Distribution network fault position identification method and system

Abstract

The invention provides a distribution network fault position identification method and system, and belongs to the technical field of fault identification, and the method specifically comprises the steps that an alarm signal classification module determines a credible alarm signal according to the composition data of suspected interference equipment of alarm signal monitoring equipment, and sends the credible alarm signal to an alarm signal processing module; the data processing module is responsible for performing data processing analysis to obtain a data processing result on the basis of a matching result of the credible alarm signal and a preset fault positioning model, and the positioning result output module is responsible for determining a positioning processing result of a fault position by using the data processing result, so that the accuracy of positioning processing of the fault position is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of fault identification, and in particular relates to a method and system for identifying a distribution network fault location. Background Art

[0002] The distribution of power users in the distribution network system is relatively dispersed. Once a fault occurs, it is often impossible to identify and process the fault location immediately, which may cause losses to power users. Therefore, in order to identify and process the fault location of the distribution network system, the invention patent application CN202510002570.2 "Distribution Network Fault Identification and Location Method, Device, Equipment, Medium and Product" determines the target fault location corresponding to the distribution network line based on the admittance parameter matrix when the morphological feature data meets the preset identification conditions, thereby improving the efficiency of the distribution network fault identification and location method. However, there are the following technical defects: When a distribution network line fails, there may be external interference, such as strong winds, tree branches, rainfall, etc., which may cause the distribution network line to generate an alarm signal. The above alarm signal is superimposed on the alarm signal of the real power grid fault, which may cause the identification and processing results of the power grid fault location to deviate. Therefore, if the interference alarm signal cannot be eliminated, the fault location cannot be accurately identified and processed.

[0003] In response to the above technical problems, the present application specifically provides a method and system for identifying the location of a distribution network fault. Summary of the Invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides a distribution network fault location identification system, specifically comprising: Alarm signal classification module, data processing module, positioning result output module; wherein the alarm signal classification module determines a credible alarm signal based on the composition data of the suspected interference device of the alarm signal monitoring device; The data processing module is responsible for performing data processing and analysis based on the matching result between the credible alarm signal and the preset fault location model to obtain a data processing result; The positioning result output module is responsible for determining the positioning processing result of the fault position using the data processing result.

[0005] A further technical solution is that the credible alarm signal is an alarm signal indicating that there is no suspected interference device in the monitoring device; A further technical solution is that the data processing result is the number of credible alarm signals that match failures at different locations.

[0006] A further technical solution is that the fault location is the location with the largest number of matching credible alarm signals when the fault occurs.

[0007] In a second aspect, the present application provides a distribution network fault location identification method, which is applied to the above-mentioned distribution network fault location identification system, specifically comprising: S1 determines a reference date for the current date using weather data, and proceeds to the next step if it is determined that the preset model is not required for locating the fault location based on historical fault interference data of different distribution network devices on the reference date; S2 determines an alarm device based on an alarm signal of a distribution network line, determines historical fault interference data of different monitoring targets on the reference date based on a monitoring target of the alarm device, and determines suspected interference targets among the different monitoring targets using the historical fault interference data; S3 obtains the composition data of the suspected interference targets in the monitoring targets of different alarm signals, and combines the distribution intervals between different suspected interference targets and the monitoring targets to determine whether the interference degree of the suspected interference targets meets the requirements, and then proceeds to the next step; S4 determines a credible alarm signal based on the constituent data of the suspected interference target in the monitoring target corresponding to different alarm signals, and determines the location of the fault position based on the constituent data of the suspected interference target of the credible alarm signal and the matching result with the preset fault location model.

[0008] The beneficial effects of the present invention are: The credible alarm signal is determined by the composition data of the suspected interference target in the monitoring target corresponding to different alarm signals, thereby realizing the elimination of the alarm signal caused by external interference factors and avoiding the interference of fault interference data during fault location processing. It not only lays the foundation for improving the accuracy of fault location processing, but also accurately realizes the screening of alarm signals with a higher probability of interference.

[0009] The fault location is determined by combining the constituent data of the suspected interference target of the credible alarm signal with the matching results of the preset fault location model. This not only takes into account the matching of the credible alarm signal with faults occurring at different locations, but also takes into account the differences in the credibility of the credible alarm signal due to the differences in the constituent data of the suspected interference target. This enables the positioning of the fault location from multiple dimensions, ensuring the accuracy and reliability of the fault location processing results.

[0010] A further technical solution is that the reference date is a historical date whose deviation from the weather data of the current date is within a preset weather data deviation range.

[0011] A further technical solution is that the historical fault interference data is fault data of the distribution network equipment under external environmental interference.

[0012] A further technical solution is that the external environment includes strong winds, rainfall and tree branches.

[0013] A further technical solution is that the historical fault interference data includes the number of historical fault interferences of the distribution network equipment on different reference dates.

[0014] A further technical solution is to determine that it is not necessary to use a preset model to locate the fault location, specifically including: Determining the number of historical fault interferences of different distribution network devices on different reference dates based on the analysis results of the historical fault interference data of different distribution network devices on the reference date; The reference date with the number of historical fault interferences is used as the interference reference date of the distribution network device, and the distribution network device whose interference reference date accounts for a greater proportion than the preset interference reference date in the reference date is used as the fault interference device; According to the number of the faulty interfering devices, it is determined whether a preset model needs to be used to locate the fault position.

[0015] A further technical solution is that, when the number of the faulty interfering devices is greater than a preset number of interfering devices, it is determined that a preset model needs to be used to locate the fault position.

[0016] A further technical solution is that the method for determining the positioning processing result of the fault position is: Determine a proportion of the number of suspected interference targets in the credible alarm signal using the composition data of the suspected interference targets in the credible alarm signal, and determine a signal deviation probability of the credible alarm signal using the composition proportion; According to the matching results of the credible alarm signal and the preset fault location model, the number of credible alarm signals matching the fault occurrence at different locations is determined, and the fault potential value of the different locations is determined according to the proportion of the matching number; The fault matching value of the location is determined by the ratio of the fault potential value of different locations to the average value of the signal deviation probability of the credible alarm signal matched when the fault occurs at the location, and the positioning processing result of the fault location is determined using the fault matching value.

[0017] A further technical solution is that the positioning processing result of the fault position is the position with the maximum fault matching value.

[0018] Other features and advantages will be described in the following description, and in part will become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings.

[0021] Figure 1 It is a framework diagram of a distribution network fault location identification system; Figure 2 It is a flow chart of a method for identifying a distribution network fault location; Figure 3 It is a flow chart for determining that it is not necessary to use a preset model to locate the fault location; Figure 4 The present invention is a flow chart of a method for determining a suspected interference target among monitoring targets. DETAILED DESCRIPTION

[0022] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the figures represent like or similar structures, and thus their detailed description will be omitted.

[0023] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0024] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a distribution network fault location identification system is provided, specifically comprising: Alarm signal classification module, data processing module, positioning result output module; wherein the alarm signal classification module determines a credible alarm signal based on the composition data of the suspected interference device of the alarm signal monitoring device; The data processing module is responsible for performing data processing and analysis based on the matching result between the credible alarm signal and the preset fault location model to obtain a data processing result; The positioning result output module is responsible for determining the positioning processing result of the fault position using the data processing result.

[0025] Furthermore, the credible alarm signal is an alarm signal indicating that there is no suspected interference device in the monitoring device.

[0026] Specifically, the data processing result is the number of credible alarm signals that match failures at different locations.

[0027] It should be noted that the fault location is the location with the largest number of matching credible alarm signals when the fault occurs.

[0028] Example 2 Second, as Figure 2 As shown, the present application provides a distribution network fault location identification method, which is applied to the above-mentioned distribution network fault location identification system, specifically comprising: S1 determines a reference date for the current date using weather data, and proceeds to the next step if it is determined that the preset model is not required for locating the fault location based on historical fault interference data of different distribution network devices on the reference date; S2 determines an alarm device based on an alarm signal of a distribution network line, determines historical fault interference data of different monitoring targets on the reference date based on a monitoring target of the alarm device, and determines suspected interference targets among the different monitoring targets using the historical fault interference data; S3 obtains the composition data of the suspected interference targets in the monitoring targets of different alarm signals, and combines the distribution intervals between different suspected interference targets and the monitoring targets to determine whether the interference degree of the suspected interference targets meets the requirements, and then proceeds to the next step; S4 determines a credible alarm signal based on the constituent data of the suspected interference target in the monitoring target corresponding to different alarm signals, and determines the location of the fault position based on the constituent data of the suspected interference target of the credible alarm signal and the matching result with the preset fault location model.

[0029] Furthermore, the reference date is a historical date whose deviation from the weather data of the current date is within a preset weather data deviation range.

[0030] It should be noted that the historical fault interference data is the fault data of the distribution network equipment under external environment interference.

[0031] Furthermore, the external environment includes strong winds, rainfall, and tree branches.

[0032] It should also be noted that the historical fault interference data includes the number of historical fault interferences of the distribution network equipment on different reference dates.

[0033] Specifically, such as Figure 3 As shown, it is determined that there is no need to use the preset model to locate the fault location, specifically including: Determining the number of historical fault interferences of different distribution network devices on different reference dates based on the analysis results of the historical fault interference data of different distribution network devices on the reference date; The reference date with the number of historical fault interferences is used as the interference reference date of the distribution network device, and the distribution network device whose interference reference date accounts for a greater proportion than the preset interference reference date in the reference date is used as the fault interference device; According to the number of the faulty interfering devices, it is determined whether a preset model needs to be used to locate the fault position.

[0034] Furthermore, when the number of the faulty interfering devices is greater than the preset number of interfering devices, it is determined that a preset model needs to be used to locate the fault position.

[0035] It should be noted that when a preset model is required to be used for locating the fault position, the alarm signal is used as the input of the preset model, and the fault position is located according to the output of the preset model.

[0036] Specifically, the alarm device is a device that sends an alarm signal in the distribution network line.

[0037] Furthermore, the monitoring target is the distribution network equipment monitored and processed by the alarm device.

[0038] It should be noted that if Figure 4 As shown, the method for determining the suspected interference target among the monitoring targets is: Determining the number of historical fault interferences of the monitoring target on different reference dates using the historical fault interference data; Using the reference date with the number of historical fault interferences as the interference reference date of the monitoring target; The monitoring targets whose interference reference dates account for a larger proportion of the number of interference reference dates than the preset proportion of the number of interference reference dates are regarded as suspected interference targets; Furthermore, the composition data of the suspected interference targets in the monitoring target includes the composition quantity of the suspected interference targets in the monitoring target.

[0039] In another possible embodiment, determining whether the interference level of the suspected interference target meets the requirement specifically includes: Determining the number ratio of the suspected interference targets in the monitoring targets of different alarm signals based on the constituent data of the suspected interference targets in the monitoring targets of different alarm signals, and determining the signal deviation value of the different alarm signals based on the number ratio of the suspected interference targets; Determine the number of suspected interference targets within a preset distance range of the monitoring target based on the distribution intervals between different suspected interference targets and the monitoring target, and determine the signal interference target in the monitoring target based on the number of suspected interference targets within the preset distance range; An interference value evaluation amount is determined based on the signal deviation values ​​of different alarm signals and the proportion of the number of signal interference targets in the monitored targets, and the interference value evaluation amount is used to determine whether the interference degree of the suspected interference target meets the requirements.

[0040] Furthermore, the signal interference target is a monitoring target whose number of suspected interference targets within a preset distance range is greater than the preset number of interference targets, wherein the preset distance range is the suspected interference targets within the nearest 2 km.

[0041] Specifically, the interference value evaluation amount is determined according to the average value of the signal deviation values ​​of different alarm signals and the average value of the proportion of the number of signal interference targets in the monitoring targets.

[0042] It should be noted that, when the interference value evaluation amount is greater than the evaluation amount preset value, it is determined that the interference level of the suspected interference target does not meet the requirements.

[0043] It is understandable that when the interference level of the suspected interference target does not meet the requirement, the preset model is used to locate the fault position.

[0044] Furthermore, the method for determining the credible alarm signal is: Determining the composition ratio of the suspected interference targets in the monitoring target corresponding to the alarm signal based on the composition data of the suspected interference targets in the monitoring target corresponding to the alarm signal; Based on the proportion of the number of components, it is determined whether the alarm signal is a credible alarm signal.

[0045] Specifically, when the component quantity ratio is less than a preset component quantity ratio threshold, the alarm signal is determined to be a credible alarm signal.

[0046] It should be noted that the method for determining the fault location processing result is: Determine a proportion of the number of suspected interference targets in the credible alarm signal using the composition data of the suspected interference targets in the credible alarm signal, and determine a signal deviation probability of the credible alarm signal using the composition proportion; According to the matching results of the credible alarm signal and the preset fault location model, the number of credible alarm signals matching the fault occurrence at different locations is determined, and the fault potential value of the different locations is determined according to the proportion of the matching number; The fault matching values ​​of different locations are determined by the ratio of the fault potential value of different locations to the average value of the signal deviation probability of the credible alarm signal matched when the fault occurs at the location, and the positioning processing result of the fault location is determined using the fault matching value.

[0047] It can be understood that the fault matching value of the location is the ratio of the fault potential value of the location to the average value of the signal deviation probability of the credible alarm signal matched when a fault occurs at the location.

[0048] Furthermore, the positioning processing result of the fault position is the position with the largest fault matching value.

[0049] Optionally, the method for determining the result of the positioning processing of the fault position is: Using the composition data of the suspected interference targets of the credible alarm signal, determining the composition number ratio of the suspected interference targets of the credible alarm signal, and using the composition number ratio to determine the signal deviation probability of the credible alarm signal, taking the credible alarm signal whose signal deviation probability is less than a preset deviation probability threshold as the target alarm signal, and using the output result of the preset fault location model to determine the alarm signal when a fault occurs at the location, if it does not include any one of the target alarm signals, then determining that the location is not a fault location; When the alarm signal when a fault occurs at the location matches the target alarm signal: Determining, based on a matching result between the credible alarm signal and a preset fault location model, the number of credible alarm signals that match faults occurring at different locations, and determining that the location is not a fault location when the number of credible alarm signals that match faults occurring at the location does not meet a requirement; When the number of credible alarm signals matching the fault at the location meets the requirement: The proportion of the number of matched credible alarm signals when a fault occurs at the location in the credible alarm signals is used as a matching number proportion; when the matching number proportion is less than a preset matching number proportion threshold, it is determined that the location is not a fault location; When the matching quantity ratio is not less than the preset matching quantity ratio threshold: Determining fault potential values ​​for different locations based on the matching number ratios, and determining a fault matching value for each location based on a ratio of the fault potential values ​​for each location to an average value of a signal deviation probability of a credible alarm signal that matches the location when a fault occurs. When the fault matching value is less than a preset fault matching value threshold, determining that the location is not a fault location. When the fault matching value is not less than the preset fault matching value threshold: The number of unmatched credible alarm signals and the signal deviation probability are obtained, and combined with the fault matching value of the position, a matching value evaluation amount of the position is determined, and the positioning processing result of the fault position is determined using the matching value evaluation amount.

[0050] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0051] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0052] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A distribution network fault location identification system, characterized in that: Specifically include: Alarm signal classification module, data processing module, positioning result output module; wherein the alarm signal classification module determines a credible alarm signal based on the composition data of the suspected interference device of the alarm signal monitoring device; The data processing module is responsible for performing data processing and analysis based on the matching result between the credible alarm signal and the preset fault location model to obtain a data processing result; The positioning result output module is responsible for determining the positioning processing result of the fault position using the data processing result.

2. The distribution network fault location identification system according to claim 1, characterized in that: The credible alarm signal is an alarm signal indicating that there is no suspected interference device in the monitoring device.

3. The distribution network fault location identification system according to claim 1, characterized in that: The data processing result is the number of credible alarm signals that match faults occurring at different locations.

4. The distribution network fault location identification system according to claim 1, characterized in that: The fault location is the location with the largest number of matching credible alarm signals when a fault occurs.

5. A distribution network fault location identification method, applied to a distribution network fault location identification system according to any one of claims 1 to 4, characterized in that: Specifically include: Using weather data to determine a reference date for the current date, and using historical fault interference data of different distribution network devices on the reference date to determine that it is not necessary to use a preset model to locate the fault location, proceed to the next step; Determine an alarm device based on an alarm signal of a distribution network line, determine historical fault interference data of different monitoring targets on the reference date based on a monitoring target of the alarm device, and determine suspected interference targets among the different monitoring targets using the historical fault interference data; Obtaining the composition data of the suspected interference targets in the monitoring targets of different alarm signals, and combining the distribution intervals between different suspected interference targets and the monitoring targets to determine whether the interference degree of the suspected interference targets meets the requirements, proceeding to the next step; The credible alarm signal is determined by the constituent data of the suspected interference target in the monitoring target corresponding to different alarm signals, and the fault location is determined by the constituent data of the suspected interference target of the credible alarm signal and the matching result with the preset fault location model.

6. The method for identifying a distribution network fault location according to claim 5, wherein: The reference date is a historical date whose weather data deviation from the current date is within a preset weather data deviation range.

7. The method for identifying a distribution network fault location according to claim 5, wherein: The historical fault interference data is the fault data of the distribution network equipment under external environment interference.

8. The method for identifying a distribution network fault location according to claim 5, wherein: Determine that the preset model is not needed for fault location processing, including: Determining the number of historical fault interferences of different distribution network devices on different reference dates based on the analysis results of the historical fault interference data of different distribution network devices on the reference date; The reference date with the number of historical fault interferences is used as the interference reference date of the distribution network device, and the distribution network device whose interference reference date accounts for a greater proportion than the preset interference reference date in the reference date is used as the fault interference device; According to the number of the faulty interfering devices, it is determined whether a preset model needs to be used to locate the fault position.

9. The method for identifying a distribution network fault location according to claim 8, wherein: When the number of the faulty interfering devices is greater than the preset number of interfering devices, it is determined that a preset model needs to be used to locate the fault position.

10. The method for identifying a distribution network fault location according to claim 5, wherein: The method for determining the result of the fault location processing is as follows: Determine a proportion of the number of suspected interference targets in the credible alarm signal using the composition data of the suspected interference targets in the credible alarm signal, and determine a signal deviation probability of the credible alarm signal using the composition proportion; According to the matching results of the credible alarm signal and the preset fault location model, the number of credible alarm signals that match the faults at different locations is determined, and the fault potential coefficient of the different locations is determined according to the proportion of the matching numbers; The fault matching coefficient of the location is determined by the ratio of the fault potential coefficient of different locations to the average value of the signal deviation probability of the credible alarm signal matched when a fault occurs at the location, and the positioning processing result of the fault location is determined using the fault matching coefficient.

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