Measurement data access processing method and system based on one graph of power grid
By analyzing the false alarm data of the measurement data in the target area of the power grid diagram and the probability of the occurrence of grid fault types, determining the focus on the measurement data of the power grid measurement data and formulating differentiated verification and processing strategies, the problem of neglecting the analysis results of the measurement data in the existing technology is solved, and the accuracy of grid fault diagnosis and efficient processing of measurement data is achieved.
Patent Information
- Application Number
- CN202510069379.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-16
- Publication Date
- 2025-05-06
AI Technical Summary
In the process of power grid measurement data access processing, the prior art ignores the generation of differentiated measurement data verification and processing strategies based on the measurement data analysis results of the Internet of Things measurement terminal.
By obtaining false alarm data of measurement data in the target area of the power grid diagram, we determine the scenarios where real-time verification strategies are not required, and based on the installation method and location of the measurement equipment, we determine the measurement data to focus on. Combining the probability of occurrence of power grid fault types and the data of measurement data changes, determine the verification and processing strategy for focusing on measurement data.
It realizes the screening of measurement data with high correlation under different grid fault types, ensures the accuracy of grid fault diagnosis and processing, and improves the accuracy of measurement data through differentiated verification processing.
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Figure CN119944644A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of power systems, and in particular, relates to a method and system for accessing and processing measurement data based on a power grid graph. Background Art
[0002] In order to ensure the status monitoring of the distribution equipment in the power grid diagram, it is often necessary to connect the measurement data of the distribution equipment to the power grid diagram. Specifically, in the invention patent application CN118626573A "A method and system for intelligent monitoring of power grid measurement data quality", real-time power grid measurement data is obtained through data streams, real-time features are extracted based on knowledge graphs, and real-time data is predicted and monitored using data quality monitoring models, and abnormal data is corrected, thereby achieving efficient monitoring and processing of power grid measurement data. However, the above technical solutions all have the following technical problems: In the process of accessing and processing the power grid measurement data, the existing technical solutions ignore the generation of differentiated measurement data verification and processing strategies based on the analysis results of the measurement data of the Internet of Things measurement terminal. In response to the above technical problems, the present application specifically provides a measurement data access processing method and system based on a power grid map. Summary of the invention
[0003] 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 method for accessing and processing measurement data based on a power grid map, specifically comprising: S1 obtains false alarm data of the measurement data of the target area of the power grid diagram, and uses the false alarm data to determine that when it is not necessary to adopt a real-time verification strategy for access verification processing, the measurement data of the measurement equipment in the target area under different power grid fault types is used to determine the measurement data of interest in the measurement data; S2: Determine similar measuring devices to the measuring device based on the installation mode and installation position of the measuring device, and determine that the deviation probability of the concerned measuring data of the measuring device meets the requirements according to the historical deviation of the concerned measuring data of the similar measuring devices, and then proceed to the next step; S3 determines the historical occurrence data of different types of power grid faults in different power grid load ranges, and determines the occurrence probability of different types of power grid faults in combination with the load forecast data of the installation location in a preset time period in the future; S4 determines the verification and processing strategy of the concerned measured data when it is connected to the power grid diagram through the occurrence probability of different power grid fault types and the change data of the measured data under different power grid fault types.
[0004] The beneficial effects of the present invention are: Based on the change data of the measurement data of the measurement equipment in the target area under different power grid fault types, the focus measurement data in the measurement data is determined, thereby realizing the change situation under different power grid fault types, determining the correlation between the measurement data and different power grid fault types, and then realizing the screening of the focus measurement data with a high degree of correlation with the power grid fault type, which also lays the foundation for ensuring the accuracy of the diagnosis and processing of the power grid fault type.
[0005] Through the occurrence probabilities of different power grid fault types and the change data of measurement data under different power grid fault types, the verification and processing strategy of the measurement data of concern when accessing the power grid diagram is determined. Not only the correlation between the measurement data of concern and different power grid fault types is taken into account, but also the differences in the occurrence probabilities of different power grid fault types in different areas are taken into account. Differentiated verification and processing of different measurement data of concern is achieved from multiple angles, ensuring the accuracy of the measurement data of concern.
[0006] A further technical solution is that the measurement data includes voltage, current, power factor, frequency, and protection device data.
[0007] A further technical solution is that the false alarm data includes the number of false alarm measuring devices and the number of false alarms on different dates.
[0008] A further technical solution is to determine that it is not necessary to use a real-time verification strategy for access verification processing, specifically including: Using the false alarm data, determining a date on which the target area has false alarm data, and using the date as the false alarm date; According to the number of measuring devices with false alarms on different false alarm dates, a date on which the number of measuring devices with false alarms is greater than a preset number of devices is determined, and the date is used as an abnormal alarm date; Based on the percentage of abnormal alarm dates, determine whether it is necessary to use a real-time verification strategy to perform access verification processing.
[0009] A further technical solution is that when the proportion of the number of abnormal alarm dates is greater than a preset proportion threshold, it is determined that a real-time verification strategy needs to be adopted to perform access verification processing.
[0010] A further technical solution is that when a real-time verification strategy is required to be used for access verification processing, all measurement data need to be verified in real time when entering the power grid diagram.
[0011] A further technical solution is that the method for determining the verification processing strategy of the concerned measurement data when accessing the power grid diagram is: Determine the fault weight coefficients of different power grid fault types based on the occurrence probabilities of different power grid fault types; Determine the change rate of different historical fault times according to the change data of the measured data under different power grid fault types, and determine the fault correlation coefficient between the measured data and different power grid fault types based on the average value of the change rate of different historical fault times; Based on the fault weight coefficient and the fault correlation coefficient, the weight sum of the fault correlation coefficient is determined, and the weight sum of the fault correlation coefficient is used to determine the verification processing strategy of the concerned measurement data when it is connected to the power grid diagram.
[0012] A further technical solution is to use the weight of the fault correlation coefficient and determine the verification and processing strategy of the concerned measurement data when it is connected to the power grid diagram, specifically including: When the weight sum of the fault correlation coefficients of the measurement data is greater than a preset weight coefficient threshold, a real-time verification strategy is used to verify the measurement data of interest when it is connected to the power grid diagram; When the weight sum of the fault correlation coefficients of the measurement data is not greater than a preset weight coefficient threshold, a preset frequency is used to perform verification processing on the measurement data of interest when it is connected to the power grid diagram.
[0013] In a second aspect, the present application provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, the above-mentioned measurement data access processing method based on a single map of the power grid is executed.
[0014] Other features and advantages will be described in the following description, and partly 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.
[0015] 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
[0016] 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 attached drawings.
[0017] Figure 1 It is a flow chart of a method for accessing and processing measurement data based on a diagram of a power grid; Figure 2 It is a flow chart for determining that there is no need to adopt a real-time verification strategy for access verification processing; Figure 3 is a flow chart of a method for determining measurement data of interest among measurement data; Figure 4 is a flow chart of a method for determining the probability of occurrence of a power grid fault type; Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION
[0018] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present invention will be comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar structures, and thus their detailed description will be omitted.
[0019] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "comprising" 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.
[0020] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, according to one aspect of the present invention, a first aspect is provided. The present application provides a measurement data access processing method based on a power grid map, specifically comprising: S1 obtains false alarm data of the measurement data of the target area of the power grid diagram, and uses the false alarm data to determine that when it is not necessary to adopt a real-time verification strategy for access verification processing, the measurement data of the measurement equipment in the target area under different power grid fault types is used to determine the measurement data of interest in the measurement data; Furthermore, the measurement data includes voltage, current, power factor, frequency, and protection device data.
[0021] Specifically, the false alarm data includes the number of false alarm measuring devices and the number of false alarms on different dates.
[0022] Specifically, Figure 2 As shown, it is determined that there is no need to use a real-time verification strategy for access verification processing, specifically including: Using the false alarm data, determining a date on which the target area has false alarm data, and using the date as the false alarm date; According to the number of measuring devices with false alarms on different false alarm dates, a date on which the number of measuring devices with false alarms is greater than a preset number of devices is determined, and the date is used as an abnormal alarm date; Based on the percentage of abnormal alarm dates, determine whether it is necessary to use a real-time verification strategy to perform access verification processing.
[0023] It should be noted that when the proportion of the number of abnormal alarm dates is greater than the preset proportion threshold, it is determined that a real-time verification strategy needs to be adopted to perform access verification processing.
[0024] It is understandable that when a real-time verification strategy is required to perform access verification processing, all measurement data need to be verified in real time when entering the power grid diagram.
[0025] Optionally, determining that it is not necessary to use a real-time verification strategy for access verification processing includes: Determine the number of measurement devices with false alarms in the target area using the false alarm data, and when the number of measurement devices with false alarms in the target area is within a preset device range, determine that it is not necessary to use a real-time verification strategy to perform access verification processing; When the number of measuring devices with false alarms in the target area is not within the preset device range: Determine the date on which the target area has false alarm data, and use it as the false alarm date. When the number of false alarm dates accounts for a percentage within a preset percentage range, it is determined that there is no need to use a real-time verification strategy for access verification processing; When the percentage of the error alarm dates is not within the preset percentage range: When the number of measurement devices with false alarms in the target area is greater than the preset number of false alarm devices, it is determined that a real-time verification strategy needs to be adopted for access verification processing; When the number of measurement devices with false alarms in the target area is not greater than the preset number of false alarm devices: According to the number of measuring devices with false alarms on different false alarm dates, the average value of the number of measuring devices with false alarms on different false alarm dates is determined. When the average value of the number of measuring devices with false alarms on different false alarm dates does not meet the requirement, it is determined that a real-time verification strategy needs to be adopted for access verification processing; When the average value of the number of measuring devices with false alarms on different false alarm dates meets the requirement: Determine the date when the number of measurement devices with false alarms is greater than the preset number of devices, and use it as the abnormal alarm date. When the number ratio of the abnormal alarm date does not meet the requirement, determine that a real-time verification strategy is required to perform access verification processing; When the number of abnormal alarm dates meets the requirements: Based on the percentage of false alarm dates and the number of measuring devices with false alarms on different false alarm dates, an alarm deviation coefficient is determined, and the alarm deviation coefficient is used to determine whether a real-time verification strategy is needed to perform access verification processing.
[0026] Furthermore, the grid fault types include harmonic anomalies, three-phase short circuits, single-phase short circuits, voltage anomalies, and ground faults.
[0027] It should be noted that if Figure 3 As shown, the method for determining the concerned measurement data in the measurement data is: Determine the variation rate interval of the measured data under different power grid fault types based on the variation data of the measured data under different power grid fault types; Determining an associated fault type of the measurement data based on a change rate interval under different power grid fault types; Whether the measurement data is concerned measurement data is determined according to the number of the associated fault types.
[0028] Furthermore, the associated fault type is a power grid fault type whose change rate interval overlaps with a preset change rate interval.
[0029] It can be understood that when the number of the associated fault types is greater than the preset number of fault types, the measurement data is determined to be the concerned measurement data.
[0030] In another possible embodiment, a method for determining the measurement data of interest in the measurement data is: S11 determines the change rate of different historical fault times of the measured data under different power grid fault types based on the change data of the measured data under different power grid fault types; S12, determining the fault correlation coefficient between the measured data and different types of power grid faults based on the average value of the change rate of different historical fault times; S13 determines a data correlation coefficient of the measurement data by using fault correlation coefficients of different power grid fault types, and determines whether the measurement data is concerned measurement data by using the data correlation coefficient.
[0031] Furthermore, the data correlation coefficient of the measured data is an average value of fault correlation coefficients with different power grid fault types.
[0032] Optionally, the above step S11 specifically includes: S111 determines the variation rate interval of the measured data under different power grid fault types based on the variation data of the measured data under different power grid fault types. When the variation rate intervals under different power grid fault types do not overlap with the preset variation rate intervals, it is determined that the measured data does not belong to the concerned measured data. When there is a power grid fault type whose variation rate interval overlaps with the preset variation rate interval, the process proceeds to step S112. S112: The power grid fault type whose change rate interval overlaps with the preset change rate interval is taken as the coincident power grid fault type. According to the change rates of different historical fault times under the coincident power grid fault type, when it is determined that there is a coincident power grid fault type whose change rates of different historical fault times are all greater than the preset change rate, it is determined that the measurement data belongs to the concerned measurement data. When there is no coincident power grid fault type whose change rates of different historical fault times are all greater than the preset change rate, the process proceeds to step S113. S113: When the change rates in different coincident power grid fault types are all greater than the preset change rates and the proportion of the number of historical faults is less than the preset number proportion, it is determined that the measurement data does not belong to the concerned measurement data; when there is a coincident power grid fault type whose change rate is greater than the preset change rate and the proportion of the number of historical faults is not less than the preset number proportion, the process proceeds to step S114; S114 uses the overlapping power grid fault types whose change rates are all greater than the preset change rates and whose proportion of historical fault times is not less than the preset proportion as the screening association types. When the number of the screening association types is greater than the preset number of association types, it is determined that the measurement data does not belong to the measurement data of interest. When the number of the screening association types is not greater than the preset number of association types, proceed to step S12.
[0033] Optionally, the above step S12 specifically includes: S121 determines the fault correlation coefficient between the measurement data and different power grid fault types based on the average value of the change rate of different historical fault times. When there is a power grid fault type with a fault correlation coefficient greater than a preset correlation coefficient, it is determined that the measurement data belongs to the concerned measurement data. When there is no power grid fault type with a fault correlation coefficient greater than the preset correlation coefficient, the process proceeds to step S122. S122: when there is a power grid fault type whose fault correlation coefficient is within the preset correlation coefficient interval, the process proceeds to step S123; when there is no power grid fault type whose fault correlation coefficient is within the preset correlation coefficient interval, it is determined that the measurement data does not belong to the concerned measurement data; S123 When the number of power grid fault types within the preset correlation coefficient interval is greater than the preset fault type number threshold, it is determined that the measurement data belongs to the focus measurement data; when the number of power grid fault types within the preset correlation coefficient interval is not greater than the preset fault type number threshold, proceed to step S13.
[0034] Specifically, when the alarm deviation coefficient is greater than the preset deviation coefficient, it is determined that a real-time verification strategy needs to be adopted to perform access verification processing.
[0035] S2: Determine similar measuring devices to the measuring device based on the installation mode and installation position of the measuring device, and determine that the deviation probability of the concerned measuring data of the measuring device meets the requirements according to the historical deviation of the concerned measuring data of the similar measuring devices, and then proceed to the next step; It should be noted that similar measuring devices of the measuring device are other measuring devices in the power grid diagram that are installed in the same manner as the measuring device and have similar power distribution data at the installation location.
[0036] Furthermore, the power distribution data are similar in that the deviations of the power distribution data on different dates are all within a preset data deviation range.
[0037] It can be understood that determining whether the deviation probability of the measurement data of interest of the measurement device meets the requirement specifically includes: Determine the number of historical deviations of the concerned measurement data of different similar measurement devices based on the historical deviations of the concerned measurement data of different similar measurement devices; According to the historical deviation times of the concerned measurement data of different similar measurement devices, determining similar measurement devices having the historical deviation times greater than the preset deviation times; Based on the proportion of similar measurement devices whose historical deviation times are greater than the preset deviation times among similar measurement devices, the deviation probability of the concerned measurement data of the measurement device is determined, and combined with the preset deviation probability threshold, it is determined whether the deviation probability of the concerned measurement data of the measurement device meets the requirements.
[0038] Specifically, when the deviation probability of the concerned measurement data of the measurement device is greater than a preset deviation probability threshold, it is determined that the deviation probability of the concerned measurement data of the measurement device does not meet the requirement.
[0039] It should also be noted that when the deviation probability of the concerned measurement data of the measurement device does not meet the requirement, it is determined to adopt a real-time verification strategy to perform verification processing on the concerned measurement data when it is connected to the power grid diagram.
[0040] S3 determines the historical occurrence data of different types of power grid faults in different power grid load ranges, and determines the occurrence probability of different types of power grid faults in combination with the load forecast data of the installation location in a preset time period in the future; Specifically, Figure 4 As shown, the method for determining the occurrence probability of the power grid fault type is: Determine the proportion of time within different power grid load ranges using the load forecast data of the installation location in a preset time period in the future, and determine the weight coefficients of different power grid load ranges using the proportion of time within different power grid load ranges; Based on the historical occurrence data of the power grid fault type in different power grid load ranges, determine the historical occurrence times in different power grid load ranges, and use the historical occurrence times in different power grid load ranges to determine the fault occurrence probability in different power grid load ranges; The probability of occurrence of the power grid fault type is determined according to the sum of the products of the fault occurrence probability and the weight coefficient in different power grid load ranges.
[0041] Furthermore, the probability of occurrence of the power grid fault type ranges from 0 to 1, wherein the greater the probability of occurrence of the power grid fault type, the greater the probability of occurrence of the power grid fault type within a preset time period in the future.
[0042] It can be understood that the load forecast data is determined based on the weather data of the installation location in the future forecast period, wherein the weather data is used as input and the output of the preset model is used as the load forecast data.
[0043] S4 determines the verification and processing strategy of the concerned measured data when it is connected to the power grid diagram through the occurrence probability of different power grid fault types and the change data of the measured data under different power grid fault types.
[0044] It should also be noted that the method for determining the verification processing strategy of the concerned measurement data when accessing the power grid diagram is as follows: Determine the fault weight coefficients of different power grid fault types based on the occurrence probabilities of different power grid fault types; Determine the change rate of different historical fault times according to the change data of the measured data under different power grid fault types, and determine the fault correlation coefficient between the measured data and different power grid fault types based on the average value of the change rate of different historical fault times; Based on the fault weight coefficient and the fault correlation coefficient, the weight sum of the fault correlation coefficient is determined, and the weight sum of the fault correlation coefficient is used to determine the verification processing strategy of the concerned measurement data when it is connected to the power grid diagram.
[0045] Furthermore, the weight of the fault correlation coefficient is used to determine the verification and processing strategy of the concerned measurement data when it is connected to the power grid diagram, specifically including: When the weight sum of the fault correlation coefficients of the measurement data is greater than a preset weight coefficient threshold, a real-time verification strategy is used to verify the measurement data of interest when it is connected to the power grid diagram; When the weight sum of the fault correlation coefficients of the measurement data is not greater than a preset weight coefficient threshold, a preset frequency is used to perform verification processing on the measurement data of interest when it is connected to the power grid diagram.
[0046] In another embodiment, the method for determining the verification processing strategy of the concerned measurement data when accessing the power grid diagram is: Determine the change rate of different historical fault times according to the change data of the concerned measurement data under different power grid fault types, and determine the fault correlation coefficient of the concerned measurement data and different power grid fault types based on the average value of the change rate of different historical fault times; Based on the occurrence probabilities of different power grid fault types, the power grid fault types with occurrence probabilities greater than a preset probability threshold are selected and regarded as the concerned fault types; When the fault correlation coefficients of the concerned measurement data in different concerned fault types are all greater than the correlation coefficient limit value, a real-time verification strategy is adopted to perform verification processing on the concerned measurement data when it is connected to the power grid diagram; When there is an associated fault type whose fault correlation coefficient is not greater than the correlation coefficient limit value: Based on the average value of the fault correlation coefficients of the concerned measurement data in different associated fault types, when it is determined that the average value of the fault correlation coefficients of the concerned measurement data in different associated fault types is greater than a preset fault correlation coefficient threshold, it is determined that a real-time verification strategy is used to perform verification processing on the concerned measurement data when it is connected to the power grid diagram; When the average value of the fault correlation coefficients of different associated fault types is not greater than the preset fault correlation coefficient threshold: Based on the probability of occurrence of different types of power grid faults, fault weight coefficients of different types of power grid faults are determined; based on the product of the fault weight coefficient and the fault correlation coefficient, correlation coefficient weight values of different types of power grid faults are determined; when the number of power grid fault types having correlation coefficient weight values greater than a preset correlation weight value is greater than a preset number of fault types, it is determined that a real-time verification strategy is adopted to perform verification processing on the concerned measurement data when it is connected to the power grid diagram; When the correlation coefficient weight value is greater than the preset correlation weight value and the number of power grid fault types is not greater than the preset number of fault types: Based on the fault weight coefficient and the fault correlation coefficient, the weight sum of the fault correlation coefficient is determined, and the weight sum of the fault correlation coefficient is used to determine the verification processing strategy of the concerned measurement data when it is connected to the power grid diagram.
[0047] Example 2 Second, as Figure 5 As shown, the present application provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, the above-mentioned measurement data access processing method based on a map of the power grid is executed.
[0048] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.
[0049] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0050] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.
Claims
1. A method for accessing and processing measurement data based on a power grid map, characterized in that: Specifically include: Acquire false alarm data of the measurement data of the target area of the power grid diagram, and when using the false alarm data to determine that it is not necessary to adopt a real-time verification strategy for access verification processing, determine the concerned measurement data in the measurement data based on the change data of the measurement data of the measurement equipment in the target area under different power grid fault types; Determine similar measuring devices to the measuring device based on the installation mode and installation position of the measuring device, and proceed to the next step when determining that the deviation probability of the concerned measurement data of the measuring device meets the requirement according to the historical deviation of the concerned measurement data of the similar measuring devices; Determine the historical occurrence data of different types of power grid faults in different power grid load ranges, and determine the probability of occurrence of different types of power grid faults in combination with the load forecast data of the installation location in the future preset time period; Based on the occurrence probabilities of different types of power grid faults and the variation data of the measured data under different types of power grid faults, the verification and processing strategy of the measured data of interest when it is connected to the power grid diagram is determined.
2. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: The measurement data includes voltage, current, power factor, frequency, and protection device data.
3. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: The false alarm data includes the number of measurement devices with false alarms and the number of false alarms on different dates.
4. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: Determine that there is no need to use a real-time verification strategy for access verification, including: Using the false alarm data, determining a date on which the target area has false alarm data, and using the date as the false alarm date; According to the number of measuring devices with false alarms on different false alarm dates, determine the date on which the number of measuring devices with false alarms is greater than a preset number of devices, and use it as the abnormal alarm date; Based on the percentage of abnormal alarm dates, determine whether it is necessary to use a real-time verification strategy to perform access verification processing.
5. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: When a real-time verification strategy is required for access verification processing, all measurement data need to be verified in real time when entering the power grid diagram.
6. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: The grid fault types include abnormal harmonics, three-phase short circuit, single-phase short circuit, abnormal voltage, and ground fault.
7. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: The method for determining the concerned measurement data in the measurement data is: Determine the variation rate interval of the measured data under different power grid fault types based on the variation data of the measured data under different power grid fault types; Determining an associated fault type of the measurement data based on a change rate interval under different power grid fault types; Whether the measurement data is concerned measurement data is determined according to the number of the associated fault types.
8. The method for accessing and processing measurement data based on a power grid map according to claim 7, characterized in that: The associated fault type is a power grid fault type whose change rate interval overlaps with a preset change rate interval.
9. The method for accessing and processing measurement data based on a power grid map according to claim 1, characterized in that: The method for determining the verification processing strategy of the concerned measurement data when accessing the power grid diagram is as follows: Determine the fault weight coefficients of different power grid fault types based on the occurrence probabilities of different power grid fault types; Determine the change rate of different historical fault times according to the change data of the measured data under different power grid fault types, and determine the fault correlation coefficient between the measured data and different power grid fault types based on the average value of the change rate of different historical fault times; Based on the fault weight coefficient and the fault correlation coefficient, the weight sum of the fault correlation coefficient is determined, and the weight sum of the fault correlation coefficient is used to determine the verification processing strategy of the concerned measurement data when it is connected to the power grid diagram.
10. A computer system comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a measurement data access processing method based on a map of a power grid as described in any one of claims 1-9 when running the computer program.