Abnormality analysis method and system for power grid measurement data

Abstract

The invention discloses an anomaly analysis method and system for power grid measurement data, and relates to the technical field of power systems, and the method comprises the steps: collecting power grid measurement related data through a data collection module, carrying out the comprehensive power grid index calculation based on the power grid measurement related data through a data processing module, and obtaining a comprehensive power grid index coefficient; then analyzing the comprehensive power grid index coefficient through a data analysis module to judge whether the power grid state is abnormal or not, if the power grid is abnormal, obtaining a power grid element state index evolution track through an abnormality judgment module, and obtaining a power grid element state index evolution frequency; and then the abnormal degree of the power grid is determined through comparison of a set threshold value and is fed back to the execution module, and the execution module is used for prompting and displaying the state of the power grid, so that the functions of automatically judging whether the state of the power grid is abnormal or not and evaluating the abnormal degree of the power grid are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system, in particular to a power grid metering data abnormality analysis method and system. BACKGROUND

[0002] In the power industry, the operation stability and reliability of the power grid system are crucial for ensuring the continuity and quality of power supply, and the abnormality analysis of power metering data is one of the key tasks to ensure the normal operation of the power grid system. In the power grid system, power metering data is affected by various factors, such as power load fluctuation, equipment failure, power theft, abnormal weather, etc. The traditional power metering data abnormality analysis method mainly relies on manual observation and offline analysis, and the analysis efficiency and accuracy are not guaranteed. SUMMARY

[0003] To solve the problems mentioned in the background, the purpose of the present application is to provide a power grid metering data abnormality analysis method and system, which can automatically determine whether the power grid state is abnormal and evaluate the degree of power grid abnormality.

[0004] In the first aspect, the purpose of the present application can be achieved by the following technical solution: a power grid metering data abnormality analysis system, comprising:

[0005] A data acquisition module for acquiring power grid metering related data and sending the power grid metering related data to a data processing module, wherein the power grid metering related data includes power grid load data, power grid power data and power metering data;

[0006] A data processing module for marking power grid metering data and calculating comprehensive power grid index coefficients based on the marked power grid metering related data, and sending the comprehensive power grid index coefficients to a data analysis module;

[0007] A data analysis module for inputting the comprehensive power grid index coefficients into a pre-established standard power grid index determination model to obtain power grid index determination results, setting a standard power grid index threshold, calculating the ratio of the power grid index determination results to the standard power grid index threshold to obtain a ratio result, setting a ratio threshold, comparing the ratio result with the ratio threshold, and determining whether the power grid metering data meets the standard according to the comparison result. If it meets the standard, an abnormality-free signal is sent to an execution module, and if it does not meet the standard, an abnormality determination signal is sent to an abnormality determination module;

[0008] Anomaly determination module: used to obtain power grid element operating state related data, perform element state comprehensive evaluation calculation based on the power grid element operating state related data, obtain a comprehensive element state evaluation coefficient, obtain a comprehensive power grid index coefficient of the data processing module, draw a power grid element state index evolution trajectory based on the comprehensive power grid index coefficient and the comprehensive element state evaluation coefficient, determine a tangent that is tangent to the power grid element state index evolution trajectory based on the power grid element state index evolution trajectory, and take the slope of the tangent as a power grid element state index evolution frequency, set a power grid element state index evolution frequency threshold, compare the obtained power grid element state index evolution frequency with the power grid element state index evolution frequency threshold, determine a power grid anomaly degree according to a comparison result, and send a power grid anomaly degree signal to the execution module;

[0009] Execution module: used to remind a worker of a power grid anomaly-free condition after receiving a no anomaly signal sent by the data analysis module, and remind the worker to perform maintenance based on the power grid anomaly degree based on the power grid anomaly degree signal sent by the anomaly determination module.

[0010] In combination with the first aspect, in some implementations of the first aspect, the system further includes a data marking process of the data processing module:

[0011] The power grid load data is marked as Fi, the power grid power data is marked as Gi, and the electric meter measurement data is marked as Li, where i is a collection number label of the data collection module, and i = 1, 2, 3,..., n, and n is a total number of collection times of the data collection module.

[0012] In combination with the first aspect, in some implementations of the first aspect, the system further includes a calculation process of the comprehensive power grid index coefficient of the data processing module as follows:

[0013] The comprehensive power grid index coefficient Zi is calculated by using the formula , where k1 is a power grid load influence coefficient, k2 is a power grid power influence coefficient, k3 is an electric meter measurement influence coefficient, G0 is a preset standard power grid load coefficient, F0 is a preset standard power grid power coefficient, L0 is a preset standard electric meter measurement coefficient, and q is a number of electric meters.

[0014] In combination with the first aspect, in some implementations of the first aspect, the system further includes a calculation process of the electric meter measurement data as follows:

[0015] The electric meter electric energy is marked as B1, the electric meter voltage is marked as B2, the electric meter current is marked as B3, the electric meter power factor is marked as B4, and the electric meter frequency is marked as B5.

[0016] The electric meter measurement data is obtained by performing electric meter measurement calculation according to the marked data, and the calculation formula is as follows:

[0017]

[0018] wherein, a and β are preset proportion coefficients.

[0019] In some implementations of the first aspect, the system further comprises that the pre-established standard power grid index determination model of the data analysis module is established based on an artificial intelligence model, and a process of the standard power grid index determination model established based on the artificial intelligence model is as follows:

[0020] The preset standard power grid measurement data is obtained, wherein the preset standard power grid measurement data includes preset standard load data, preset standard power data, and preset standard power meter measurement data.

[0021] The artificial intelligence model is trained based on the preset standard power grid measurement data, and a standard power grid index determination model is output.

[0022] In some implementations of the first aspect, the system further comprises that the data analysis module comprises:

[0023] When the ratio result is less than or equal to the ratio threshold value, an abnormality-free signal is sent to the execution module.

[0024] When the ratio result is greater than the ratio threshold value, an abnormality determination signal is sent to the abnormality determination module for abnormality determination.

[0025] In some implementations of the first aspect, the system further comprises that a calculation process of the abnormality determination module to calculate the comprehensive element state evaluation coefficient comprises the following steps:

[0026] The element related parameter is marked as Yj, the measurement data is marked as Cj, and the element operation topology relationship parameter is marked as Tj, wherein j is a collection number label of the collected power grid element operation state related data, and j = 1, 2, 3, …, m, and m is a total number of the collected power grid element operation state related data.

[0027] A formula for calculating the comprehensive element state evaluation coefficient is as follows:

[0028]

[0029] wherein, Xj is the comprehensive element state evaluation coefficient, P1 and P2 are element operation related coefficients, and W is an operation topology related coefficient.

[0030] In combination with the first aspect, in some implementations of the first aspect, the system further comprises: the abnormality determination module determines a tangent line tangent to the evolution trajectory of the grid element state index, and obtains a slope of the tangent line tangent to the evolution trajectory of the grid element state index as the evolution frequency H of the grid element state index;

[0031] An evolution frequency threshold H0 of the grid element state index is set, the obtained evolution frequency H of the grid element state index is compared with the evolution frequency threshold H0 of the grid element state index, and the degree of grid abnormality is determined according to the comparison result:

[0032] When 0≤H<H0, the degree of grid abnormality is a low-level abnormality degree, and a low-level abnormality signal is sent to the execution module;

[0033] When H0≤H<2H0, the degree of grid abnormality is a medium-level abnormality degree, and a medium-level abnormality signal is sent to the execution module;

[0034] When H≥2H0, the degree of grid abnormality is a high-level abnormality degree, and a high-level abnormality signal is sent to the execution module.

[0035] In combination with the first aspect, in some implementations of the first aspect, the system further comprises: after receiving the low-level abnormality signal, the execution module reminds the staff to overhaul the grid equipment elements, after receiving the medium-level abnormality signal, the execution module reminds the staff to partially overhaul and replace the grid equipment elements, and after receiving the high-level abnormality signal, the execution module reminds the staff to directly replace the abnormal grid equipment elements.

[0036] Secondly, in order to achieve the above-mentioned purpose, the application discloses an abnormality analysis method of grid measurement data, which comprises the following steps:

[0037] Grid measurement related data is obtained, and data marking is performed, comprehensive grid index coefficients are obtained by using the marked grid measurement related data for comprehensive grid index calculation, wherein the grid measurement related data comprises grid load data, grid power data and electric meter measurement data;

[0038] The comprehensive grid index coefficients are input into a pre-established standard grid index determination model, and grid index determination results are output, a standard grid index threshold is set, the grid index determination results are compared with the standard grid index threshold, and a ratio result is obtained by ratio calculation;

[0039] A ratio threshold is set, the ratio result is compared with the ratio threshold, and whether the grid measurement data meets the standard is determined according to the comparison result, if the grid measurement data meets the standard, the grid is normal, if the grid measurement data does not meet the standard, grid element operation state related data is obtained, including element related parameters, measurement data and element operation topology relationship parameters;

[0040] Based on the grid element operation state related data, element state comprehensive evaluation calculation is carried out to obtain a comprehensive element state evaluation coefficient, and based on the comprehensive grid index coefficient and the comprehensive element state evaluation coefficient, a grid element state index evolution trajectory is drawn;

[0041] Based on the grid element state index evolution trajectory, a tangent line tangent to the grid element state index evolution trajectory is determined, and the slope of the tangent line is taken as the grid element state index evolution frequency, a grid element state index evolution frequency threshold is set, the obtained grid element state index evolution frequency is compared with the grid element state index evolution frequency threshold, and the grid abnormality degree is determined according to the comparison result.

[0042] The beneficial effects of the present application are:

[0043] The present application collects grid metering related data through the data acquisition module, then carries out comprehensive grid index calculation based on the grid metering related data through the data processing module to obtain a comprehensive grid index coefficient, then analyzes the comprehensive grid index coefficient through the data analysis module to determine whether the grid state is abnormal, if the grid is abnormal, the grid element state index evolution trajectory is obtained through the abnormality determination module, and the grid element state index evolution frequency is obtained, then the threshold is set for comparison to determine the grid abnormality degree, and feedback to the execution module, the grid state is prompted and displayed through the execution module, which realizes the function of automatically judging whether the grid state is abnormal and evaluating the grid abnormality degree. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows, and obviously, other drawings can be obtained by those skilled in the art without creative labor on the premise of not paying creative labor;

[0045] Figure 1 is a system structure schematic diagram of the present application;

[0046] Figure 2 is a method flowchart of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0048] Embodiment one:

[0049] Next, the related terms involved in the embodiments of the application are introduced:

[0050] Power grid: the whole of power system composed of substations and transmission and distribution lines of various voltages, called power grid. It contains three units of power transformation, power transmission and power distribution. The task of the power grid is to transport and distribute electric energy and change voltage.

[0051] Power system: a unified whole composed of power generation, power supply (power transmission, power transformation, power distribution), power utilization facilities, and the necessary regulating control and relay protection and safety automation devices, metering devices, dispatching automation, power communication and other secondary facilities to ensure normal operation.

[0052] The power system is a power production and consumption system composed of power plants, transmission and transformation lines, power supply and distribution stations, and power utilization. Its function is to convert primary energy in nature into electric energy through power generation power plants, and then supply electric energy to users through power transmission, power transformation and power distribution. In order to realize this function, the power system has corresponding information and control systems at each link and different levels to measure, regulate, control, protect, communicate and dispatch the production process of electric energy to ensure that users obtain safe and high-quality electric energy. The main structure of the power system includes power sources (hydroelectric power stations, thermal power plants, nuclear power plants, etc.), substations (step-up substations, load center substations, etc.), transmission and distribution lines and load centers. Each power source is also connected to each other to realize the exchange and regulation of electric energy between different regions, thereby improving the safety and economy of power supply. The network formed by the transmission line and the substation is usually called the power network. The information and control system of the power system is composed of various detection equipment, communication equipment, safety protection devices, automatic control devices and monitoring automation and dispatching automation systems. The structure of the power system should ensure that on the basis of advanced technology and high economic efficiency, the production and consumption of electric energy are reasonably coordinated.

[0053] As shown in Figure 1 , an abnormal analysis system of power grid metering data, comprising:

[0054] a data acquisition module, a data processing module, a data analysis module, an abnormality determination module and an execution module;

[0055] The data acquisition module is used for acquiring power grid metering related data and sending the acquired power grid metering related data to the data processing module, wherein the power grid metering related data includes power grid load data, power grid power data and electric metering data.

[0056] Specifically, the following embodiments are used to further illustrate the application:

[0057] The power grid load data is the power consumption data of each power grid node in the power system, which is usually presented in the form of a load curve and can reflect the supply-demand situation and load balance of the power system at each time period;

[0058] The power grid power data is the power conversion rate data of each node in the power system, which is usually presented in the form of a power curve and can reflect the power output and transfer of the power system at each time period. In the power system, power data plays an important role in power quality assurance, power metering, energy efficiency evaluation, etc.

[0059] The metering data is obtained by calculating the meter power, voltage, current, power factor and frequency. These parameters can reflect the working state and power consumption of the meter.

[0060] Specifically, the calculation process of the metering data is as follows:

[0061] The meter power is marked as B1, the meter voltage is marked as B2, the meter current is marked as B3, the meter power factor is marked as B4, and the meter frequency is marked as B5.

[0062] According to the marked data, the metering data is calculated, and the calculation formula is as follows:

[0063]

[0064] In the formula, α and β are preset proportion coefficients.

[0065] The preset proportion coefficient is a coefficient of the value required for proportion conversion when calculating the metering data.

[0066] After receiving the power grid metering related data sent by the data acquisition module, the data processing module performs data processing. Specifically, the processing process of the data processing module includes the following steps:

[0067] The power grid metering related data is marked to obtain the marked power grid metering related data. Specifically, the power grid load data is marked as Fi, the power grid power data is marked as Gi, and the metering data is marked as Li. In the formula, i is the collection number label of the data acquisition module, and i = 1, 2, 3,..., n, n is the total number of collection times of the data acquisition module.

[0068] The marked power grid metering related data is calculated to obtain the comprehensive power grid index coefficient. The calculation process of the comprehensive power grid index coefficient of the data processing module is as follows:

[0069] The formula is as follows: The comprehensive power grid index coefficient Zi is calculated, wherein k1 is a power grid load influence coefficient, k2 is a power grid power influence coefficient, k3 is a power meter measurement influence coefficient, G0 is a preset standard power grid load coefficient, F0 is a preset standard power grid power coefficient, L0 is a preset standard power meter measurement coefficient, and q is the number of power meters.

[0070] Further, in the specific implementation process, the preset standard power grid load coefficient, the preset standard power grid power coefficient, and the preset standard power meter measurement coefficient are obtained by daily collection of power grid load data, power grid power data, and power meter measurement data, and multiple simulation calculations and data averaging.

[0071] In this embodiment, the power grid load influence coefficient, the power grid power influence coefficient, and the power meter measurement influence coefficient are obtained by daily collection of power grid load data, power grid power data, and power meter measurement data, and comprehensive evaluation and calculation according to external factors, including human factors, machine detection, and environmental factors.

[0072] The data processing module sends the calculated comprehensive power grid index coefficient to the data analysis module.

[0073] After receiving the comprehensive power grid index coefficient sent by the data processing module, the data analysis module performs data analysis. Specifically, the analysis process of the data analysis module includes the following steps:

[0074] The comprehensive power grid index coefficient is input into the pre-established standard power grid index determination model in the data analysis module, and a power grid index determination result is output.

[0075] Specifically, the pre-established standard power grid index determination model is established based on an artificial intelligence model. The process of establishing the standard power grid index determination model based on the artificial intelligence model is as follows:

[0076] The preset standard power grid measurement data is obtained, wherein the preset standard power grid measurement data includes preset standard load data, preset standard power data, and preset standard power meter measurement data.

[0077] Based on the preset standard power grid measurement data, the artificial intelligence model is trained, and a standard power grid index determination model is output. The artificial intelligence model includes a deep convolutional neural network model and an RBF neural network model.

[0078] The standard grid index threshold is set, the grid index determination result is calculated by ratio with the standard grid index threshold, a ratio result is obtained, a ratio threshold is set, the ratio result is compared with the ratio threshold, and whether the grid measurement data meets the standard is determined according to the comparison result;

[0079] Specifically, when the ratio result is less than or equal to the ratio threshold, it indicates that the grid measurement data has met the standard, and the data analysis module sends a no-abnormal signal to the execution module;

[0080] When the ratio result is greater than the ratio threshold, it indicates that the grid measurement data has not met the standard, and the data analysis module sends an abnormal determination signal to the abnormal determination module for abnormal determination;

[0081] The abnormal determination module performs abnormal determination after receiving the abnormal determination signal sent by the data analysis module. Specifically, the determination process of the abnormal determination module includes the following steps:

[0082] The running state of the grid element corresponding to the non-standard grid measurement data is monitored to obtain grid element running state related data, wherein the grid element running state related data includes element related parameters, measurement data, and element running topology relationship parameters;

[0083] Based on the grid element running state related data, a comprehensive element state evaluation coefficient is calculated. Specifically, the calculation process of the abnormal determination module for calculating the comprehensive element state evaluation coefficient includes the following steps:

[0084] The element related parameters are marked as Yj, the measurement data are marked as Cj, and the element running topology relationship parameters are marked as Tj, wherein j is the collection number label of the collected grid element running state related data, and j = 1, 2, 3,..., m, and m is the total number of the collected grid element running state related data;

[0085] Based on the marked element related parameters, measurement data, and element running topology relationship parameters, a comprehensive element state evaluation coefficient is calculated, and the calculation formula is as follows:

[0086]

[0087] In the formula, Xj is the comprehensive element state evaluation coefficient, P1 and P2 are element running related coefficients, and W is a running topology related coefficient;

[0088] The comprehensive grid index coefficient Zi processed by the data processing module is obtained, a plane rectangular coordinate system is established, based on the comprehensive grid index coefficient Zi and the comprehensive element state evaluation coefficient Xj, the comprehensive grid index coefficient Zi is taken as the horizontal coordinate, the comprehensive element state evaluation coefficient Xj is taken as the vertical coordinate, and the grid element state index evolution trajectory is drawn.

[0089] Based on the evolution trajectory of the power grid element state index, a tangent is determined which is tangent to the evolution trajectory of the power grid element state index, and the slope of the tangent is obtained as the evolution frequency H of the power grid element state index;

[0090] The evolution frequency threshold H0 of the power grid element state index is set, the obtained evolution frequency H of the power grid element state index is compared with the evolution frequency threshold H0 of the power grid element state index, and the degree of abnormality of the power grid is determined according to the comparison result, specifically:

[0091] When 0≤H<H0, it is determined that the degree of abnormality of the power grid at this time is low, and the abnormality determination module sends a low abnormality signal to the execution module;

[0092] When H0≤H<2H0, it is determined that the degree of abnormality of the power grid at this time is medium, and the abnormality determination module sends a medium abnormality signal to the execution module;

[0093] When H≥2H0, it is determined that the degree of abnormality of the power grid at this time is high, and the abnormality determination module sends a high abnormality signal to the execution module;

[0094] It needs to be further explained that the evolution frequency threshold of the power grid element state index is obtained by averaging after removing the maximum and minimum values after obtaining the evolution frequency of the power grid element state index for multiple times;

[0095] The low abnormality degree represents that there are more than 0 but less than 30% of the elements in the power grid that have abnormal problems;

[0096] The medium abnormality degree represents that there are more than 30% but less than 60% of the elements in the power grid that have abnormal problems;

[0097] The high abnormality degree represents that there are more than 60% of the elements in the power grid that have abnormal problems;

[0098] The execution module reminds the staff that the power grid is normal after receiving the no abnormality signal, reminds the staff to overhaul the power grid equipment elements after receiving the low abnormality signal sent by the abnormality determination module, reminds the staff to partially overhaul and replace the power grid equipment elements after receiving the medium abnormality signal sent by the abnormality determination module, and reminds the staff to directly replace the abnormal power grid equipment elements after receiving the high abnormality signal sent by the abnormality determination module.

[0099] Embodiment two: an abnormality analysis method of power grid metering data, the method comprising the following steps:

[0100] The power grid measurement related data is acquired and marked, the comprehensive power grid index coefficient is calculated by using the marked power grid measurement related data, and the comprehensive power grid index coefficient is obtained, wherein the power grid measurement related data comprises power grid load data, power grid power data and power meter measurement data.

[0101] The comprehensive power grid index coefficient is input into a pre-established standard power grid index determination model, and a power grid index determination result is output, a standard power grid index threshold is set, the power grid index determination result is compared with the standard power grid index threshold, and a ratio result is obtained.

[0102] A ratio threshold is set, the ratio result is compared with the ratio threshold, and whether the power grid measurement data meets the standard is determined according to a comparison result; if the standard is met, the power grid is normal, and if the standard is not met, power grid element operation state related data is acquired, comprising element related parameters, measurement data and element operation topology relationship parameters.

[0103] The element state comprehensive evaluation calculation is performed based on the power grid element operation state related data, the comprehensive element state evaluation coefficient is obtained, and the power grid element state index evolution track is drawn based on the comprehensive power grid index coefficient and the comprehensive element state evaluation coefficient.

[0104] Based on the power grid element state index evolution track, a tangent line tangent to the power grid element state index evolution track is determined, and the slope of the tangent line is used as a power grid element state index evolution frequency; a power grid element state index evolution frequency threshold is set, the obtained power grid element state index evolution frequency is compared with the power grid element state index evolution frequency threshold, and the power grid abnormality degree is determined according to a comparison result.

[0105] Based on the same inventive concept, the application further provides a computer device, which comprises one or more processors and a memory for storing one or more computer programs; the program comprises program instructions, and the processor is used for executing the program instructions stored in the memory. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, and are used for implementing one or more instructions, and are specifically used for loading and executing one or more instructions in the computer storage medium to realize the above method.

[0106] It should be further noted that based on the same inventive concept, the present application also provides a computer storage medium, which stores a computer program, and the computer program is run by a processor to execute the above method. The storage medium can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (non-exhaustive list) of the computer readable storage medium include: electrical connections having one or more wires, portable computer disks, hard drives, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component.

[0107] The above formulas are calculated by removing the dimension and taking the numerical value, the formula is obtained by collecting a large amount of data to simulate the closest real situation, and the preset parameters and the preset threshold in the formula are set by the person skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0108] In the description of the present specification, the description referring to the terms "one embodiment", "an example", "a specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0109] The basic principles, main features and advantages of the present disclosure are shown and described above. It should be understood by those skilled in the art that the present disclosure is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, various changes and improvements can be made to the present disclosure, and these changes and improvements all fall within the scope of the claimed present disclosure.

Claims

1. A system for analyzing anomalies in power grid metering data, characterized in that, include: Data acquisition module: used to collect power grid metering-related data and send the power grid metering-related data to the data processing module. The power grid metering-related data includes: power grid load data, power grid power data, and electricity metering data. Data processing module: used to mark the power grid metering data, calculate the comprehensive power grid index on the marked power grid metering data, obtain the comprehensive power grid index coefficient, and send the comprehensive power grid index coefficient to the data analysis module; The data analysis module is used to input the comprehensive power grid index coefficients into the pre-established standard power grid index judgment model to obtain the power grid index judgment result, set the standard power grid index threshold, calculate the ratio between the power grid index judgment result and the standard power grid index threshold, set the ratio threshold, compare the ratio result with the ratio threshold, and determine whether the power grid metering data meets the standard based on the comparison result. If it meets the standard, a no-abnormality signal is sent to the execution module; if it does not meet the standard, an abnormality judgment signal is sent to the abnormality judgment module. Anomaly Detection Module: This module acquires relevant data on the operating status of power grid components, performs comprehensive evaluation calculations of component status based on this data, obtains comprehensive component status evaluation coefficients, acquires comprehensive power grid index coefficients from the data processing module, plots the evolution trajectory of power grid component status indicators based on the comprehensive power grid index coefficients and comprehensive component status evaluation coefficients, determines the tangent line tangent to the evolution trajectory based on the evolution trajectory, uses the slope of the tangent line as the evolution frequency of power grid component status indicators, sets a threshold for the evolution frequency of power grid component status indicators, compares the obtained evolution frequency of power grid component status indicators with the threshold, determines the degree of power grid anomaly based on the comparison result, and sends a power grid anomaly degree signal to the execution module. Execution module: After receiving a no-abnormality signal from the data analysis module, it reminds staff that there are no abnormalities in the power grid. After receiving a power grid abnormality level signal from the abnormality determination module, it prompts staff to carry out maintenance based on the degree of power grid abnormality.

2. The anomaly analysis system for power grid metering data according to claim 1, characterized in that, The data processing module performs the data tagging process as follows: The power grid load data is labeled as Fi, the power grid power data as Gi, and the meter reading data as Li. In the formula, i is the data acquisition number of the data acquisition module, and i = 1, 2, 3, ..., n, where n is the total number of data acquisitions by the data acquisition module.

3. The anomaly analysis system for power grid metering data according to claim 2, characterized in that, The calculation process of the comprehensive power grid index coefficient of the data processing module is as follows: Using formula The comprehensive power grid index coefficient Zi is calculated, where k1 is the power grid load influence coefficient, k2 is the power grid power influence coefficient, k3 is the metering influence coefficient, G0 is the preset standard power grid load coefficient, F0 is the preset standard power grid power coefficient, L0 is the preset standard metering coefficient, and q is the number of meters.

4. The anomaly analysis system for power grid metering data according to claim 1, characterized in that, The calculation process for the electricity meter readings is as follows: Mark the meter's electrical energy as B1, the meter's voltage as B2, the meter's current as B3, the meter's power factor as B4, and the meter's frequency as B5. The electricity meter readings are calculated based on the marked data, and the meter readings are obtained using the following formula: In the formula, α and β are preset proportionality coefficients.

5. The anomaly analysis system for power grid metering data according to claim 1, characterized in that, The pre-established standard power grid indicator judgment model of the data analysis module is based on an artificial intelligence model. The process of establishing the standard power grid indicator judgment model based on the artificial intelligence model is as follows: By acquiring preset standard power grid metering data, wherein the preset standard power grid metering data includes: preset standard load data, preset standard power data, and preset standard electricity metering data; Based on preset standard power grid metering data, an artificial intelligence model is trained, and a standard power grid index judgment model is output.

6. The anomaly analysis system for power grid metering data according to claim 5, characterized in that, Within the data analysis module: When the ratio result is less than or equal to the ratio threshold, a no-error signal is sent to the execution module. When the ratio result is greater than the ratio threshold, an anomaly determination signal is sent to the anomaly determination module for anomaly determination.

7. The anomaly analysis system for power grid metering data according to claim 1, characterized in that, The calculation process of the anomaly detection module for the comprehensive component status evaluation coefficient includes the following steps: The component-related parameters are labeled as Yj, the measurement data are labeled as Cj, and the component operation topology parameters are labeled as Tj, where j is the number of times the power grid component operation status related data is collected, and j = 1, 2, 3, ..., m, where m is the total number of times the power grid component operation status related data is collected; The formula for calculating the overall component condition assessment coefficient is as follows: In the formula, Xj is the comprehensive component status evaluation coefficient, P1 and P2 are the component operation correlation coefficients, and W is the operation topology correlation coefficient.

8. The anomaly analysis system for power grid metering data according to claim 7, characterized in that, The anomaly determination module determines the tangent line that is tangent to the evolution trajectory of the power grid component status index based on the evolution trajectory of the power grid component status index, and obtains the slope of the tangent line that is tangent to the evolution trajectory of the power grid component status index as the evolution frequency H of the power grid component status index. Set a threshold value H0 for the evolution frequency of power grid component state indicators. Compare the obtained evolution frequency H of power grid component state indicators with the threshold value H0. Determine the degree of power grid anomaly based on the comparison result. When 0≤H<H0, the power grid anomaly level is low-level, and a low-level anomaly signal is sent to the execution module. When H0≤H<2H0, the power grid anomaly level is medium, and a medium anomaly signal is sent to the execution module. When H≥2H0, the power grid anomaly level is high-level, and a high-level anomaly signal is sent to the execution module.

9. The anomaly analysis system for power grid metering data according to claim 1, characterized in that, Upon receiving a low-level anomaly signal, the execution module reminds staff to inspect and repair the power grid equipment components. Upon receiving a medium-level anomaly signal, it reminds staff to perform partial inspection and replacement of the power grid equipment components. Upon receiving a high-level anomaly signal, it reminds staff to directly replace the abnormal power grid equipment components.

10. A method for anomaly analysis of power grid metering data, characterized in that, The method includes the following steps: Acquire grid metering-related data and mark the data. Use the marked grid metering-related data to calculate the comprehensive grid index and obtain the comprehensive grid index coefficient. The grid metering-related data includes: grid load data, grid power data and electricity metering data. The comprehensive power grid index coefficients are input into the pre-established standard power grid index judgment model, and the power grid index judgment result is output. The standard power grid index threshold is set, and the ratio of the power grid index judgment result to the standard power grid threshold is calculated to obtain the ratio result. Set a ratio threshold, compare the ratio result with the ratio threshold, and determine whether the power grid metering data meets the standard based on the comparison result. If it meets the standard, the power grid is not abnormal. If it does not meet the standard, obtain relevant data on the operating status of power grid components, including component-related parameters, measurement data, and component operating topology parameters. Based on the relevant data of the operating status of power grid components, a comprehensive evaluation of the component status is calculated to obtain the comprehensive component status evaluation coefficient. Based on the comprehensive power grid index coefficient and the comprehensive component status evaluation coefficient, the evolution trajectory of the power grid component status index is plotted. Based on the evolution trajectory of power grid component status indicators, a tangent line is determined that is tangent to the evolution trajectory of power grid component status indicators, and the slope of the tangent line is used as the evolution frequency of power grid component status indicators. A threshold for the evolution frequency of power grid component status indicators is set, and the obtained evolution frequency of power grid component status indicators is compared with the threshold for the evolution frequency of power grid component status indicators. The degree of power grid anomaly is determined based on the comparison result.

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