A power distribution network fault automatic positioning method, device and medium

Abstract

This invention discloses an automatic fault location method, device, and medium for distribution networks, relating to the field of power system reliability. The method includes: constructing a multi-source data fusion center, establishing a top-down integrated power grid model, and acquiring power outage events in the distribution network; integrating power grid operation information, equipment status, and power grid network topology to initiate distribution network fault analysis and determine the fault tripping point; combining the detected distribution transformer data to analyze the tripping point and line fault intervals, and then restoring power supply to loads in non-faulty areas, achieving rapid fault self-healing. Using this invention for distribution network fault analysis can effectively improve the accuracy and timeliness of fault analysis, providing effective technical support for distribution network dispatching and on-site handling to comprehensively, quickly, and accurately respond to faults and early warning events.

Description

Technical Field

[0001] This invention relates to the field of power system reliability, particularly to the analysis of tripping points and fault sections in 10kV distribution network line fault outages, and specifically to an automatic fault location method, equipment, and medium for distribution networks. Background Technology

[0002] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0003] The distribution network is one of the most complex components of the power grid. Its complex structure, geographically dispersed nature, varying equipment age, and variable operating environment make it susceptible to various human-induced or natural faults, posing significant operational safety risks. In actual fault handling, it is often difficult to accurately locate the fault point, resulting in most of the handling time being spent searching for the fault, delayed power restoration, and increased customer complaints. Therefore, strengthening intelligent analysis of distribution network faults, achieving automatic location of tripping points and fault sections, and providing online assistance to dispatchers for rapid decision-making and handling are essential for improving the emergency response capabilities of the distribution network dispatching system and increasing the efficiency of fault repair.

[0004] Currently, fault diagnosis in distribution networks is mostly conducted by dispatchers and maintenance personnel based on the symptom information of the power grid for comprehensive analysis and fault location. The literature (Zhang Yuanlai, Yi Wentao, Fan Qijun, et al. Fault diagnosis scheme for distribution networks based on dispatch operation management system [J]. Automation of Electric Power Systems, 2015, 39(1): 220-225.) proposes a fault diagnosis system for distribution networks based on dispatch operation management system, which uses a collection method to diagnose and locate faults according to the real-time status of the distribution network. The literature (Xu Yongsheng, Cheng Ming, Chen Jian. Discussion on fault diagnosis and alarm analysis methods for distribution network lines [J]. Anhui Electric Power, 2017, 34(1): 9-11.) stores the data collected by the power consumption acquisition system and the dispatch energy management system into the database, uses the public transformer load data and feeder topology to calculate the fault point, and realizes circuit breaker fault tripping and fuse fault alarm. The literature (Yao Ying, Xi Xiaoguang, Gao Shiwei, et al. Distribution network fault assessment technology using multiple data sources [J]. Journal of Electric Power System and Automation, 2017, 29(2): 50-55.) uses quantum genetic algorithm and wavelet theory for theoretical analysis of faults, and uses DS evidence theory for information fusion. The literature (Song Jie, Xie Haining, Yang Zenghui, et al. Statistical analysis of distribution network fault information based on multi-source heterogeneous data mining [J]. Electric Power System Protection and Control, 2016, V44(3): 141-147. Zhang Yuanlai, Yi Wentao, Fan Qijun, et al. Distribution network fault assessment scheme based on dispatch operation management system [J]. Automation of Electric Power System, 2015, 39(1): 220-225.) uses the power grid topology and real-time load in the distribution automation system to carry out fault assessment.

[0005] However, the existing fault assessment has the following problems: First, in terms of the selection of multi-source data, the power grid company has established multiple distribution network management systems (Yang Jianxiang, Chang Zhongxue, Dou Minna, et al. A frequency band adaptive acquisition method for single-phase grounding selection in distribution network [J]. Power System Protection and Control, 2015, V43(15):60-66.), but these systems are generally built only to meet certain specific functional requirements. The systems are isolated from each other and operate independently, with strict information barriers, and the value of system data has not been effectively mined; Second, the current so-called assessment focuses more on fault perception and lacks decision support for assessment, handling and power transmission stages; Third, there is a lack of post-fault evaluation standards, which cannot guarantee the correctness and effectiveness of the fault process.

[0006] Therefore, to address the above issues, this paper proposes an automatic fault location method, equipment, and medium for distribution networks. By aggregating monitoring and alarm information from distribution automation systems, dispatch automation systems, and electricity consumption information collection systems, a multi-source data fusion center is established. An overall architecture for fault analysis is proposed, enabling automated analysis and location of distribution network faults. This provides guidance for dispatchers in handling faults and for on-site personnel in carrying out emergency repairs. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of existing power distribution network fault assessment methods, which fail to break down information barriers between various business systems and cannot consider detailed fault information, resulting in poor fault assessment accuracy. This invention proposes an automatic fault location method, device, and medium for power distribution networks. This method can collect data and information from the entire network, extract effective fault event information, and achieve automated assessment and location of fault points and fault zones. This helps dispatching and on-site repair personnel improve fault handling efficiency and enhance the reliability of power supply in the power distribution network.

[0008] The technical solution of the present invention is as follows: An automatic fault location method for distribution networks based on multi-source data fusion analysis includes: Step S1: Collect substation operation information from the dispatch automation system, terminal operation information from the distribution automation system, and power outage event information from the power consumption and collection system; construct a multi-source data fusion center; establish a mapping relationship between substations, feeders, and distribution transformers; and filter power outage event information from the distribution network. Step S2: Based on the obtained power outage information of the distribution network fault, obtain the distribution transformers in all unplanned power outage sections on the line, and compare the historical operation data of the multi-source data fusion center with the data returned by the recall to classify the distribution transformers into four categories: those that have just lost power, those that have already lost power, those that are suspected of losing power, and those that are energized. Step S3: Based on the information of the power outage transformer obtained, query the power supply path of the power outage transformer, analyze each switch on the power supply path from back to front, determine the energized transformer attribute of the switch, and determine the line trip point. Step S4: Search for the first switch downstream of the line tripping point that does not show an overcurrent signal or the first fault indicator that does not operate, and determine the line fault section; Step S5: Output the trip point and fault section analysis results.

[0009] Further, step S1 includes: Step S11: Collect substation operation information from the dispatch automation system, mainly including: real-time switch position information, fault signals, real-time cross-section information, etc.; terminal operation information from the distribution automation system, mainly including: real-time equipment status, terminal fault information, etc.; and power outage event information, mainly including: distribution transformer operation data, power outage information, etc. Step S12: Establish a mapping relationship model between power plant, feeder, and distribution transformer; based on the information from the multi-source data fusion center, construct a top-down integrated power grid model and establish the electrical connection topology between the three types of equipment: power plant S, feeder L, and distribution transformer T. Step S13: Filter outage events; Based on the integrated power grid model, integrate real-time / near real-time data of the power grid and electrical equipment, find the current outage equipment area and the user information affected, filter out all distribution transformers in the non-pre-arranged outage sections on the line, and obtain the outage events caused by the fault; If the outage event is an FA event, jump to step S4, otherwise proceed to step S21.

[0010] Furthermore, the electrical connection topology among the three types of equipment—the substation S, the feeder L, and the transformer T—is as follows:

[0011] in: Indicates the first The set of topological mapping states of distribution transformers in the integrated power grid model; Indicates the first One substation; Indicates the first One feeder line; Indicates the first Taiwan-supplied change; 0 indicates that the device is in a power outage state; 1 indicates that the device is energized.

[0012] Further, step S2 includes: Classification of power outage transformers: Data from the three sampling time points of the transformers are obtained from the multi-source data fusion center and compared with the data returned by the recall. The transformers are classified into four categories: those that have just lost power, those that have already lost power, those that are suspected of losing power, and those that are energized. If no relevant data of the transformers in the recall are obtained, the transformers are assumed to be energized at the three sampling time points of the previous three sampling time points.

[0013] Furthermore, the classification in step S2 specifically includes the following steps: Step S21: Initial classification; ①If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is less than or equal to 20 (20 is the zero drift value, and less than 20 is considered 0), the transformer is classified as having already lost power. ②If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is not all less than or equal to 20, the transformer is classified as suspected power failure. ③ If the voltage of phase A of the transformer returned by the recall test is greater than 20, and the transformer is a dedicated transformer and the user type is a self-provided power user, a small hydropower or multi-power point transformer, a grid port transformer, or a distributed power transformer, then it is classified as a suspected power outage. ④ If the voltage of phase A of the transformer returned by the recall is greater than 20, and it does not belong to the special transformer in ③, then it is classified as a live transformer; Step S22: Secondary classification; ① If a power outage event exists, upgrade the transformer in the suspected power outage event to one that has just lost power; ② Check if there are any recently de-energized transformers in the classification results. If there are no recently de-energized transformers, the analysis ends; otherwise, proceed to the next step of the analysis.

[0014] Further, step S3 includes: Step S31: Determine the tripping point; search for disconnecting devices (hereinafter referred to as switches) on the power supply path of the recently de-energized transformer: If the search fails or the length of the searched transformer power supply path is 0, stop analyzing the transformer; otherwise, based on the searched power supply path, analyze the switches on each power supply path one by one from back to front, and determine whether the switch "has the attribute of a live transformer": ① Obtain the current of phase A of the switch. If it is greater than the "minimum telemetry value of the switch being energized" and the telemetry value has been refreshed, then the switch is determined to be energized, and the "has energized transformer attribute" of this switch is set to Y; otherwise, the switch is determined to be de-energized, and its "has energized transformer attribute" is set to N. ② If the current of phase A of the switch cannot be obtained, then all distribution transformers within its power supply range are judged. If there is a live distribution transformer, then the "has live distribution transformer attribute" of the switch is set to Y; otherwise, the switch is judged to be non-energized, and its "has live distribution transformer attribute" is set to N. If the switch has the attribute of "having a live distribution transformer", then continue to determine whether the switch is the closest switch to the de-energized distribution transformer. If it is, then this distribution transformer will not be analyzed again; otherwise, then push one switch to the next as the trip point and record it. If the "has live distribution transformer attribute" of the switch is N, then determine whether the number of distribution transformers in the power supply range of the switch is the same as the number of distribution transformers in the power supply range of the previous switch. If they are the same, then record the previous switch in the suspected trip point. Otherwise, clear the suspected trip points on the power supply path of the previously de-energized distribution transformer and then record the switch as the trip point. Step S32: Trip point merging; First, filter out single transformer trip points and trip points that are fuse trip points; then, find the common power supply path for the remaining trip points. If no common power supply path is found, the merging fails, the analysis is unsuccessful, and the analysis terminates; if a common power supply path can be found, the last switch of the common power supply path is taken as the trip point, the merging is successful, and the analysis terminates.

[0015] Further, step S4 includes: Based on the operation of the fault indicator or the overcurrent signal of the automatic switch, the fault range is located after the last switch that gave an overcurrent signal or the last fault indicator that was activated, and before the next switch that did not give an overcurrent signal or the next fault indicator that did not activate.

[0016] Further, step S5 includes: Analysis results of the output line tripping point and fault section.

[0017] The present invention also proposes an electronic device, comprising: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the instructions stored in the memory to perform the method described above.

[0018] The present invention also proposes a computer-readable storage medium for storing instructions that, when executed, cause the method described above to be implemented.

[0019] Compared with existing technologies, the advantages of this invention are: 1. This invention breaks down the information barriers between various business systems, establishes a multi-source data fusion center, shares power grid data and information, and expands the full range of perception for distribution network fault handling and status monitoring.

[0020] 2. This invention proposes an intelligent method for judging power distribution network faults, which can identify power outage events online and realize the active judgment of fault points and fault sections, overcoming the problems of existing methods that focus on fault perception, lack of analysis methods, and lack of technical support for handling processes.

[0021] 3. This invention has a complete fault information extraction and full-process analysis mode, which significantly improves the accuracy and timeliness of fault judgment and can provide effective technical support for distribution network dispatch to respond to faults and early warning events in a comprehensive, fast and accurate manner. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0023] Figure 1A flowchart of a method for accurate fault location in distribution networks based on multi-source data fusion analysis; Figure 2 The diagram shows the power distribution network of SB Power Supply Company in this embodiment. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0024] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0025] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0026] Example 1 Please see Figure 1 An automatic fault location method for distribution networks based on multi-source data fusion analysis includes the following steps: 1) Collect substation operation information from the dispatch automation system, terminal operation information from the distribution automation system, and power outage event information from the power consumption and collection system; construct a multi-source data fusion center; establish a mapping relationship between substations, feeders, and distribution transformers; and filter power outage event information from the distribution network. This step specifically includes: 1.1) Construct a multi-source data fusion center The system collects substation operation information from the dispatch automation system, mainly including: real-time switch position information, fault signals, real-time cross-section information, etc.; terminal operation information from the distribution automation system, mainly including: real-time equipment status, terminal fault information, etc.; and power outage event information, mainly including: distribution transformer operation data, power outage information, etc. 1.2) Establish a mapping relationship model between power plants, feeders, and distribution transformers. Based on information from a multi-source data fusion center, a top-down integrated power grid model is constructed, establishing the electrical connection topology among three types of equipment: substations (S), feeders (L), and distribution transformers (T).

[0027] in: Indicates the first The set of topological mapping states of distribution transformers in the integrated power grid model; Indicates the first One substation; Indicates the first One feeder line; Indicates the first Taiwan-supplied change; 0 indicates that the device is in a power outage state; 1 indicates that the device is energized.

[0028] 1.3) Screening for power outage events Based on the integrated power grid model, by combining real-time / near real-time data of the power grid and electrical equipment, the current outage equipment area and its affected user information are identified. All distribution transformers within unplanned outage sections on the line are then selected to determine the outage event caused by the fault. If the outage event is a fault-related (FA) event, proceed to step 4; otherwise, proceed to step 2.1. 2) Based on the obtained power outage information from the distribution network faults, identify all distribution transformers within the unplanned outage sections of the line. Compare the historical operating data from the multi-source data fusion center with the data returned from the recall, classifying the distribution transformers into four categories: recently de-energized, already de-energized, suspected de-energized, and energized. This step specifically includes: Classification of power outage transformers: Data from the three previous sampling points of the transformers are obtained from the multi-source data fusion center and compared with the data returned from the recall. The transformers are classified into four categories: just lost power, already lost power, suspected of being lost power, and energized. If no relevant data for the recalled transformers is available, it is assumed that the transformer was energized at the three previous sampling points.

[0029] 2.1) Initial Classification ①If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is less than or equal to 20 (20 is the zero drift value, and less than 20 is considered 0), the transformer is classified as having already lost power. ②If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is not all less than or equal to 20, the transformer is classified as suspected power failure. ③ If the voltage of phase A of the transformer returned by the recall test is greater than 20, and the transformer is a dedicated transformer and the user type is a self-provided power user, a small hydropower or multi-power point transformer, a grid port transformer, or a distributed power transformer, then it is classified as a suspected power outage. ④ If the voltage of phase A of the transformer returned by the recall is greater than 20, and it does not belong to the special transformer in ③, then it is classified as a live transformer; 2.2) Secondary classification ① If a power outage event exists, upgrade the transformer in the suspected power outage event to one that has just lost power; ② Check if there are any recently de-energized transformers in the classification results. If there are no recently de-energized transformers, the analysis is complete; otherwise, proceed to the next step of the analysis. 3) Based on the information about the recently de-energized transformer, query the power supply path of the transformer, analyze each switch along the power supply path from the end to the beginning, determine the energized transformer attributes of the switches, and identify the line tripping point; this step specifically includes: 3.1) Determine the tripping point Search for disconnecting devices (hereinafter referred to as switches) on the power supply path of the recently de-energized transformer: If the search fails or the length of the searched transformer power supply path is 0, stop analyzing the transformer; otherwise, analyze the switches on each power supply path from back to front according to the searched power supply path, and determine whether the switch "has the attribute of a live transformer": ① Obtain the current of phase A of the switch. If it is greater than the "minimum telemetry value of the switch being energized" and the telemetry value has been refreshed, then the switch is determined to be energized, and the "has energized transformer attribute" of this switch is set to Y; otherwise, the switch is determined to be de-energized, and its "has energized transformer attribute" is set to N. ② If the current of phase A of the switch cannot be obtained, then all distribution transformers within its power supply range are judged. If there is a live distribution transformer, then the "has live distribution transformer attribute" of the switch is set to Y; otherwise, the switch is judged to be non-energized, and its "has live distribution transformer attribute" is set to N. If the switch has the attribute of "having a live distribution transformer", then continue to determine whether the switch is the closest switch to the de-energized distribution transformer. If it is, then this distribution transformer will not be analyzed again; otherwise, then push one switch to the next as the trip point and record it. If the "has live distribution transformer attribute" of the switch is N, then determine whether the number of distribution transformers in the power supply range of the switch is the same as the number of distribution transformers in the power supply range of the previous switch. If they are the same, then record the previous switch in the suspected trip point. Otherwise, clear the suspected trip points on the power supply path of the previously de-energized distribution transformer and then record the switch as the trip point. 3.2) Trip point merging First, filter out single transformer trip points and trip points that are fuse trip points; then, find the common power supply path for the remaining trip points. If no common power supply path is found, the merging fails, the analysis is unsuccessful, and the analysis is terminated; if a common power supply path is found, the last switch of the common power supply path is taken as the trip point, the merging is successful, and the analysis is terminated. 4) Based on the operation of the fault indicator or the overcurrent signal of the automatic switch, the fault range is located after the last switch that gave an overcurrent signal or the last fault indicator that was activated, and before the next switch that did not give an overcurrent signal or the next fault indicator that did not activate. 5) Analysis results of the output line tripping point and fault section.

[0030] Based on the same technical concept, embodiments of the present invention also provide an electronic device that can implement the automatic fault location method for power distribution networks based on multi-source data fusion analysis provided in the above embodiments of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic equipment. Figure 3 As shown, the electronic device may include: At least one processor and a memory connected to the at least one processor. In this embodiment of the invention, the specific connection medium between the processor and the memory is not limited. Figure 3 The example used is the connection between the processor and memory via a bus. The bus... Figure 3 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Buses can be divided into address buses, data buses, control buses, etc., but for ease of representation, [the specific bus type is not shown here]. Figure 3 The processor is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, a processor can also be called a controller; there are no restrictions on the name.

[0031] In this embodiment of the invention, the memory stores instructions executable by at least one processor. By executing the instructions stored in the memory, the at least one processor can perform the aforementioned method for automatic fault location in a distribution network based on multi-source data fusion analysis. The processor can implement... Figure 3 The functions of each module in the device shown.

[0032] The processor is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory and calling data stored in memory, it can monitor the device's various functions and process data, thereby enabling overall monitoring of the device.

[0033] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0034] The processor can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the automatic fault location method for distribution networks based on multi-source data fusion analysis disclosed in the embodiments of this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0035] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia cards, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), and electrically erasable programmable read-only memory (EPROM). Only memory (EEPROM), magnetic storage, magnetic disks, optical disks, etc. A memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures, and accessible by a computer, but is not limited thereto. The memory in embodiments of this invention can also be a circuit or any other device capable of performing storage functions for storing program instructions and / or data.

[0036] By designing and programming the processor, the code corresponding to the automatic fault location method for distribution networks based on multi-source data fusion analysis described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the steps of the method described in the foregoing embodiments during operation. How to design and program the processor is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0037] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing computer instructions, which, when executed on a computer, cause the computer to execute the aforementioned method for automatic fault location in a distribution network based on multi-source data fusion analysis.

[0038] In some alternative embodiments, the present invention also provides a method for automatic fault location in a distribution network based on multi-source data fusion analysis, which can also be implemented as a program product including program code. When the program product is run on a device, the program code is used to cause the control device to perform the steps in the method for automatic fault location in a distribution network based on multi-source data fusion analysis according to various exemplary embodiments of the present invention as described above.

[0039] It should be noted that although several units or sub-units of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the invention, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. Furthermore, although the operation of the method of the invention is described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0040] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can be implemented in one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs) containing computer-usable program code. The form of a computer program product implemented on ROM, optical memory, etc.

[0041] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0042] Program code for performing the operations of this invention can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0043] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0044] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0045] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0046] Example 2 This embodiment uses a 10kV distribution network as an example to describe in detail the proposed method for accurate fault location in distribution networks based on multi-source data analysis, and verifies the effects achieved by the invention. The wiring of the distribution network is as follows: Figure 2 As shown in the example, this case study uses the 10kV Zifu line as an example. After a fault occurs, the fault analysis system displays a pop-up interface showing the fault signal: [Power Outage Event] 11:50:43 Power outage event at 10kV Fushuang Line #5 transformer. [Power Outage Event] 11:50:45 Power outage event at 10kV Fushuang Line #3 transformer. [Power Outage Event] 11:50:45 Power outage event at 10kV Fushuang Line #4 transformer. [Referring to the event] 11:50:15 10kV Tzefork Line #5 Overcurrent Alarm [Referring to the event] 11:50:15 10kV Tsuf line #22 overcurrent alarm [Referring to the event] 11:50:15 10kV Fushuang Line #2 Overcurrent Alarm [Alarm Event] 11:50:15 Overcurrent alarm at 10kV Fushuang Line #14 pole switch [Alarm Event] 11:50:15 Overcurrent alarm at 10kV Fushuang Line #14-6 pole switch After the fault occurred, there were no clear circuit breaker protection operation signals or tripping signals, and the fault handling process was determined to be a non-FA (Feature-Assisted) power outage event. The analysis module first classified the power-outage transformers, identifying three transformers that had just lost power in this fault handling process. Then, it determined that each circuit breaker along the path from the load side to the power supply side of each transformer "has the attribute of a live transformer," and finally determined the tripping point to be the #28 pole switch of the 10kV Zifu line. The fault indicators of the 10kV Zifu line #5, 10kV Zifu line #22, and Fushuang line #2 were activated, and the #14 pole switches and #14-6 pole switches of the 10kV Fushuang line showed overcurrent signals.

[0047] Fault analysis results: The system analysis indicates that the fault point is located downstream of the Fushuang Line #14-6 pole switch. Recommendation for isolation and power restoration: Isolate the Fushuang Line #14-6 pole switch and then restore the 10kV Cifu Line #3 pole switch.

[0048] The calculation results show that, under the conditions of good operation of all professional systems, normal operation of online monitoring devices, and correct operation of line protection, a comprehensive analysis of the power outages and fault indicator actions before and after the fault reveals that the line tripping point and fault section were correctly identified, consistent with the results of on-site line inspections. The calculation example demonstrates that the determination method in this invention can achieve automatic fault location in the distribution network.

[0049] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

[0050] This background section is provided to generally present the context of the invention. The work of the currently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither expressly nor impliedly acknowledged as prior art to the invention.

Claims

1. A method for automatic fault location in distribution networks based on multi-source data fusion analysis, characterized in that, include: Step S1: Collect substation operation information from the dispatch automation system, terminal operation information from the distribution automation system, and power outage event information from the power consumption and collection system; construct a multi-source data fusion center; establish a mapping relationship between substations, feeders, and distribution transformers; and filter power outage event information from the distribution network. Step S2: Based on the obtained power outage information of the distribution network fault, obtain the distribution transformers in all unplanned power outage sections on the line, and compare the historical operation data of the multi-source data fusion center with the data returned by the recall to classify the distribution transformers into four categories: those that have just lost power, those that have already lost power, those that are suspected of losing power, and those that are energized. Step S3: Based on the information of the power outage transformer obtained, query the power supply path of the power outage transformer, analyze each switch on the power supply path from back to front, determine the energized transformer attribute of the switch, and determine the line trip point. Step S4: Search for the first switch downstream of the line tripping point that does not show an overcurrent signal or the first fault indicator that does not operate, and determine the line fault section; Step S5: Output the trip point and fault section analysis results.

2. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 1, characterized in that, Step S1 includes: Step S11: Construct a multi-source data fusion center; collect substation operation information from the dispatch automation system, including: real-time switch position information, fault signals, and real-time cross-sections; terminal operation information from the distribution automation system, including: real-time equipment status and terminal faults; and power outage event information, including: distribution transformer operation data and power outages. Step S12: Establish a mapping relationship model between power plant, feeder, and distribution transformer; based on the information from the multi-source data fusion center, construct a top-down integrated power grid model and establish the electrical connection topology between the three types of equipment: power plant S, feeder L, and distribution transformer T. Step S13: Filter outage events; Based on the integrated power grid model, integrate real-time / near real-time data of the power grid and electrical equipment, find the current outage equipment area and the user information affected, filter out all distribution transformers in the non-pre-arranged outage sections on the line, and obtain the outage events caused by the fault; If the outage event is an FA event, jump to step S4, otherwise proceed to step S2.

3. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 2, characterized in that, The electrical connection topology among the three types of equipment—plant S, feeder L, and transformer T—is shown below: in: Indicates the first The set of topological mapping states of distribution transformers in the integrated power grid model; Indicates the first One substation; Indicates the first One feeder line; Indicates the first Taiwan-supplied change; 0 indicates that the device is in a power outage state; 1 indicates that the device is energized.

4. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 1, characterized in that, Step S2 includes: Classification of power outage transformers: Data from the three sampling time points of the transformers are obtained from the multi-source data fusion center and compared with the data returned by the recall. The transformers are classified into four categories: those that have just lost power, those that have already lost power, those that are suspected of losing power, and those that are energized. If no relevant data of the transformers in the recall are obtained, the transformers are assumed to be energized at the three sampling time points of the previous three sampling time points.

5. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 4, characterized in that, The classification in step S2 specifically includes the following steps: Step S21: Initial classification; ①If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is less than or equal to 20, the transformer is classified as having already lost power. ②If the voltage of phase A of the transformer is empty when the test returns, and the voltage of phase A of the transformer at the first three points is not all less than or equal to 20, the transformer is classified as suspected power failure. ③ If the voltage of phase A of the transformer returned by the recall test is greater than 20, and the transformer is a dedicated transformer and the user type is a self-provided power user, a small hydropower or multi-power point transformer, a grid port transformer, or a distributed power transformer, then it is classified as a suspected power outage. ④ If the voltage of phase A of the transformer returned by the recall is greater than 20, and it does not belong to the special transformer in ③, then it is classified as a live transformer; Step S22: Secondary classification; ① If a power outage event exists, upgrade the transformer in the suspected power outage event to one that has just lost power; ② Check if there are any recently de-energized transformers in the classification results. If there are no recently de-energized transformers, the analysis ends; otherwise, proceed to the next step of the analysis.

6. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 1, characterized in that, Step S3 includes: Step S31: Determine the tripping point; search for disconnected equipment on the power supply path of the recently de-energized transformer: if the search fails or the length of the searched transformer power supply path is 0, stop analyzing the transformer; otherwise, based on the searched power supply path, analyze the switches on each power supply path one by one from back to front, and determine whether the switch "has the attribute of a live transformer": ① Obtain the current of phase A of the switch. If it is greater than the "minimum telemetry value of the switch being energized" and the telemetry value has been refreshed, then the switch is determined to be energized, and the "has energized transformer attribute" of this switch is set to Y; otherwise, the switch is determined to be de-energized, and its "has energized transformer attribute" is set to N. ② If the current of phase A of the switch cannot be obtained, then all distribution transformers within its power supply range are judged. If there is a live distribution transformer, then the "has live distribution transformer attribute" of the switch is set to Y; otherwise, the switch is judged to be non-energized, and its "has live distribution transformer attribute" is set to N. If the switch's "has live transformer attribute" is Y, then continue to determine whether the switch is the closest switch to the de-energized transformer. If it is, then this transformer will not be analyzed again; otherwise, then push one switch to the next as the trip point and record it. If the "has live distribution transformer attribute" of the switch is N, then determine whether the number of distribution transformers in the power supply range of the switch is the same as the number of distribution transformers in the power supply range of the previous switch. If they are the same, then record the previous switch in the suspected trip point. Otherwise, clear the suspected trip points on the power supply path of the previously de-energized distribution transformer, and then record the switch as the trip point. Step S32: Trip point merging; First, filter out single transformer trip points and trip points that are fuse trip points; then, find the common power supply path for the remaining trip points. If no common power supply path is found, the merging fails, the analysis is unsuccessful, and the analysis terminates; if a common power supply path can be found, the last switch of the common power supply path is taken as the trip point, the merging is successful, and the analysis terminates.

7. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 1, characterized in that, Step S4 includes: Based on the operation of the fault indicator or the overcurrent signal of the automatic switch, the fault range is located after the last switch that gave an overcurrent signal or the last fault indicator that was activated, and before the next switch that did not give an overcurrent signal or the next fault indicator that did not activate.

8. The automatic fault location method for distribution networks based on multi-source data fusion analysis according to claim 1, characterized in that, Step S5 includes: Analysis results of the output line tripping point and fault section.

9. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store instructions that, when executed, cause the method as described in any one of claims 1-8 to be implemented.

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