A power distribution automation detection method and detection system

Abstract

The application discloses a power distribution automation detection method and a detection system. The detection method comprises the following steps: performing regional division on a power distribution network to obtain a plurality of to-be-detected regions; a plurality of detection devices are included in one to-be-detected region; detection data of the detection devices in the plurality of to-be-detected regions are acquired, and a plurality of detection tables corresponding to the plurality of to-be-detected regions are generated; the detection table comprises the detection data of the plurality of detection devices in the same to-be-detected region; and it is determined whether there is abnormal data according to the detection table. Through the above scheme, a large number of detection devices in the power distribution network can be managed in a partitioned manner. The detection data of the plurality of detection devices in the same to-be-detected region are integrated in one detection table, and the detection data of the detection devices are automatically compared by filling the detection table, so that the integration degree of the detection data in the same to-be-detected region is improved, the data analysis efficiency is improved, and efficient and automatic processing of daily inspection data is realized.

Description

TECHNICAL FIELD

[0001] The embodiment of the application relates to the technical field of power distribution networks, in particular to a power distribution automation detection method and a detection system. BACKGROUND

[0002] The power distribution system mainly relies on manual inspection and simple relay protection devices for fault judgment. This method is inefficient and has a high probability of missed detection. With the progress of science and technology, various detection devices such as sensors, intelligent switches and the like have been put into use. These devices can collect operating parameters in real time and perform fault diagnosis to provide a basis for subsequent decision-making. This method improves the accuracy and efficiency of detection.

[0003] After the detection devices are laid out in the power distribution network, the daily system inspection of the power distribution network is often to obtain the detection data of the detection devices, and to realize the automatic detection of the working state of the power distribution network after analysis. In the prior art, the analysis of the detection data is often one-to-one analysis, that is, after the detection data of the detection devices is obtained, it is sent to a corresponding background processing system. Thus, once the background processing system fails, the detection of the power distribution network data will fail, and the centralized processing of a large number of detection devices will result in complicated data, high requirements for hardware, and slow data processing speed. SUMMARY

[0004] Therefore, the embodiment of the application provides a power distribution automation detection method and a detection system to improve the data analysis efficiency and realize efficient and automatic processing of daily inspection data.

[0005] In a first aspect, the embodiment of the application provides a power distribution automation detection method, which comprises the following steps:

[0006] The power distribution network is regionally divided to obtain a plurality of to-be-inspected regions; each to-be-inspected region comprises a plurality of detection devices;

[0007] Detection data of the detection devices in the plurality of to-be-inspected regions is obtained, and a plurality of detection tables corresponding to the plurality of to-be-inspected regions respectively are generated; the detection table comprises detection data of a plurality of detection devices in the same to-be-inspected region;

[0008] It is determined whether there is abnormal data according to the detection table.

[0009] In a second aspect, the embodiment of the application further provides a power distribution automation detection system, which is suitable for the power distribution automation detection method provided by any embodiment of the application, and comprises the following:

[0010] A region division module is configured to divide the power distribution network regionally to obtain a plurality of to-be-inspected regions; each to-be-inspected region comprises a plurality of detection devices;

[0011] a data acquisition module configured to acquire detection data of the detection devices in the plurality of the to-be-inspected areas and generate detection tables corresponding to the plurality of the to-be-inspected areas respectively; the detection table comprises detection data of the detection devices in the same to-be-inspected area;

[0012] an anomaly analysis module configured to determine whether there is abnormal data according to the detection table.

[0013] The power distribution automation detection method provided by the embodiment of the present application first divides the power distribution network into areas to obtain a plurality of to-be-inspected areas; each to-be-inspected area comprises a plurality of detection devices; then acquires detection data of the detection devices in the plurality of to-be-inspected areas and generates detection tables corresponding to the plurality of to-be-inspected areas respectively; the detection table comprises detection data of the detection devices in the same to-be-inspected area; finally, determines whether there is abnormal data according to the detection table. By dividing the power distribution network into areas, a large number of detection devices in the power distribution network can be managed in zones. The detection data of the detection devices in the same to-be-inspected area are integrated in a detection table, and the filling of the detection table is used to realize automatic comparison of the detection data of the detection devices, which can improve the integration of the detection data in the same to-be-inspected area, avoid the problems of complicated data and slow data processing speed caused by one-to-one data analysis in the prior art, and realize efficient and automatic processing of daily inspection data. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 FIG. 1 is a flowchart of a power distribution automation detection method provided by an embodiment of the present application;

[0015] Figure 2 FIG. 2 is a flowchart of a power distribution automation detection method provided by an embodiment of the present application;

[0016] Figure 3 FIG. 3 is a flowchart of a power distribution automation detection method provided by an embodiment of the present application;

[0017] Figure 4 FIG. 4 is a structural diagram of a power distribution automation detection system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0018] The present application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, for the convenience of description, only the parts related to the present application are shown in the drawings, but not all the structures.

[0019] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc. Moreover, embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0020] The term "comprising" and its variations as used in this invention are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment".

[0021] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish the corresponding contents and are not used to limit the order or interdependence.

[0022] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0023] Example 1

[0024] Figure 1 This is a flowchart illustrating a power distribution automation detection method provided in Embodiment 1 of the present invention. This method is applicable to the automatic monitoring and detection of power distribution networks. It can be implemented using a power distribution automation detection platform, which is applied within a power distribution automation detection system. For example... Figure 1 As shown, the power distribution automation detection method provided in Embodiment 1 of the present invention includes the following steps:

[0025] S110. Divide the power distribution network into regions to obtain multiple regions to be inspected.

[0026] A power distribution automation detection system may include a zone division module, a data acquisition module, and an anomaly analysis module. The zone division module can divide the detection devices in the power distribution network according to regions (i.e., locations), creating multiple inspection zones. Each inspection zone contains multiple detection devices. These multiple detection devices within an inspection zone may be geographically adjacent to each other.

[0027] By dividing the power distribution network into regions, a large number of monitoring devices in the power distribution network can be divided into zones, thereby enabling zoned monitoring and management of the monitoring devices.

[0028] S120. Obtain the detection data of the detection devices in multiple areas to be inspected, and generate detection tables corresponding to the multiple areas to be inspected respectively.

[0029] Furthermore, each detection device can feed back its own operating data in real time or at intervals. The operating data fed back by the detection devices is the power grid data, which is the detection data to be acquired in this embodiment. The data acquisition module can acquire the detection data of multiple detection devices in each area to be inspected and generate a detection table corresponding to each area to be inspected. The data acquisition module sends the detection table to the anomaly analysis module.

[0030] A single test table can include test data from multiple testing devices within the same test area. By integrating the test data from multiple testing devices within the same test area into one test table, the integration rate of test data within the same test area can be improved.

[0031] The embodiments of the present invention do not limit the form of the detection table. It should be noted that the detection table should reflect the location information (or address information) carried by each detection device and the corresponding detection data of the detection device.

[0032] S130. Determine whether there is any abnormal data based on the test table.

[0033] Furthermore, the test table includes the test data of the testing device, and the anomaly analysis module can determine whether there is abnormal data in the test area based on the test table of each test area.

[0034] Abnormal data refers to operating data that exceeds the preset operating threshold range of the detection device. The preset operating threshold range refers to the range of operating data values ​​corresponding to the safe operation of the detection device.

[0035] It is understandable that when the actual detection data of the detection device exceeds the preset working threshold range, it indicates that the detection device may be malfunctioning. At this time, the detection data can be marked as abnormal data to realize the automatic judgment of abnormal situations of the detection data, thereby automatically monitoring the working status of the detection device.

[0036] Optionally, in some embodiments, the anomaly analysis module may store preset working threshold ranges for each detection device. After receiving the detection tables for each area to be inspected, it can automatically compare the actual detection data of the detection devices with the preset working threshold ranges and determine whether there is abnormal data based on the comparison results. Alternatively, in other embodiments, the data acquisition module may store preset working threshold ranges for each detection device. After receiving the detection data from the detection devices, the data acquisition module can generate a detection table containing the detection data of each detection device and the preset working threshold ranges. The anomaly analysis module can directly compare the actual detection data of each detection device in the detection table with the preset working threshold ranges, and then determine whether there is abnormal data based on the comparison results.

[0037] The power distribution automation detection method provided in Embodiment 1 of this invention first divides the power distribution network into multiple inspection areas; each inspection area includes multiple detection devices; then, it acquires the detection data of the detection devices in the multiple inspection areas and generates multiple detection tables corresponding to each inspection area; the detection tables include the detection data of multiple detection devices in the same inspection area; finally, it determines whether there is abnormal data based on the detection tables. In this invention, by dividing the power distribution network into areas, a large number of detection devices in the power distribution network can be managed by region. Integrating the detection data of multiple detection devices in the same inspection area into a single detection table, and using the filling of the detection table to achieve automated comparison of the detection data of the detection devices, can improve the integration of detection data in the same inspection area, avoid the problems of cumbersome data and slow data processing speed caused by one-to-one data analysis in the prior art, and achieve efficient automated processing of daily inspection data.

[0038] Based on the above embodiments, the present invention also proposes variant embodiments of the above embodiments. It should be noted that, in order to keep the description brief, only the differences from the above embodiments are described in the variant embodiments.

[0039] For example, in some embodiments, the detection table also includes a preset working threshold range corresponding to the detection device, the preset working threshold range being the operating data corresponding to the safe operation of the detection device; (S130) in the above embodiment can be refined as follows: comparing the detection data of each detection device in the same detection table with the preset working threshold range; marking abnormal data when the detection data exceeds the corresponding preset working threshold range.

[0040] The system can pre-collect the range of operating data from the testing device under safe working conditions, using this range as the preset operating threshold range for the device. The preset operating threshold range refers to the operating data values ​​between the device's minimum and maximum safe operating thresholds. When generating the test table, the collected testing data and the preset operating threshold range can be simultaneously populated into the table. This facilitates automated comparison of subsequent testing data with the preset operating threshold range.

[0041] In the test table, the test data of the testing devices and the preset working threshold ranges are in a one-to-one correspondence. When testing a certain area to be tested, the test table corresponding to that area is obtained, and the test data of the testing devices in the test table is compared with the preset working threshold ranges one by one. When the test data of a certain testing device exceeds its preset working threshold range, that is, when the test data is less than the minimum safe working threshold or greater than the maximum safe working threshold, it indicates that the testing device is malfunctioning. At this time, the test data can be marked as abnormal data, and the corresponding testing device can be marked as an abnormal device.

[0042] Further optionally, in some embodiments, before (S120) of the above embodiment, the method further includes: marking coordinates and timing all detection devices in the same inspection area; (S120) can be refined to: acquiring detection data of the detection devices with coordinates and timing, and generating multiple inspection tables corresponding to the inspection areas respectively; the inspection table includes coordinates, timing, detection data, and preset working threshold ranges of multiple detection devices in the same inspection area; after (marking abnormal data when the detection data exceeds the corresponding preset working threshold range) of the above embodiment, the method may further include: determining the coordinates of the detection devices with abnormal data markings to locate the abnormal devices.

[0043] In this embodiment, the detection devices in the power distribution network can have coordinate markers. Different detection devices have different coordinate markers, which serve as unique identifiers for each device. Before generating the detection table, coordinate markers and detection time markers can be applied to several detection devices within the same inspection area. The coordinate markers reflect the location information of the detection devices, and the detection time markers reflect the acquisition time of the detection data.

[0044] Coordinate markers and acquisition time markers can serve as spatiotemporal marker information. After acquiring the detection data of each detection device within the inspection area, a detection table for the same inspection area can be generated based on the spatiotemporal marker information of the detection devices, resulting in a detection table corresponding to each inspection area. By setting the detection table and spatiotemporal marker information, rapid filling and comparison of detection data can be achieved through mapping, further improving the processing efficiency of detection data.

[0045] The form of the coordinate markers and acquisition time markers is not limited. For example, the coordinate markers can be location coordinates, and the acquisition time markers can be the acquisition time or acquisition period, but are not limited to these.

[0046] Table 1 is a detection table provided in an embodiment of the present invention. Taking Table 1 as an example, the content of the detection table can be arranged with the coordinate markers corresponding to multiple detection devices as the vertical column of the table header, the detection time markers as the horizontal column of the table header, and the intersection of the vertical and horizontal columns as the detection data collected by the detection devices. Notably, Table 1 does not show the preset working threshold range of the detection devices. This parameter can be located in one cell of the coordinate markers in the vertical column, or it can be located in the same cell as the detection data; this embodiment does not impose any limitations on this.

[0047] Table 1

[0048] Acquisition time stamp …… Acquisition time stamp Coordinate marker Detection data Detection data Detection data …… Detection data Detection data Detection data Coordinate marker Detection data Detection data Detection data

[0049] Furthermore, by marking the coordinates and detection time of the detection device, the device can be accurately located directly in the detection table. When abnormal data occurs, the abnormal device can be located using the coordinate markers corresponding to the abnormal data, allowing for quick acquisition of the device's specific location information and facilitating immediate repair.

[0050] Example 2

[0051] Figure 2 This is a flowchart illustrating a power distribution automation detection method according to Embodiment 2 of the present invention. Embodiment 2 is an optimization based on the above embodiment. In this embodiment, before (S130) in the above embodiment, it further includes: S221, selecting a region to be inspected as the current region to be inspected, and at least one other region to be inspected as a shared region to be inspected; S222, sending the detection data corresponding to the current region to be inspected to the detection tables of the current region to be inspected and the shared region to be inspected respectively; (S130) can be refined to: S230, determining whether there is abnormal data by combining the detection table of the current region to be inspected and the detection table of the shared region to be inspected. For details not covered in this embodiment, please refer to Embodiment 1, such as... Figure 2 As shown, the power distribution automation detection method provided in this embodiment includes the following steps:

[0052] S210. Divide the power distribution network into regions to obtain multiple regions to be inspected.

[0053] A region to be inspected includes multiple detection devices.

[0054] S220. Obtain the detection data of the detection devices in multiple areas to be inspected, and generate detection tables corresponding to the multiple areas to be inspected respectively.

[0055] The test report includes test data from multiple testing devices in the same area to be tested.

[0056] S221. Select one area to be inspected as the current area to be inspected, and at least one other area to be inspected as a shared area to be inspected.

[0057] In this embodiment, the automated detection of each area to be inspected can be performed sequentially. First, any area to be inspected can be selected as the current area to be inspected. The current area to be inspected refers to the area to which the detection device about to perform data comparison belongs. Besides the current area to be inspected, at least one of the remaining areas to be inspected can be selected as a co-operating area to be inspected. A co-operating area to be inspected refers to the area to which the detection device currently does not require data comparison, i.e., the co-operating area to be inspected is in an idle state.

[0058] S222. Send the detection data corresponding to the current area to be inspected to the detection tables of the current area to be inspected and the shared area to be inspected.

[0059] Furthermore, the detection data of the devices in the current inspection area can be synchronously shared to the shared inspection area, so that the detection tables in both the current inspection area and the shared inspection area store the detection data of the devices in the current inspection area. In other words, the detection data in the current inspection area can be filled into the detection table of the shared inspection area.

[0060] For example, the detection device in the current area to be inspected can be defined as the current detection device, and the detection data of the current detection device can be defined as the current detection data. The detection table corresponding to the current area to be inspected is itself filled with the current detection data. In this step, the current detection data can be simultaneously shared with the detection tables of the collaborative areas to be inspected, so that the detection tables in the collaborative areas to be inspected are also filled with the current detection data. That is, both the detection table corresponding to the current area to be inspected and the detection table corresponding to the collaborative areas to be inspected are filled with the detection data of the current area to be inspected.

[0061] S230. Determine whether there is any abnormal data by combining the test table of the current area to be inspected and the test table of the shared area to be inspected.

[0062] The anomaly detection module can determine whether there are any anomalies in the detection devices in the current inspection area by combining the detection data from the detection tables in the current inspection area and the collaborative inspection areas. Automated comparison of the current detection data is performed using the idle collaborative inspection areas, essentially a re-examination of the current detection data. Through collaborative comparison processing across different inspection areas, a distributed processing approach ensures the accuracy of the detection data processing, thereby providing a more precise guarantee for the identification of data anomalies.

[0063] Based on the above embodiments, the present invention also proposes variant embodiments of the above embodiments. It should be noted that, in order to keep the description brief, only the differences from the above embodiments are described in the variant embodiments.

[0064] Optionally, in some embodiments, the detection table also includes a preset working threshold range corresponding to the detection device, the preset working threshold range being the operating data corresponding to the safe operation of the detection device; (S230) in the above embodiment can be refined as follows: compare the detection data in the detection table of the current area to be inspected with the preset working threshold range to obtain a first comparison result; compare the detection data in the detection table of one of the auxiliary areas to be inspected with the preset working threshold range to obtain a second comparison result; when the first comparison result and the second comparison result are consistent, determine that the first comparison result of the current area to be inspected is correct, and determine whether there is abnormal data based on the first comparison result.

[0065] In this embodiment, the detection data of each detection device in the detection table of the current area to be inspected is first compared with a preset working threshold range to obtain a first comparison result. The first comparison result is the data comparison result obtained based on the detection table of the current area to be inspected. Then, the detection data of each detection device in the detection table of the shared area to be inspected is compared with a preset working threshold range to obtain a second comparison result. The second comparison result is the data comparison result obtained based on the detection table of the shared area to be inspected. The first comparison result can be regarded as the initial comparison result, and the second comparison result can be regarded as the re-examination comparison result.

[0066] Furthermore, the first comparison result and the second comparison result can be compared. If the first comparison result and the second comparison result are consistent, that is, the abnormal data marked in the two comparison results are the same, then the first comparison result of the current area to be inspected (and the second comparison result of the area to be inspected) can be determined to be correct. At this time, the presence of abnormal data can be determined based on the data comparison result of the detection table in the current area to be inspected, and abnormal data can be marked when abnormal data is present.

[0067] Further optionally, based on the above embodiments, the above (S230) may further include the following steps: when the first comparison result and the second comparison result are inconsistent, the detection data in the detection table of another co-assisted inspection area is compared with the preset working threshold range to obtain a third comparison result; when the first comparison result and the third comparison result are consistent, it is determined that the first comparison result of the current inspection area is correct, the second comparison result of the initial co-assisted inspection area is abnormal, and it is determined whether there is abnormal data based on the first comparison result; when the first comparison result and the third comparison result are inconsistent, and the second comparison result and the third comparison result are consistent, it is determined that the first comparison result of the current inspection area is abnormal, the second comparison result of the initial co-assisted inspection area is correct, and it is determined whether there is abnormal data based on the second comparison result.

[0068] Specifically, if the first and second comparison results are inconsistent, meaning the abnormal data marked in the two comparison results are different, then one or more additional areas to be jointly inspected are selected. The first selected area to be jointly inspected can be defined as the initial area, and the next selected area as the subsequent area. The detection data is then compared again based on the detection table of the subsequent areas. The second comparison result is the data comparison result of the detection table corresponding to the initial area, and the third comparison result is the data comparison result of the detection table corresponding to the subsequent areas.

[0069] Furthermore, the first and third comparison results can be compared. If the first and third comparison results are consistent, meaning the abnormal data marked in the first and third comparison results are the same, it indicates that the first comparison result of the current area to be inspected (and the subsequent third comparison result of the jointly inspected area) is correct, and the second comparison result of the initial jointly inspected area is abnormal. At this point, it can be determined whether there is abnormal data based on the data comparison results of the detection table in the current area to be inspected, and abnormal data can be marked when it appears. In addition, when it is determined that the second comparison result of the initial jointly inspected area is abnormal, the initial jointly inspected area can be marked as an abnormal area to be repaired, indicating that the detection table of this area may be incorrect and the detection data may be abnormal.

[0070] If the first and third comparison results are inconsistent, the second and third comparison results can be compared. If the second and third comparison results are consistent, meaning the abnormal data marked in the second and third comparison results are the same, it indicates that the first comparison result of the current area to be inspected is abnormal, while the data comparison results (including the second and third comparison results) of the collaborative areas to be inspected (including the initial collaborative area and subsequent collaborative areas to be inspected) are normal. In this case, the presence of abnormal data can be determined based on the data comparison results of the detection tables in the collaborative areas to be inspected, and abnormal data can be marked when it is found. Additionally, when the first comparison result of the current area to be inspected is determined to be abnormal, the current area to be inspected can be marked as an abnormal area to be repaired, indicating that the detection table in this area may be incorrect and the detection data may be abnormal.

[0071] It should be noted that the aforementioned subsequent joint inspection areas may include multiple joint inspection areas. The data comparison results of multiple subsequent joint inspection areas can be compared with the first comparison result in turn, so as to conduct a re-examination based on the first comparison result.

[0072] Further optionally, the above (S230) may also include: issuing an alarm when the first comparison result, the second comparison result and the third comparison result are inconsistent.

[0073] If, after comparing the second and third comparison results, there is a discrepancy between the first, second, and third comparison results, an alarm can be triggered to introduce manual review and perform abnormal repairs on the multiple areas to be inspected involved in the comparison.

[0074] In addition, if a certain idle area is repeatedly selected as a co-inspection area, an alarm can be triggered, manual review can be introduced, and abnormal repairs can be performed on multiple inspection areas participating in the comparison.

[0075] In this embodiment, the accuracy of the automated comparison results of the detection data can be guaranteed by using information cross-validation.

[0076] For example, suppose there are four areas to be inspected: A, B, C, and D. Area A can be selected as the current area to be inspected, while the remaining three idle areas (B, C, and D) are designated as shared inspection areas. The detection data of area A is shared with the three shared inspection areas (B, C, and D). Specifically, area B can be selected as the initial shared inspection area. The first comparison result of area A and the second comparison result of area B are compared. If they match, the first comparison result is considered correct; if they do not match, areas C and D can be selected successively as subsequent shared inspection areas. The first comparison result of area A to be inspected is compared with the third comparison result of area C to be inspected. If they match, the first comparison result is determined to be correct and the second comparison result to be abnormal. If they do not match, the second comparison result of area B to be inspected is compared with the third comparison result of area C to be inspected. If they match, the first comparison result is determined to be abnormal and the second comparison result to be correct. If they do not match, the comparison continues to be performed between the first comparison result of area A to be inspected and the third comparison result of area D to be inspected. If the first comparison result matches the third comparison result of area D to be inspected, the first comparison result is determined to be correct and the second comparison result to be abnormal. If the first comparison result does not match the third comparison result of area D to be inspected, the second comparison result of area B to be inspected is compared with the third comparison result of area D to be inspected. If they match, the first comparison result is determined to be abnormal and the second comparison result to be correct. If they do not match, it indicates that the comparison results of multiple areas to be inspected are abnormal. In this case, an alarm can be issued and manual review can be introduced.

[0077] Optionally, in possible embodiments, before (S221) in the above embodiments, it may further include: forming a detection set by assembling a plurality of adjacent areas to be inspected; (S221) may be refined to: selecting one area to be inspected in the detection set as the current area to be inspected, and at least one other area to be inspected as a co-inspection area.

[0078] Based on the location of the areas to be inspected, multiple adjacent areas can be grouped into a detection set. Any one area in the detection set is selected as the current area to be inspected, and at least one other area in the set is designated as a shared area to be inspected. Using the detection set as a unit, the detection data within each area is automatically compared sequentially to complete the anomaly detection of the detection device.

[0079] For example, assuming the first detection set includes four adjacent inspection areas A, B, C and D, one of the four inspection areas A, B, C and D can be selected as the current inspection area, and the remaining three inspection areas can be used as co-inspection areas. In this way, the detection data in the four inspection areas A, B, C and D are automatically compared in turn, and the abnormal detection of the detection devices in the four inspection areas A, B, C and D is completed in turn.

[0080] Example 3

[0081] Figure 3 This is a flowchart illustrating a power distribution automation detection method according to Embodiment 3 of the present invention. This embodiment is a refinement of the above embodiment. Specifically, after the step of (marking abnormal data when the detection data exceeds the corresponding preset working threshold range) in Embodiment 1, the following steps may be added: S341, determining that the detection device corresponding to the abnormal data is an abnormal device; S342, obtaining the working log of the abnormal device; S343, determining whether the abnormal device is in a working state based on the working log; S344, issuing an abnormal data alarm when the abnormal device is in a working state, and canceling the abnormal data alarm when the abnormal device is in a standby state.

[0082] like Figure 3 As shown, the power distribution automation detection method provided in this embodiment includes the following steps:

[0083] S310. Divide the power distribution network into regions to obtain multiple regions to be inspected.

[0084] A region to be inspected includes multiple detection devices.

[0085] S320. Obtain the detection data of the detection devices in multiple areas to be inspected, and generate detection tables corresponding to the multiple areas to be inspected respectively.

[0086] The test table includes test data from multiple testing devices in the same test area, as well as the preset operating threshold range for each testing device.

[0087] S330. Compare the detection data of each detection device in the same detection table with the preset working threshold range; mark abnormal data when the detection data exceeds the corresponding preset working threshold range.

[0088] The specific implementation methods of S310-S330 described above can be found in the above embodiments, and will not be repeated here.

[0089] S341. Determine that the detection device corresponding to the abnormal data is an abnormal device.

[0090] The detection device that produces abnormal data can be identified based on the coordinate markings, and the detection device can be marked as an abnormal device.

[0091] S342. Obtain the working log of the malfunctioning device.

[0092] S343. Determine whether the abnormal device is in working condition based on the work log.

[0093] S344. Issue an abnormal data alarm when the abnormal device is in working state, and cancel the abnormal data alarm when the abnormal device is in standby state.

[0094] To reduce the false alarm rate of abnormal data alarms and ensure their accuracy, this embodiment proposes that after identifying an abnormal device, its operational log can be obtained, and the device's operational status can be analyzed based on the log. It is understood that abnormal data can only occur when the device is operational. An abnormal data alarm is triggered when the abnormal device is determined to be operational; conversely, the alarm is canceled when the device is determined to be not operational (i.e., in standby mode).

[0095] In the third embodiment of the present invention, by obtaining the working log of the detection device with abnormality, and judging whether the abnormal device is in working state based on the working log, and judging whether to improve the abnormal data alarm based on the working state, the accuracy of abnormal data alarm can be further improved.

[0096] Example 4

[0097] Embodiment 4 of the present invention provides a power distribution automation detection system. Figure 4 This is a schematic diagram of a power distribution automation detection system provided in Embodiment 4 of the present invention. This system can execute the power distribution automation detection method provided in any embodiment of the present invention and possesses all the technical features and corresponding beneficial effects of the power distribution automation detection method provided in any embodiment of the present invention. For example... Figure 4 As shown, the power distribution automation detection system includes:

[0098] The area division module 100 is used to divide the power distribution network into multiple areas to be inspected; each area to be inspected includes multiple detection devices.

[0099] The data acquisition module 200 is used to acquire the detection data of the detection devices in multiple areas to be inspected, and generate detection tables corresponding to the multiple areas to be inspected respectively; the detection table includes the detection data of multiple detection devices in the same area to be inspected;

[0100] The anomaly analysis module 300 is used to determine whether there is abnormal data based on the detection table.

[0101] The power distribution automation detection system provided in Embodiment 4 of this invention can manage a large number of detection devices in the power distribution network by dividing the network into regions. The detection data of multiple detection devices in the same inspection area are integrated into a single detection table. The table is filled to achieve automated comparison of the detection data, improving the integration of detection data within the same inspection area. This avoids the problems of cumbersome data processing and slow data processing speed caused by one-to-one data analysis in existing technologies, achieving efficient and automated processing of daily inspection data.

[0102] Optionally, in possible embodiments, the power distribution automation detection system may further include a test area selection unit, used to select a test area as the current test area, and at least one other test area as a shared test area, and send the detection data corresponding to the current test area to the detection tables of the current test area and the shared test area respectively. The anomaly analysis module can specifically be used to determine whether abnormal data exists by combining the detection tables of the current test area and the shared test area.

[0103] Optionally, in a possible embodiment, the detection table further includes a preset working threshold range corresponding to the detection device, where the preset working threshold range is the operating data corresponding to the safe operation of the detection device. The anomaly analysis module may include a data comparison unit and a verification comparison unit. The data comparison unit is used to compare the detection data in the detection table of the current area to be inspected with the preset working threshold range to obtain a first comparison result; and to compare the detection data in the detection table of one of the shared areas to be inspected with the preset working threshold range to obtain a second comparison result. The verification comparison unit is used to compare the first comparison result and the second comparison result, and if the first comparison result and the second comparison result are consistent, it determines that the first comparison result of the current area to be inspected is correct, and determines whether there is abnormal data based on the first comparison result.

[0104] Optionally, in a possible embodiment, the data comparison unit is further configured to compare the detection data in the detection table of another collaborative inspection area with a preset working threshold range when the first comparison result and the second comparison result are inconsistent, to obtain a third comparison result. The verification comparison unit is further configured to compare the first comparison result and the third comparison result, and when the first comparison result and the third comparison result are consistent, determine that the first comparison result of the current inspection area is correct, the second comparison result of the initial collaborative inspection area is abnormal, and determine whether there is abnormal data based on the first comparison result; the verification comparison unit is further configured to determine that the first comparison result of the current inspection area is abnormal, the second comparison result of the initial collaborative inspection area is correct, and determine whether there is abnormal data based on the second comparison result when the first comparison result and the third comparison result are inconsistent and the second comparison result and the third comparison result are consistent.

[0105] Optionally, in possible embodiments, the verification and comparison unit is further configured to issue an alarm when the first comparison result, the second comparison result, and the third comparison result are all inconsistent.

[0106] Optionally, in possible embodiments, the power distribution automation detection system may further include a detection set division unit, used to form a detection set by combining multiple adjacent areas to be inspected; the area to be inspected selection unit is specifically used to select one area to be inspected in the detection set as the current area to be inspected, and at least one other area to be inspected as a shared area to be inspected.

[0107] Optionally, in possible embodiments, the anomaly analysis module may include a data comparison unit for comparing the detection data of each detection device in the same detection table with a preset working threshold range; and marking abnormal data when the detection data exceeds the corresponding preset working threshold range.

[0108] Optionally, in possible embodiments, the power distribution automation detection system may further include a spatiotemporal marking unit and a device positioning unit. The spatiotemporal marking unit is used to mark the coordinates and detection time of all detection devices in the same inspection area. Specifically, the data acquisition module can be used to acquire the detection data of the detection devices with coordinate and detection time marks, and generate multiple inspection tables corresponding to different inspection areas; the inspection tables include the coordinate marks, detection time marks, detection data, and preset working threshold ranges of multiple detection devices in the same inspection area. The device positioning unit is used to determine the coordinate marks of detection devices with abnormal data marks, in order to locate the abnormal devices.

[0109] Optionally, in possible embodiments, the device location unit is further configured to determine that the detection device corresponding to the abnormal data is an abnormal device. The power distribution automation detection system may also include a log analysis unit and an alarm unit. The log analysis unit is configured to acquire the working log of the abnormal device and determine whether the abnormal device is in a working state based on the working log; the alarm unit is configured to issue an abnormal data alarm when the abnormal device is in a working state and cancel the abnormal data alarm when the abnormal device is in a standby state.

[0110] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A power distribution automation detection method, characterized in that, include: The power distribution network is divided into regions, resulting in multiple regions to be inspected; One of the areas to be inspected includes multiple detection devices; The detection data of the detection devices in multiple areas to be inspected are acquired, and multiple detection tables corresponding to the multiple areas to be inspected are generated respectively; the detection table includes the detection data of multiple detection devices in the same area to be inspected; Select one of the areas to be inspected as the current area to be inspected, and at least one other area to be inspected as a shared area to be inspected; The detection data corresponding to the current area to be inspected is sent to the detection tables of the current area to be inspected and the shared area to be inspected, respectively. By combining the detection table of the current area to be inspected and the detection table of the shared area to be inspected, it can be determined whether there is abnormal data; The detection table also includes a preset working threshold range corresponding to the detection device, and the preset working threshold range is the operating data corresponding to the safe operation of the detection device; Determining whether abnormal data exists by combining the detection table of the current area to be inspected and the detection table of the shared area to be inspected includes: The detection data in the detection table of the current area to be inspected is compared with the preset working threshold range to obtain a first comparison result; The detection data in the detection table of one of the jointly inspected areas is compared with the preset working threshold range to obtain a second comparison result; When the first comparison result and the second comparison result are consistent, the first comparison result of the current area to be inspected is determined to be correct, and the presence of abnormal data is determined based on the first comparison result.

2. The power distribution automation detection method according to claim 1, characterized in that, Determining whether abnormal data exists by combining the detection table of the current area to be inspected and the detection table of the shared area to be inspected also includes: When the first comparison result and the second comparison result are inconsistent, the detection data in the detection table of the other jointly inspected areas are compared with the preset working threshold range to obtain a third comparison result; When the first comparison result and the third comparison result are consistent, the first comparison result of the current area to be inspected is determined to be correct, the second comparison result of the initial area to be inspected is abnormal, and the presence of abnormal data is determined based on the first comparison result. When the first comparison result and the third comparison result are inconsistent, and the second comparison result and the third comparison result are consistent, the first comparison result of the current area to be inspected is determined to be abnormal, the second comparison result of the jointly inspected area is initially correct, and abnormal data is determined based on the second comparison result.

3. The power distribution automation detection method according to claim 2, characterized in that, Determining whether abnormal data exists by combining the detection table of the current area to be inspected and the detection table of the shared area to be inspected also includes: An alarm will be issued if the first comparison result, the second comparison result, and the third comparison result are all inconsistent.

4. The power distribution automation detection method according to claim 1, characterized in that, Before selecting one of the areas to be inspected as the current area to be inspected, and at least one other area to be inspected as a co-inspection area, the method further includes: The adjacent regions to be inspected are combined into a detection set; Select one of the areas to be inspected as the current area to be inspected, and at least one other area to be inspected as a shared area to be inspected, including: One of the regions to be inspected in the detection set is selected as the current region to be inspected, and at least one other region to be inspected is selected as the co-inspection region.

5. The power distribution automation detection method according to claim 1, characterized in that, The detection table also includes a preset working threshold range corresponding to the detection device, and the preset working threshold range is the operating data corresponding to the safe operation of the detection device; Determining whether there is abnormal data based on the detection table includes: The detection data of each detection device in the same detection table are compared with the preset working threshold range; When the detected data exceeds the corresponding preset working threshold range, abnormal data is marked.

6. The power distribution automation detection method according to claim 5, characterized in that, Before acquiring the detection data of the detection devices in multiple areas to be inspected and generating detection tables corresponding to each of the multiple areas to be inspected, the method further includes: All detection devices in the same area to be inspected are marked with coordinates and detection time. Acquire detection data from the detection devices in multiple areas to be inspected, and generate multiple detection tables corresponding to each of the areas to be inspected, including: The detection data of the detection device with the coordinate mark and the detection time mark is obtained, and multiple detection tables corresponding to the areas to be inspected are generated respectively; the detection table includes the coordinate mark, the detection time mark, the detection data and the preset working threshold range of multiple detection devices in the same area to be inspected; After marking abnormal data when the detected data exceeds the corresponding preset working threshold range, the method further includes: The coordinate markers of the detection device with the abnormal data markers are determined in order to locate the abnormal device.

7. The power distribution automation detection method according to claim 5, characterized in that, After marking abnormal data when the detected data exceeds the corresponding preset working threshold range, the method further includes: The detection device corresponding to the abnormal data is determined to be an abnormal device; Obtain the operating log of the malfunctioning device; Determine whether the malfunctioning device is in a working state based on the work log; An abnormal data alarm is triggered when the abnormal device is in operation, and the abnormal data alarm is canceled when the abnormal device is in standby mode.

8. A power distribution automation detection system, characterized in that, The distribution automation detection system is applicable to the distribution automation detection method according to any one of claims 1-7, and the distribution automation detection system comprises: The area division module is used to divide the power distribution network into multiple areas to be inspected; each area to be inspected includes multiple detection devices. The data acquisition module is used to acquire the detection data of the detection devices in multiple areas to be inspected, and generate multiple detection tables corresponding to the multiple areas to be inspected respectively; the detection table includes the detection data of multiple detection devices in the same area to be inspected; The power distribution automation detection system further includes a test area selection unit, used to select a test area as the current test area, and at least one other test area as a shared test area, and send the detection data corresponding to the current test area to the test tables of the current test area and the shared test area respectively; the test table also includes a preset working threshold range corresponding to the detection device, and the preset working threshold range is the operating data corresponding to the safe operation of the detection device; An anomaly analysis module is used to determine whether abnormal data exists based on the detection table. The anomaly analysis module includes a data comparison unit and a verification comparison unit. The data comparison unit is used to compare the detection data in the detection table of the current area to be inspected with the preset working threshold range to obtain a first comparison result; and to compare the detection data in the detection table of one of the shared areas to be inspected with the preset working threshold range to obtain a second comparison result. The verification comparison unit is used to compare the first comparison result and the second comparison result, and if the first comparison result and the second comparison result are consistent, it is determined that the first comparison result of the current area to be inspected is correct, and the presence of abnormal data is determined based on the first comparison result.

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