Fault rapid positioning method, system and device for distribution network line

Abstract

This invention discloses a method, system, and device for rapid fault location in distribution network lines, relating to the field of distribution network fault measurement and location. The method includes: acquiring line equipment, constructing topology relationships, and generating a distribution network line topology diagram database; acquiring voltage event records uploaded by smart meters within a preset window; traversing and distinguishing the completeness of event records to obtain complete and incomplete voltage event record sets; performing associated topology prediction and completion on the incomplete voltage event record set based on the smart meter identifier, the topology diagram database, and the complete voltage event record set; determining high-confidence fault sections based on the smart meter identifier, the topology diagram database, and the complete and completed voltage event record sets; cross-validating the fault with the fault indicator and feeder terminal; and using the high-confidence fault section as the fault location result after successful cross-validation. This addresses the technical problem of low accuracy in existing fault location methods, achieving a significant improvement in fault location accuracy.

Description

Technical Field

[0001] This application relates to the field of distribution network fault measurement and location, and in particular to methods, systems and equipment for rapid location of distribution network line faults. Background Technology

[0002] Rapid and accurate fault location in distribution network lines is crucial for ensuring power supply reliability and reducing outage losses. This is especially true in complex power grid environments with distributed generation and enhanced user-side interaction, where fault location efficiency directly impacts emergency repair resource allocation and user satisfaction. Currently, the industry primarily relies on traveling wave or impedance methods based on fault indicator action signals, combined with topology analysis from distribution automation master stations, to determine fault sections. However, existing methods overly depend on the real-time signal transmission quality of a single type of sensor and are susceptible to line parameter errors, multi-branch topology interference, and reverse power flow from distributed generation in tree-like or ring-like distribution networks. This leads to a high rate of false fault identification, particularly in transient or weak fault scenarios where blind spots exist.

[0003] Currently, the accuracy of fault location in distribution network lines is low. Summary of the Invention

[0004] This application provides a method, system, and equipment for rapid fault location in distribution network lines. It employs techniques such as constructing a topology database of the target distribution network line, collecting voltage event records within a preset window of a smart energy meter and classifying them into complete and incomplete data, using topology correlation prediction to complete missing records, combining complete and supplemented data to locate high-confidence fault sections, and finally determining the fault location through cross-verification of fault indicators and feeder terminal action records. These techniques solve the technical problem of low accuracy in existing distribution network line fault location and achieve the technical effect of improving fault location accuracy.

[0005] This application provides a method for rapid fault location in distribution network lines, comprising: acquiring the line equipment of the target distribution network line and constructing a topology relationship based on a distribution automation system to generate a distribution network line topology diagram database; acquiring voltage event records uploaded by smart meters of the target distribution network line within a preset window to obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart meter identifier; traversing the voltage event record set to distinguish event record integrity, obtaining a complete voltage event record set and an incomplete voltage event record set; performing associated topology prediction and completion on the incomplete voltage event record set based on the smart meter identifier, the distribution network line topology diagram database, and the complete voltage event record set to obtain a completed voltage event record set; determining a high-confidence fault section of the target distribution network line based on the smart meter identifier, the distribution network line topology diagram database, the complete voltage event record set, and the completed voltage event record set; cross-validating the high-confidence fault section by interacting with the action records of the fault indicator and the feeder terminal; if the verification is successful, the high-confidence fault section is taken as the fault location result.

[0006] In a possible implementation, the voltage event record set is traversed to distinguish event record integrity, resulting in a complete voltage event record set and an incomplete voltage event record set. The following processing is then performed: the voltage event record set is identified for event record integrity according to preset record fields, resulting in a complete voltage event record set and an incomplete voltage event record set; a first incomplete voltage event record is extracted from the incomplete voltage event record set; based on the smart meter identifier, all complete voltage event records with the same smart meter identifier as the first incomplete voltage event record are selected from the complete voltage event record set to form a first matching complete voltage event record set; and combined with the record timestamp identifier, it is determined whether there is a complete voltage event record in the first matching complete voltage event record set whose record time interval with the first incomplete voltage event record is within a preset time interval threshold. If so, the first incomplete voltage event record is added to the complete voltage event record set; otherwise, the first incomplete voltage event record is retained in the incomplete voltage event record set.

[0007] In a possible implementation, the incomplete voltage event record set is supplemented by associative topology prediction based on the smart meter identifier, the distribution network topology database, and the complete voltage event record set to obtain a complete voltage event record set. The following processing is then performed: based on the smart meter identifier corresponding to the incomplete voltage event record set, the smart meter is located in the distribution network topology database, and a neighboring set of candidate smart meters is extracted; based on the neighboring set of candidate smart meters, the corresponding complete voltage event record is extracted from the complete voltage event record set to obtain a neighboring set of associated complete voltage event records; the propagation path is extracted from the distribution network topology database, and combined with the neighboring set of associated complete voltage event records, associative topology prediction is performed on the incomplete voltage event record set to obtain the complete voltage event record set.

[0008] In a possible implementation, the propagation path is extracted from the distribution network line topology diagram database. Combined with the neighborhood set of associated complete voltage event records, the incomplete voltage event record set is subjected to associated topology prediction and completion to obtain the completed voltage event record set. The following processing is then performed: based on the missing fields in the incomplete voltage event record set, associated topology prediction and completion rules are invoked to perform data analysis on the neighborhood set of associated complete voltage event records according to the propagation path, thereby obtaining the completed voltage event record set. The associated topology prediction and completion rules include start time completion rules, amplitude and duration completion rules, and phase completion rules.

[0009] In a possible implementation, the following process is performed: determine whether the neighborhood quantity in the neighborhood set of the associated candidate smart energy meters meets the requirements; if not, expand the neighborhood in the distribution network line topology diagram database from the two dimensions of topological similarity and signal similarity, and add the expanded associated candidate smart energy meters into the corresponding associated candidate smart energy meter neighborhood.

[0010] In a possible implementation, based on smart meter identifiers, a distribution network topology database, a complete voltage event record set, and a complete voltage event record set, a high-confidence fault section of the target distribution network line is determined, and the following processing is performed: Based on the smart meter identifiers in the complete voltage event record set and the complete voltage event record set, a candidate fault section search is performed in the distribution network topology database to determine multiple candidate fault sections, multiple complete voltage event record sets for multiple candidate fault sections, and multiple complete voltage event record sets for multiple candidate fault sections; the complete voltage event record sets for multiple candidate fault sections and the complete voltage event record sets for multiple candidate fault sections are extracted according to preset voltage drop characteristics to obtain the complete voltage event record sets for multiple candidate fault sections. A voltage sag feature set and a complete voltage sag feature set for multiple candidate fault segments are generated. The preset voltage sag features include voltage sag amplitude, duration, event timing differences, and phase consistency. The complete voltage sag feature set for multiple candidate fault segments and the complete voltage sag feature set for multiple candidate fault segments are merged into a single voltage sag feature set for multiple candidate fault segments. The voltage sag feature set for multiple candidate fault segments is then filtered according to the central iterative update bandwidth to determine the central voltage sag feature for multiple candidate fault segments. Fault confidence analysis is performed based on the central voltage sag feature for multiple candidate fault segments to determine multiple fault confidence levels. The candidate fault segment corresponding to the maximum value among the multiple fault confidence levels is designated as a high-confidence fault segment.

[0011] In a possible implementation, the voltage drop feature sets of multiple candidate fault sections are filtered according to the center iterative update bandwidth to determine the center voltage drop features of multiple candidate fault sections. The following processing is performed: the mean of the voltage drop feature sets of multiple candidate fault sections is calculated to obtain the mean of the voltage drop features of multiple candidate fault sections; the mean of the voltage drop features of multiple candidate fault sections is iteratively updated in the voltage drop feature sets of multiple candidate fault sections according to the center iterative update bandwidth to obtain multiple iterative candidate fault section voltage drop features; it is determined whether the center coefficient of the multiple iterative candidate fault section voltage drop features is greater than the center coefficient of the mean of the voltage drop features of multiple candidate fault sections. If so, the multiple iterative candidate fault section voltage drop features are iteratively updated according to the preset center point iterative update bandwidth until the center coefficient of the iterative candidate fault section voltage drop features obtained in this iteration is less than or equal to the center coefficient of the iterative candidate fault section voltage drop features obtained in the previous iteration. The iteration is stopped, and the iterative candidate fault section voltage drop features obtained in the previous iteration are respectively used as the center voltage drop features of multiple candidate fault sections.

[0012] In a possible implementation, the line equipment of the target distribution network line is obtained, and a topology relationship is constructed based on the distribution automation system to generate a distribution network line topology diagram database. The following processes are performed: data extraction and unified encoding of the line equipment based on the distribution automation system are performed to construct a standardized equipment dataset; node objects and edge objects are extracted from the standardized equipment dataset, wherein node objects include transformer low-voltage busbars, switch terminals, branch joints, meter box nodes, and energy meter nodes, and edge objects include conductor segments and cable segments; based on switch status and physical connection relationships, as well as the node objects and edge objects, the distribution network line topology relationship is constructed to obtain the distribution network line topology diagram database.

[0013] This application also provides a rapid fault location system for distribution network lines, including: a topology construction module, used to acquire the line equipment of the target distribution network line and construct the topology based on the distribution automation system to generate a distribution network line topology diagram database; a voltage event record acquisition module, used to acquire voltage event records uploaded by smart meters of the target distribution network line within a preset window to obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart meter identifier; and an event record integrity differentiation module, used to traverse the voltage event record set to differentiate event record integrity, obtaining a complete voltage event record set and an incomplete voltage event record set. The system includes: an event record set; a topology prediction and completion module, used to perform topology prediction and completion on the incomplete voltage event record set based on the smart meter identifier, the distribution network line topology diagram database, and the complete voltage event record set, to obtain a completed voltage event record set; and a fault location module, used to determine the high-confidence fault section of the target distribution network line based on the smart meter identifier, the distribution network line topology diagram database, the complete voltage event record set, and the completed voltage event record set. The module cross-verifies the high-confidence fault section using the action records of the interactive fault indicator and the feeder terminal. If the verification is successful, the high-confidence fault section is taken as the fault location result.

[0014] This application also provides an electronic device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement a method for rapid fault location in a power distribution network.

[0015] The proposed method, system, and equipment for rapid fault location in distribution network lines first acquire the line equipment of the target distribution network line and construct a topology relationship based on the distribution automation system to generate a distribution network line topology diagram database. Then, it acquires voltage event records uploaded by smart meters of the target distribution network line within a preset window to obtain a voltage event record set. Each voltage event record includes a recording timestamp and a smart meter identifier. Next, it traverses the voltage event record set to distinguish event record completeness, obtaining a complete voltage event record set and an incomplete voltage event record set. Then, based on the smart meter identifier, the distribution network line topology diagram database, and the complete voltage event record set, it performs associative topology prediction to complete the incomplete voltage event record set, obtaining a complete voltage event record set. Finally, based on the smart meter identifier, the distribution network line topology diagram database, the complete voltage event record set, and the complete voltage event record set, it determines the high-confidence fault section of the target distribution network line. The action records of the interactive fault indicator and feeder terminal are used to cross-verify the high-confidence fault section. If the verification is successful, the high-confidence fault section is taken as the fault location result. This achieved the technical effect of improving the accuracy of fault location. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating the method for rapid fault location in distribution network lines provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the structure of the rapid fault location system for distribution network lines provided in the embodiments of this application.

[0019] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0020] Explanation of reference numerals in the attached figures: Topology relationship construction module 10, voltage event record acquisition module 20, event record integrity differentiation module 30, associated topology prediction and completion module 40, fault location module 50, input device 301, processor 302, memory 303, output device 304. Detailed Implementation

[0021] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0024] This application provides a method for rapid fault location in distribution network lines, such as... Figure 1 As shown, the method includes: Step S100: Obtain the line equipment of the target distribution network line, and construct the topology relationship based on the distribution automation system to generate a distribution network line topology diagram database.

[0025] Specifically, the system obtains relevant information about all line equipment in the target distribution network line, such as equipment type, equipment number, and equipment location, through the interface provided by the distribution automation system. Using graph structure construction algorithms from graph theory, the line equipment is treated as nodes in the graph, and the connections between equipment are treated as edges, thus constructing the topology of the distribution network line. This constructed topology is stored in a database, forming a distribution network line topology graph database. This database supports fast querying and retrieval of topology connection information between equipment. The distribution automation system is a comprehensive information management system integrating computer technology, data transmission, control technology, modern equipment, and management. It is used for real-time monitoring, control, and management of the distribution network, improving power supply reliability and quality.

[0026] For example, in a real distribution network, there are multiple substations, branch boxes, and user terminals. After obtaining detailed information about these devices through the distribution automation system, starting from the substation, the branch boxes and user terminals are connected sequentially according to the actual connection order of the line, constructing the topology of the entire distribution network and storing it in a database. For example, substation A connects to branch box B, and branch box B connects to user terminals C and D respectively. In the database, this connection relationship is represented by corresponding nodes and edges.

[0027] In one possible implementation, the line equipment of the target distribution network line is acquired, and a topology relationship is constructed based on the distribution automation system to generate a distribution network line topology diagram database. Step S100 further includes step S110, which involves extracting and uniformly encoding data from the line equipment based on the distribution automation system to construct a standardized equipment dataset. Specifically, the distribution automation system stores massive amounts of raw data on various line equipment in the target distribution network line. This data comes from different subsystems or equipment manufacturers, and the formats and standards differ. In this step, data extraction tools, such as ETL tools (Extract-Transform-Load), are used to extract relevant data of the line equipment from various data sources in the distribution automation system, including basic equipment information, operating parameters, location information, etc. After data extraction, the equipment is encoded according to pre-defined unified encoding rules to ensure that each device has a unique and standardized code. The extracted and encoded data is stored in the database to form a standardized equipment dataset.

[0028] For example, the original data for a transformer with model number S11-M-500 / 10 includes the equipment name "Transformer 1", model number "S11-M-500 / 10", and installation location "XX substation 10kV side". Following a unified coding rule, the code is composed of the equipment type code, substation code, and equipment serial number. For example, assuming the transformer's equipment type code is T, the substation code is XX, and the equipment serial number is 001, then the transformer's code is "T-XX-001". All extracted equipment data is processed in this way and stored in the database to form a standardized equipment dataset.

[0029] Step S120: Extract node objects and edge objects from the standardized equipment dataset. Node objects include transformer low-voltage busbars, switch terminals, branch joints, meter box nodes, and energy meter nodes. Edge objects include conductor segments and cable segments. Specifically, node objects and edge objects are defined based on the physical structure and electrical characteristics of the distribution network lines. Node objects represent key connection points or equipment points in the distribution network lines, and edge objects represent the conductors or cables connecting these nodes. From the standardized equipment dataset, through data querying and filtering, equipment information conforming to the node object definition is extracted, including transformer low-voltage busbars, switch terminals, branch joints, meter box nodes, and energy meter nodes. Simultaneously, information representing conductor segments and cable segments is extracted as edge objects, including attributes such as conductor or cable type, length, and specifications.

[0030] Step S130: Based on the switch status and physical connection relationships, as well as the node objects and edge objects, a distribution network line topology relationship is constructed to obtain a distribution network line topology diagram database. Specifically, the switch status directly affects the distribution network line topology structure, such as closed and open. Combining the real-time switch status information obtained from the distribution automation system, and the node objects and edge objects extracted in step S120, the topology relationship of the distribution network lines is constructed using graph construction algorithms in graph theory. Node objects are used as vertices in the graph, and edge objects are used as edges in the graph. The connection method between edges and nodes is determined according to the physical connection relationships and switch status. For example, when the switch is in the closed state, the corresponding edge connects two nodes, indicating that there is an electrical connection between these two nodes; when the switch is in the open state, the corresponding edge is disconnected, indicating that there is electrical isolation between these two nodes. After the topology relationship is constructed, the topology structure is stored in the database in a graphical or data structured form to form a distribution network line topology diagram database.

[0031] Step S200: Obtain the voltage event records uploaded by the smart energy meters of the target distribution network line within a preset window, and obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart energy meter identifier.

[0032] Specifically, a smart meter is an energy meter with functions such as energy metering, information storage and processing, real-time monitoring, automatic control, and information interaction. It can record electrical parameters such as voltage, current, and power, as well as information such as voltage events. A preset window refers to a pre-defined time range used to collect and process the data uploaded by the smart meter in segments, such as every 15 minutes, 30 minutes, or 1 hour.

[0033] Specifically, a voltage event recording function is set up in the smart energy meter. When an abnormal voltage change occurs, the smart energy meter automatically records the timestamp of the event and its own identification information. Abnormal voltage changes include voltage drops, surges, and interruptions. The recorded voltage events are uploaded to the main station system via a communication network according to a preset time window. The main station system collects and organizes the received voltage event records to form a voltage event record set.

[0034] Step S300: Traverse the voltage event record set to distinguish the integrity of the event records, and obtain a complete voltage event record set and an incomplete voltage event record set.

[0035] Specifically, a set of rules for judging the integrity of voltage event records is established. For example, a complete voltage event record should include key information such as the event start time, event end time, and voltage change amplitude. Each record in the voltage event record set is traversed, and its integrity is checked according to these rules. Records that meet the integrity requirements are added to the complete voltage event record set, while those that do not meet the requirements are added to the incomplete voltage event record set.

[0036] In one possible implementation, the voltage event record set is traversed to distinguish event record integrity, resulting in a complete voltage event record set and an incomplete voltage event record set. Step S300 further includes step S310, which identifies the event record integrity of the voltage event record set according to preset record fields, resulting in a complete voltage event record set and an incomplete voltage event record set. Specifically, a set of key record fields for determining the integrity of voltage event records is predefined. These fields include, but are not limited to, event type, event occurrence time, event duration, voltage amplitude change, and smart meter identification. Then, each record in the voltage event record set is traversed, and each record is checked to see if it contains all the preset key record fields. If a record contains all the key fields, and the values ​​of these fields meet the corresponding data format and valid range requirements, then the record is determined to be a complete voltage event record and placed in the complete voltage event record set; conversely, if any key field is missing or the field value does not meet the requirements, then it is determined to be an incomplete voltage event record and placed in the incomplete voltage event record set.

[0037] Step S320: Extract the first incomplete voltage event record from the incomplete voltage event record set. Specifically, from the incomplete voltage event record set obtained in step S310, extract any record in a certain order as the first incomplete voltage event record. That is, the first incomplete voltage event record is any record in the incomplete voltage event record set that needs to be analyzed and processed.

[0038] Step S330: Based on the smart meter identifier, select all complete voltage event records in the complete voltage event record set whose smart meter identifiers are the same as the first incomplete voltage event record, forming a first matching complete voltage event record set. Combined with the recording timestamp identifier, determine whether there is a complete voltage event record in the first matching complete voltage event record set whose recording time interval is within a preset time interval threshold of the first incomplete voltage event record. If so, add the first incomplete voltage event record to the complete voltage event record set. Specifically, firstly, extract the smart meter identifier from the first incomplete voltage event record. Then, in the complete voltage event record set, select all records whose smart meter identifiers are the same as the first incomplete voltage event record, forming a first matching complete voltage event record set. Next, extract the recording timestamp, i.e., the event occurrence time, from the first incomplete voltage event record, and calculate the time interval between each record in the first matching complete voltage event record set and the first incomplete voltage event record. If there is at least one complete voltage event record whose time interval with the first incomplete voltage event record is within a preset time interval threshold, then this first incomplete voltage event record is considered to be able to assist in the analysis through other complete records, and therefore is added to the complete voltage event record set.

[0039] Step S340: If not, the first incomplete voltage event record is retained in the incomplete voltage event record set. Specifically, if in the determination of step S330, there is no matching complete voltage event record in the first matching complete voltage event record set whose recording time interval is within a preset time interval threshold, then this first incomplete voltage event record cannot be analyzed with the help of other complete records and needs to be retained in the incomplete voltage event record set for subsequent data repair.

[0040] Step S400: Based on the smart energy meter identifier, the distribution network line topology database, and the complete voltage event record set, perform correlation topology prediction to complete the incomplete voltage event record set, thereby obtaining the complete voltage event record set.

[0041] Specifically, based on the smart meter's identifier, the location of the meter and other connected devices are located in the distribution network topology database. Using information from the complete voltage event record set, the propagation patterns and topological relationships of voltage events in the distribution network are analyzed. For each record in the incomplete voltage event record set, a topology-based prediction method is used to complete the missing information based on its location and the voltage event information of adjacent devices, thus obtaining a complete voltage event record set.

[0042] In one possible implementation, the incomplete voltage event record set is supplemented by associative topology prediction based on the smart meter identifier, the distribution network topology map database, and the complete voltage event record set to obtain a complete voltage event record set. Step S400 further includes step S410, which involves locating the smart meter in the distribution network topology map database based on the smart meter identifier corresponding to the incomplete voltage event record set and extracting a neighborhood set of associated candidate smart meters. Specifically, the corresponding smart meter identifier is extracted from each incomplete voltage event record. The distribution network topology map database stores the location information of all smart meters in the distribution network and their connection relationships. Using the smart meter identifier as an index, the specific location of the smart meter in the topology map is quickly located in the database. Based on the physical characteristics of the distribution network lines and actual operating experience, a neighborhood range is pre-defined. This neighborhood range can be other smart meters within a certain distance from the smart meter, or smart meters directly connected in the topology and smart meters on certain levels of branches. Then, in the topology graph, all smart meters located within that neighborhood are identified, forming a neighborhood set of associated candidate smart meters.

[0043] Step S420: Based on the associated candidate smart meter neighborhood set, extract the corresponding complete voltage event record from the complete voltage event record set to obtain the associated complete voltage event record neighborhood set. Specifically, traverse the complete voltage event record set. For each complete voltage event record in the set, check whether its smart meter identifier belongs to the associated candidate smart meter neighborhood set. If so, extract the complete voltage event record and put it into a new set, which is the associated complete voltage event record neighborhood set.

[0044] Step S430: Extract the propagation path from the distribution network line topology diagram database, and combine it with the neighborhood set of associated complete voltage event records to perform associated topology prediction and completion on the incomplete voltage event record set to obtain the completed voltage event record set. Specifically, in the distribution network line topology diagram database, the propagation path of voltage events in the distribution network lines is extracted according to the propagation characteristics of voltage events. Voltage events typically propagate along power lines, and the propagation path can be determined by the connection relationships in the topology diagram. For example, a voltage sag event starts from the power source point and propagates along the main line and branch lines to each smart meter.

[0045] Analyze the event characteristics of records in the neighborhood set of associated complete voltage event records, such as event type, event occurrence time, event duration, and voltage amplitude change. Combined with the extracted propagation path, determine whether there is a correlation between these complete events and incomplete voltage event records. If a correlation exists, for example, along the propagation path, after a complete event occurs, the incomplete event may be a subsequent event occurring in the same propagation process, following the propagation direction and time sequence. Based on the characteristics of associated complete events and the propagation path, use time-series-based prediction methods or propagation model-based prediction methods to complete the incomplete voltage event records. Based on the known information of the complete events, infer the missing field values ​​in the incomplete events, such as event occurrence time and voltage amplitude change. Add the completed records to the complete voltage event record set.

[0046] In one possible implementation, the propagation path is extracted from the distribution network line topology diagram database, and combined with the neighborhood set of associated complete voltage event records, the incomplete voltage event record set is subjected to associated topology prediction and completion to obtain the completed voltage event record set. Step S430 further includes step S431, which, based on the missing fields in the incomplete voltage event record set, calls the associated topology prediction and completion rules to perform data analysis on the neighborhood set of associated complete voltage event records according to the propagation path to obtain the completed voltage event record set; wherein, the associated topology prediction and completion rules include start time completion rules, amplitude and duration completion rules, and phase completion rules.

[0047] Specifically, the principle of the start time completion rule is as follows: In a distribution network, voltage events propagate along the power line at a certain speed. Knowing the propagation path, the start time of incomplete event records can be calculated based on the start time difference between complete event records between adjacent smart meters, combined with the propagation distance and speed. The propagation speed may be affected by various factors, such as line type, voltage level, and ambient temperature. In this application, the propagation speed range for different line types and voltage levels can be pre-set based on historical data and actual operating experience. For example, for a 10kV overhead line, the propagation speed of a voltage sag event can be set to 0.8 times the speed of light.

[0048] First, from the neighborhood set of associated complete voltage event records, identify the complete event records corresponding to smart meters adjacent to the smart meter containing the incomplete voltage event record on the propagation path. Then, calculate the distance between adjacent smart meters. This distance can be obtained from the distribution network topology database, which stores the physical connection distances between various smart meters. Next, based on the propagation speed and distance, calculate the time required for the event to propagate from the adjacent smart meter to the smart meter containing the incomplete event record. Finally, add the propagation time to the start time of the complete event record of the adjacent smart meter to obtain the predicted start time of the incomplete event record.

[0049] The principle behind the amplitude and duration completion rule is as follows: The amplitude and duration of a voltage event may be affected by factors such as line impedance and load conditions during propagation, but there is a certain correlation overall. By analyzing the amplitude and duration of complete event records in the neighborhood set of associated complete voltage event records, and combining this with line parameters along the propagation path, a model for the variation of amplitude and duration is established, thereby predicting and completing the amplitude and duration of incomplete event records.

[0050] For amplitude variation models, considering the attenuation characteristics of the line, the amplitude decreases as the propagation distance increases. For example, for voltage sag events, the amplitude change may have a linear relationship with the propagation distance, i.e. Where U is the predicted amplitude, U0 is the amplitude of adjacent complete event records, k is the attenuation coefficient, and s is the propagation distance. The attenuation coefficient can be calibrated according to the line type and actual measurement data.

[0051] For duration variation models, the duration is affected by parameters such as line capacitance and inductance. In some cases, the duration may slightly increase with increasing propagation distance. The relationship between duration and propagation distance can be fitted using historical data, such as... Where T is the predicted duration, T0 is the duration of adjacent complete event records, m is the variation coefficient, and s is the propagation distance.

[0052] The amplitude and duration of complete event records from neighboring smart meters are obtained from the set of associated complete voltage event records. The propagation distance is determined based on the propagation path. Using the aforementioned amplitude and duration variation models, the predicted amplitude and predicted duration are calculated respectively.

[0053] The principle of phase completion rules is as follows: In a three-phase power system, voltage events may occur simultaneously in multiple phases, or there may be a certain correlation between different phases. By analyzing the phase information of complete event records in the neighborhood set of associated complete voltage event records, and combining the propagation path and the characteristics of the three-phase system, the phase of incomplete event records can be predicted and completed. If a complete event record from an adjacent smart meter occurs in a certain phase, and there is no obvious phase switching device in the propagation path, then the incomplete event record also occurs in the same phase. Furthermore, in some cases, the same event may occur simultaneously in multiple phases, such as a three-phase short-circuit fault. In this case, the phase combination of incomplete event records can be determined based on the phase information of the complete event records.

[0054] Check the phase information of complete event records from adjacent smart meters in the neighborhood set of associated complete voltage event records. Determine if a phase conversion device exists on the propagation path. If not, the phase of the incomplete event record is the same as that of the adjacent complete event record; if it exists, further analyze the operating status and conversion rules of the phase conversion device to determine the phase of the incomplete event record.

[0055] For each record in the incomplete voltage event record set, based on its missing fields, the aforementioned start time completion rules, amplitude and duration completion rules, and phase completion rules are applied respectively to perform prediction and completion. The completed record is then added to the complete voltage event record set to form a complete voltage event record set.

[0056] In one possible implementation, step S400 further includes step S440, determining whether the neighborhood quantity in the neighborhood set of the associated candidate smart energy meters meets the requirements. If not, then the neighborhood is expanded in the distribution network line topology diagram database from two dimensions: topological similarity and signal similarity, and the associated candidate smart energy meters obtained from the expansion are added to the corresponding neighborhood of the associated candidate smart energy meters.

[0057] Specifically, a threshold for the number of smart meters in the neighborhood is set before expanding the neighborhood. This threshold can be determined based on the actual application scenario and requirements. For example, when analyzing voltage events in a distribution network, if the number of smart meters in the current set of candidate smart meters is less than 5, the neighborhood is considered insufficient and expansion is required. The set of candidate smart meters in the neighborhood is counted to determine the number of smart meters it contains. This number is then compared with the preset threshold. If the count is less than the threshold, it indicates that the neighborhood is insufficient and neighborhood expansion is necessary.

[0058] Topological similarity refers to the similarity in the connection relationships and locations of smart meters in the distribution network topology diagram. For example, two smart meters are considered topologically similar if they are connected to the same bus or if their connection paths have similar nodes and line types. The topological information of each smart meter in the neighborhood set of the current associated candidate smart meters is obtained from the distribution network topology diagram database, including its connected bus, line type, and connection relationships with other devices. A threshold for topological similarity is set according to actual needs. Topological similarity can be measured by calculating indicators such as the topological distance between two smart meters and the number of shared connection nodes. For example, if the topological distance between two smart meters is less than 3 nodes and they share at least 2 connection nodes, they are considered topologically similar. The distribution network topology diagram database is then searched for other smart meters with topological similarities to the smart meters in the neighborhood set of the current associated candidate smart meters. Graph search algorithms, such as breadth-first search (BFS) or depth-first search (DFS), can be used to start from smart meters in the current neighborhood and gradually expand the search range to find smart meters that meet the topological similarity threshold. The topologically similar smart meters found are then added to the neighborhood set of the associated candidate smart meters.

[0059] Signal similarity refers to the similarity in waveform, amplitude, and duration of voltage event signals recorded by smart meters. For example, voltage sag events recorded by two smart meters can be considered similar in signal quality if their waveforms are highly similar, their amplitude change trends are consistent, and their durations are similar. The process involves retrieving voltage event record signal data from the neighborhood set of the current candidate smart meters, as well as voltage event record signal data from other smart meters in the distribution network topology database. Signal processing techniques, such as Dynamic Time Warping (DTW) and correlation coefficients, are used to calculate the similarity between the voltage event record signals of two smart meters. For example, DTW can be used to calculate the time alignment distance between two signal waveforms; the smaller the distance, the higher the similarity. The correlation coefficient measures the consistency of the amplitude change trends of two signals; the closer the correlation coefficient is to 1, the higher the similarity. A threshold for signal similarity is set according to actual needs. For example, if the DTW distance between two signals is less than 10, or the correlation coefficient is greater than 0.8, they can be considered similar in signal quality. In the distribution network topology database, search for other smart meters whose signals are similar to those of the smart meters in the current candidate smart meter neighborhood set. Add the smart meters with similar signals found to the candidate smart meter neighborhood set.

[0060] After expanding the neighborhood based on both topological and signal similarity, some duplicate smart meters may be obtained. Therefore, it is necessary to deduplicate the expanded neighborhood set of candidate smart meters to ensure that each smart meter appears only once in the set. The deduplicated smart meters are then added to the neighborhood set of candidate smart meters, completing the neighborhood expansion operation.

[0061] Step S500: Based on the smart energy meter identifier, the distribution network line topology database, the complete voltage event record set, and the supplementary voltage event record set, determine the high-confidence fault section of the target distribution network line. Cross-verify the high-confidence fault section using the action records of the interactive fault indicator and the feeder terminal. If the verification is successful, the high-confidence fault section is taken as the fault location result.

[0062] Specifically, based on smart meter identification, the location relationships of each meter are determined in the distribution network topology database. Combining complete and supplementary voltage event record sets, the occurrence range and propagation path of voltage events in the distribution network are analyzed. Fault section location methods are employed, such as cluster analysis based on the temporal and spatial distribution of voltage events, to identify high-confidence fault sections in the target distribution network. Interaction with the action records of fault indicators and feeder terminals is used to check whether they have detected fault signals within the high-confidence fault sections. If a fault signal is detected, the verification is considered successful, and the high-confidence fault section is taken as the fault location result. A fault indicator is a device installed on the distribution network line to detect fault current in the line and indicate the fault location through methods such as illumination and flip-up signs. A feeder terminal is a distribution automation terminal installed on poles or other locations in the distribution network feeder circuit to monitor and control the feeder, detect fault signals on the feeder, and upload the information to the main station system.

[0063] In one possible implementation, a high-confidence fault section of the target distribution network line is determined based on smart meter identifiers, a distribution network line topology database, a complete voltage event record set, and a supplementary voltage event record set. Step S500 further includes step S510, which involves searching for candidate fault sections in the distribution network line topology database based on the smart meter identifiers in the complete voltage event record set and the supplementary voltage event record set, thereby determining multiple candidate fault sections, multiple complete voltage event record sets for candidate fault sections, and multiple supplementary voltage event record sets for candidate fault sections. Specifically, the topology information of the distribution network line is obtained from the distribution network line topology database, including each node and the lines connecting these nodes, and the smart meter identifiers connected to each node are determined. All relevant smart meter identifiers are extracted from the complete voltage event record set and the supplementary voltage event record set, respectively. Based on the position of the smart meter identifiers in the topology, the line sections containing these smart meters are determined as candidate fault sections. For each candidate fault segment, based on the smart meter identifier it contains, corresponding records are selected from the complete voltage event record set and the supplementary voltage event record set to form multiple candidate fault segment complete voltage event record sets and multiple candidate fault segment supplementary voltage event record sets, respectively.

[0064] Step S520: Extract the complete voltage event record sets and the supplementary voltage event record sets of the multiple candidate fault sections according to preset voltage drop characteristics to obtain the complete voltage drop feature sets and the supplementary voltage drop feature sets of the multiple candidate fault sections. The preset voltage drop characteristics include voltage drop amplitude, duration, event timing difference, and phase consistency. Specifically, voltage drop amplitude refers to the maximum voltage drop from the normal value, expressed as a percentage. For example, if the normal voltage is 220V and the voltage drops to 180V, the drop amplitude is (220-180) / 220×100%≈18.18%. Duration refers to the total time from the start of the voltage drop to its recovery to normal, and the unit can be seconds, milliseconds, etc. Event timing difference refers to the difference in the temporal order of voltage drop events recorded by different smart meters, used to analyze fault propagation characteristics. Phase consistency refers to checking whether the voltage drop characteristics of each phase are consistent for three-phase voltage, and determining whether it is a three-phase simultaneous fault or a single-phase fault.

[0065] For each candidate fault segment's complete voltage event record set, the aforementioned preset voltage drop features are extracted record by record. Similarly, for each candidate fault segment's complete voltage event record set, the same feature extraction operation is performed. All features extracted from each candidate fault segment's complete and complete voltage event record sets are then combined into corresponding feature sets.

[0066] Step S530: The complete voltage drop feature sets and the supplementary voltage drop feature sets of the multiple candidate fault segments are merged into a single candidate fault segment voltage drop feature set. Specifically, for each candidate fault segment, its corresponding complete voltage drop feature set and supplementary voltage drop feature set are merged. During the merging process, all feature information of each record is retained to form a comprehensive feature set containing both complete and supplementary record features.

[0067] Step S540: Following the center iterative update bandwidth, the voltage drop feature sets of the multiple candidate fault sections are filtered to determine the center voltage drop features of the multiple candidate fault sections. Specifically, the center iterative update bandwidth is a method for data filtering and determining center features. By continuously adjusting the bandwidth parameter, the data in the feature set is clustered or filtered to find representative center features.

[0068] Specifically, an initial bandwidth value is set based on experience or preset rules. Taking a certain feature in the voltage drop feature set of candidate fault sections as an example, records whose feature values ​​are within the range of the center value ± bandwidth are grouped into one category. The average feature value of all records in the current category is calculated and used as the new center value. The bandwidth is adjusted according to certain rules, and the data clustering and center update operations are repeated until a stopping condition is met, such as the bandwidth being less than a certain threshold or the change in the center value being less than a certain threshold. After multiple iterations, the feature corresponding to the final center value is the center voltage drop feature of the candidate fault section.

[0069] Step S550: Fault confidence analysis is performed based on the center voltage drop characteristics of the multiple candidate fault sections to determine multiple fault confidence levels. Specifically, a weight is assigned to each preset voltage drop characteristic to reflect its importance in fault judgment. For example, the weight of voltage drop amplitude is 0.4, the weight of duration is 0.3, the weight of event timing difference is 0.2, and the weight of phase consistency is 0.1. For the center voltage drop characteristics of each candidate fault section, it is compared with preset normal range or ideal fault characteristics, and the fault confidence level is calculated based on the degree of difference and the characteristic weight.

[0070] Step S560: The candidate fault segment corresponding to the maximum value among the multiple fault confidence scores is designated as a high-confidence fault segment. Specifically, the fault confidence scores of all candidate fault segments are compared, and the maximum value is found. The candidate fault segment corresponding to the maximum fault confidence score is determined as the high-confidence fault segment.

[0071] In one possible implementation, the voltage drop feature sets of the multiple candidate fault sections are filtered according to the central iterative update bandwidth to determine the central voltage drop features of the multiple candidate fault sections. Step S540 further includes step S541, calculating the mean of the voltage drop feature sets of the multiple candidate fault sections to obtain the mean of the voltage drop features of the multiple candidate fault sections. Specifically, for each voltage drop feature of each candidate fault section, the arithmetic mean of all its recorded values ​​is calculated. After calculation, each candidate fault section will obtain a set of mean voltage drop features, including the mean of voltage drop amplitude, the mean of duration, the mean of event timing difference, and the mean of phase consistency, etc.

[0072] Step S542: According to the central iterative update bandwidth, the average voltage drop feature of the multiple candidate fault segments is iteratively updated in the multiple candidate fault segment voltage drop feature set to obtain multiple iterative candidate fault segment voltage drop features. Specifically, the initial bandwidth value is set according to experience or preset rules. Initially, the average voltage drop feature of the candidate fault segments calculated in step S541 is used as the initial value of the iterative candidate fault segment voltage drop feature. Taking voltage drop amplitude as an example, suppose one candidate fault segment has an initial average voltage drop amplitude of 17% and an initial bandwidth of 3%. In the voltage drop feature set, find all records with voltage drop amplitude values ​​within the range of 17%±3%. Calculate the average voltage drop amplitude of these records as the new iterative candidate fault segment voltage drop amplitude feature value. Suppose there are 3 records in this range with voltage drop amplitudes of 15%, 16%, and 17% respectively, then the new voltage drop amplitude feature value is (15%+16%+17%) / 3=16%. The same operation is performed sequentially on features such as duration, event timing difference, and phase consistency to obtain a new iterative value for each feature.

[0073] Step S543: Determine whether the central coefficient of the voltage drop features of the multiple candidate fault sections is greater than the central coefficient of the average voltage drop features of the multiple candidate fault sections. If so, continue to iterate and update the voltage drop features of the multiple candidate fault sections according to the preset central point iterative update bandwidth until the central coefficient of the voltage drop features of the multiple candidate fault sections obtained in this iteration update is less than or equal to the central coefficient of the voltage drop features of the multiple candidate fault sections obtained in the previous iteration update. Stop iterating and take the voltage drop features of the multiple candidate fault sections obtained in the previous iteration update as the central voltage drop features of the multiple candidate fault sections.

[0074] Specifically, taking the voltage drop amplitude as an example, the initial mean is 17%, and the bandwidth is 3%. In the voltage drop feature set, the number of records with voltage drop amplitude values ​​within the range of 17% ± 3% is counted; this number is the central coefficient of the initial mean. Assuming there are 3 records within this range, the central coefficient of the initial mean is 3. After each iteration, for a new iterative candidate fault segment voltage drop amplitude feature value, the number of surrounding features is counted according to the set bandwidth to obtain the central coefficient of that iterative candidate feature. For example, if the voltage drop amplitude feature value obtained after the first iteration is 16%, and the bandwidth remains 3%, the number of records within the range of 16% ± 3% is counted; assuming there are 4 records, the central coefficient of the first iterative candidate feature is 4.

[0075] Compare the center coefficient of the voltage drop feature of the current iterative candidate fault segment with the center coefficient of the previous iteration. If the current center coefficient is greater than the previous center coefficient, it indicates that more similar features have gathered around the current iterative candidate feature, and it may not have reached a stable center position yet, requiring continued iteration. According to the preset center point iteration update bandwidth, perform a new round of iteration update for the voltage drop feature of the iterative candidate fault segment, i.e., repeat step S542 to obtain new iterative candidate features and new center coefficients. When the center coefficient of the voltage drop feature of the iterative candidate fault segment obtained in this iteration update is less than or equal to the center coefficient of the voltage drop feature of the iterative candidate fault segment obtained in the previous iteration update, stop the iteration. Use the voltage drop feature of the iterative candidate fault segment obtained in the previous iteration update as the center voltage drop feature of the candidate fault segment.

[0076] Similarly, for characteristics such as duration, event timing differences, and phase consistency, their center values ​​are determined using the same method, ultimately yielding a set of center voltage drop characteristics for the candidate fault section, including center voltage drop amplitude, center duration, center event timing differences, and center phase consistency. Other candidate fault sections are also determined using this method to determine their center voltage drop characteristics.

[0077] This application embodiment constructs a topology database of the target distribution network line, collects voltage event records within a preset window of the smart energy meter and classifies them into complete and incomplete data, uses topology correlation prediction to complete missing records, combines complete and completed data to locate high-confidence fault sections, and finally determines the fault location through cross-verification of fault indicators and feeder terminal action records. These technical means solve the technical problem of low accuracy in fault location of existing distribution network lines and achieve the technical effect of improving the accuracy of fault location.

[0078] In the above text, refer to Figure 1 A method for rapid fault location in distribution network lines according to embodiments of the present invention is described in detail. Next, reference will be made to... Figure 2A rapid fault location system for distribution network lines according to an embodiment of the present invention is described.

[0079] The rapid fault location system for distribution network lines according to embodiments of the present invention addresses the technical problem of low accuracy in existing distribution network line fault location, thereby improving the accuracy of fault location. The rapid fault location system for distribution network lines includes: a topology relationship construction module 10, a voltage event record acquisition module 20, an event record integrity differentiation module 30, an associated topology prediction and completion module 40, and a fault location module 50.

[0080] The topology construction module 10 is used to acquire the line equipment of the target distribution network line and construct the topology based on the distribution automation system to generate a distribution network line topology diagram database; the voltage event record acquisition module 20 is used to acquire the voltage event records uploaded by the smart energy meters of the target distribution network line within a preset window to obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart energy meter identifier; the event record integrity differentiation module 30 is used to traverse the voltage event record set to differentiate the integrity of the event records, and obtain a complete voltage event record set and an incomplete voltage event record set; the associated topology... The fault prediction and completion module 40 is used to perform correlation topology prediction and completion on the incomplete voltage event record set based on the smart energy meter identifier, the distribution network line topology diagram database, and the complete voltage event record set to obtain a complete voltage event record set; the fault location module 50 is used to determine the high-confidence fault section of the target distribution network line based on the smart energy meter identifier, the distribution network line topology diagram database, the complete voltage event record set, and the complete voltage event record set, and to cross-verify the high-confidence fault section by interacting with the action records of the fault indicator and the feeder terminal. If the verification is successful, the high-confidence fault section is taken as the fault location result.

[0081] The detailed description of the specific configuration of the event record integrity differentiation module 30 is explained as follows: As mentioned above, the voltage event record set is traversed to perform event record integrity differentiation, obtaining a complete voltage event record set and an incomplete voltage event record set. The event record integrity differentiation module 30 may further include: an event record integrity identification unit used to perform event record integrity identification on the voltage event record set according to a preset record field, obtaining a complete voltage event record set and an incomplete voltage event record set; a first incomplete voltage event record extraction unit used to extract a first incomplete voltage event record from the incomplete voltage event record set; and a judgment processing unit used to filter out all complete voltage event records in the complete voltage event record set whose smart meter identifiers are the same as the first incomplete voltage event record, forming a first matching complete voltage event record set, and combined with the record timestamp identifier, to determine whether there is a complete voltage event record in the first matching complete voltage event record set whose recording time interval is within a preset time interval threshold with the first incomplete voltage event record. If so, the first incomplete voltage event record is added to the complete voltage event record set; if not, the first incomplete voltage event record is retained in the incomplete voltage event record set.

[0082] The detailed description of the specific configuration of the associated topology prediction and completion module 40 is explained as follows: As mentioned above, the associated topology prediction and completion module 40 performs associated topology prediction and completion on the incomplete voltage event record set based on the smart meter identifier, the distribution network line topology diagram database, and the complete voltage event record set to obtain a completed voltage event record set. The associated topology prediction and completion module 40 may further include: a positioning unit used to locate the smart meter in the distribution network line topology diagram database based on the smart meter identifier corresponding to the incomplete voltage event record set, and extract the associated candidate smart meter neighborhood set; a complete voltage event record extraction unit used to extract the corresponding complete voltage event record from the complete voltage event record set based on the associated candidate smart meter neighborhood set to obtain an associated complete voltage event record neighborhood set; and an associated topology prediction and completion unit used to extract the propagation path from the distribution network line topology diagram database, and combine it with the associated complete voltage event record neighborhood set to perform associated topology prediction and completion on the incomplete voltage event record set to obtain the completed voltage event record set.

[0083] Specifically, the propagation path is extracted from the distribution network line topology diagram database, and combined with the neighborhood set of associated complete voltage event records, the incomplete voltage event record set is subjected to associated topology prediction and completion to obtain the completed voltage event record set. The associated topology prediction and completion unit may further include: a data analysis subunit used to, based on the missing fields in the incomplete voltage event record set, call the associated topology prediction and completion rules to perform data analysis on the neighborhood set of associated complete voltage event records according to the propagation path to obtain the completed voltage event record set; wherein, the associated topology prediction and completion rules include start time completion rules, amplitude and duration completion rules, and phase completion rules.

[0084] The associated topology prediction and completion module 40 may further include: a neighborhood expansion unit for determining whether the neighborhood quantity in the neighborhood set of the associated candidate smart energy meters meets the requirements; if not, then performing neighborhood expansion in the distribution network line topology diagram database from two dimensions: topology similarity and signal similarity, and adding the expanded associated candidate smart energy meters into the corresponding associated candidate smart energy meter neighborhood.

[0085] The detailed description of the specific configuration of the fault location module 50 is explained as follows: As mentioned above, based on the smart meter identifier, the distribution network line topology database, the complete voltage event record set, and the supplementary voltage event record set, the high-confidence fault section of the target distribution network line is determined. The fault location module 50 may further include: a candidate fault section retrieval unit used to perform candidate fault section retrieval in the distribution network line topology database based on the smart meter identifier of the complete voltage event record set and the supplementary voltage event record set, to determine multiple candidate fault sections, multiple candidate fault section complete voltage event record sets, and multiple candidate fault section supplementary voltage event record sets; and an extraction unit used to extract the multiple candidate fault section complete voltage event record sets and multiple candidate fault section supplementary voltage event record sets according to preset voltage drop characteristics, respectively, to obtain multiple candidate fault sections. The system comprises: a complete voltage dip feature set for a fault section and a supplementary voltage dip feature set for multiple candidate fault sections; wherein the preset voltage dip features include voltage dip amplitude, duration, event timing differences, and phase consistency; a merging unit for merging the complete voltage dip feature set and the supplementary voltage dip feature set for multiple candidate fault sections into a single set of voltage dip features for multiple candidate fault sections; a filtering unit for filtering the set of voltage dip features for multiple candidate fault sections according to the central iterative update bandwidth to determine the central voltage dip features of multiple candidate fault sections; a fault confidence analysis unit for performing fault confidence analysis based on the central voltage dip features of multiple candidate fault sections to determine multiple fault confidence levels; and a high-confidence fault section determination unit for identifying the candidate fault section corresponding to the maximum value among the multiple fault confidence levels as a high-confidence fault section.

[0086] Specifically, the voltage drop feature set of multiple candidate fault sections is filtered according to the central iterative update bandwidth to determine the central voltage drop features of multiple candidate fault sections. The filtering unit may further include: a mean calculation subunit for calculating the mean of the voltage drop feature set of multiple candidate fault sections to obtain the mean of the voltage drop features of multiple candidate fault sections; an iterative update subunit for iteratively updating the mean of the voltage drop features of multiple candidate fault sections in the voltage drop feature set according to the central iterative update bandwidth to obtain multiple iterative candidate fault section voltage drop features; and a judgment of multiple If the central coefficient of the voltage drop feature of each candidate fault segment is greater than the central coefficient of the average voltage drop feature of the multiple candidate fault segments, then the voltage drop features of the multiple candidate fault segments are iteratively updated according to the preset central point iterative update bandwidth until the central coefficient of the voltage drop feature of the candidate fault segment obtained in this iteration is less than or equal to the central coefficient of the voltage drop feature of the candidate fault segment obtained in the previous iteration. Then the iteration stops, and the voltage drop feature of the candidate fault segment obtained in the previous iteration is taken as the central voltage drop feature of the multiple candidate fault segments.

[0087] The detailed description of the specific configuration of the topology relationship construction module 10 is explained as follows: As mentioned above, the module acquires the line equipment of the target distribution network line and constructs the topology relationship based on the distribution automation system to generate a distribution network line topology diagram database. The topology relationship construction module 10 may further include: a data extraction unit for extracting and uniformly encoding data of the line equipment based on the distribution automation system to construct a standardized equipment dataset; an object extraction unit for extracting node objects and edge objects from the standardized equipment dataset, wherein node objects include transformer low-voltage busbars, switch terminals, branch joints, meter box nodes, and energy meter nodes, and edge objects include conductor segments and cable segments; and a distribution network line topology relationship construction unit for constructing the distribution network line topology relationship based on switch status and physical connection relationships, as well as the node objects and edge objects, to obtain a distribution network line topology diagram database.

[0088] The rapid fault location system for distribution network lines provided in this embodiment of the invention can execute the rapid fault location method for distribution network lines provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0089] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0090] Based on the foregoing embodiments, this application also provides an electronic device. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention. This electronic device is in the form of a general-purpose computing device, and its components may include, but are not limited to, an input device 301, a processor 302, a memory 303, and an output device 304. The processor 302 may be one or more; the memory 303 may include a computer-readable medium and at least one program product having a set (at least one) of program modules configured to perform the functions of the embodiments of this application.

[0091] The memory 303 shown in this embodiment of the invention can be any combination of one or more computer-readable media. The computer-readable storage medium can be, but is not limited to, infrared, semiconductor systems, devices or components, or any combination thereof, for storing software programs, computer-executable programs and modules, such as the program instructions / modules corresponding to the rapid fault location method for distribution network lines in this embodiment of the invention. The processor 302 executes various functional applications and data processing of the computer device by running the software programs, instructions and modules stored in the memory 303, thereby realizing the above-mentioned rapid fault location method for distribution network lines.

[0092] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for quickly locating a fault in a network configuration line, characterized in that, The method includes: Obtain the line equipment of the target distribution network line, and construct the topology relationship based on the distribution automation system to generate a distribution network line topology diagram database; Obtain the voltage event records uploaded by the smart meters of the target distribution network line within a preset window, and obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart meter identifier; Traverse the voltage event record set to distinguish between complete and incomplete voltage event record sets; Based on the smart energy meter identifier, the distribution network line topology database, and the complete voltage event record set, the incomplete voltage event record set is completed by performing correlation topology prediction; Based on the smart energy meter identification, the distribution network line topology database, the complete voltage event record set, and the supplementary voltage event record set, the high-confidence fault section of the target distribution network line is determined. The action records of the interactive fault indicator and the feeder terminal are used to cross-verify the high-confidence fault section. If the verification is successful, the high-confidence fault section is taken as the fault location result.

2. The network provisioning line fault rapid location method of claim 1, wherein, The voltage event record set is traversed to distinguish event record integrity, resulting in a complete voltage event record set and an incomplete voltage event record set, including: The voltage event record set is subjected to event record integrity identification according to preset record fields to obtain a complete voltage event record set and an incomplete voltage event record set. Extract the first incomplete voltage event record from the incomplete voltage event record set; Based on the smart meter identifier, all complete voltage event records with the same smart meter identifier as the first incomplete voltage event record are selected from the complete voltage event record set to form a first matching complete voltage event record set. Combined with the recording timestamp identifier, it is determined whether there is a complete voltage event record in the first matching complete voltage event record set whose recording time interval is within a preset time interval threshold of the first incomplete voltage event record. If so, the first incomplete voltage event record is added to the complete voltage event record set. If not, the first incomplete voltage event record is retained in the incomplete voltage event record set.

3. The network provisioning line fault rapid location method of claim 1, wherein, Based on the smart meter identifiers, the distribution network line topology database, and the complete voltage event record set, the incomplete voltage event record set is supplemented by associative topology prediction to obtain the complete voltage event record set, including: Based on the smart meter identifiers corresponding to the incomplete voltage event record set, the smart meter is located in the distribution network topology database, and the neighborhood set of associated candidate smart meters is extracted. Based on the neighborhood set of the associated candidate smart energy meters, the corresponding complete voltage event records are extracted from the complete voltage event record set to obtain the neighborhood set of associated complete voltage event records; The propagation path is extracted from the distribution network line topology diagram database, and combined with the neighborhood set of the associated complete voltage event records, the associated topology prediction is performed to complete the incomplete voltage event record set to obtain the complete voltage event record set.

4. The network provisioning line fault rapid location method of claim 3, wherein, Propagation paths are extracted from the distribution network line topology database. Combined with the neighborhood set of associated complete voltage event records, associated topology prediction is performed on the incomplete voltage event record set to obtain the completed voltage event record set, including: Based on the missing fields in the incomplete voltage event record set, the associated topology prediction completion rule is invoked to perform data analysis on the neighborhood set of the associated complete voltage event records according to the propagation path, so as to obtain the completed voltage event record set. The associated topology prediction completion rules include start time completion rules, amplitude and duration completion rules, and phase completion rules.

5. The network provisioning line fault rapid location method of claim 3, wherein, Determine whether the neighborhood quantity in the neighborhood set of the associated candidate smart energy meters meets the requirements. If not, expand the neighborhood in the distribution network line topology diagram database from the two dimensions of topological similarity and signal similarity, and add the expanded associated candidate smart energy meters into the corresponding associated candidate smart energy meter neighborhood.

6. The method of claim 1, wherein, Based on smart meter identification, distribution network topology database, complete voltage event record set, and supplementary voltage event record set, the high-confidence fault section of the target distribution network line is determined, including: Based on the smart meter identifiers of the complete voltage event record set and the supplementary voltage event record set, candidate fault sections are retrieved in the distribution network line topology diagram database to determine multiple candidate fault sections, multiple complete voltage event record sets of candidate fault sections, and multiple supplementary voltage event record sets of candidate fault sections. The complete voltage event record set and the supplementary voltage event record set of the multiple candidate fault sections are extracted according to the preset voltage drop characteristics to obtain the complete voltage drop feature set and the supplementary voltage drop feature set of the multiple candidate fault sections. The preset voltage drop characteristics include voltage drop amplitude, duration, event timing difference and phase consistency. The complete voltage sag feature set of the multiple candidate fault sections and the supplementary voltage sag feature set of the multiple candidate fault sections are merged into a voltage sag feature set of multiple candidate fault sections; According to the central iterative update bandwidth, the voltage drop feature set of the multiple candidate fault sections is filtered to determine the central voltage drop feature of the multiple candidate fault sections. Based on the voltage drop characteristics of the center of the multiple candidate fault sections, a fault confidence analysis is performed to determine multiple fault confidence levels; The candidate fault segment corresponding to the maximum value among the multiple fault confidence scores is taken as the high-confidence fault segment.

7. The network provisioning line fault rapid location method of claim 6, wherein, Based on the central iterative update bandwidth, the voltage drop feature sets of the multiple candidate fault sections are filtered to determine the central voltage drop features of the multiple candidate fault sections, including: Calculate the mean of the voltage drop feature set of the multiple candidate fault sections to obtain the mean of the voltage drop features of the multiple candidate fault sections; According to the central iterative update bandwidth, the mean value of the voltage drop features of the multiple candidate fault sections is iteratively updated in the multiple candidate fault section voltage drop feature set to obtain multiple iterative candidate fault section voltage drop features. If the central coefficient of the voltage drop features of multiple candidate fault sections is greater than the central coefficient of the average voltage drop features of the multiple candidate fault sections, then the voltage drop features of the multiple candidate fault sections are iteratively updated according to the preset central point iterative update bandwidth until the central coefficient of the voltage drop features of the multiple candidate fault sections obtained in this iteration update is less than or equal to the central coefficient of the voltage drop features of the multiple candidate fault sections obtained in the previous iteration update. Then the iteration stops, and the voltage drop features of the multiple candidate fault sections obtained in the previous iteration update are respectively used as the central voltage drop features of the multiple candidate fault sections.

8. The method for rapid fault location in distribution network lines as described in claim 1, characterized in that, Obtain the line equipment of the target distribution network line, and construct the topology relationship based on the distribution automation system to generate a distribution network line topology database, including: Based on the power distribution automation system, data is extracted and uniformly encoded from the line equipment to construct a standardized equipment dataset; Node objects and edge objects are extracted from the standardized equipment dataset. The node objects include transformer low-voltage busbars, switch terminals, branch joints, meter box nodes, and energy meter nodes. The edge objects include conductor segments and cable segments. Based on the switch status and physical connection relationship, as well as the node object and edge object, the distribution network line topology relationship is constructed to obtain the distribution network line topology structure diagram database.

9. A rapid fault location system for distribution network lines, characterized in that, The system is used to implement the rapid fault location method for distribution network lines according to any one of claims 1-8, and the system comprises: The topology construction module is used to obtain the line equipment of the target distribution network line and construct the topology relationship based on the distribution automation system to generate a distribution network line topology diagram database. The voltage event record acquisition module is used to acquire voltage event records uploaded by the smart energy meters of the target distribution network line within a preset window, and obtain a voltage event record set, wherein each voltage event record includes a recording timestamp and a smart energy meter identifier. The event record integrity differentiation module is used to traverse the voltage event record set to differentiate the event record integrity and obtain the complete voltage event record set and the incomplete voltage event record set. The associated topology prediction and completion module is used to perform associated topology prediction and completion on the incomplete voltage event record set based on the smart energy meter identifier, the distribution network line topology diagram database and the complete voltage event record set, so as to obtain the complete voltage event record set. The fault location module is used to determine the high-confidence fault section of the target distribution network line based on the smart energy meter identification, the distribution network line topology database, the complete voltage event record set, and the supplementary voltage event record set. The action records of the interactive fault indicator and the feeder terminal are used to cross-verify the high-confidence fault section. If the verification is successful, the high-confidence fault section is taken as the fault location result.

10. An electronic device, comprising: The electronic device includes: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the method for rapid fault location of distribution network lines as described in any one of claims 1 to 8.

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