Fault location method, device, equipment, storage medium and product of power distribution network

Abstract

The application relates to a power distribution network fault positioning method, device, equipment, storage medium and product. The method comprises the following steps: in response to a fault occurring in a power distribution network, acquiring electrical signals of different fault recording devices in the power distribution network before and after the fault occurring in the power distribution network; processing each electrical signal respectively to obtain time-frequency characteristics of the corresponding fault recording device; selecting at least one candidate fault line from different power distribution lines of the power distribution network according to the time-frequency characteristics; and determining a target fault position of the power distribution network according to the time-frequency characteristics and historical fault information of each candidate fault line. The method can improve the fault positioning efficiency and meet the real-time requirement.

Description

Technical Field

[0001] This application relates to the field of power monitoring technology, and in particular to a method, apparatus, equipment, storage medium and product for fault location in power distribution networks. Background Technology

[0002] As a key link in the power system facing users, the power distribution network is of paramount importance in terms of power supply reliability. Therefore, fault location in the distribution network has gradually become a research hotspot in the field of power system security.

[0003] In traditional technologies, common fault location methods mainly utilize traveling wave data collected in real time by fault recording devices to perform global calculations, traversing all nodes to locate the fault.

[0004] However, this method suffers from technical problems such as low fault location efficiency and difficulty in meeting real-time requirements when dealing with distribution networks with complex topologies. Summary of the Invention

[0005] Therefore, it is necessary to provide a fault location method, device, equipment, storage medium, and product for power distribution networks that can improve fault location efficiency and meet real-time requirements, in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a fault location method for a distribution network, including:

[0007] In response to a fault in the distribution network, the electrical signals of different fault recording devices in the distribution network before and after the fault occurs are acquired.

[0008] Each electrical signal is processed separately to obtain the time-frequency characteristics of the corresponding fault recording device;

[0009] Based on the time-frequency characteristics, at least one candidate fault line is selected from different distribution lines in the distribution network.

[0010] Based on the time-frequency characteristics and historical fault information of each candidate fault line, the target fault location of the distribution network is determined.

[0011] In one embodiment, selecting at least one candidate fault line from different distribution lines of the distribution network based on each time-frequency feature includes: clustering each time-frequency feature to obtain at least two clusters; determining the membership degree of each time-frequency feature relative to the corresponding cluster based on the at least two clusters; selecting at least two target fault recording devices from each fault recording device based on each membership degree; and selecting at least one candidate fault line from different distribution lines of the distribution network based on each target fault recording device.

[0012] In one embodiment, selecting at least one candidate fault line from different distribution lines of the distribution network based on each target fault recording device includes: determining the location of each target fault recording device in the distribution network based on the topology information of the distribution network; determining the upstream common line of each target fault recording device based on the location of each target fault recording device in the distribution network; and selecting at least one candidate fault line from different distribution lines of the distribution network based on the upstream common line and the distribution lines connected to the end nodes of the upstream common line.

[0013] In one embodiment, determining the target fault location of the distribution network based on each time-frequency characteristic and the historical fault information of each candidate fault line includes: determining the target fault area in the distribution network based on the historical fault information of each candidate fault line; and determining the target fault location of the distribution network from the target fault area based on each time-frequency characteristic.

[0014] In one embodiment, each electrical signal is processed to obtain the time-frequency characteristics of the corresponding fault recording device, including: performing a phase-mode transformation on each electrical signal to obtain a zero-mode component and a line-mode component; performing wavelet transform on the zero-mode component and the line-mode component to obtain the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the line-mode component; and determining the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time.

[0015] In one embodiment, determining the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time includes: determining the difference between the first arrival time and the second arrival time; and determining the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first wavelet transform coefficient, the second wavelet transform coefficient, and the difference.

[0016] Secondly, this application also provides a fault location device for a power distribution network, comprising:

[0017] The acquisition module is used to acquire electrical signals from different fault recording devices in the distribution network before and after the fault occurs in response to a fault in the distribution network.

[0018] The processing module is used to process each electrical signal separately to obtain the time-frequency characteristics of the corresponding fault recording device;

[0019] The selection module is used to select at least one candidate fault line from different distribution lines in the distribution network based on various time-frequency characteristics.

[0020] The determination module is used to determine the target fault location of the distribution network based on various time-frequency characteristics and historical fault information of each candidate fault line.

[0021] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the various method embodiments of the first aspect described above.

[0022] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method embodiments of the first aspect described above.

[0023] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the method embodiments of the first aspect described above.

[0024] The aforementioned fault location method, device, equipment, storage medium, and product for the distribution network, in response to a fault in the distribution network, acquire electrical signals from different fault recording devices in the distribution network before and after the fault occurs; process each electrical signal to obtain the time-frequency characteristics of the corresponding fault recording device; select at least one candidate fault line from different distribution lines in the distribution network based on each time-frequency characteristic; and determine the target fault location of the distribution network based on each time-frequency characteristic and the historical fault information of each candidate fault line. In this way, each electrical signal is first processed to obtain the time-frequency characteristics of the corresponding fault recording device. This overcomes the shortcomings of traditional technology, which directly relies on the original electrical signals and is easily affected by noise interference, thus affecting the reliability of subsequent fault location. Based on each time-frequency characteristic, at least one candidate fault line is selected from different distribution lines in the distribution network, narrowing the scope of the target fault location and avoiding the computational redundancy and time consumption caused by traversing all distribution lines. Furthermore, the time-frequency characteristics of the fault recording device and the historical fault information of the candidate fault line are integrated to determine the target fault location. This method uses the time-frequency characteristics to reflect the propagation law of traveling waves and uses historical fault information to provide prior probability guidance, making up for the shortcomings of the inability to densely install fault recording devices along the entire distribution network and the limited data foundation they provide. This improves the accuracy and speed of fault location in the distribution network, thereby increasing the efficiency of fault location and meeting the real-time operation and maintenance needs of complex distribution networks. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is an application environment diagram of a fault location method for a power distribution network in one embodiment;

[0027] Figure 2 This is a flowchart illustrating a fault location method for a distribution network in one embodiment;

[0028] Figure 3 This is a flowchart illustrating the processing of various electrical signals in one embodiment;

[0029] Figure 4 This is a flowchart illustrating the time-frequency characteristics of a fault recording device corresponding to an electrical signal in one embodiment.

[0030] Figure 5 This is a flowchart illustrating the process of selecting at least one candidate faulty line in one embodiment.

[0031] Figure 6 This is a flowchart illustrating the selection of at least one candidate faulty line in another embodiment;

[0032] Figure 7 This is a flowchart illustrating the process of determining the target fault location in a power distribution network in one embodiment.

[0033] Figure 8 This is a flowchart illustrating a fault location method for a distribution network in another embodiment;

[0034] Figure 9 This is a structural block diagram of a fault location device for a power distribution network in one embodiment;

[0035] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0037] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0038] To save costs, fault recording devices in the distribution network cannot be densely installed along the entire line. This means that when the number of fault recording devices is limited, the electrical signals collected by some of the devices are affected by noise, distortion, or clock errors, which can easily introduce erroneous information and cause large errors in fault location. Furthermore, traversing all nodes in the distribution network based on the electrical signals collected by all fault recording devices consumes a lot of computational resources, resulting in low location efficiency and making it difficult to meet the real-time requirements of the distribution network for rapid power restoration.

[0039] In view of this, embodiments of this application provide a fault location method for a power distribution network.

[0040] The fault location method for distribution networks provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the fault recording device 102 communicates with the server 104 via a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated onto the server 104, or it can be located on a cloud or other network server. The server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The fault recording device is deployed at nodes on the distribution lines in the power distribution network to collect transient electrical signals before and after a fault, and uploads the collected electrical signals to the data storage system. The server 104 can obtain electrical signals from the data storage system to determine the target fault location in the power distribution network.

[0041] In one exemplary embodiment, such as Figure 2 As shown, a fault location method for a distribution network is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0042] S201, in response to a fault in the distribution network, acquires electrical signals from different fault recording devices in the distribution network before and after the fault occurs.

[0043] The distribution network is a network in the power system that directly distributes electrical energy to users. It consists of multiple distribution lines, each with multiple nodes. The fault recording device is triggered when a fault occurs in the distribution network (such as a short-circuit fault or ground fault), and it collects electrical signals from the device's location in real time before and after the fault, according to a preset sampling frequency.

[0044] Optionally, the electrical signals before and after a fault in the distribution network can be the three-phase current signal and three-phase voltage signal collected by the fault recording device at the corresponding location within a preset time period before and after the fault. The length of the preset time period can be flexibly set according to actual needs. This application embodiment does not limit this, for example, it can be 2ms before the fault occurs to 2ms after the fault occurs.

[0045] Optionally, the fault occurrence status of the distribution network can be determined based on the detection of the detection device and / or the triggering status of the fault recording device in the distribution network. If the fault occurrence status indicates that a fault has occurred in the distribution network, the electrical signals of different fault recording devices in the distribution network before and after the fault can be directly read from the data storage system.

[0046] S202 processes each electrical signal to obtain the time-frequency characteristics of the corresponding fault recording device.

[0047] Optionally, the time-frequency characteristics of the fault recording device are used to reflect the propagation and abrupt change characteristics of the electrical signal of the corresponding fault recording device in the time and frequency dimensions.

[0048] Optionally, for each fault recording device, the electrical signals before and after a fault occurs in the distribution network can be first extracted to obtain time-domain features that reflect the propagation and abrupt change characteristics of the electrical signal in the time dimension. Then, the electrical signal can be converted from time to frequency to extract features from the converted frequency-domain signal to obtain frequency-domain features that reflect the propagation and abrupt change characteristics of the electrical signal in the frequency dimension. Finally, the time-domain features and frequency-domain features can be fused to obtain the time-frequency features of the fault recording device.

[0049] S203, based on the time and frequency characteristics, select at least one candidate fault line from different distribution lines in the distribution network.

[0050] Optionally, the fault correlation of different distribution lines in the distribution network can be determined based on the time-frequency characteristics of each fault recording device, and the distribution lines with fault correlation higher than the preset correlation threshold can be identified as candidate fault lines.

[0051] Specifically, time-frequency characteristics can be mapped to fault contribution rates to reflect the proximity of the fault recording device corresponding to the time-frequency characteristics to the target fault location. A higher fault contribution rate indicates that the fault recording device is closer to the target fault location. Furthermore, for each distribution line in the distribution network, one or more fault recording devices that are close to or related to the distribution line can be selected based on the network's topology information. The fault correlation of the distribution line can then be determined based on the fault contribution rate of the selected fault recording devices. A higher fault correlation rate indicates a stronger correlation between the corresponding distribution line and the target fault location. Therefore, the fault correlation rate of each distribution line can be compared with a preset correlation threshold to identify candidate fault lines from among the distribution lines.

[0052] S204. Based on the time-frequency characteristics and historical fault information of each candidate fault line, determine the target fault location of the distribution network.

[0053] Optionally, the historical fault information of the candidate fault line can be statistical data on the faults that occurred on the candidate fault line within a historical time period. For example, the historical fault information of the candidate fault line includes the proportion of the number of times the nodes of the candidate fault line failed within a historical time period to the total number of faults that occurred in the distribution network within the historical time period.

[0054] Optionally, based on the historical fault information of each candidate fault line and the frequency of repeated occurrence of each node in all candidate fault lines, the similarity between each node and the target fault location can be determined. Furthermore, starting from the node with the highest similarity, based on the time-frequency characteristics of the fault recording device associated with each node, it can be determined whether the corresponding node meets the convergence condition corresponding to the target fault location, and the node that meets the convergence condition is determined as the target fault location.

[0055] The above-mentioned fault location method for distribution networks responds to a fault in the distribution network by acquiring electrical signals from different fault recording devices in the distribution network before and after the fault occurs; processing each electrical signal to obtain the time-frequency characteristics of the corresponding fault recording device; selecting at least one candidate fault line from different distribution lines in the distribution network based on each time-frequency characteristic; and determining the target fault location of the distribution network based on each time-frequency characteristic and the historical fault information of each candidate fault line. In this way, each electrical signal is first processed to obtain the time-frequency characteristics of the corresponding fault recording device. This overcomes the shortcomings of traditional technology, which directly relies on the original electrical signals and is easily affected by noise interference, thus affecting the reliability of subsequent fault location. Based on each time-frequency characteristic, at least one candidate fault line is selected from different distribution lines in the distribution network, narrowing the scope of the target fault location and avoiding the computational redundancy and time consumption caused by traversing all distribution lines. Furthermore, the time-frequency characteristics of the fault recording device and the historical fault information of the candidate fault line are integrated to determine the target fault location. This method uses the time-frequency characteristics to reflect the propagation law of traveling waves and uses historical fault information to provide prior probability guidance, making up for the shortcomings of the inability to densely install fault recording devices along the entire distribution network and the limited data foundation they provide. This improves the accuracy and speed of fault location in the distribution network, thereby increasing the efficiency of fault location and meeting the real-time operation and maintenance needs of complex distribution networks.

[0056] Based on the above embodiments, in an exemplary embodiment, such as Figure 3 As shown, the above-mentioned S202 process, which processes each electrical signal to obtain the time-frequency characteristics of the corresponding fault recording device, may include the following steps:

[0057] S301 performs phase-mode transformation on each electrical signal to obtain zero-mode and line-mode components.

[0058] Optionally, when the electrical signal is three-phase current data, a preset transformation matrix can be used to perform phase-mode transformation on the three-phase current data to obtain the zero-mode component and line-mode component of the three-phase current data.

[0059] For example, the preset transformation matrix can be a Karen Bell phase mode transformation matrix, and the process of performing phase mode transformation on electrical signals can be seen in the following equation (1).

[0060] (1)

[0061] in, , , These are the zero-mode component and the line-mode component of the three-phase current data, respectively. Components, Linear Model Quantity, , , These are the three-phase current data, and the line mode can be viewed here. The component is taken as the line-mode component of the three-phase current data and expressed as... And representing the zero-mode component of the three-phase current data as .

[0062] S302, perform wavelet transform on the zero-mode component and the linear-mode component respectively to obtain the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the linear-mode component.

[0063] Optionally, for the zero-mode component and the line-mode component, a wavelet basis that satisfies the preset conditions of support and regularity can be selected to perform discrete wavelet decomposition on the zero-mode component and the line-mode component respectively to obtain wavelet transform coefficients at different decomposition scales. Furthermore, the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the line-mode component can be determined based on the local modulus maxima in each wavelet transform coefficient, and the first wavelet transform coefficient corresponding to the first arrival time and the second wavelet transform coefficient corresponding to the second arrival time can be recorded.

[0064] The first wavelet transform coefficients are used to reflect the energy concentration or abrupt change intensity of the zero-mode component at the first arrival time and the first arrival frequency corresponding to the first arrival time. Correspondingly, the second wavelet transform coefficients are used to reflect the energy concentration or abrupt change intensity of the linear-mode component at the second arrival time and the second arrival frequency corresponding to the second arrival time.

[0065] S303, based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time, determine the time-frequency characteristics of the fault recording device corresponding to the electrical signal.

[0066] Optionally, the time-frequency characteristics can be in vector form; therefore, for each electrical signal of the fault recording device, the corresponding first arrival time can be determined. First wavelet transform coefficients Second arrival time and the second wavelet transform coefficients They are directly combined into a four-dimensional feature vector, and this feature vector is used as the time-frequency feature of the fault recording device corresponding to the electrical signal.

[0067] In this embodiment, the three-phase coupled electrical signals are decoupled into independent modal components by phase mode transformation, effectively eliminating inter-phase interference. Wavelet transform is used to determine the first arrival time corresponding to the zero-mode component and the second arrival time corresponding to the line-mode component. Based on the first arrival time, the first wavelet transform coefficient of the first arrival time, and the second arrival time and the second wavelet transform coefficient of the second arrival time, the time-frequency characteristics of the fault recording device corresponding to the electrical signal are determined. This ensures that the determined time-frequency characteristics can introduce local energy information at waveform abrupt changes while preserving the propagation law of the traveling wave in the time domain, providing a more comprehensive feature dimension for subsequent fault location, thereby improving the accuracy and reliability of fault location.

[0068] Based on the above embodiments, in an exemplary embodiment, such as Figure 4 As shown, the above-mentioned S303, which determines the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time, may include the following steps:

[0069] S401, determine the difference between the first arrival time and the second arrival time.

[0070] The difference between the first arrival time and the second arrival time can reflect the difference in the propagation speed of the zero-mode component and the linear-mode component during the propagation of the fault traveling wave from the target fault location to the corresponding fault recording device. The larger the difference, the longer the propagation path between the target fault location and the corresponding fault recording device.

[0071] S402, based on the first wavelet transform coefficient, the second wavelet transform coefficient, and the difference, determine the time-frequency characteristics of the fault recording device corresponding to the electrical signal.

[0072] Optionally, referring to equation (2), the first wavelet transform coefficients, the second wavelet transform coefficients, and the calculated difference can be combined to obtain the time-frequency characteristics of the fault recording device corresponding to the electrical signal. .

[0073] (2)

[0074] in, Let be the difference between the first arrival time and the second arrival time corresponding to the i-th fault recording device, i.e. .

[0075] In this embodiment, time-frequency features are constructed by combining the difference between the arrival time of the zero-mode traveling wave front and the arrival time of the linear-mode traveling wave front with the corresponding wavelet transform coefficients. This overcomes the shortcomings of traditional techniques that only use a single time dimension to construct fault filtering devices, and do not consider the differences in propagation speed of different modes of traveling waves, resulting in weak feature representation capabilities. This ensures that the obtained time-frequency features can more accurately reflect the distance between each fault recording device and the target fault location, providing an accurate, comprehensive, and reliable data foundation for subsequent fault location.

[0076] Based on the above embodiments, in an exemplary embodiment, such as Figure 5 As shown, in step S203 above, selecting at least one candidate fault line from different distribution lines in the distribution network based on various time-frequency characteristics may include the following steps:

[0077] S501, cluster each time-frequency feature to obtain at least two clusters.

[0078] Optionally, a fuzzy c-means clustering algorithm can be used, with multiple different clustering combinations preset, and the clustering cost function value corresponding to different clustering combinations calculated according to the following formula (3). The clusters included in the clustering combination that meets the convergence condition are taken as the clusters obtained by clustering.

[0079] (3)

[0080] in, Let N be the clustering cost function, and N be the total number of fault recording devices. For ease of calculation, the number of clusters is set to 2, meaning that the fault recording device corresponding to the time-frequency characteristics in the first cluster is farther from the target fault location than the fault recording device corresponding to the time-frequency characteristics in the second cluster. Let be the membership degree of the time-frequency characteristics of the i-th fault recording device relative to the k-th cluster. Let the cluster center be the k-th cluster. For fuzzy weighted index, It is the Euclidean norm, used to measure the distance between a sample and the cluster center.

[0081] S502, based on at least two clusters, determine the membership degree of each time-frequency feature relative to the corresponding cluster.

[0082] Optionally, the following formulas (4) and (5) can be used to alternately optimize and update the cluster center of each cluster and the membership degree of each time-frequency feature relative to the corresponding cluster, so as to obtain a cluster combination whose cluster cost function value satisfies the convergence condition. Furthermore, for each time-frequency feature, the membership degree of the time-frequency feature relative to the second cluster can be used as the final determined membership degree of the time-frequency feature relative to the corresponding cluster. That is, the membership degree of the time-frequency feature is used to reflect the distance or correlation degree between the fault recording device corresponding to the time-frequency feature and the target fault location.

[0083] (4)

[0084] in, Here, the cluster center of the k-th cluster is given by the condition that the cluster centers of the clusters are fixed. Let j be the cluster center of the j-th cluster.

[0085] (5)

[0086] S503, based on each membership degree, select at least two target fault recording devices from each fault recording device. Optionally, a membership degree threshold can be preset, and fault recording devices corresponding to time-frequency characteristics with membership degrees not lower than the preset membership degree threshold can be determined as target fault recording devices, and a target fault recording device set S can be constructed based on all target fault recording devices. high .

[0087] S504, based on each target fault recording device, select at least one candidate fault line from different distribution lines of the distribution network.

[0088] After a fault occurs at the target fault location, the fault traveling wave will propagate upstream and / or downstream along the distribution line. Therefore, the location of the target fault recording device is on the effective propagation path of the fault traveling wave. Thus, at least one candidate fault line can be identified from the distribution network based on the distribution line where each target fault recording device is located and the associated distribution line.

[0089] In this embodiment, the membership degree is determined by clustering analysis of the time-frequency characteristics of each fault recording device to quantify the distance or correlation between each fault recording transpose and the target fault location. Based on each membership degree, candidate fault lines are screened. This overcomes the technical defects of traditional technology, which directly uses the raw data collected by all fault recording devices and is susceptible to interference from low-quality and low-correlation data. This ensures the scientificity and reliability of candidate fault line screening. At the same time, it reduces the amount of subsequent data processing, provides a reliable data foundation for subsequent fault location, and saves computing resources.

[0090] Based on the above embodiments, in an exemplary embodiment, such as Figure 6As shown, in step S504 above, selecting at least one candidate fault line from different distribution lines in the distribution network based on each target fault recording device may include the following steps:

[0091] S601, based on the topology information of the distribution network, determine the location of each target fault recording device in the distribution network.

[0092] Among them, the topology information is used to describe the physical connection relationship and current supply direction between power distribution lines, nodes, and fault recording devices in the power distribution network.

[0093] Optionally, the topology information can be pre-stored in the data storage system. Therefore, the topology information of the distribution network can be directly obtained from the data storage system to determine the location of each target fault recording device in the distribution network based on the topology information. For example, it can include the identification of the distribution line to which the target fault recording device belongs and the distance between the target fault recording device and the end node of the distribution line to which it belongs.

[0094] S602, determine the upstream common line of each target fault recording device based on its location in the distribution network.

[0095] Optionally, for each target fault recording device, the upstream power distribution line of the target fault recording device can be determined according to its location in the power distribution network. Furthermore, based on the upstream power distribution lines of each target fault recording device, the overlapping part of the upstream power distribution lines of all target fault recording devices can be determined, and the overlapping part is taken as the upstream common line of each target fault recording device.

[0096] S603, select at least one candidate fault line from different distribution lines of the distribution network based on the upstream common line and the distribution lines connected to the end nodes of the upstream common line.

[0097] Optionally, based on the topology information of the distribution network, the location of the terminal node of the upstream common line (i.e., the downstream node in the upstream common line) can be determined first, and all downstream distribution lines with the terminal node as the upstream node and equipped with fault recording devices can be determined, so as to select candidate fault lines from all downstream distribution lines and the upstream common line.

[0098] Specifically, if the distance between any two downstream distribution lines and any two upstream common lines does not exceed the distance threshold, all downstream distribution lines and upstream common lines can be directly regarded as candidate fault lines; however, if one or more downstream distribution lines and the distance between them and the remaining lines exceeds the distance threshold, the remaining lines other than those one or more lines can be regarded as candidate fault lines.

[0099] In this embodiment, by combining the distribution network topology information, the upstream common line and the downstream power supply line of the terminal node of each target fault recording device are traced to determine the candidate fault line. This overcomes the shortcomings of traditional technology, which only determines the candidate fault line based on the location of the fault recorder, resulting in the wrong selection of non-fault related lines or an excessively large scope. This further narrows the scope of fault investigation, avoids the traversal calculation of irrelevant distribution lines, and thus improves the efficiency of fault location.

[0100] Based on the above embodiments, in an exemplary embodiment, such as Figure 7 As shown, S204 above, determining the target fault location of the distribution network based on various time-frequency characteristics and historical fault information of each candidate faulty line, may include the following steps:

[0101] S701 determines the target fault area from the distribution network based on the historical fault information of each candidate faulty line.

[0102] Optionally, for each candidate faulty line, the weighted probability of the existence of a target fault location on the candidate faulty line can be determined based on the historical fault information of the candidate faulty line and the time-frequency characteristics associated with the candidate faulty line. If the weighted probability is higher than the preset probability, the candidate faulty line corresponding to the weighted probability is determined as the target faulty line. Then, the target fault area is determined based on all target faulty lines.

[0103] For example, candidate fault lines can be calculated according to the following formula (6). The weighted probability of the target fault location exists. .

[0104] (6)

[0105] in, Candidate faulty lines The value is the proportion of the number of times a node in a candidate faulty line fails within a historical time period to the total number of faults in the distribution network within the historical time period, where M (j, k ∈ M and j, k, and M are all positive integers) is the total number of candidate faulty lines. Candidate faulty lines The arithmetic mean of the membership degrees of the time-frequency characteristics of all associated fault recording devices in the candidate fault line. In the case of deploying fault recording devices in China, Candidate faulty lines The arithmetic mean of the membership degrees of the time-frequency characteristics of each fault recording device deployed in the center, in the candidate fault line. In the case of deploying fault recording devices in China, You can directly choose a smaller preset value, and correspondingly, Candidate faulty lines The proportion of the number of times a node in a candidate faulty line fails within a historical period to the total number of faults in the distribution network within the historical period. Candidate faulty lines The arithmetic mean of the membership degrees of the time-frequency characteristics of each fault recording device deployed in the center.

[0106] For example, each target faulty line can be directly merged and the merged area can be used as the target faulty area. Alternatively, a pre-defined area can be defined as the target faulty area based on the location of each target faulty line.

[0107] S702 determines the target fault location of the distribution network from the target fault area based on various time and frequency characteristics.

[0108] Optionally, the target fault area can be searched first with a step length to obtain multiple candidate fault locations. The location loss function value of each candidate fault location is calculated based on various time-frequency characteristics. The candidate fault location with the smallest loss function value is selected as the reference fault center. The system then expands upstream and downstream of this reference fault center by a first preset length to form a reference fault area. A new target fault area is determined based on this reference fault area and the target fault area. The target fault area is then searched with a second step length (smaller than the first step length) to obtain multiple new candidate fault locations. The location loss function value of each new candidate fault location is calculated based on various time-frequency characteristics. The smallest location loss function value is selected, and it is determined whether this smallest location loss function value satisfies the requirements. If the preset location loss function threshold is met, the candidate fault location corresponding to the smallest location loss function value can be used as the target fault location. If the preset location loss function threshold is not met, the candidate fault location with the smallest loss function value can be used as a new reference fault center. A new reference fault region is formed by expanding upstream and downstream of this new reference fault center along a second preset length. The process then returns to the previous steps, determining a new target fault region based on the reference fault region and the target fault region, and searching for the target fault region with a second step size (the second step size is less than the first step size), or with other smaller step sizes, until the target fault location is determined. The second preset length can be obtained by weighting the first preset length.

[0109] For example, the localization loss function shown in equation (7) can be used. Calculate the location loss function value of the candidate fault location F.

[0110] (7)

[0111] in, and These represent the wave velocities of the zero mode and the linear mode, respectively. This represents the distance the traveling wave travels to the i-th waveform recorder when the candidate fault location F is the target fault location. This represents the distance the fault traveling wave travels to the j-th waveform recorder when the candidate fault location F is the target fault location. It is the difference between the first arrival time and the second arrival time corresponding to the j-th fault recording device.

[0112] For example, a new target fault region is determined based on the reference fault region and the target fault region. The process can be expressed as follows (8).

[0113] (8)

[0114] in, For the previously identified target fault area, For reference fault area, For reference fault center, R is the first preset length.

[0115] In this embodiment, the target fault area is first determined based on the historical fault information of each candidate faulty line, and then the target fault location is determined by combining time and frequency characteristics. This overcomes the shortcomings of traditional technology, which relies solely on real-time data collected by fault recording devices for fault location. When the number of fault recording devices is limited, location deviations and low troubleshooting efficiency are likely to occur. Thus, by using prior guidance from historical fault information, the target fault area is first locked, and then precise location is achieved by combining time and frequency characteristics. This realizes the fusion of prior information and real-time data, thereby improving the accuracy of fault location, reducing computational redundancy in the global search, and accelerating the location speed.

[0116] Based on the above embodiments, in an exemplary embodiment, an optional fault location method for a distribution network is provided, such as... Figure 8 As shown, the following steps may be included:

[0117] S801, in response to a fault in the distribution network, acquires electrical signals from different fault recording devices in the distribution network before and after the fault occurs.

[0118] S802 performs phase-mode transformation on each electrical signal to obtain zero-mode and line-mode components.

[0119] S803 performs wavelet transform on the zero-mode component and the linear-mode component respectively to obtain the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the linear-mode component.

[0120] S804, determine the difference between the first arrival time and the second arrival time.

[0121] S805, based on the first wavelet transform coefficient, the second wavelet transform coefficient, and the difference, determine the time-frequency characteristics of the fault recording device corresponding to the electrical signal.

[0122] S806, cluster each time-frequency feature to obtain at least two clusters.

[0123] S807, based on at least two clusters, determine the membership degree of each time-frequency feature relative to the corresponding cluster.

[0124] S808, select at least two target fault recording devices from each fault recording device according to each membership degree.

[0125] S809 determines the location of each target fault recording device in the distribution network based on the topology information of the distribution network.

[0126] S810 determines the location of each target fault recording device in the distribution network based on the topology information of the distribution network.

[0127] S811, select at least one candidate fault line from different distribution lines of the distribution network based on the upstream common line and the distribution lines connected to the end nodes of the upstream common line.

[0128] S812 determines the target fault area from the distribution network based on the historical fault information of each candidate faulty line.

[0129] S813 determines the target fault location of the distribution network from the target fault area based on various time and frequency characteristics.

[0130] The specific processes of S801-S813 described above can be found in the description of the above method embodiments. Their implementation principles and technical effects are similar, and will not be repeated here.

[0131] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0132] Based on the same inventive concept, this application also provides a fault location device for a distribution network to implement the fault location method for the distribution network described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more fault location device embodiments for distribution networks provided below can be found in the limitations of the fault location method for distribution networks described above, and will not be repeated here.

[0133] In one exemplary embodiment, such as Figure 9 As shown, a fault location device for a power distribution network is provided, comprising: an acquisition module 910, a processing module 920, a selection module 930, and a determination module 940, wherein:

[0134] The acquisition module 910 is used to acquire electrical signals from different fault recording devices in the distribution network before and after the fault occurs in response to a fault in the distribution network.

[0135] The processing module 920 is used to process each electrical signal separately to obtain the time-frequency characteristics of the corresponding fault recording device;

[0136] Selection module 930 is used to select at least one candidate fault line from different distribution lines in the distribution network based on various time-frequency characteristics.

[0137] The determination module 940 is used to determine the target fault location of the distribution network based on the time-frequency characteristics and historical fault information of each candidate fault line.

[0138] In one embodiment, the processing module 920 may include:

[0139] The phase-mode conversion unit is used to perform phase-mode conversion on each electrical signal to obtain the zero-mode component and the line-mode component.

[0140] The wavelet transform unit is used to perform wavelet transform on the zero-mode component and the line-mode component respectively to obtain the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the line-mode component.

[0141] The first determining unit is used to determine the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time.

[0142] In one embodiment, the first determining unit is specifically used to determine the difference between the first arrival time and the second arrival time; and to determine the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first wavelet transform coefficient, the second wavelet transform coefficient and the difference.

[0143] In one embodiment, the selection module 930 may include:

[0144] Clustering units are used to cluster each time-frequency feature to obtain at least two clusters.

[0145] The second determining unit is used to determine the membership degree of each time-frequency feature relative to the corresponding cluster based on at least two clusters.

[0146] The first selection unit is used to select at least two target fault recording devices from each fault recording device according to each membership degree.

[0147] The second selection unit is used to select at least one candidate fault line from different distribution lines of the distribution network according to each target fault recording device.

[0148] In one embodiment, the second selection unit is specifically used to determine the location of each target fault recording device in the distribution network based on the topology information of the distribution network; determine the upstream common line of each target fault recording device based on the location of each target fault recording device in the distribution network; and select at least one candidate fault line from different distribution lines of the distribution network based on the upstream common line and the distribution line connected to the end node of the upstream common line.

[0149] In one embodiment, the determining module 940 is specifically used to determine the target fault area from the distribution network based on the historical fault information of each candidate fault line; and to determine the target fault location of the distribution network from the target fault area based on each time-frequency characteristic.

[0150] Each module in the aforementioned fault location device for the power distribution network can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0151] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores electrical signals. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When the computer program is executed by the processor, it implements a fault location method for a power distribution network.

[0152] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0153] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0154] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0155] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0156] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0157] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0158] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for fault location of a power distribution network, characterized in that, The method includes: In response to a fault in the distribution network, the electrical signals of different fault recording devices in the distribution network before and after the fault occurs are acquired. Each electrical signal is processed separately to obtain the time-frequency characteristics of the corresponding fault recording device; Based on the time-frequency characteristics, at least one candidate fault line is selected from different power distribution lines of the power distribution network. Based on the time-frequency characteristics and the historical fault information of each candidate fault line, the target fault location of the distribution network is determined.

2. The method of claim 1, wherein, The step of selecting at least one candidate fault line from different distribution lines of the distribution network based on various time-frequency characteristics includes: Clustering is performed on each of the aforementioned time-frequency features to obtain at least two clusters; Based on at least two clusters, determine the membership degree of each time-frequency feature relative to the corresponding cluster; Based on the membership degree, at least two target fault recording devices are selected from each of the fault recording devices; Based on the target fault recording devices, at least one candidate fault line is selected from different distribution lines of the power distribution network.

3. The method of claim 2, wherein, The step of selecting at least one candidate fault line from different distribution lines of the distribution network according to each of the target fault recording devices includes: Based on the topology information of the power distribution network, determine the location of each target fault recording device in the power distribution network; Based on the location of each target fault recording device in the power distribution network, determine the upstream common line of each target fault recording device; Based on the upstream common line and the distribution lines connected to the end node of the upstream common line, at least one candidate fault line is selected from different distribution lines of the distribution network.

4. The method of claim 1, wherein, The step of determining the target fault location of the distribution network based on each time-frequency characteristic and the historical fault information of each candidate fault line includes: Based on the historical fault information of each of the candidate fault lines, the target fault area is determined from the distribution network; Based on the aforementioned time-frequency characteristics, the target fault location of the distribution network is determined from the target fault region.

5. The method of claim 1, wherein, The process of processing each electrical signal to obtain the time-frequency characteristics of the corresponding fault recording device includes: For each of the electrical signals, a phase-mode transformation is performed on the electrical signal to obtain a zero-mode component and a line-mode component; Wavelet transforms are performed on the zero-mode component and the linear-mode component respectively to obtain the first arrival time of the traveling wave front of the zero-mode component and the second arrival time of the traveling wave front of the linear-mode component. The time-frequency characteristics of the fault recording device corresponding to the electrical signal are determined based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time.

6. The method of claim 5, wherein, The step of determining the time-frequency characteristics of the fault recording device corresponding to the electrical signal based on the first arrival time, the first wavelet transform coefficient of the first arrival time, the second arrival time, and the second wavelet transform coefficient of the second arrival time includes: Determine the difference between the first arrival time and the second arrival time; The time-frequency characteristics of the fault recording device corresponding to the electrical signal are determined based on the first wavelet transform coefficient, the second wavelet transform coefficient, and the difference.

7. A fault location device for an electrical distribution network, characterised in that, The device includes: The acquisition module is used to acquire electrical signals from different fault recording devices in the distribution network before and after the fault occurs in the distribution network in response to a fault in the distribution network. The processing module is used to process each electrical signal separately to obtain the time-frequency characteristics of the corresponding fault recording device; The selection module is used to select at least one candidate fault line from different distribution lines of the distribution network based on various time-frequency characteristics. The determination module is used to determine the target fault location of the distribution network based on each time-frequency characteristic and the historical fault information of each candidate fault line.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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