Power distribution network fault automatic processing method and system

Abstract

The invention discloses an automatic power distribution network fault processing method and system, and relates to the technical field of power distribution automation, and the method comprises the steps: monitoring power parameters in real time, recognizing abnormal nodes through an abnormality recognition method, and judging the types of the abnormal nodes; performing power test on the abnormal points, and generating corresponding processing signals for the faults based on test data; and a fault current signal is obtained and returned, and the fault point location is fed back to the online server processing platform. According to the method, the zero-sequence voltage transformer is used for monitoring the power parameters of the power distribution network in real time, so that faults in the power distribution network can be identified and diagnosed more accurately, and missing report and false report are reduced; by introducing an efficient positioning algorithm, the fault line and position can be quickly confirmed, the fault processing time is greatly shortened, and the risk of fault operation of the power distribution network system is reduced; and through rapid and accurate fault positioning, risks of equipment damage and fault expansion are reduced, and the overall operation reliability of the power distribution network is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution automation, and in particular to a method and system for automatically handling power distribution network faults. Background Art

[0002] The distribution network refers to the power grid that receives electric energy from the transmission network or regional power plants and distributes it locally or step by step according to voltage to various users through distribution facilities. The distribution network consists of multiple branches to transmit electric energy to users. These branches are scattered in rural and urban areas and are easily affected by various factors and cause failures. Once a failure occurs and cannot be diagnosed and handled in time, it will not only affect the normal life of residents, but also may cause huge losses.

[0003] At present, the distribution lines of the distribution network have the characteristics of complex network structure and scattered load distribution. The frequency of line faults is high, especially single-phase grounding faults are more prominent and hidden. Failure in fault line selection and location will cause the system to operate with faults for a long time, thereby damaging electrical equipment, expanding the scope of faults, and destroying the stable operation of the system. Therefore, quickly determining the fault line and fault detection are of great significance to the safe and stable operation of the distribution network. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the existing distribution network fault handling method has the problems of low fault detection accuracy, slow fault location speed, lack of intelligence and automation in the fault handling process, and insufficient utilization of fault data, as well as how to achieve rapid detection, precise location and intelligent processing of distribution network faults.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for automatically handling distribution network faults, comprising real-time monitoring of power parameters, identifying abnormal nodes and determining the categories of abnormal nodes through an abnormal identification method; performing power tests on abnormal points, and generating corresponding processing signals for the faults based on the test data; acquiring and returning fault current signals, and feeding back the fault point to an online server processing platform.

[0007] As a preferred solution of the method for automatic handling of distribution network faults described in the present invention, wherein: the real-time monitoring of power parameters includes monitoring power parameters through a data monitoring device; the real-time monitoring of power parameters includes monitoring power parameters through a data monitoring device; the data monitoring device includes a voltage monitoring unit in the data monitoring device, and a zero-sequence voltage transformer is installed at the neutral point of the distribution network transformer bus.

[0008] As a preferred solution of the method for automatically handling distribution network faults described in the present invention, wherein: the identifying of abnormal nodes includes identifying whether the power parameters monitored by the data monitoring device belong to abnormal nodes through an abnormal identification method.

[0009] As a preferred solution of the method for automatically handling distribution network faults described in the present invention, wherein: the determination of abnormal node categories includes determining the abnormal node categories based on abnormal nodes through an abnormal identification method; the abnormal point categories include single-group abnormal points and linked abnormal points; and the linked abnormal points are further analyzed to determine whether the linked abnormal points are synchronous abnormal points or single-group abnormal points.

[0010] As a preferred solution of the method for automatically handling distribution network faults described in the present invention, wherein: the generation of corresponding processing signals for faults based on test data includes determining the internal resistance heating curve based on the test data, determining whether there is an internal resistance heating problem at the abnormal point through the internal resistance heating curve, and generating corresponding processing signals.

[0011] As a preferred solution of the method for automatically handling distribution network faults described in the present invention, the method of obtaining and returning the fault current signal includes confirming the fault time point data of the distribution network through a data monitoring device and issuing a data call command; and obtaining and returning the fault current signal corresponding to the fault time point according to the corresponding signal generated by the data.

[0012] As a preferred solution of the method for automatically handling distribution network faults described in the present invention, wherein: the feedback of the fault point to the online server processing platform includes locating the fault grounding point of the distribution network according to the current signal and feeding it back to the online server processing platform.

[0013] Another object of the present invention is to provide an automatic handling system for distribution network faults, which can achieve real-time monitoring and response to distribution network faults by utilizing the de-energization and fault monitoring functions of the zero-sequence voltage transformer and the edge computing of the fault location algorithm, thereby effectively improving the accuracy and timeliness of fault location, speeding up the processing speed of power grid faults, and solving the problems of low fault detection accuracy, slow fault location speed, and insufficient utilization of fault data in the prior art.

[0014] As a preferred solution of the automatic handling system for distribution network faults described in the present invention, it includes: an abnormality identification module, a fault judgment module, and a fault location module; the abnormality identification module is used to monitor power parameters in real time, identify abnormal nodes and determine the categories of abnormal nodes through abnormality identification methods; the fault judgment module is used to perform power tests on abnormal points, and generate corresponding processing signals for faults based on test data; the fault location module is used to obtain and return fault current signals, and feed back the fault point to an online server processing platform.

[0015] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a method for automatically handling distribution network faults.

[0016] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for automatically handling distribution network faults.

[0017] Beneficial effects of the present invention: The automatic fault handling method of the distribution network provided by the present invention can not only more accurately identify and diagnose faults in the distribution network, but also reduce missed reports and false reports by using a zero-sequence voltage transformer to monitor the power parameters of the distribution network in real time; by introducing an efficient positioning algorithm, not only can the fault line and location be quickly confirmed, but also the fault handling time is greatly shortened, and the risk of the distribution network system running with faults is reduced; through in-depth analysis and mining of fault data, fast and accurate fault positioning can not only optimize the operating status of the distribution network, but also reduce the risk of equipment damage and fault expansion, and improve the overall operating reliability of the distribution network; at the same time, it also reduces the demand for manual inspection and maintenance, reduces the cost of fault handling, and improves the economic benefits of the distribution network; reduces the power outage time caused by faults, and improves the power supply quality and user satisfaction. The present invention has achieved better results in terms of rapid fault positioning, fault detection accuracy, and automatic and intelligent fault handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0019] Figure 1 An overall flow chart of a method for automatically handling distribution network faults provided in the first embodiment of the present invention.

[0020] Figure 2 This is an overall flow chart of a distribution network fault automatic processing system provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0022] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a method for automatically handling distribution network faults, comprising:

[0023] S1: Monitor power parameters in real time, identify abnormal nodes through abnormal identification methods and determine the categories of abnormal nodes.

[0024] Furthermore, real-time monitoring of power parameters includes monitoring power parameters through a data monitoring device;

[0025] The data monitoring device includes a voltage monitoring unit in the data monitoring device, and a zero-sequence voltage transformer installed at the neutral point of the busbar of the distribution network transformer.

[0026] It should be noted that identifying an abnormal node includes identifying whether the power parameter monitored by the data monitoring device belongs to an abnormal node through an abnormal identification method.

[0027] It should also be noted that determining the abnormal node category includes determining the abnormal node category based on the abnormal node through an abnormal identification method; the abnormal point category includes a single group of abnormal points and linked abnormal points; further analyzing the linked abnormal points to determine whether the linked abnormal points are synchronous abnormal points or single group abnormal points.

[0028] It should also be noted that the anomaly identification method may be to identify anomalies by analyzing changes in grid load, or to identify anomalies by analyzing the sound of grid equipment during operation, or other suitable distribution network anomaly detection methods.

[0029] In this embodiment, the abnormality identification method uses a data monitoring device to monitor the power parameters, check the power parameters with the preset interval, and determine whether the node is a data abnormality node based on the verification result; through the abnormal point classification end, identify whether the points interconnected before and after the abnormal point have abnormal conditions, and based on the identification result, mark the abnormal point as a single group of abnormal points or linked abnormal points; through the linked point determination end, analyze whether the power parameter fluctuations of different points in the linked abnormal points are consistent, and based on the analysis result, mark the abnormal point as a synchronous abnormal point or a single group of abnormal points.

[0030] In an optional embodiment, the abnormality identification method uses an analysis of changes in the power grid load to identify abnormal points. Specifically, the load data of the power grid is collected in real time through a data monitoring device, the statistical characteristics of the load data are analyzed, the key characteristics of the load curve are extracted, and a normal operation model of the load is established using historical normal load data. The real-time load data is compared with the normal load model to identify deviations, and the real-time load data in the distribution network is identified using a preset abnormal load threshold. Based on the identified abnormal curve characteristics, the abnormal points are further calibrated as single-group abnormal points or synchronous abnormal points.

[0031] It should also be noted that the fault identification of the distribution network includes obtaining the fundamental long-term change value of the zero-sequence voltage through the voltage detection unit and the corresponding zero-sequence voltage sensor set in the system, subtracting the fundamental long-term change value of the n-1th cycle from the fundamental long-term change value of the nth cycle, and accumulating all the differences in sequence to obtain the long-term voltage change value; wherein n>1, N≥1;

[0032] Determine whether the effective value of the fundamental amplitude of the zero-sequence voltage exceeds a preset amplitude threshold within a preset time length, and determine whether the long-term voltage change value exceeds a preset long-term voltage threshold;

[0033] When the effective value of the fundamental amplitude of the zero-sequence voltage exceeds the amplitude threshold within a preset time period, or the long-term voltage change value exceeds the long-term voltage threshold, a ground fault is identified in the distribution network.

[0034] S2: Perform power testing on the abnormal point and generate corresponding processing signals for the fault based on the test data.

[0035] Furthermore, generating a corresponding processing signal for the fault based on the test data includes determining an internal resistance heating curve based on the test data, determining whether there is an internal resistance heating problem at the abnormal point through the internal resistance heating curve, and generating a corresponding processing signal.

[0036] It should be noted that for a single group of abnormal points, a power test is directly performed, and the internal resistance heating curve is determined based on the test data, and then it is determined whether there is an internal resistance heating problem based on the internal resistance heating curve;

[0037] For synchronous abnormal points, a group of points are randomly selected for testing. If the selected points are tested without problems, another point is directly marked as a fault point. If there are multiple groups of synchronous abnormal points, they are tested one by one. If the corresponding fault point is detected, the detection is stopped.

[0038] It should be noted that a test current is input to the abnormal point, the test current is a preset current, a single group of abnormal points is periodically tested based on the test current, and the internal resistance heating curve generated by this cycle is recorded;

[0039] Determine the trend change value between different temperature points of the internal resistance heating curve, then the trend change value = vertical coordinate difference between adjacent points / lateral coordinate difference between adjacent points;

[0040] If the trend change value is greater than Y1, where Y1 represents the preset trend change value, the line segments of the adjacent points are calibrated as abnormal temperature line segments, otherwise, no calibration is performed;

[0041] Determine the ratio of the abnormal temperature line segment to the internal resistance heating curve, then the ratio = abnormal temperature line segment length / internal resistance heating curve site;

[0042] If the proportion value is greater than Y2, where Y2 represents the preset proportion value, an internal resistance heating abnormality signal is generated.

[0043] It should also be noted that the electrical test performed on the abnormal point may be a short circuit test, a resistance test, or other electrical tests suitable for performing on the abnormal point.

[0044] In the embodiment of the present application, the power test uses a short-circuit test. Before the test, the abnormal points of the short-circuit test are confirmed, and the appropriate test current and test time are set according to the specifications of the device being tested and the test purpose. It is ensured that the protection measures of the test equipment are in place to prevent overcurrent from damaging the equipment. The short-circuit current is applied, and the short-circuit current, test time and other power parameter data are recorded.

[0045] In an optional embodiment, the power test uses a resistance test. Before the test, the abnormal points of the resistance test are confirmed, and a suitable test range and resolution are selected according to the specifications of the device being tested and the test purpose. The test voltage is applied, the current passing through the test point is measured, and the resistance value is calculated using Ohm's law. The test voltage, test current, calculated resistance value and other environmental conditions that may affect the resistance value are recorded, including temperature, humidity, etc.

[0046] S3: Acquire and return the fault current signal, and feed back the fault point to the online server processing platform.

[0047] Furthermore, obtaining and returning the fault current signal includes confirming the fault time point data of the distribution network through a data monitoring device and issuing a data call command; obtaining and returning the fault current signal corresponding to the fault time point according to the corresponding signal generated by the data.

[0048] It should be noted that the data monitoring device confirms the data at the fault time point of the distribution network, including determining whether the amplitude mutation amount exceeds a preset amplitude mutation threshold;

[0049] When it is determined that the amplitude mutation exceeds the amplitude mutation threshold, when it is detected that M consecutive incremental data exceed the preset incremental threshold, the sampling time point corresponding to the first incremental data in the M incremental data is taken as the fault time point, and the fault time point is used as the timestamp of the data call instruction.

[0050] It should also be noted that all current monitoring units installed on each three-phase bus receive the data call command, so that the current monitoring units respond to the data call command, obtain and return the fault current signal corresponding to the fault time point.

[0051] The fault grounding point of the distribution network is located according to the fault current signal and fed back to the online server processing platform for processing.

[0052] Embodiment 2 is an embodiment of the present invention, which provides a method for automatically handling distribution network faults. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0053] This embodiment is carried out in a typical urban distribution network environment. The distribution network consists of multiple branch lines with a total length of about 100 kilometers and a total load of about 200 megawatts. The types of faults that may occur in the distribution network include single-phase grounding faults, phase-to-phase short circuit faults, etc.

[0054] First, the simulation experiment is prepared. Zero-sequence voltage transformers are installed at key nodes of the distribution network and connected to data monitoring devices for real-time monitoring of power parameters. An abnormality identification module is deployed to analyze monitoring data, identify abnormal nodes and determine the types of abnormal nodes. A fault judgment module is deployed to perform power tests on abnormal points and generate corresponding processing signals based on current signal data. A fault location module is deployed to obtain and return fault current signals, locate the fault grounding point of the distribution network based on the current signal, and feed back the fault point information to the online server processing platform. An online server processing platform is established to receive fault point information and process it. The processing includes fault analysis, fault recording, fault warning, etc. A set of traditional distribution network fault processing methods are also prepared. Traditional distribution network fault processing methods include manual inspections, fault indicators, etc.

[0055] Secondly, a simulation experiment is carried out to simulate various fault types in the distribution network, and the time and location of the fault are recorded. For example, a single-phase grounding fault is simulated on line 1 at 10:00:00 on October 1, and the location of the simulated fault, abnormality identification time, fault location time, fault processing time and other data of the present invention and the traditional distribution network fault handling method are recorded to obtain the results shown in Table 1.

[0056] Table 1 Distribution network fault simulation test data

[0057]

[0058] It can be seen from the data in the table that the present invention can identify abnormal nodes in a short time, with an average abnormality identification time of less than 30s, can accurately locate the fault location, with an average fault location time of less than 40s, and can accurately locate the fault location. It can reduce the fault processing time by quickly identifying the abnormality and the abnormality type and locating the fault location. Compared with the existing method, the present invention shortens the fault processing time, improves the fault processing efficiency, and reduces the risk of faulty operation of the distribution network system.

[0059] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides a distribution network fault automatic processing system, including an abnormality identification module, a fault determination module, and a fault location module.

[0060] The abnormal identification module is used to monitor power parameters in real time, identify abnormal nodes and determine the categories of abnormal nodes through abnormal identification methods; the fault judgment module is used to perform power tests on abnormal points and generate corresponding processing signals for faults based on test data; the fault location module is used to obtain and return fault current signals and feedback the fault point to the online server processing platform.

[0061] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0062] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0063] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0064] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0065] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for automatically handling distribution network faults, characterized in that: include: Monitor power parameters in real time, identify abnormal nodes through abnormal identification methods and determine the abnormal node categories; Conduct power tests on abnormal points and generate corresponding processing signals for faults based on test data; Acquire and return the fault current signal, and feed back the fault point to the online server processing platform.

2. The automatic processing method for power distribution network fault according to claim 1, characterized in that: The real-time monitoring of power parameters includes monitoring power parameters through a data monitoring device; The data monitoring device comprises a voltage monitoring unit in the data monitoring device, and a zero-sequence voltage transformer is installed at the neutral point of the busbar of the distribution network transformer.

3. The automatic processing method for power distribution network fault according to claim 2, characterized in that: The identifying of abnormal nodes includes identifying whether the power parameter monitored by the data monitoring device belongs to an abnormal node through an abnormal identification method.

4. The method for automatically handling distribution network faults according to claim 3, characterized in that: The determining the abnormal node category includes determining the abnormal node category based on the abnormal node by an abnormality identification method; The abnormal point categories include single group abnormal points and linked abnormal points; The linked abnormal points are further analyzed to determine whether they are synchronous abnormal points or single group abnormal points.

5. The automatic processing method for power distribution network fault according to claim 4, characterized in that: The generating a corresponding processing signal for the fault based on the test data includes determining an internal resistance heating curve based on the test data, determining whether there is an internal resistance heating problem at the abnormal point through the internal resistance heating curve, and generating a corresponding processing signal.

6. The method for automatically handling distribution network faults according to claim 5, characterized in that: The obtaining and returning of the fault current signal includes confirming the fault time point data of the distribution network through a data monitoring device and issuing a data call command; According to the corresponding signal generated by the data, the fault current signal corresponding to the fault time point is obtained and returned.

7. The method for automatically handling distribution network faults according to claim 6, characterized in that: Feedback of the fault point to the online server processing platform includes locating the fault grounding point of the distribution network according to the current signal and feeding it back to the online server processing platform.

8. A system using the method for automatically handling distribution network faults as claimed in any one of claims 1 to 7, characterized in that: It includes an abnormality identification module, a fault determination module, and a fault location module; The abnormality identification module is used to monitor power parameters in real time, identify abnormal nodes through an abnormality identification method, and determine the category of abnormal nodes; The fault determination module is used to perform power testing on abnormal points and generate corresponding processing signals for the faults based on the test data; The fault location module is used to obtain and return the fault current signal, and feed back the fault point to the online server processing platform.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for automatically handling distribution network faults according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for automatically handling distribution network faults according to any one of claims 1 to 7 are implemented.

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