A power grid device topology data processing system and method

Abstract

The application discloses a kind of power grid equipment topology data processing system and method, comprising: data monitoring acquisition module, data check module, data time marking module, aging calculation module, data processing module, data verification module, topology model, problem positioning module, problem display module;Data check module is used to detect the data collected in data monitoring acquisition module;Data time marking module is used to mark the detection time of the correct data detected in the data monitoring acquisition module;Data processing module is used to process the data marked in data time marking module, verify the data after processing using data verification module, and transmit to topology model;Topology model is used to obtain the problem of power grid according to the data after processing verified using data verification module and the data of aging calculation module, locate the problem of power grid using problem positioning module, show the problem through problem display module, maintain power grid stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid system, and particularly relates to a power grid equipment topology data processing system and method. BACKGROUND

[0002] The power grid equipment topology data processing system is an information system for managing, analyzing and processing the connection relationship and topology structure among various devices in the power grid. Through such a system, the reliability, safety and economy of power grid operation can be improved, and the stable supply of power can be effectively ensured.

[0003] The existing power grid equipment topology data processing system is prone to not timely detect problems in detection components during the working process, which will lead to data errors in the system, and thus the system will calculate according to the wrong data and obtain wrong results, affecting the judgment of the staff. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a power grid equipment topology data processing system and method to solve the problem that the existing technology cannot timely detect problems in detection components during the working process, which will lead to data errors in the system, and thus the system will calculate according to the wrong data and obtain wrong results, affecting the judgment of the staff.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a power grid equipment topology data processing system, comprising: a data monitoring and collecting module, a data checking module, a data time marking module, an aging calculation module, a data processing module, a data verification module, a topology model, a problem positioning module, and a problem display module.

[0008] The data checking module is configured to detect the data collected by the data monitoring and collecting module.

[0009] The data time marking module is configured to mark the detection time of the correct data detected by the data monitoring and collecting module.

[0010] The data processing module is configured to process the data marked by the data time marking module, verify the processed data by using the data verification module, and transmit the processed data to the topology model.

[0011] The topology model is used for verifying the processed data by the data verification module and the data of the aging calculation module, obtaining the problems of the power grid, positioning the problems of the power grid by the problem positioning module, and displaying the problems by the problem display module.

[0012] As a preferred scheme of the power grid equipment topology data processing system, the data checking module comprises a data item checking module, an alarm module, a missing item marking module, a data deviation detection module, a first rechecking module, and a second rechecking module.

[0013] The data item checking module detects all detection items of the data collected by the data monitoring and collecting module, and the alarm module alarms the undetected data.

[0014] The missing item marking module marks the missing items detected by the data item checking module, and the first rechecking module feeds back the marked missing items to the data monitoring and collecting module to recheck the missing items.

[0015] As a preferred scheme of the power grid equipment topology data processing system, the data checking module comprises a data item checking module, an alarm module, a missing item marking module, a data deviation detection module, a first rechecking module, and a second rechecking module.

[0016] The data deviation detection module checks the detected data with the data detected last time, the second rechecking module determines that the data deviation of both sides is greater than a first threshold value, controls the data monitoring and collecting module to perform third data detection, and selects one of the two groups of data to use.

[0017] As a preferred scheme of the power grid equipment topology data processing system, the aging calculation module comprises a historical data storage module, a time arrangement module, and an equipment aging inference module, a geographic information collecting module, and an aging deviation data module.

[0018] The historical data storage module stores the data marked by the data time marking module to obtain a historical database.

[0019] The time arrangement module takes out all the data stored by the historical data storage module according to a first time threshold value, arranges the data according to time, and arranges the data in time sequence.

[0020] The equipment aging inference module calculates the aging degree of the power grid equipment according to the data of the time arrangement module and the geographic information collecting module.

[0021] As a preferred scheme of the power grid equipment topology data processing system, the data checking module comprises a data item checking module, an alarm module, a missing item marking module, a data deviation detection module, a first rechecking module, and a second rechecking module.

[0022] The geographic information collection module collects the position of the power grid equipment and detects the geographic environment at the position.

[0023] The aging deviation data module calculates the data influence of the power grid equipment caused by aging according to the result inferred by the equipment aging inference module, and obtains abnormal data of the equipment caused by aging.

[0024] In a second aspect, the present application provides a power grid equipment topology data processing method, comprising:

[0025] Obtaining power grid data, detecting the power grid data to obtain first detection data and second detection data, preprocessing the first detection data to obtain third detection data;

[0026] Processing the third detection data to obtain processed detection data, verifying the processed detection data and the second detection data to obtain correct data;

[0027] Obtaining historical data, calculating the aging degree of the power grid equipment and the data influence of the power grid equipment caused by aging according to the historical data, obtaining equipment aging abnormal data and aging deviation data;

[0028] Using the correct data, the equipment aging abnormal data and the aging deviation data to analyze the topology structure of the power grid by using a fault diagnosis algorithm, and identifying and positioning the power grid problem.

[0029] As a preferred scheme of the power grid equipment topology data processing method of the present application, wherein:

[0030] The fault diagnosis algorithm comprises:

[0031] When a fault occurs, the fault current and voltage are measured, the fault distance is calculated by the ratio of the fault voltage and current, and compared with the preset setting value;

[0032] If the fault distance is less than or equal to the preset setting value, the corresponding action is triggered;

[0033] If the fault distance is greater than the preset setting value, no action is taken.

[0034] As a preferred scheme of the power grid equipment topology data processing method of the present application, wherein:

[0035] Using artificial neural network to obtain power grid operation data, preprocessing the power grid operation data, extracting features from the preprocessed data, inputting the extracted features into the neural network model for training to obtain a first neural network model;

[0036] The first neural network model maps the input feature vector to an output space, and according to an output result, judges the existing fault of the power grid and the fault type and position.

[0037] In a third aspect, the present application provides a computing device, comprising:

[0038] a memory and a processor;

[0039] The memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions, which realize the steps of the power grid equipment topology data processing method when executed by the processor.

[0040] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer executable instructions, which realize the steps of the power grid equipment topology data processing method when executed by the processor.

[0041] Compared with the prior art, the present application has the beneficial effects that: through the work of the data item checking module, the missing item marking module and the rechecking module, it can ensure that the collected data is complete, avoid missing data of the system caused by damage of the detection element, thereby reducing calculation errors, selecting the most accurate data for subsequent processing through multiple data detection and deviation calculation, improving the accuracy of the data, thereby improving the reliability of the system calculation result, improving the overall reliability, safety and economy of the power grid operation through accurate data management and fault processing, and effectively guaranteeing the stable supply of power. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0043] Figure 1 The system flowchart of the power grid equipment topology data processing system and method according to an embodiment of the present application;

[0044] Figure 2 The data checking module flowchart of the power grid equipment topology data processing system and method according to an embodiment of the present application;

[0045] Figure 3 The aging calculation module flowchart of the power grid equipment topology data processing system and method according to an embodiment of the present application;

[0046] Figure 4The overall flow logical diagram of the power grid equipment topology data processing system and method according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0047] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0048] Embodiment 1

[0049] Reference Figures 1-4 According to an embodiment of the present application, a power grid equipment topology data processing system is provided, comprising:

[0050] Figure 1 A system structure diagram of the power grid equipment topology data processing system and method is shown, comprising:

[0051] The data monitoring and collecting module 100, the data checking module 200, the data time marking module 300, the aging calculation module 400, the data processing module 500, the data verification module 600, the topology model 700, the problem positioning module 800, and the problem display module 900.

[0052] The data checking module 200 is used for detecting the data collected in the data monitoring and collecting module 100.

[0053] The data time marking module 300 is used for marking the detection time of the correct data detected in the data monitoring and collecting module 100.

[0054] The data processing module 500 is used for processing the data marked in the data time marking module 300, verifying the processed data by using the data verification module 600, and transmitting the processed data to the topology model 700.

[0055] The topology model 700 is used for obtaining the problem of the power grid according to the verified processed data of the data verification module 600 and the data of the aging calculation module 400, positioning the problem of the power grid by using the problem positioning module 800, and displaying the problem by using the problem display module 900.

[0056] Specifically, as shown in Figure 1 The output end of the data monitoring and collecting module 100 is connected with the data time marking module 300. The data time marking module 300 marks the time of the correct data detected by the data monitoring and collecting module 100, and marks the detection time of the correct data.

[0057] The aging calculation module 400 is connected to the output end of the data time marking module 300, and the aging calculation module 400 infers the aging degree of the equipment in the power grid according to the data change in each period of time.

[0058] The output end of the data time marking module 300 is connected to the data processing module 500, and the data processing module 500 can process the data marked by the data time marking module 300, so that the format and content of the data are more in line with the calculation requirements.

[0059] As shown in Figure 1 The output end of the data processing module 500 is connected to the data verification module 600, and the data verification module 600 can ensure that the data processed by the data processing module 500 does not lose important data, and then the correct data verified by the data verification module 600 is transmitted to the topology model 700 for work.

[0060] The topology model 700 is connected to the output end of the data verification module 600, and the topology model 700 calculates the problems existing in the power grid according to the data of the data verification module 600 and the data of the aging calculation module 400.

[0061] The output end of the topology model 700 is connected to the problem positioning module 800, and the problem positioning module 800 can locate the problems according to the problems, so as to calculate the position and reason of the problems, and then display the problems on the problem display module 900, so as to facilitate the staff to find and process the problems. The problem positioning module 800 adopts a fault diagnosis algorithm to quickly detect and locate the faulty equipment or area in the power grid by analyzing the topology structure and related data.

[0062] It should be noted that the system ensures that the data detected each time is complete data, avoiding missing data due to damage of the detection element, thereby causing calculation errors;

[0063] The device compares all the data, and calculates the deviation of the data in and out twice. If the data deviation is large, the data will be detected again, thereby forming three groups of data, and then selecting one group of similar data, so as to determine that the selected data is correct data, avoiding that one-time error causes the data used by the entire system to be wrong, thereby affecting the calculation result of the system;

[0064] By calculating the aging degree of the power grid equipment in this period of time and the data deviation of the power grid equipment caused by aging in this period of time, the system can remove the data deviation caused by the aging of the power grid equipment in the working process, thereby avoiding the influence of the aging problem on the decision of the system.

[0065] In the embodiment of the present application, as shown in Figure 2As shown, the data checking module 200 includes a data item checking module 201, an alarm module 202, a missing item marking module 203, a data deviation detection module 205, a first rechecking module 204 and a second rechecking module 206;

[0066] The data item checking module 201 checks all detection items of the data collected by the data monitoring and collecting module 100, and the alarm module 202 alarms the data that cannot be detected.

[0067] The missing item marking module 203 marks the missing items detected by the data item checking module 201, and the first rechecking module 204 feeds the marked missing items back to the data monitoring and collecting module 100 for re-detection of the missing items.

[0068] The data deviation detection module 205 checks the detected data with the data detected last time, and the second rechecking module 206 determines that the data deviation on both sides is greater than the first threshold value, controls the data monitoring and collecting module 100 to perform third data detection, and selects one of the two groups of data closest to use.

[0069] Specifically, the data checking module 200 is input and output connected with the data monitoring and collecting module 100, and includes the data item checking module 201, the alarm module 202, the missing item marking module 203 and the first rechecking module 204. The data item checking module 201 is connected to the output end of the data monitoring and collecting module 100, and checks the detection data item in the data monitoring and collecting module 100, so as to ensure that the data monitoring and collecting module 100 monitors all detection items.

[0070] The alarm module 202 is connected to the output end of the data item checking module 201, and the alarm module 202 alarms when it is determined that a certain data cannot be detected, so as to facilitate the staff to repair the problem in time.

[0071] The missing item marking module 203 is connected to the output end of the data item checking module 201, and the alarm module 202 and the missing item marking module 203 are connected in parallel. The missing item marking module 203 can mark the missing items detected by the data item checking module 201, so as to make the system clear which part of the data is missing.

[0072] The first rechecking module 204 is connected to the output end of the missing item marking module 203, and the first rechecking module 204 can feed the missing items marked by the missing item marking module 203 to the data monitoring and collecting module 100, so as to make the data monitoring and collecting module 100 re-detect the missing items.

[0073] The data item checking module 201 finds that the data detected by the data monitoring and collecting module 100 has missing items, marks the missing data types through the missing item marking module 203, and then controls the data monitoring and collecting module 100 to perform data rechecking through the first rechecking module 204, so as to supplement the missing data. The supplemented data is also detected by the data item checking module 201. If the data item checking module 201 still detects data missing, the alarm module 202 will alarm to let the staff check the detector to determine whether the detector is damaged, so as to ensure that the data detected by the data monitoring and collecting module 100 each time is complete data, avoid missing data of the system due to damage of the detection element, and thus avoid calculation errors.

[0074] Specifically, the data checking module 200 further includes a data deviation detection module 205 and a second rechecking module 206. The output end of the data item checking module 201 is connected with the data deviation detection module 205, and the data deviation detection module 205 is connected in parallel with the data item checking module 201, the alarm module 202 and the first rechecking module 204. The data deviation detection module 205 can check the data detected last time and the data detected later, so as to form multiple detections of the data and ensure the accuracy of the detection data.

[0075] The second rechecking module 206 is connected to the output end of the data deviation detection module 205. When the data deviation detection module 205 determines that the data deviation of the two sides is greater than the first threshold value of 60, the second rechecking module 206 controls the data monitoring and collecting module 100 to perform third data detection, so as to compare three groups of data and select one group of data from the two groups of recent data.

[0076] The data item checking module 201 sends all the checked data and the data detected by the data monitoring and collecting module 100 again to the data deviation detection module 205 for comparison, so as to calculate the deviation of the two groups of data. If the data deviation is greater than 60, the second rechecking module 206 will detect the data again, so as to form three groups of data, select one group of data from the two groups of recent data, and determine the selected data as correct data, so as to avoid errors of the system due to one-time errors, and affect the calculation results of the system.

[0077] In the embodiment of the application, as shown in Figure 3 The aging calculation module 400 includes a historical data storage module 401, a time arrangement module 402, a device aging inference module 403, a geographic information collecting module 404 and an aging deviation data module 405.

[0078] The historical data storage module 401 stores the data marked in the data time marking module 300 to obtain a historical database.

[0079] The time arrangement module 402 takes out all the data stored by the historical data storage module 401 according to the first time threshold, arranges the data according to time, and arranges the data in time sequence;

[0080] The device aging inference module 403 calculates the aging degree of the power grid device according to the data of the time arrangement module 402 and the geographic information collection module 404.

[0081] The geographic information collection module 404 collects the location of the power grid device and detects the geographic environment at the location;

[0082] The aging deviation data module 405 calculates the data influence of the power grid device caused by aging according to the inference result of the device aging inference module 403, and obtains the abnormal data caused by aging of the device.

[0083] Specifically, the aging calculation module 400 includes a historical data storage module 401, a time arrangement module 402, and a device aging inference module 403. The historical data storage module 401 can store the data marked by the data time marking module 300, thereby forming a historical database;

[0084] The time arrangement module 402 is connected to the output end of the historical data storage module 401. The time arrangement module 402 takes out all the data stored by the historical data storage module 401 in 60s according to the first threshold of 60s, then arranges the data according to time, and arranges all the detection data of the same time together in time sequence;

[0085] The device aging inference module 403 is located at the output end of the time arrangement module 402. The device aging inference module 403 can calculate the aging degree of the power grid device according to the data of the time arrangement module 402 and the geographic information collection module 404.

[0086] As shown in Figure 3 The aging calculation module 400 further includes a geographic information collection module 404 and an aging deviation data module 405. The input end of the device aging inference module 403 is connected to the geographic information collection module 404, and the geographic information collection module 404 is connected in parallel with the time arrangement module 402. The geographic information collection module 404 can collect the location of the power grid device and detect the geographic environment at the location.

[0087] The aging deviation data module 405 is connected to the output end of the device aging inference module 403. The aging deviation data module 405 can calculate the data influence of the power grid device caused by aging according to the inference result of the device aging inference module 403, thereby eliminating the data abnormality problem caused by aging of the device.

[0088] It should be noted that through the cooperative work of the data item checking module 201, the alarm module 202, the missing item marking module 203, and the first rechecking module 204, the system can ensure the completeness of the collected data, timely find and supplement the missing data, thereby avoiding calculation errors caused by data loss. The introduction of the data deviation detection module 205 and the second rechecking module 206 enables the system to check the continuously detected data, ensuring the consistency and reliability of the data. When the data deviation exceeds the first preset threshold (for example, 60), the system triggers re-detection, selects one of the two most similar groups of data as the correct data, thereby improving the anti-interference ability of the system. Through multiple data detection and rechecking mechanisms, the system can quickly identify potential faults and timely notify the staff for maintenance through the alarm module 202, reducing the impact of faults on power grid operation.

[0089] The aging calculation module 400 can accurately infer the aging degree of the power grid equipment according to historical data and geographic information, and exclude data anomalies caused by equipment aging through the aging deviation data module 405, thereby prolonging the service life of the equipment and reducing maintenance costs. Through accurate equipment aging management and fault detection, the system can reduce the risk of unexpected power outages and equipment failures, improve the operating efficiency and safety of the power grid.

[0090] As shown in Figure 4 The embodiment also provides a power grid equipment topology data processing method, which comprises the following steps:

[0091] S100: acquiring power grid data, detecting the power grid data to obtain first detection data and second detection data, pre-processing the first detection data to obtain third detection data;

[0092] S200: performing data processing on the third detection data to obtain processed detection data, verifying the processed detection data and the second detection data to obtain correct data;

[0093] S300: acquiring historical data, calculating the aging degree of power grid equipment and the data impact of aging on power grid equipment according to the historical data, and obtaining equipment aging anomaly data and aging deviation data;

[0094] S400: using the correct data, the equipment aging anomaly data, and the aging deviation data to analyze the topology structure of the power grid by using a fault diagnosis algorithm, and identifying and positioning the power grid problem.

[0095] Specifically, the fault diagnosis algorithm comprises a distance protection-based method or an artificial intelligence-based method.

[0096] In the distance protection-based method, the fault distance is represented as Z = V / I, wherein V is the fault phase voltage, and I is the fault phase current.

[0097] The method based on artificial intelligence trains the RBFN model by inputting the extracted features as an input vector into the RBFN model, and calculating the output of each hidden neuron, which is expressed as:

[0098]

[0099] wherein x is the input vector, c is the center of the i-th hidden neuron, s is the variance of the i-th hidden neuron, and ||x-c|| is the Euclidean distance between x and c;

[0100] The output layer calculates the result of the output layer according to the hidden layer output and the weight, which is expressed as:

[0101]

[0102] wherein yk(x) is the output of the k-th output neuron, w ik is the weight between the i-th hidden neuron and the k-th output neuron, and M is the number of hidden neurons;

[0103] The weight is adjusted by using the least square method or other optimization algorithms so that the output of the network is close to the expected fault diagnosis result, and the weight is expressed by the least square method as:

[0104] W = F T Y

[0105] wherein F is the matrix of the hidden layer output, and Y is the expected output vector.

[0106] It should be noted that by obtaining the first detection data and the second detection data, and performing preprocessing and data processing, the accuracy and integrity of the data are ensured. By using correct data, device aging abnormal data, and aging deviation data, and combining the fault diagnosis algorithm, the topology of the power grid can be accurately analyzed, the power grid problem can be identified and located, the method based on distance protection can quickly determine the fault location by calculating the fault distance, and the method based on artificial intelligence can quickly and accurately perform fault diagnosis by training the RBFN model. In the method based on artificial intelligence, the output of the hidden neuron and the result of the output layer are calculated, and the weight is adjusted by using the least square method or other optimization algorithms so that the output of the network is close to the expected fault diagnosis result, thereby improving the performance and accuracy of the neural network.

[0107] The above is a schematic scheme of the power grid equipment topology data processing system of the embodiment. It should be noted that the technical scheme of the power grid equipment topology data processing system belongs to the same concept as the technical scheme of the power grid equipment topology data processing system described above. The technical scheme of the power grid equipment topology data processing system in the embodiment is not described in detail, and the description of the technical scheme of the power grid equipment topology data processing system can be referred to.

[0108] The system of the power grid equipment topology data processing method in the embodiment comprises:

[0109] The detection module is configured to acquire power grid data, detect the power grid data to obtain first detection data and second detection data, pre-process the first detection data to obtain third detection data, and acquire historical data, and calculate the aging degree of power grid equipment and the data influence of aging on power grid equipment according to the historical data to obtain equipment aging anomaly data and aging deviation data.

[0110] The verification module is configured to perform data processing on the third detection data to obtain processed detection data, and verify the processed detection data and the second detection data to obtain correct data.

[0111] The calculation module is configured to acquire historical data, and calculate the aging degree of power grid equipment and the data influence of aging on power grid equipment according to the historical data to obtain equipment aging anomaly data and aging deviation data.

[0112] The recognition module is configured to analyze the topology structure of the power grid by using the correct data, the equipment aging anomaly data, and the aging deviation data by using a fault diagnosis algorithm, and recognize and locate to obtain a power grid problem.

[0113] The embodiment also provides a computing device suitable for the power grid equipment topology data processing case, which comprises:

[0114] The storage and the processor; the storage is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions to realize the power grid equipment topology data processing system proposed in the above embodiment.

[0115] The embodiment also provides a storage medium having a computer program stored thereon, and the program is executed by the processor to realize the power grid equipment topology data processing system proposed in the above embodiment.

[0116] The storage medium proposed in the embodiment and the power grid equipment topology data processing system proposed in the above embodiment belong to the same inventive concept, and the technical details not described in the embodiment can be referred to the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.

[0117] Those skilled in the art can clearly understand the present application by the above description of the embodiments, and the present application can be realized by software and necessary general hardware, and of course, can also be realized by hardware. Based on such understanding, the technical solutions of the present application or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH, a hard disk, or an optical disc, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.

Claims

1. A power grid equipment topology data processing system, characterized by, The utility model relates to a power grid aging data processing system, including: Data monitoring and collecting module (100), data checking module (200), data time marking module (300), aging calculation module (400), data processing module (500), data verification module (600), topology model (700), problem positioning module (800), problem display module (900); The data checking module (200) is used for detecting the data collected in the data monitoring and collecting module (100); The data time marking module (300) is used for marking the detection time of the correct data detected in the data monitoring and collecting module (100); The data processing module (500) is used for processing the data marked in the data time marking module (300), verifying the processed data by using the data verification module (600), and transmitting the processed data to the topology model (700); The topology model (700) is used for obtaining the problem of the power grid according to the verified processed data of the data verification module (600) and the data of the aging calculation module (400), positioning the problem of the power grid by using the problem positioning module (800), and displaying the problem by using the problem display module (900); The aging calculation module (400) includes a historical data storage module (401), a time arrangement module (402), a device aging inference module (403), a geographic information collection module (404), and an aging deviation data module (405); The historical data storage module (401) stores the data marked in the data time marking module (300) to obtain a historical database; The time arrangement module (402) extracts all the data stored in the historical data storage module (401) according to a first time threshold, arranges the data according to time, and arranges the data in time sequence; The device aging inference module (403) calculates the aging degree of the power grid device according to the data of the time arrangement module (402) and the geographic information collection module (404); Further comprising: The geographic information collection module (404) collects the position of the power grid device and detects the geographic environment at the position; The aging deviation data module (405) calculates the influence of the data of the power grid device caused by aging according to the result inferred by the device aging inference module (403) to obtain abnormal data caused by aging of the device.

2. The power grid equipment topology data processing system of claim 1, wherein, The data checking module (200) includes a data item checking module (201), an alarm module (202), a missing item marking module (203), a data deviation detection module (205), a first rechecking module (204), and a second rechecking module (206); The data item checking module (201) detects all detection items of the data collected in the data monitoring and collecting module (100), and the alarm module (202) alarms the data that cannot be detected. The missing item marking module (203) marks the missing items detected by the data item checking module (201), and feeds the marked missing items to the data monitoring and collecting module (100) by using the first rechecking module (204) to recheck the missing items.

3. The power grid equipment topology data processing system of claim 2, wherein, Further comprising: The data deviation detecting module (205) checks the detected data with the last detected data, determines that the data deviation on both sides is greater than the first threshold value by using the second rechecking module (206), and controls the data monitoring and collecting module (100) to perform third data detection, and selects one of the two groups of data to use.

4. The method of processing grid equipment topology data, applied to the system of processing grid equipment topology data according to any one of claims 1-3, characterized in that, Comprising: Obtaining power grid data, detecting the power grid data to obtain first detection data and second detection data, pre-processing the first detection data to obtain third detection data; Processing the third detection data to obtain processed detection data, verifying the processed detection data and the second detection data to obtain correct data; Obtaining historical data, calculating the aging degree of power grid equipment and the data influence of aging on power grid equipment according to the historical data to obtain equipment aging abnormal data and aging deviation data; Using the correct data, equipment aging abnormal data and aging deviation data to analyze the topology structure of the power grid by using a fault diagnosis algorithm, and identifying and locating the power grid problem.

5. The power grid equipment topology data processing method of claim 4, wherein, The fault diagnosis algorithm comprises: When a fault occurs, measure the fault current and voltage, calculate the fault distance by the ratio of the fault voltage and current, and compare it with the preset setting value; If the fault distance is less than or equal to the preset setting value, trigger the corresponding action; If the fault distance is greater than the preset setting value, no action is taken.

6. The power grid equipment topology data processing method of claim 4, wherein, Further comprising: Obtaining power grid operation data by using an artificial neural network, pre-processing the power grid operation data, extracting features from the pre-processed data, inputting the extracted features into a neural network model for training to obtain a first neural network model; The first neural network model maps the input feature vector to the output space, and judges the fault existing in the power grid and the fault type and location according to the output result. 7.An electronic device, comprising: a memory and a processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, which realize the steps of the power grid equipment topology data processing method in any one of claims 4 to 6 when executed by the processor. 8.A computer readable storage medium storing computer executable instructions, which realize the steps of the power grid equipment topology data processing method in any one of claims 4 to 6 when executed by the processor.

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