Automatic verification method and system based on power grid data sharing center

Abstract

The invention provides an automatic verification method and system based on a power grid data sharing center, and relates to the technical field of data verification, and the method comprises the steps: carrying out the preprocessing of obtained power grid resource data, and carrying out the grouping and subpackage operation of the preprocessed power grid resource data; constructing a verification rule base, performing verification rule matching on the preprocessed power grid resource data, selecting a corresponding verification rule from the verification rule base to automatically perform data verification, and generating a verification report; feeding back problem data and correcting the problem data according to a result of the verification report; updating of business rules and equipment types of the power grid is monitored in real time, integrated adjustment of different equipment resource verification rules is carried out, and updating of the verification rule base is completed. According to the method, multi-dimensional verification is carried out on the power grid resource data, high quality of the power grid data is ensured, data classification and batch verification are carried out, and the verification speed is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of data verification, and in particular to an automated verification method and system based on a power grid data sharing center. Background Art

[0002] With the continuous deepening of power grid construction and intelligent transformation, the management and application of power grid data have gradually become the core of ensuring the safety and stability of power grid operation. As a key node in the information management of power grid, the power grid data sharing center carries a large amount of power equipment data and operation status information. Therefore, accurate and timely quality verification of these data is of great significance to ensure the accuracy, integrity and consistency of power grid resources.

[0003] In the power grid system, there are many types of data, which need to be verified through different verification rules. The efficiency and accuracy of verification become very important issues in data verification. Therefore, this article provides an automated verification method. Summary of the invention

[0004] In order to solve the above-mentioned problems, the present invention provides an automated verification method based on a power grid data sharing center, which ensures the high quality of power grid data by performing multi-dimensional verification of power grid resource data, and performs data classification and batch verification to improve the verification speed.

[0005] To solve the above problems, in a first aspect, the present invention provides an automated verification method based on a power grid data sharing center, the method comprising: Preprocessing the acquired power grid resource data, and performing grouping and subpackaging operations on the preprocessed power grid resource data; Build a verification rule library, match the verification rules for the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; Feedback the problem data and correct the problem data according to the results of the verification report; Monitor the business rules and equipment types of the power grid in real time, make integrated adjustments to the verification rules for different equipment resources, and complete the update of the verification rule library.

[0006] Further, the preprocessing includes data cleaning to remove duplicate, invalid or missing records; The preprocessing also includes identifying the data type of the power grid resource data, using a preset marking rule to type-mark the power grid resource data after data cleaning according to the data type, grouping the power grid resource data according to the type marking, and using the same verification rule to verify the power grid resource data in the same group. After grouping, the power grid resource data of each group is packaged to ensure that the number of data to be verified in each package is within a preset number threshold; The preset marking rule is specifically: the power grid resource data that is verified by the same verification rule is marked with the same type.

[0007] Furthermore, before performing the subpackaging operation on each group of power grid resource data, the number m of the nth group of power grid resource data to be subpacked is obtained, and the number of packets into which the nth group of power grid resource data to be subpacked needs to be divided is calculated. The specific calculation formula is as follows:

[0008] in, is the preset quantity threshold, is the number of packets into which the nth group of power grid resource data is finally divided, for The minimum value of is a natural number, is the number of power grid resource data in each packet, The number of power grid resource data in the packet is The number of packets.

[0009] Furthermore, the pre-processed power grid resource data is matched with verification rules, and the corresponding verification rules are selected from the verification rule library to automatically verify the data and generate a verification report, which specifically includes: Perform verification rule matching on the power grid resource data after the grouping operation, select the corresponding verification rule from the verification rule library, and complete the verification rule confirmation; Using the confirmed verification rules, batch verification is performed on the power grid resource data in each package in the group in turn, and the verification time used to complete the verification process for each package and the amount of power grid resource data in the processed package are recorded; After the verification process, a verification report is generated, wherein the verification report includes the type, location, specific problem of the abnormal data and correction suggestions; For problematic data found in the verification report, the operation and maintenance personnel can make corrections based on the suggestions, and the corrected data will be re-entered into the system for verification until the verification result passes.

[0010] Furthermore, after the verification and correction process, the verification results and the correction results are analyzed, including: Integrate the problem data of the power grid resource data in the same group, classify and count the problem data of the group according to the problem type, and draw a statistical chart of the problem data of the group; Analyze the number of each question type in the group of question data according to the question data statistical chart, and mark the question types whose number is greater than or equal to the preset standard number as common question types; Record the correction process of each common problem type, count the number of corrections from the problem data of each problem type to the verification result passing, and summarize the correction experience of the problem data of each problem type; The problem data in each package is corrected until the number of corrections that pass the verification result exceeds the preset standard number, and then marked. If the number of marks that exceed the preset standard number is greater than or equal to the preset standard number of marks, the verification rules used to correct the problem data are updated.

[0011] Further, the real-time monitoring of the business rules and equipment types of the power grid is updated, and the integrated adjustment of the verification rules of different equipment resources is performed to complete the update of the verification rule library. The specific process is as follows: All verification rules are stored in the verification rule base, which is dynamically added, deleted, modified and checked according to actual needs; When new equipment is put into use, corresponding verification rules can be added according to the characteristics of the new equipment; As the grid operation mode changes, the system automatically adjusts data verification rules according to business needs to ensure the perfection of verification work in new business scenarios; According to the actual situation of the power grid operation, the verification rules that match the current environment are automatically selected. If new equipment types or new operating modes appear, the appropriate verification rules are actively learned based on historical data and recommended.

[0012] Furthermore, we actively learn and recommend appropriate verification rules based on historical data. The specific process is as follows: Collect and organize historical data, determine the validity of historical data, and identify the distribution patterns of historical data; Analyze historical data, identify verification rules that have been used, and learn and identify verification rules that can improve data quality among the used verification rules through annotated samples of historical data, the annotated samples including erroneous data and correct data; Based on the learned models and features, a set of candidate verification rules are automatically generated. Based on the analysis and learning of historical data, the most appropriate verification rules are recommended according to the current input data features. Continue to learn from historical data, optimize recommended validation rules, and continuously update and iterate validation rules based on data changes to ensure the validity of validation rules and compliance with the latest data characteristics.

[0013] In a second aspect, the present invention provides an automated verification system based on a power grid data sharing center, the system comprising: A preprocessing module is used to preprocess the acquired power grid resource data, and to group and subpackage the preprocessed power grid resource data; A construction module is used to construct a verification rule library, match the verification rules to the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; A correction module is used to feedback and correct the problem data according to the results of the verification report; The monitoring and updating module is used to monitor the business rules and equipment type updates of the power grid in real time, make integrated adjustments to the resource verification rules of different equipment, and complete the update of the verification rule library.

[0014] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, characterized in that the one or more programs include instructions, which, when executed by a computing device, enable the computing device to perform any of the methods described.

[0015] In a third aspect, a computing device for an automated verification method based on a power grid data sharing center is provided, comprising: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods described.

[0016] The present invention is based on an automated verification method and system of a power grid data sharing center, which ensures the high quality of power grid data by performing multi-dimensional verification of power grid resource data, such as digital consistency verification, missing equipment in substations, flying points and flying lines, and abnormal number of access point meter boxes. At the same time, considering the changes in business rules and equipment types in power grid operation, the method supports integrated adjustment of rule-based verification rules to adapt to new operational needs and management strategies.

[0017] The present invention is based on an automated verification method and system of a power grid data sharing center. When performing data verification, the verification speed is improved through data classification and batch verification, and the adaptability of verification rules in the statistical verification process is convenient for updating the verification rules. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of the automated verification method based on the power grid data sharing center of the present invention; Figure 2 The block diagram of the automatic verification system based on the power grid data sharing center of the present invention. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the following Figure 1-2 The specific embodiments of the present invention are described in detail.

[0020] like Figure 1 As shown, an embodiment of the present invention provides an automated verification method based on a power grid data sharing center, the method comprising: Preprocessing the acquired power grid resource data, and performing grouping and subpackaging operations on the preprocessed power grid resource data; Build a verification rule library, match the verification rules for the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; Feedback the problem data and correct the problem data according to the results of the verification report; Monitor the business rules and equipment types of the power grid in real time, make integrated adjustments to the verification rules for different equipment resources, and complete the update of the verification rule library.

[0021] Among them, common verification rules include the following: Data-to-physical consistency check: By comparing the equipment data in the power grid data sharing center with the actual equipment status, check whether the data is consistent with the actual object; for example, by real-time monitoring of the equipment status, ensure that the power equipment status reflected in the data center is consistent with the actual operating status; Area equipment missing check: By comparing the known equipment list in the area with the actual equipment data, check whether there is equipment missing; for example, when the power facilities are updated, some equipment data may not be updated in time, resulting in data missing; Flying point and flying line verification: refers to the connection errors or equipment disconnection of power equipment in the power grid, which causes the system to fail to operate normally. Flying point and flying line verification can identify abnormal connection relationships in the data and indicate possible connection problems. Abnormal check of the number of access point meter boxes: In the power grid data, the number of access point meter boxes is usually fixed. If the number of access point meter boxes does not match the preset rules, it means that there may be equipment failure or data error.

[0022] As a further solution of this embodiment, the preprocessing includes data cleaning to remove duplicate, invalid or missing records; The preprocessing also includes identifying the data type of the power grid resource data, using a preset marking rule to type-mark the power grid resource data after data cleaning according to the data type, grouping the power grid resource data according to the type marking, and using the same verification rule to verify the power grid resource data in the same group. After grouping, the power grid resource data of each group is packaged to ensure that the number of data to be verified in each package is within a preset number threshold; The preset marking rule is specifically: the power grid resource data that is verified by the same verification rule is marked with the same type.

[0023] As a further solution of this embodiment, before performing the subpackaging operation on each group of power grid resource data, the number m of the power grid resource data of the nth group to be subpacked is obtained, and the number of packets into which the power grid resource data of the nth group to be subpacked needs to be divided is calculated. The specific calculation formula is as follows:

[0024] in, is the preset quantity threshold, is the number of packets into which the nth group of power grid resource data is finally divided, for The minimum value of is a natural number, is the number of power grid resource data in each packet, The number of power grid resource data in the packet is The number of packets.

[0025] Indicates taking The integer part of the quotient of .

[0026] As a further solution of this embodiment, the pre-processed power grid resource data is matched with verification rules, and the corresponding verification rules are selected from the verification rule library to automatically perform data verification and generate a verification report, which specifically includes: Perform verification rule matching on the power grid resource data after the grouping operation, select the corresponding verification rule from the verification rule library, and complete the verification rule confirmation; Using the confirmed verification rules, batch verification is performed on the power grid resource data in each package in the group in turn, and the verification time used to complete the verification process for each package and the amount of power grid resource data in the processed package are recorded; After the verification process, a verification report is generated, wherein the verification report includes the type, location, specific problem of the abnormal data and correction suggestions; For problematic data found in the verification report, the operation and maintenance personnel can make corrections based on the suggestions, and the corrected data will be re-entered into the system for verification until the verification result passes.

[0027] As a further solution of this embodiment, after the verification and correction processing, the verification results and the correction results are analyzed, specifically including: Integrate the problem data of the power grid resource data in the same group, classify and count the problem data of the group according to the problem type, and draw a statistical chart of the problem data of the group; Analyze the number of each question type in the group of question data according to the question data statistical chart, and mark the question types whose number is greater than or equal to the preset standard number as common question types; Record the correction process of each common problem type, count the number of corrections from the problem data of each problem type to the verification result passing, and summarize the correction experience of the problem data of each problem type; The problem data in each package is corrected until the number of corrections that pass the verification result exceeds the preset standard number, and then marked. If the number of marks that exceed the preset standard number is greater than or equal to the preset standard number of marks, the verification rules used to correct the problem data are updated.

[0028] As a further solution of this embodiment, the real-time monitoring of the business rules and equipment types of the power grid is updated, and the integrated adjustment of the verification rules of different equipment resources is performed to complete the update of the verification rule base. The specific process is as follows: All verification rules are stored in the verification rule base, which is dynamically added, deleted, modified and checked according to actual needs; When new equipment is put into use, corresponding verification rules can be added according to the characteristics of the new equipment; As the grid operation mode changes, the system automatically adjusts data verification rules according to business needs to ensure the perfection of verification work in new business scenarios; According to the actual situation of the power grid operation, the verification rules that match the current environment are automatically selected. If new equipment types or new operating modes appear, the appropriate verification rules are actively learned based on historical data and recommended.

[0029] As a further solution of this embodiment, the appropriate verification rules are actively learned and recommended based on historical data. The specific process is as follows: Collect and organize historical data, determine the validity of historical data, and identify the distribution pattern of historical data; Specifically, the system will first collect and organize historical data, which may come from different sources, such as user input data, logs, business process data, etc.; the original data may contain missing values, noise or irrelevant information. The system will ensure data quality through cleaning and preprocessing steps, such as removing duplicate data, filling missing values, and data normalization; At the same time, based on the type and structure of the data, the system will select and extract important features; for example, time, location, category, value range, etc. These features can help the system determine the validity of the data; the system will perform statistical analysis on these features to identify the distribution pattern of the data; for example, identify which values ​​are common, which are abnormal, and which conform to a certain pattern; Analyze historical data, identify the verification rules that have been used, and learn and identify the verification rules that can improve data quality among the verification rules that have been used through the labeled samples of historical data, which include erroneous data and correct data; specifically, the system identifies the verification rules that have been used, such as length verification, type verification, range verification, etc., by analyzing historical data; if machine learning technology is used, the system will model based on supervised learning or unsupervised learning methods; through the labeled samples in the historical data (such as erroneous data and correct data), the system learns to identify which verification rules can improve data quality; the system trains the model through the existing labeled data (such as "legal" and "illegal" data samples) to predict the legitimacy of the data; for unlabeled data, the system identifies possible error patterns or data structures through clustering, anomaly detection and other methods; Based on the learned models and features, a set of candidate verification rules are automatically generated. Based on the analysis and learning of historical data, the most appropriate verification rules are recommended according to the current input data features. Specifically, the system automatically generates a set of candidate verification rules based on the learned models and features. These rules can be based on traditional verification methods (such as regular expressions) or rules based on model inference (such as outlier detection). Based on the analysis and learning of historical data, the system will recommend the most appropriate verification rules according to the current input data features. The recommended rules usually take into account the accuracy of the rules and the adaptability of the data to ensure the effectiveness of the rules. At the same time, the system will verify the effectiveness of the recommended validation rules in actual operation and evaluate their performance in actual data. For example, it will verify whether the rules can accurately identify erroneous data through automated testing or manual review. When users or the system find that certain rules are invalid or inaccurate, they can provide feedback. The system will further learn and optimize based on this feedback, and gradually adjust and improve the recommended rules. Continuously learn from historical data, optimize recommended validation rules, and continuously update and iterate validation rules according to data changes to ensure the validity of validation rules and conformity to the latest data characteristics. Specifically, as data increases and business changes, the system will continue to learn from historical data and optimize recommended validation rules; machine learning models will be updated regularly to adapt to new data patterns and changes in demand; recommended validation rules are not static, and the system will continuously update and iterate rules according to data changes to ensure that they are always valid and conform to the latest data characteristics.

[0030] Automated verification methods can help operation and maintenance personnel detect equipment status in real time, discover potential fault hazards, and take timely measures to reduce the occurrence of power outages and failures; improved data quality is helpful for subsequent analysis, scheduling decisions and power grid planning; for example, when the power grid is expanded or migrated, accurate data can greatly improve the accuracy of planning; as equipment is continuously upgraded, old equipment may be replaced by new equipment. Automated verification can detect data changes in a timely manner to ensure the consistency of the configuration and data of the new equipment.

[0031] In summary, the automated verification method based on the power grid data sharing center can effectively improve the quality of power grid data and ensure the consistency, integrity and accuracy of the data. Through flexible verification rules and dynamic adjustment mechanisms, it can cope with the ever-changing business needs and equipment types of the power grid, and provide strong guarantees for the safe operation and intelligent management of the power grid. With the advancement of technology and the continuous growth of power grid management needs, further improving this verification method will become an important means to improve power grid operation efficiency and reduce operation and maintenance costs.

[0032] like Figure 2 As shown, another embodiment of the present invention provides an automatic verification system based on a power grid data sharing center, the system comprising: A preprocessing module is used to preprocess the acquired power grid resource data, and to group and subpackage the preprocessed power grid resource data; A construction module is used to construct a verification rule library, match the verification rules to the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; A correction module is used to feedback and correct the problem data according to the results of the verification report; The monitoring and updating module is used to monitor the business rules and equipment types of the power grid in real time, perform integrated adjustment of the verification rules of different equipment resources, and complete the update of the verification rule library. The present invention can be a system, method and / or computer program product. The computer program product can include a computer-readable storage medium on which computer-readable program instructions are loaded for causing a processor to implement various aspects of the present invention.

[0033] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. The computer-readable storage medium used herein is not to be interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0034] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0035] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

[0036] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention, and these changes and modifications will fall within the protection scope of the present invention.

Claims

1. An automated verification method based on a power grid data sharing center, characterized in that: The method comprises: Preprocessing the acquired power grid resource data, and performing grouping and subpackaging operations on the preprocessed power grid resource data; Build a verification rule library, match the verification rules for the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; Feedback the problem data and correct the problem data according to the results of the verification report; Monitor the business rules and equipment types of the power grid in real time, make integrated adjustments to the verification rules for different equipment resources, and complete the update of the verification rule library.

2. The automated verification method based on the power grid data sharing center according to claim 1 is characterized in that: The preprocessing includes data cleaning to remove duplicate, invalid or missing records; The preprocessing also includes identifying the data type of the power grid resource data, using a preset marking rule to type-mark the power grid resource data after data cleaning according to the data type, grouping the power grid resource data according to the type marking, and using the same verification rule to verify the power grid resource data in the same group. After grouping, the power grid resource data of each group is packaged to ensure that the number of data to be verified in each package is within a preset number threshold; The preset marking rule is specifically: the power grid resource data that is verified by the same verification rule is marked with the same type.

3. The automated verification method based on the power grid data sharing center according to claim 2 is characterized in that: Before performing the subpackaging operation on each group of power grid resource data, the number m of the power grid resource data of the nth group to be subpacked is obtained, and the number of packets into which the power grid resource data of the nth group to be subpacked needs to be divided is calculated. The specific calculation formula is as follows: ， in, is the preset quantity threshold, is the number of packets into which the nth group of power grid resource data is finally divided, for The minimum value of is a natural number, is the number of power grid resource data in each packet, The number of power grid resource data in the packet is The number of packets.

4. The automated verification method based on the power grid data sharing center according to claim 3 is characterized in that: The pre-processed power grid resource data is matched with verification rules, and the corresponding verification rules are selected from the verification rule library to automatically verify the data and generate a verification report, including: Perform verification rule matching on the power grid resource data after the grouping operation, select the corresponding verification rule from the verification rule library, and complete the verification rule confirmation; Using the confirmed verification rules, batch verification is performed on the power grid resource data in each package in the group in turn, and the verification time used to complete the verification process for each package and the amount of power grid resource data in the processed package are recorded; After the verification process, a verification report is generated, wherein the verification report includes the type, location, specific problem of the abnormal data and correction suggestions; For problematic data found in the verification report, the operation and maintenance personnel can make corrections based on the suggestions, and the corrected data will be re-entered into the system for verification until the verification result passes.

5. The automated verification method based on the power grid data sharing center according to claim 4 is characterized in that: After the verification and correction process, the verification and correction results are analyzed, including: Integrate the problem data of the power grid resource data in the same group, classify and count the problem data of the group according to the problem type, and draw a statistical chart of the problem data of the group; Analyze the number of each question type in the group of question data according to the question data statistical chart, and mark the question types whose number is greater than or equal to the preset standard number as common question types; Record the correction process of each common problem type, count the number of corrections from the problem data of each problem type to the verification result passing, and summarize the correction experience of the problem data of each problem type; The problem data in each package is corrected until the number of corrections that pass the verification result exceeds the preset standard number, and then marked. If the number of marks that exceed the preset standard number is greater than or equal to the preset standard number of marks, the verification rules used to correct the problem data are updated.

6. The automated verification method based on the power grid data sharing center according to claim 1 is characterized in that: The real-time monitoring of the business rules and equipment types of the power grid is updated, and the integrated adjustment of the verification rules of different equipment resources is performed to complete the update of the verification rule library. The specific process is as follows: All verification rules are stored in the verification rule library, which is dynamically added, deleted, modified and checked according to actual needs; When new equipment is put into use, corresponding verification rules can be added according to the characteristics of the new equipment; As the grid operation mode changes, the system automatically adjusts data verification rules according to business needs to ensure the perfection of verification work in new business scenarios; According to the actual situation of the power grid operation, the verification rules that match the current environment are automatically selected. If new equipment types or new operating modes appear, the appropriate verification rules are actively learned based on historical data and recommended.

7. The automated verification method based on the power grid data sharing center according to claim 6 is characterized in that: Actively learn and recommend appropriate verification rules based on historical data. The specific process is as follows: Collect and organize historical data, determine the validity of historical data, and identify the distribution patterns of historical data; Analyze historical data, identify verification rules that have been used, and learn and identify verification rules that can improve data quality among the used verification rules through annotated samples of historical data, the annotated samples including erroneous data and correct data; Based on the learned models and features, a set of candidate verification rules are automatically generated. Based on the analysis and learning of historical data, the most appropriate verification rules are recommended according to the current input data features. Continue to learn from historical data, optimize recommended validation rules, and continuously update and iterate validation rules based on data changes to ensure that the validation rules are effective and in line with the latest data characteristics.

8. An automated verification system based on a power grid data sharing center, characterized in that: The system comprises: A preprocessing module is used to preprocess the acquired power grid resource data, and to group and subpackage the preprocessed power grid resource data; A construction module is used to construct a verification rule library, match the verification rules to the pre-processed power grid resource data, select the corresponding verification rules from the verification rule library to automatically verify the data, and generate a verification report; A correction module is used to feedback and correct the problem data according to the results of the verification report; The monitoring and updating module is used to monitor the business rules and equipment type updates of the power grid in real time, make integrated adjustments to the resource verification rules of different equipment, and complete the update of the verification rule library.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions which, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1-7.

10. A computing device based on an automated verification method of a power grid data sharing center, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods according to claims 1-7.

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