in the negative-sequence current amplitude, with no significant sudden changes in the trend; a sudden change refers to a large fluctuation in the negative-sequence current amplitude, manifested as a dramatic change in current, which may be related to a grid fault or equipment abnormality.

[0108] Once the negative-sequence current status of all feeder monitoring nodes under test is determined, the feeders can be grouped according to the subsequence of negative-sequence current amplitudes that exhibit a sudden change. Specifically, the monitoring nodes of the feeder under test that exhibit a sudden change on the same feeder are combined to form several feeder groups. The nodes within each feeder group exhibit a sudden change in negative-sequence current amplitude, so the status of these nodes is analyzed as a whole.

[0109] Next, for each feeder group, the number of negative-sequence current amplitude subsequences in the group that are in a mutation state is calculated and recorded as the number of mutations for the feeder group. The number of mutations reflects how many nodes in the feeder group have a mutation in the negative-sequence current amplitude. Then, the number of mutations for the feeder group is divided by the number of mutation monitoring nodes of the feeder to be tested in the group to obtain the second number of mutations for the feeder to be tested corresponding to the feeder group. The second number of mutations characterizes the frequency and distribution of the mutation phenomenon in the time series data of the negative-sequence current of the feeder. If no monitoring node of the feeder to be tested in a mutation state in a feeder group, the second number of mutations corresponding to the feeder will be recorded as zero, which means that no significant mutation of the negative-sequence current has occurred in the feeder during the observation period.

[0110] Preferably, the dynamic current threshold of the negative sequence current amplitude subsequence is calculated by the following formula:

[0111]

[0112] Among them, Q n is the dynamic current threshold of the nth negative sequence current amplitude subsequence; is the mean negative sequence current amplitude of the nth negative sequence current amplitude subsequence; Q min is the preset minimum current threshold; β is the preset current threshold proportional coefficient.

[0113] This step helps improve the accuracy of distribution network fault identification and response efficiency by identifying the number of sudden changes in zero-sequence voltage and negative-sequence current.

[0114] Step S3: determining whether there is an abnormality in the distribution network according to the first mutation number and the second mutation number;

[0115] Preferably, according to the first number of mutations and the second number of mutations, the first number of mutations of the bus to be tested and the second number of mutations of each feeder to be tested are summed respectively to obtain the total number of zero-sequence voltage mutations and the total number of negative-sequence current mutations; the two are added to obtain the total number of mutations of the distribution network as a whole, and compared with a preset mutation judgment threshold; if the total number of mutations is greater than the threshold, it is determined that there is an abnormality in the distribution network; otherwise, it is determined that the operation status of the distribution network is normal.

[0116] It should be noted that during the normal operation of the distribution network, individual mutation points may appear in the time series data of the zero-sequence voltage or negative-sequence current due to factors such as load fluctuations, changes in distributed power supply access, and measurement errors. However, such mutations do not necessarily mean that there is an actual fault. Therefore, by setting a mutation number judgment threshold, only when the sum of the first mutation number and the second mutation number exceeds the threshold, is it determined that there may be an abnormality in the distribution network, which helps to improve the accuracy of abnormality identification and the robustness of system operation.

[0117] Step S4: When an abnormality occurs in the distribution network, a three-phase current asymmetry degree sequence of each feeder terminal node is calculated based on the current time series data;

[0118] Specifically, in the event of an anomaly in the distribution network, a three-phase current asymmetry sequence is calculated at each feeder terminal node based on the current time series data. The ratio between the maximum and minimum three-phase currents at each moment is used as an asymmetry indicator, which intuitively reflects the degree of deviation in the three-phase currents at that moment. By continuously calculating these ratios at each moment, a three-phase current asymmetry sequence is generated that reflects changes in node operational stability, providing a data foundation for further identifying anomaly types.

[0119] Step S5: Determine the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data.

[0120] Specifically, determining the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data includes:

[0121] Extracting the negative-sequence current amplitude sequence of each feeder monitoring node to be measured from the negative-sequence current time series data; extracting the zero-sequence current amplitude sequence of each feeder monitoring node to be measured from the zero-sequence current time series data;

[0122] Adding the negative-sequence current amplitude in the negative-sequence current amplitude sequence of each feeder monitoring node to the negative-sequence current amplitude set; adding the zero-sequence current amplitude in the zero-sequence current amplitude sequence of each feeder monitoring node to the zero-sequence current amplitude set;

[0123] Adding the three-phase current asymmetry degree in the three-phase current asymmetry degree sequence of each feeder terminal node to the three-phase current asymmetry degree set;

[0124] If any zero-sequence current amplitude in the zero-sequence current amplitude set is greater than a preset zero-sequence current threshold, and any three-phase current asymmetry degree in the three-phase current asymmetry degree set does not exceed a preset symmetry degree threshold, it is determined that a single-phase grounding fault exists in the distribution network;

[0125] If any negative-sequence current amplitude in the negative-sequence current amplitude set is greater than the preset negative-sequence current threshold, and the three-phase current asymmetry degree in the three-phase current asymmetry degree set is greater than the preset symmetry degree threshold, it is determined that a single-phase line break fault exists in the distribution network.

[0126] In an optional embodiment, first, the negative-sequence current amplitude sequence of each feeder monitoring node to be tested is extracted from the negative-sequence current time series data; negative-sequence current is a typical manifestation of the destruction of symmetry in three-phase current, and can be used to characterize the severity of current imbalance. Secondly, the zero-sequence current amplitude sequence of each feeder monitoring node to be tested is extracted from the zero-sequence current time series data; zero-sequence current usually appears in asymmetric faults to the ground such as single-phase grounding, and is a direct reflection of grounding anomalies. Then, each amplitude in the negative-sequence current amplitude sequence of each feeder monitoring node to be tested is added to the negative-sequence current amplitude set, and each amplitude in the zero-sequence current amplitude sequence of each node is added to the zero-sequence current amplitude set. At the same time, each numerical value in the three-phase current asymmetry degree sequence of each feeder end node is added to the three-phase current asymmetry degree set, forming three feature data sets for the entire network.

[0127] On this basis, determine whether the above three types of characteristic indicators exceed the preset thresholds:

[0128] If any zero-sequence current amplitude in the zero-sequence current amplitude set is greater than the preset zero-sequence current threshold, and all values in the three-phase current asymmetry degree set do not exceed the symmetry degree threshold, that is, the three-phase current as a whole is still in a symmetrical operating state, it can be determined as a single-phase grounding fault, that is, only one phase current to ground path is abnormal but the three-phase current amplitude is not obviously unbalanced.

[0129] If any negative-sequence current amplitude in the negative-sequence current amplitude concentration is greater than the preset negative-sequence current threshold, and the three-phase current asymmetry concentration contains a value that is not less than the symmetry threshold, that is, there is a significant difference between the current amplitudes, then it can be determined as a single-phase line break fault, that is, the open circuit of a phase conductor causes three-phase current imbalance.

[0130] This step can accurately identify common abnormal conditions such as single-phase grounding faults and single-phase disconnection faults in the distribution network by comprehensively analyzing the three-phase current asymmetry degree sequence and current time series data.

[0131] In a preferred embodiment, after determining that a single-phase grounding fault exists in the power distribution network, the method further includes:

[0132] The moment when the zero-sequence voltage time series data exceeds the preset reference voltage is regarded as the fault moment, and the first fault moment is regarded as the fault start moment;

[0133] Add the zero-sequence current time series data of each feeder head end node in one cycle after the fault initiation moment to the zero-sequence current waveform set to be analyzed;

[0134] Based on a preset ground fault sensitivity coefficient and according to a zero-sequence current waveform set to be analyzed, the fault type of the single-phase ground fault and the fault line of the single-phase ground fault are determined.

[0135] Specifically, the determining the fault type of the single-phase grounding fault and the fault line of the single-phase grounding fault according to the preset grounding fault sensitivity coefficient and the zero-sequence current waveform set to be analyzed includes:

[0136] sequentially calculating the cosine similarity between each zero-sequence current time series data in the zero-sequence current waveform set to be analyzed, generating an inter-feeder cosine similarity set, and constructing a correlation matrix based on the inter-feeder cosine similarity set;

[0137] Calculating the cumulative value of each row element in the correlation matrix to generate the sum of feeder similarities corresponding to each feeder to be tested;

[0138] Determine whether the difference between the second smallest value in the sum of the feeder similarities and the minimum value in the sum of the feeder similarities is less than a preset ground fault sensitivity coefficient; if so, determine that the single-phase ground fault type is a busbar ground fault; if not, determine that the fault type is a feeder ground fault;

[0139] When the fault type of the single-phase grounding fault is a busbar grounding fault, the busbar is regarded as the fault line of the single-phase grounding fault;

[0140] When the fault type of the single-phase grounding fault is a feeder grounding fault, based on a preset feeder similarity threshold and according to the sum of feeder similarities corresponding to each feeder to be tested, the fault line of the feeder grounding fault is determined.

[0141] In an optional embodiment, during the fault detection and location process, the moment when the preset reference voltage is exceeded is first extracted from the zero-sequence voltage time-series data, and this moment is defined as the fault moment. Next, the first moment after this moment is used as the fault start moment to ensure that the fault start time can be accurately captured. At this point, the zero-sequence current time-series data of each feeder headend node within a period after the fault start moment is added to the zero-sequence current waveform set to be analyzed. This waveform data enables accurate analysis and location of the fault. During further analysis, the zero-sequence current waveform set to be analyzed is processed based on a preset ground fault sensitivity coefficient to determine the specific fault type and fault line of the single-phase ground fault.

[0142] Once a busbar ground fault is determined, the faulty line is directly identified as the busbar. If the fault type is a feeder ground fault, the faulty line is further determined by combining the set feeder similarity threshold with the sum of the similarities of each feeder. This process can efficiently and accurately determine the type of single-phase ground fault and identify the specific fault line, providing important support for subsequent troubleshooting and repair.

[0143] Optionally, when the fault type of the single-phase grounding fault is a feeder grounding fault, determining the fault line of the feeder grounding fault based on a preset feeder similarity threshold and the sum of feeder similarities corresponding to each feeder to be tested includes:

[0144] After determining the fault type is a feeder ground fault, the system then filters out feeders whose summed similarity exceeds a preset feeder similarity threshold. If the summed similarity of multiple feeders exceeds the threshold, multiple feeder ground faults may exist. Further analysis of these feeders can identify those with strong similarities to the busbar or other feeders, effectively identifying all feeders with potential ground faults and providing more comprehensive fault location information to maintenance personnel.

[0145] Preferably, when the fault type of the single-phase grounding fault is a feeder grounding fault, after determining the fault line of the feeder grounding fault based on the sum of feeder similarities corresponding to each feeder to be tested based on a preset feeder similarity threshold, the method further includes:

[0146] The fault line of the feeder grounding fault is recorded as the target fault feeder;

[0147] Based on the zero-sequence current time series data of each monitoring node corresponding to the target fault feeder, the zero-sequence current cosine similarity between adjacent monitoring nodes of the target fault feeder is calculated to generate a zero-sequence current similarity set of adjacent nodes;

[0148] From the zero-sequence current similarity set of adjacent nodes, the minimum cosine similarity of zero-sequence current is selected as the target similarity;

[0149] Determine whether the target similarity is less than the preset section location coefficient. If so, determine that the two monitoring nodes corresponding to the target similarity are fault nodes, and the section between the fault nodes is the fault feeder section;

[0150] If not, it is determined that the end section after the end node of the faulty line of the single-phase grounding fault is the faulty feeder section.

[0151] In a preferred embodiment, the faulty line is first identified as the target fault feeder. Next, based on the zero-sequence current time series data of each monitoring node on the target fault feeder, the zero-sequence current cosine similarity between adjacent monitoring nodes on the target fault feeder is calculated to generate a set of adjacent node zero-sequence current similarities. By calculating the zero-sequence current cosine similarity between adjacent nodes, the similarity of the current characteristics of each monitoring node at the time of the fault can be effectively measured, providing support for fault location.

[0152] From the set of zero-sequence current similarities between adjacent nodes, the minimum zero-sequence current cosine similarity is selected as the target similarity. This target similarity is then compared with a preset segment location coefficient. If the target similarity is less than the preset segment location coefficient, it indicates that the current characteristics of the two monitoring nodes differ significantly, suggesting a potential faulty node. In this case, the two monitoring nodes are determined to be faulty nodes, and the segment between them is identified as the faulty feeder segment, allowing for further localization of the fault.

[0153] If the target similarity is at least a preset segment location coefficient, it indicates that the current characteristics of adjacent nodes are similar, suggesting a possible continuation of the fault area. In this case, the system determines that the terminal segment following the terminal node of the target faulty feeder is the faulty feeder segment and further locates the fault's terminal region. This location method is effective in situations with high current similarity and helps accurately identify the specific fault location.

[0154] This similarity-based segment positioning method can more accurately divide the fault area, avoid misjudgment caused by locating a single fault node, and improve the accuracy of overall fault diagnosis.

[0155] In a specific implementation, after determining that a single-phase disconnection fault exists in the distribution network, the method further includes:

[0156] In the three-phase current asymmetry degree sequence of each monitoring node, if any asymmetry degree exists that is greater than a preset symmetry degree threshold, the feeder corresponding to the monitoring node is taken as the target broken feeder;

[0157] If all the feeders to be tested are target broken feeders, it is determined that a single-phase broken fault exists on the busbar; if not all the feeders to be tested are target broken feeders, it is determined that the target broken feeder is the broken feeder;

[0158] For each broken feeder, the negative sequence current mutation amplitude of all monitoring nodes on the current broken feeder is calculated and generated; based on the negative sequence current mutation amplitude of all monitoring nodes, the negative sequence current mutation amplitude ratio of adjacent nodes on the broken feeder is calculated in the order from the feeder head end node to the feeder end node;

[0159] If the negative sequence current mutation amplitude ratio is greater than the preset line break fault sensitivity coefficient, the section corresponding to the adjacent node is determined to be a line break fault section;

[0160] If all negative sequence current mutation amplitude ratios on the broken feeder are less than the preset broken fault sensitivity coefficient, the end section after the end node of the broken feeder is determined to be a broken fault section.

[0161] Specifically, the negative sequence current mutation amplitude is determined by the following method:

[0162] Since each monitoring node has a negative-sequence current amplitude sequence, each negative-sequence current amplitude sequence is divided into a number of negative-sequence current amplitude subsequences according to a preset number of second sampling points;

[0163] For each negative-sequence current amplitude subsequence, there is a second opposite difference, that is, the absolute difference between the negative-sequence current amplitude subsequence before the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the next negative-sequence current amplitude subsequence;

[0164] The average of the second opposite differences of all negative sequence current amplitude subsequences is calculated as the negative sequence current mutation amplitude of the monitoring node.

[0165] By introducing a joint criterion of the degree of three-phase current asymmetry and the negative-sequence current mutation amplitude, it is possible to effectively distinguish single-phase line break faults on the bus side and the feeder side, and further locate the specific fault section within the faulty feeder; among them, the calculation method of the opposite difference based on the segmented waveform can enhance the sensitivity and robustness of the mutation characteristics, which is conducive to accurately extracting the mutation amplitude of the negative-sequence current under complex operating conditions, and improving the accuracy and reliability of fault location.

[0166] Based on the above method embodiments, the present invention provides corresponding device embodiments.

[0167] like Figure 2 As shown, an embodiment of the present invention provides a single-phase fault identification device for a power distribution network, comprising: a data acquisition module, an abnormality monitoring module, a current asymmetry degree calculation module, and an abnormality type identification module;

[0168] The data acquisition module is used to obtain the zero-sequence voltage time series data of the busbar to be tested in the distribution network, and the current time series data of the monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; the current time series data includes negative sequence current time series data, zero sequence current time series data and positive sequence current time series data;

[0169] The abnormality monitoring module is configured to determine a first mutation number of the zero-sequence voltage of the bus to be measured based on the zero-sequence voltage time series data; determine a second mutation number of the negative-sequence current of each feeder to be measured based on the negative-sequence current time series data; and determine whether there is an abnormality in the distribution network based on the first mutation number and the second mutation number;

[0170] The current asymmetry degree calculation module is used to calculate the three-phase current asymmetry degree sequence of each feeder terminal node based on the current time series data when an abnormality occurs in the distribution network;

[0171] The abnormality type identification module is used to determine the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data.

[0172] It should be noted that the embodiment of the device described above corresponds to the above-mentioned embodiment of the present invention, and it can implement any one of the above-mentioned methods for identifying single-phase faults in the distribution network of the present invention. In addition, the embodiment of the above-mentioned device is merely schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the embodiment of the device provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0173] Based on the above method embodiment of the present invention, a corresponding electronic device embodiment is provided.

[0174] An embodiment of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the distribution network single-phase fault identification method described in any one of the present invention is implemented, or when the processor executes the computer program, the functions of the modules in the above-mentioned device embodiments are implemented.

[0175] Exemplarily, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0176] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0177] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0178] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created based on the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0179] Based on the above method embodiment, the present invention provides a corresponding storage medium embodiment;

[0180] Another embodiment of the present invention provides a storage medium, which includes a stored computer program. When the computer program is executed, the device where the storage medium is located is controlled to execute any of the above-mentioned distribution network single-phase fault identification methods of the present invention.

[0181] The storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium.

[0182] In the description of this specification, the reference terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" mean that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and integrate different embodiments or examples described in this specification, as well as features of different embodiments or examples, unless they are mutually inconsistent.

[0183] The above is 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 principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for identifying single-phase faults in a distribution network, characterized in that: include: Obtain zero-sequence voltage time series data of a busbar to be tested in a distribution network, and current time series data of monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; and the current time series data include negative-sequence current time series data, zero-sequence current time series data, and positive-sequence current time series data; Determine the first mutation number of the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data; determine the second mutation number of the negative-sequence current of each feeder to be measured according to the negative-sequence current time series data; Determining whether there is an abnormality in the distribution network according to the first mutation number and the second mutation number; In the event of an abnormality in the distribution network, a three-phase current asymmetry degree sequence at each feeder terminal node is calculated based on the current time series data; The abnormality type of the power distribution network is determined according to the three-phase current asymmetry degree sequence and the current time series data.

2. The method for identifying single-phase faults in a distribution network according to claim 1, wherein: Determining the first mutation number of the zero-sequence voltage of the bus to be measured according to the zero-sequence voltage time series data includes: Extracting a zero-sequence voltage amplitude sequence of the bus to be measured from the zero-sequence voltage time series data; Dividing the zero-sequence voltage amplitude sequence into a plurality of zero-sequence voltage amplitude subsequences according to a preset number of first sampling points; Calculating the average value of the zero-sequence voltage amplitude in each zero-sequence voltage amplitude subsequence to generate a corresponding zero-sequence voltage amplitude mean value; generating a dynamic voltage threshold corresponding to each zero-sequence voltage amplitude subsequence according to the zero-sequence voltage amplitude mean; For each zero-sequence voltage amplitude subsequence, the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence is calculated to generate a first forward difference of the current zero-sequence voltage amplitude subsequence; the absolute difference between the current zero-sequence voltage amplitude subsequence and the mean value of the zero-sequence voltage amplitude of the next zero-sequence voltage amplitude subsequence is calculated to generate a first backward difference of the current zero-sequence voltage amplitude subsequence; and the absolute difference between the mean value of the zero-sequence voltage amplitude of the previous zero-sequence voltage amplitude subsequence and the next zero-sequence voltage amplitude subsequence is calculated to generate a first opposite direction difference of the current zero-sequence voltage amplitude subsequence. determining whether the first forward difference, the first backward difference, and the first opposite difference are all less than a dynamic voltage threshold of a current zero-sequence voltage amplitude subsequence; if so, determining that the current zero-sequence voltage amplitude subsequence is in a stable state; if not, determining that the current zero-sequence voltage amplitude subsequence is in a sudden change state; The first mutation number of the zero-sequence voltage of the bus to be measured is determined according to the number of zero-sequence voltage amplitude subsequences in the mutation state.

3. The method for identifying single-phase faults in a distribution network according to claim 2, wherein: Determining the second mutation number of the negative sequence current of each feeder to be tested according to the negative sequence current time series data includes: Repeat the negative-sequence current state determination operation until all feeder monitoring nodes to be tested have undergone negative-sequence current state determination, and determine a negative-sequence current amplitude subsequence in a stable state and a negative-sequence current amplitude subsequence in a sudden change state for each feeder monitoring node to be tested; Combine the sudden-change feeder monitoring nodes to be tested on the same feeder to generate a plurality of feeder groups; wherein the sudden-change feeder monitoring nodes to be tested are feeder monitoring nodes to be tested that have a negative-sequence current amplitude subsequence in a sudden state; For each feeder group, the number of negative sequence current amplitude subsequences in the mutation state in the current feeder group is calculated, and recorded as the mutation number of the current feeder group; the quotient of the mutation number of the current feeder group and the number of monitoring nodes of the feeder to be tested with mutation in the current feeder group is calculated, and the result is recorded as the second mutation number of the negative sequence current of the feeder to be tested corresponding to the current feeder group; The second mutation number corresponding to the feeder to be tested that does not have a mutation feeder monitoring node to be tested is recorded as zero; The negative sequence current state determination operation includes: The current feeder monitoring node to be tested is recorded as the target node; wherein the initial feeder monitoring node to be tested is any feeder monitoring node to be tested for which the negative sequence current state has not been determined; Extracting the corresponding negative-sequence current amplitude sequence from the negative-sequence current time series data of the target node; Dividing the negative-sequence current amplitude sequence into a plurality of negative-sequence current amplitude subsequences according to a preset number of second sampling points; Calculating an average value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence to generate a mean value of the negative-sequence current amplitudes of each negative-sequence current amplitude subsequence; generating a dynamic current threshold value for each negative-sequence current amplitude subsequence according to the negative-sequence current amplitude mean value of each negative-sequence current amplitude subsequence and a preset minimum current threshold value; For each negative-sequence current amplitude subsequence, the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence is calculated to generate a second forward difference of the current negative-sequence current amplitude subsequence; the absolute difference between the current negative-sequence current amplitude subsequence and the mean negative-sequence current amplitude of the next negative-sequence current amplitude subsequence is calculated to generate a second backward difference of the current negative-sequence current amplitude subsequence; and the absolute difference between the mean negative-sequence current amplitude of the previous negative-sequence current amplitude subsequence and the next negative-sequence current amplitude subsequence is calculated to generate a second opposite direction difference of the current negative-sequence current amplitude subsequence. determining whether the second forward difference, the second backward difference, and the second opposite difference are all less than the dynamic current threshold of the current negative-sequence current amplitude subsequence; if so, determining that the current negative-sequence current amplitude subsequence is in a stable state; if not, determining that the current negative-sequence current amplitude subsequence is in a sudden change state; If there is still a feeder monitoring node to be tested whose negative sequence current state has not been determined, any feeder monitoring node to be tested whose negative sequence current state has not been determined is selected and updated as the current feeder monitoring node to be tested.

4. The method for identifying single-phase faults in a distribution network according to claim 3, wherein: Determining the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data includes: Extracting the negative sequence current amplitude sequence of each feeder monitoring node to be tested from the negative sequence current time series data; Extracting the zero-sequence current amplitude sequence of each feeder monitoring node to be tested from the zero-sequence current time series data; Adding the negative-sequence current amplitude in the negative-sequence current amplitude sequence of each feeder monitoring node to be measured to the negative-sequence current amplitude set; Adding the zero-sequence current amplitude in the zero-sequence current amplitude sequence of each feeder monitoring node to be measured to the zero-sequence current amplitude set; Adding the three-phase current asymmetry degree in the three-phase current asymmetry degree sequence of each feeder terminal node to the three-phase current asymmetry degree set; If any zero-sequence current amplitude in the zero-sequence current amplitude set is greater than a preset zero-sequence current threshold, and any three-phase current asymmetry degree in the three-phase current asymmetry degree set does not exceed a preset symmetry degree threshold, it is determined that a single-phase grounding fault exists in the distribution network; If any negative-sequence current amplitude in the negative-sequence current amplitude set is greater than the preset negative-sequence current threshold, and the three-phase current asymmetry degree in the three-phase current asymmetry degree set is greater than the preset symmetry degree threshold, it is determined that a single-phase line break fault exists in the distribution network.

5. The method for identifying single-phase faults in a distribution network according to claim 4, wherein: The monitoring node also includes a feeder head end node; After determining that a single-phase grounding fault exists in the distribution network, the following steps are also required: The moment when the zero-sequence voltage time series data exceeds the preset reference voltage is regarded as the fault moment, and the first fault moment is regarded as the fault start moment; Add the zero-sequence current time series data of each feeder head end node in one cycle after the fault initiation moment to the zero-sequence current waveform set to be analyzed; Based on a preset ground fault sensitivity coefficient and according to a zero-sequence current waveform set to be analyzed, the fault type of the single-phase ground fault and the fault line of the single-phase ground fault are determined.

6. The method for identifying single-phase faults in a distribution network according to claim 5, wherein: The determining of the fault type of the single-phase grounding fault and the fault line of the single-phase grounding fault according to a preset grounding fault sensitivity coefficient and a zero-sequence current waveform set to be analyzed includes: sequentially calculating the cosine similarity between each zero-sequence current time series data in the zero-sequence current waveform set to be analyzed, generating an inter-feeder cosine similarity set, and constructing a correlation matrix based on the inter-feeder cosine similarity set; Calculating the cumulative value of each row element in the correlation matrix to generate the sum of feeder similarities corresponding to each feeder to be tested; Determine whether the difference between the second smallest value in the sum of the feeder similarities and the minimum value in the sum of the feeder similarities is less than a preset ground fault sensitivity coefficient; if so, determine that the single-phase ground fault type is a busbar ground fault; if not, determine that the fault type is a feeder ground fault; When the fault type of the single-phase grounding fault is a busbar grounding fault, the busbar is regarded as the fault line of the single-phase grounding fault; When the fault type of the single-phase grounding fault is a feeder grounding fault, based on a preset feeder similarity threshold and according to the sum of feeder similarities corresponding to each feeder to be tested, the fault line of the feeder grounding fault is determined.

7. The method for identifying single-phase faults in a distribution network according to claim 6, wherein: When the fault type of the single-phase grounding fault is a feeder grounding fault, after determining the fault line of the feeder grounding fault according to the sum of feeder similarities corresponding to each feeder to be tested based on a preset feeder similarity threshold, the method further includes: The fault line of the feeder grounding fault is recorded as the target fault feeder; Based on the zero-sequence current time series data of each monitoring node corresponding to the target fault feeder, the zero-sequence current cosine similarity between adjacent monitoring nodes of the target fault feeder is calculated to generate a zero-sequence current similarity set of adjacent nodes; From the zero-sequence current similarity set of adjacent nodes, the minimum cosine similarity of zero-sequence current is selected as the target similarity; Determine whether the target similarity is less than the preset section location coefficient. If so, determine that the two monitoring nodes corresponding to the target similarity are fault nodes, and the section between the fault nodes is the fault feeder section; If not, it is determined that the end section after the end node of the faulty line of the single-phase grounding fault is the faulty feeder section.

8. A single-phase fault identification device for a distribution network, characterized in that: include: Data acquisition module, abnormality monitoring module, current asymmetry degree calculation module and abnormality type identification module; The data acquisition module is used to obtain the zero-sequence voltage time series data of the busbar to be tested in the distribution network, and the current time series data of the monitoring nodes of each feeder to be tested; wherein the busbar to be tested is connected to each feeder to be tested; the monitoring nodes include feeder end nodes; the current time series data includes negative sequence current time series data, zero sequence current time series data and positive sequence current time series data; The abnormality monitoring module is configured to determine a first mutation number of the zero-sequence voltage of the bus to be measured based on the zero-sequence voltage time series data; determine a second mutation number of the negative-sequence current of each feeder to be measured based on the negative-sequence current time series data; and determine whether there is an abnormality in the distribution network based on the first mutation number and the second mutation number; The current asymmetry degree calculation module is used to calculate the three-phase current asymmetry degree sequence of each feeder terminal node based on the current time series data when an abnormality occurs in the distribution network; The abnormality type identification module is used to determine the abnormality type of the distribution network according to the three-phase current asymmetry degree sequence and the current time series data.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for identifying a single-phase fault in a distribution network according to any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute the method for identifying single-phase faults in a distribution network according to any one of claims 1 to 7.

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