System and method for processing topological data of power grid equipment

Abstract

The invention discloses a power grid equipment topological data processing system and method. The system comprises a data monitoring and acquisition module, a data checking module, a data time marking module, an aging calculation module, a data processing module, a data verification module, a topological model, a problem positioning module and a problem display module. The data checking module is used for detecting data collected in the data monitoring and collecting module; the data time marking module is used for marking the detection time of the correct data detected in the data monitoring and collecting module; the data processing module is used for processing the data marked in the data time marking module, verifying the processed data by using the data verification module, and transmitting the data to the topological model; and the topology model is used for obtaining the problem of the power grid according to the data verified by the data verification module and the data of the aging calculation module, positioning the problem of the power grid by using the problem positioning module, displaying the problem through the problem display module, and maintaining the stability of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid systems, and in particular to a power grid equipment topology data processing system and method. Background Art

[0002] The power grid equipment topology data processing system is an information system used to manage, analyze and process the connection relationship and topological structure between various types of equipment in the power grid. Through such a system, the reliability, safety and economy of the power grid operation can be improved, and the stable supply of electricity can be effectively guaranteed.

[0003] The existing power grid equipment topology data processing system is prone to failure to promptly detect component problems during operation, which can lead to data errors in the system, causing the system to calculate based on erroneous data, resulting in erroneous results and affecting the judgment of staff. Summary of the invention

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

[0005] Therefore, the present invention provides a power grid equipment topology data processing system and method to solve the problem that the existing technology cannot detect the problem of the components in time during the working process, resulting in data errors in the system, which will cause the system to calculate according to the wrong data, get wrong results, and affect the judgment of the staff.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a power grid equipment topology data processing system, comprising: a data monitoring and acquisition module, a data verification module, a data time stamping module, an aging calculation module, a data processing module, a data verification module, a topology model, a problem location module, and a problem display module;

[0008] The data checking module is used to detect the data collected in the data monitoring and collecting module;

[0009] The data time marking module is used to mark the detection time of the correct data detected in the data monitoring and acquisition module;

[0010] The data processing module is used to process the data marked in the data time marking module, verify the processed data using the data verification module, and transmit it to the topology model;

[0011] The topology model is used to verify the processed data and the data of the aging calculation module according to the data verification module, obtain the problem of the power grid, use the problem location module to locate the problem of the power grid, and display the problem through the problem display module.

[0012] As a preferred solution of the power grid equipment topology data processing system of the present invention, wherein: the data checking module includes 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 uses the alarm module to alarm for the data that cannot be detected;

[0014] The missing item marking module marks the missing items detected by the data item checking module, and uses the first rechecking module to feed back the marked missing items to the data monitoring and collection module to re-detect the missing items.

[0015] As a preferred solution of the power grid equipment topology data processing system of the present invention, it also includes:

[0016] The data deviation detection module compares the detected data with the data of the last detection, uses the second re-check module to determine that the data deviation on both sides is greater than the first threshold, controls the data monitoring and acquisition module to perform a third data detection, and selects one of the two most recent sets of data for use.

[0017] As a preferred solution of the power grid equipment topology data processing system described in the present invention, wherein: the aging calculation module includes a historical data storage module, a time sorting module and an equipment aging inference module, a geographic information collection module and an aging deviation data module;

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

[0019] The time sorting module retrieves all data stored in the historical data storage module according to the first time threshold, sorts them according to time, and arranges them in chronological order;

[0020] The equipment aging inference module calculates the aging degree of the power grid equipment based on the data from the time sorting module and the geographic information collection module.

[0021] As a preferred solution of the power grid equipment topology data processing system of the present invention, it also includes:

[0022] The geographic information collection module collects the location of the power grid equipment and detects the geographical environment at the location;

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

[0024] In a second aspect, the present invention provides a method for processing topological data of a power grid device, comprising:

[0025] Acquire power grid data, detect the power grid data to obtain first detection data and second detection data, and pre-process the first detection data to obtain third detection data;

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

[0027] Acquire historical data, calculate the aging degree of power grid equipment and the impact of aging on the data of power grid equipment based on the historical data, and obtain equipment aging abnormality data and aging deviation data;

[0028] The correct data, equipment aging abnormal data and aging deviation data are used to analyze the topology of the power grid using a fault diagnosis algorithm to identify and locate power grid problems.

[0029] As a preferred solution of the method for processing topological data of power grid equipment described in the present invention, wherein:

[0030] The fault diagnosis algorithm includes:

[0031] When a fault occurs, the fault current and voltage are measured, and 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 will be taken.

[0034] As a preferred solution of the method for processing topological data of power grid equipment described in the present invention, it also includes:

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

[0036] The first neural network model maps the input feature vector to the output space and determines the faults existing in the power grid, as well as the fault type and location, based on the output results.

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

[0038] Memory and processor;

[0039] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for processing topology data of power grid equipment are implemented.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the power grid device topology data processing method.

[0041] Compared with the prior art, the present invention has the following beneficial effects: the present invention can ensure that the collected data is complete through the work of the data item verification module, the missing item marking module and the re-inspection module, avoid system missing data due to damage to the detection element, thereby reducing calculation errors, and through multiple data detections and deviation calculations, select the most accurate data for subsequent processing, thereby improving the accuracy of the data, thereby improving the reliability of the system calculation results, and through precise data management and fault handling, improve the overall reliability, safety and economy of the power grid operation, effectively guarantee the stable supply of electricity. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0043] Figure 1 A system flow chart of a power grid equipment topology data processing system and method according to an embodiment of the present invention;

[0044] Figure 2 A data checking module flow chart of a power grid equipment topology data processing system and method according to an embodiment of the present invention;

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

[0046] Figure 4The present invention is a schematic diagram of the overall process logic of a power grid equipment topology data processing system and method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] Example 1

[0049] Reference Figure 1-Figure 4 , as an embodiment of the present invention, provides a power grid equipment topology data processing system, including:

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

[0051] Data monitoring and collection 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 location module 800, problem display module 900;

[0052] The data checking module 200 is used to detect the data collected by the data monitoring and collecting module 100;

[0053] The data time marking module 300 is used to mark the detection time of the correct data detected in the data monitoring and collection module 100;

[0054] The data processing module 500 is used to process the data marked in the data time marking module 300, verify the processed data using the data verification module 600, and transmit it to the topology model 700;

[0055] The topology model 700 is used to verify the processed data and the data of the aging calculation module 400 according to the data verification module 600, obtain the problem of the power grid, locate the problem of the power grid using the problem location module 800, and display the problem through the problem display module 900.

[0056] Specifically, Figure 1 As shown, the output end of the data monitoring and acquisition module 100 is connected to the data time marking module 300, and the data time marking module 300 performs time marking on the correct data detected by the data monitoring and acquisition module 100, marking the detection time of this group of correct data.

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

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

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

[0060] The topology model 700 is connected to the output end of the data verification module 600 . 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 a problem location module 800, which can locate the problem according to the problem, thereby calculating the location and cause of the problem, and then display the problem on the problem display module 900, so that the staff can find the problem and deal with it. The problem location module 800 adopts a fault diagnosis algorithm to quickly detect and locate faulty equipment or areas in the power grid by analyzing the topological structure and related data.

[0062] It should be noted that this system ensures that the data detected each time is complete, to avoid missing data and thus calculation errors due to damage to the detection components;

[0063] The device compares all the data and calculates the deviation between the two data inputs and outputs. If the data deviation is large, the device will detect the data again to form three groups of data, and then select one of the two groups of similar data to determine that the selected data is the correct data, so as to avoid a mistake that causes the data used by the entire system to be wrong, affecting the calculation results of the system;

[0064] By inferring the aging degree of the power grid equipment during this period, and calculating the data deviation caused by the aging of the power grid equipment during this period, the data deviation caused by the aging of the power grid equipment can be removed during the operation of the system, avoiding the impact of aging problems on the system's decision-making.

[0065] In the embodiments of the present application, 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 detects all detection items of the data collected by the data monitoring and collecting module 100, and uses the alarm module 202 to alarm for 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 uses the first rechecking module 204 to feed back the marked missing items to the data monitoring and collecting module 100 to recheck the missing items.

[0068] The data deviation detection module 205 checks the detected data with the data of the last detection, uses the second re-check module 206 to determine that the data deviation on both sides is greater than the first threshold, controls the data monitoring and acquisition module 100 to perform a third data detection, and selects one of the two most recent sets of data for use.

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

[0070] The alarm module 202 is connected to the output end of the data item checking module 201. When the alarm module 202 determines that a certain data item cannot be detected, it performs an alarm process, so that the staff can 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 that the system can clearly know which part of the data is missing;

[0072] The first recheck module 204 is connected to the output end of the missing item marking module 203. The first recheck module 204 can feed back the missing items marked by the missing item marking module 203 to the data monitoring and collection module 100, so that the data monitoring and collection module 100 rechecks the missing items.

[0073] When the data item verification module 201 finds that there are missing items in the data detected by the data monitoring and acquisition module 100, it will mark the missing data type through the missing item marking module 203, and then control the data monitoring and acquisition module 100 to recheck the data through the first re-check module 204, so as to supplement the missing data. The supplemented data will also be tested by the data item verification module 201. If the data item verification module 201 still detects that there are missing items, the alarm module 202 will be used to alarm, so that the staff will go to the inspection end to determine whether the detector is damaged, thereby ensuring that the data detected by the data monitoring and acquisition module 100 each time is complete data, avoiding damage to the detection element, resulting in missing data in the system and thus 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 to 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 later with the data detected last time, thereby forming multiple detections of the data to ensure the accuracy of the detected data;

[0075] The second re-check 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 on both sides is greater than the first threshold value of 60, the second re-check module 206 can control the data monitoring and acquisition module 100 to perform a third data detection, thereby performing three data comparisons and selecting one of the two most recent groups of data for use.

[0076] The data item verification module 201 transmits all the verified data and the data re-detected by the data monitoring and acquisition module 100 to the data deviation detection module 205 for comparison, so as to calculate the deviation of the two data in and out. If the data deviation is greater than 60, the second re-check module 206 will perform data detection again to form three groups of data, so as to select one of the two most recent groups of data, so as to determine that the data selected for use is the correct data, so as to avoid a mistake that causes the data used by the entire system to be wrong, affecting the calculation results of the system.

[0077] In the embodiments of the present application, Figure 3 As shown, the aging calculation module 400 includes a historical data storage module 401, a time sorting module 402, an equipment aging inference module 403, a geographic information collection 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 sorting module 402 retrieves all the data stored in the historical data storage module 401 according to the first time threshold, sorts them according to time, and arranges them in chronological order;

[0080] The equipment aging inference module 403 calculates the aging degree of the power grid equipment based on the data from the time sorting module 402 and the geographic information collection module 404 .

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

[0082] The aging deviation data module 405 calculates the data impact of aging on the power grid equipment based on the result inferred by the equipment aging inference module 403, and obtains the abnormal data caused by the aging of the equipment.

[0083] Specifically, the aging calculation module 400 includes a historical data storage module 401, a time sorting module 402 and an equipment 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 sorting module 402 is connected to the output end of the historical data storage module 401. The time sorting module 402 takes out all the data stored in the historical data storage module 401 during the period of 60 seconds according to the first threshold value of 60 seconds, and then sorts them according to time, sorts all the detection data at the same time together, and arranges them in chronological order;

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

[0086] like Figure 3 As shown, the aging calculation module 400 also includes a geographic information collection module 404 and an aging deviation data module 405. The input end of the equipment 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 sorting module 402. The geographic information collection module 404 can collect the location of the power grid equipment and detect the geographical environment at the location;

[0087] The aging deviation data module 405 is connected to the output end of the equipment aging inference module 403. The aging deviation data module 405 can calculate the data impact of aging on the power grid equipment based on the results inferred by the equipment aging inference module 403, thereby eliminating data anomalies caused by equipment aging.

[0088] It should be noted that, through the collaborative work of the data item verification module 201, the alarm module 202, the missing item marking module 203 and the first recheck module 204, the system can ensure the integrity of the collected data, timely discover and supplement the missing data, thereby avoiding calculation errors caused by missing data. The introduction of the data deviation detection module 205 and the second recheck module 206 enables the system to check the continuously detected data to ensure the consistency and reliability of the data. When the data deviation exceeds the preset first threshold (for example, 60), the system will trigger re-detection and select one of the two closest groups of data as the correct data, thereby improving the system's anti-interference ability. Through multiple data detection and recheck mechanisms, the system can quickly identify potential faults and promptly notify the staff through the alarm module 202 to carry out maintenance, thereby reducing the impact of faults on power grid operation.

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

[0090] like Figure 4 As shown, this embodiment also provides a method for processing power grid equipment topology data, including:

[0091] S100: Acquire power grid data, detect the power grid data to obtain first detection data and second detection data, and pre-process the first detection data to obtain third detection data;

[0092] S200: Process the third detection data to obtain processed detection data, and verify the processed detection data with the second detection data to obtain correct data;

[0093] S300: Acquire historical data, calculate the aging degree of power grid equipment and the impact of aging on the data of power grid equipment according to the historical data, and obtain equipment aging abnormal data and aging deviation data;

[0094] S400: Analyze the topology of the power grid using the correct data, the abnormal aging data of the equipment, and the aging deviation data using a fault diagnosis algorithm, and identify and locate the power grid problem.

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

[0096] In the distance protection-based method, the fault distance is expressed as Z = V / I, where V is the fault phase voltage and I is the fault phase current;

[0097] Based on the artificial intelligence method, the training of the RBFN model includes inputting the extracted features as input vectors into the RBFN model and calculating the output of each hidden layer neuron as:

[0098]

[0099] Where x is the input vector, c is the center of the i-th hidden neuron, σ is the variance of the i-th hidden neuron, and ‖xc‖ is the Euclidean distance between x and c;

[0100] The output layer is calculated based on the hidden layer output and weights, and the result is expressed as:

[0101]

[0102] Among them, yk(x) is the output of the kth output neuron, ω ik is the weight between the i-th hidden layer neuron and the k-th output neuron, and M is the number of hidden layer neurons;

[0103] Use the least squares method or other optimization algorithms to adjust the weights so that the network output is close to the expected fault diagnosis result. The weights are expressed by the minimum multiplication method as:

[0104] W=Φ T Y

[0105] Among them, Φ is the matrix of hidden layer output, and Y is the expected output vector.

[0106] It should be noted that by acquiring the first detection data and the second detection data, and performing preprocessing and data processing, the accuracy and completeness of the data are ensured. By using correct data, equipment aging abnormal data and aging deviation data, combined with a fault diagnosis algorithm, the topology of the power grid can be accurately analyzed, power grid problems can be identified and located, and the distance protection-based method can quickly determine the fault location by calculating the fault distance, while the artificial intelligence-based method can quickly and accurately perform fault diagnosis by training the RBFN model. In the artificial intelligence-based method, the output of the hidden layer neurons and the results of the output layer are calculated, and the weights are adjusted using the least squares 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 a power grid equipment topology data processing system of this embodiment. It should be noted that the technical scheme of the power grid equipment topology data processing system and the technical scheme of the power grid equipment topology data processing system described above belong to the same concept, and the details of the technical scheme of the power grid equipment topology data processing system in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the power grid equipment topology data processing system described above.

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

[0109] A detection module, used for acquiring power grid data, detecting the power grid data to obtain first detection data and second detection data, and preprocessing the first detection data to obtain third detection data;

[0110] A verification module, used for performing data processing on the third detection data to obtain processed detection data, and verifying the processed detection data with the second detection data to obtain correct data;

[0111] A calculation module is used to obtain historical data, calculate the aging degree of power grid equipment and the impact of aging on the data of power grid equipment according to the historical data, and obtain equipment aging abnormality data and aging deviation data;

[0112] The identification module is used to analyze the topological structure of the power grid by using the correct data, equipment aging abnormal data and aging deviation data using a fault diagnosis algorithm, and identify and locate power grid problems.

[0113] This embodiment further provides a computing device, which is applicable to the processing of topological data of power grid equipment, and includes:

[0114] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the power grid equipment topology data processing system proposed in the above embodiment.

[0115] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the power grid device topology data processing system proposed in the above embodiment is implemented.

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

[0117] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

Claims

1. A power grid equipment topology data processing system, characterized in that: include: A data monitoring and collection module (100), a data checking module (200), a data time marking module (300), an aging calculation module (400), a data processing module (500), a data verification module (600), a topology model (700), a problem location module (800), and a problem display module (900); The data checking module (200) is used to detect the data collected in the data monitoring and collecting module (100); The data time marking module (300) is used to mark the detection time of the correct data detected in the data monitoring and collection module (100); The data processing module (500) is used to process the data marked in the data time marking module (300), verify the processed data using the data verification module (600), and transmit the processed data to the topological model (700); The topology model (700) is used to verify the processed data and the data of the aging calculation module (400) according to the data verification module (600), obtain the problem of the power grid, use the problem location module (800) to locate the problem of the power grid, and display the problem through the problem display module (900).

2. The power grid equipment topology data processing system according to claim 1, characterized in that: The data checking module (200) comprises 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 by the data monitoring and collecting module (100), and uses the alarm module (202) to alarm for data that cannot be detected; The missing item marking module (203) marks the missing items detected by the data item checking module (201), and uses the first rechecking module (204) to feed back the marked missing items to the data monitoring and collecting module (100) to recheck the missing items.

3. The power grid equipment topology data processing system according to claim 2, characterized in that: Also includes: The data deviation detection module (205) checks the detected data with the data detected last time, uses the second recheck module (206) to determine that the data deviation on both sides is greater than the first threshold, controls the data monitoring and collection module (100) to perform a third data detection, and selects one of the two most recent sets of data for use.

4. The power grid equipment topology data processing system according to claim 1 or 3, characterized in that: The aging calculation module (400) comprises a historical data storage module (401), a time sorting module (402), an equipment 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 sorting module (402) retrieves all data stored in the historical data storage module (401) according to the first time threshold, sorts the data according to time, and arranges the data in chronological order; The equipment aging inference module (403) calculates the aging degree of the power grid equipment based on the data of the time sorting module (402) and the geographic information collection module (404).

5. The power grid equipment topology data processing system according to claim 4, characterized in that: Also includes: The geographic information collection module (404) collects the location of the power grid equipment and detects the geographical environment at the location; The aging deviation data module (405) calculates the data impact of aging on the power grid equipment based on the result inferred by the equipment aging inference module (403), and obtains abnormal data caused by aging of the equipment.

6. A method for processing topological data of power grid equipment according to any one of claims 1 to 5, characterized in that: include: Acquire power grid data, detect the power grid data to obtain first detection data and second detection data, and pre-process the first detection data to obtain third detection data; Processing the third detection data to obtain processed detection data, and verifying the processed detection data with the second detection data to obtain correct data; Acquire historical data, calculate the aging degree of power grid equipment and the impact of aging on the data of power grid equipment based on the historical data, and obtain equipment aging abnormality data and aging deviation data; The correct data, equipment aging abnormal data and aging deviation data are used to analyze the topology of the power grid using a fault diagnosis algorithm to identify and locate power grid problems.

7. The method for processing power grid equipment topology data according to claim 6, characterized in that: The fault diagnosis algorithm includes: When a fault occurs, the fault current and voltage are measured, and the fault distance is calculated by the ratio of the fault voltage and current, and compared with the preset setting value; If the fault distance is less than or equal to the preset setting value, the corresponding action is triggered; If the fault distance is greater than the preset setting value, no action will be taken.

8. The method for processing power grid equipment topology data according to claim 6, characterized in that: Also includes: Using an artificial neural network to obtain power grid operation data, preprocessing the power grid operation data, extracting features from the preprocessed data, and 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 determines the faults existing in the power grid, as well as the fault type and location, based on the output results.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the power grid equipment topology data processing method described in any one of claims 6 to 8 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the method for processing topology data of power grid equipment according to any one of claims 6 to 8.

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