A power grid data sharing and real-time monitoring method

Abstract

The application relates to the technical field of data processing, and discloses a power grid data sharing and real-time monitoring method and device, which comprises the following steps: performing target processing operation on acquired multi-source heterogeneous data to obtain processed heterogeneous data; when a sharing instruction of the processed heterogeneous data is received, performing sharing processing on the processed heterogeneous data according to the sharing instruction; in the process of the sharing processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated according to the calling parameters, so that the monitoring information is sent to a monitoring object of the processed heterogeneous data. In this way, the multi-source heterogeneous data can be first processed, and then the sharing and monitoring process of the processed heterogeneous data can be realized, the processing reliability and accuracy of the multi-source heterogeneous data are improved, the transmission timeliness and accuracy of the multi-source heterogeneous data are improved, and therefore the adaptation capability between the multi-source heterogeneous data and multiple terminals is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method for power grid data sharing and real-time monitoring. Background Technology

[0002] In the process of power grid digital transformation, data sharing and real-time monitoring are core components supporting business decision-making and improving operational efficiency. Currently, existing power grid system data is scattered across independent modules in multiple business domains, lacking a unified standardized governance system. This results in inconsistent data formats, significant barriers to cross-system sharing, and difficulties in achieving efficient circulation and reuse. Simultaneously, existing data monitoring methods are limited to a single dimension, and data quality inspection relies on manual intervention, making it impossible to fully guarantee the timeliness and accuracy of data transmission. Furthermore, the system's concurrency capacity is limited, easily experiencing response delays when facing large-scale user access, and its multi-terminal adaptability is poor, failing to meet the needs of personnel at all levels to grasp the business status in real time, severely restricting the level of precision in power grid digital operation. Therefore, proposing a new method for power grid data sharing and real-time monitoring is particularly important. Summary of the Invention

[0003] This invention provides a method and apparatus for power grid data sharing and real-time monitoring, which improves the reliability and accuracy of processing multi-source heterogeneous data, thereby improving the timeliness and accuracy of multi-source heterogeneous data transmission, and thus helps to improve the adaptability of multi-source heterogeneous data with multiple terminals.

[0004] To address the aforementioned technical problems, the first aspect of this invention discloses a method for power grid data sharing and real-time monitoring, the method comprising: Acquire multi-source heterogeneous data under preset power grid business scenarios; the multi-source heterogeneous data includes power grid operation data, equipment status data, user behavior data, and system operation data; The multi-source heterogeneous data is subjected to target processing operations to obtain processed heterogeneous data; When a sharing instruction for the processed heterogeneous data is received, the processed heterogeneous data is shared according to the sharing instruction; During the shared processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated based on the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

[0005] As an optional implementation, in the first aspect of the present invention, the target processing operation on the multi-source heterogeneous data to obtain processed heterogeneous data includes: The system acquires anomalies in the multi-source heterogeneous data and performs cleaning operations on the multi-source heterogeneous data based on the anomalies to obtain cleaned heterogeneous data. The anomalies include at least one of fluctuation anomalies, field missing anomalies, and data duplication anomalies. The cleaning operations include at least one of data filtering operations, data interpolation and completion operations, and deduplication and merging operations. The scene access parameters of the cleaned heterogeneous data are obtained, and the cleaned heterogeneous data is standardized according to the scene access parameters to obtain standardized heterogeneous data; the scene access parameters include at least one of scene access type parameters, scene access time parameters, and scene access unit parameters. Obtain the desensitization information of the standardized heterogeneous data, and desensitize the standardized heterogeneous data according to the desensitization information to obtain desensitized heterogeneous data; The desensitized heterogeneous data is subjected to a target enhancement operation to obtain enhanced heterogeneous data, which is used as processed heterogeneous data.

[0006] As an optional implementation, in the first aspect of the present invention, the step of performing a target enhancement operation on the desensitized heterogeneous data to obtain enhanced heterogeneous data includes: The target link parameters of the desensitized heterogeneous data are obtained, and based on the target link parameters, forward and reverse lineage penetration operations are performed on the desensitized heterogeneous data to obtain the forward and reverse lineage relationship parameters of the desensitized heterogeneous data; the target link parameters include generation link parameters, processing link parameters, flow link parameters and application link parameters; The lineage extension element parameters of the anonymized heterogeneous data are obtained, and lineage extension operations are performed on the anonymized heterogeneous data according to the forward and reverse lineage relationship parameters and the lineage extension element parameters to obtain the extended lineage relationship parameters of the anonymized heterogeneous data; the lineage extension element parameters include at least one of the following: business scenario element parameters, data governance requirement element parameters, security requirement element parameters, system operation and maintenance element parameters, and value mining element parameters; Based on the extended bloodline parameters, a multi-dimensional association operation is performed on the desensitized heterogeneous data to obtain associated heterogeneous data. Then, based on the preset quality inspection requirements parameters, the associated heterogeneous data is inspected to obtain the quality inspection results of the associated heterogeneous data. When the quality inspection result indicates that the correlated heterogeneous data has passed the quality inspection, the correlated heterogeneous data is identified as enhanced heterogeneous data. When the quality inspection result indicates that the associated heterogeneous data fails the quality inspection, the associated heterogeneous data is identified as the de-identified heterogeneous data, and the operation of obtaining the target link parameters of the de-identified heterogeneous data is triggered.

[0007] As an optional implementation, in the first aspect of the present invention, the step of performing sharing processing on the processed heterogeneous data according to the sharing instructions includes: The shared instruction is parsed to obtain the instruction parsing parameters corresponding to the shared instruction; the instruction parsing parameters include at least one of the following: shared data identifier parameters, shared object parameters, shared scope parameters, shared duration parameters, and shared purpose parameters; Based on the instruction parsing parameters, the sharing type of the processed heterogeneous data is determined, and according to the sharing type, matching permission control operations are performed on the processed heterogeneous data; the sharing type includes internal platform sharing type or cross-system integration sharing type; After completing the access control operation, the security protection requirements parameters of the processed heterogeneous data are determined according to the instruction parsing parameters, and the security protection processing operation is performed on the processed heterogeneous data according to the security protection requirements parameters; the security protection requirements parameters include at least one of the following: data transmission encryption requirements parameters, access control hardening requirements parameters, and sensitive field protection requirements parameters. After completing the security protection processing operation, the processed heterogeneous data is shared and transmitted.

[0008] As an optional implementation, in the first aspect of the present invention, the step of performing matching permission control operations on the processed heterogeneous data according to the sharing type includes: When the sharing type includes the internal platform sharing type, determine the unit-level permission parameters and role-level permission parameters of the processed heterogeneous data, and determine the accessible data range of the processed heterogeneous data based on the unit-level permission parameters and role-level permission parameters. Based on the instruction parsing parameters and the accessible data range, determine the usage permission display parameters that match the sharing type of the internal platform, and perform differentiated display control operations on the processed heterogeneous data according to the usage permission display parameters; the usage permission display parameters include at least one of scenario development permission display parameters, report generation permission display parameters, and business decision-making permission display parameters. When the sharing type includes the cross-system integration sharing type, a temporary access permission parameter for the processed heterogeneous data is determined, and a temporary access token for the processed heterogeneous data is generated based on the temporary access permission parameter, so as to bind the temporary access token to the access authorization credential of the third-party sharing system of the processed heterogeneous data; the temporary access permission parameter includes at least one of a temporary access duration parameter, a temporary access data range parameter, and a temporary access operation permission parameter. After the binding is completed, the data integration method of the processed heterogeneous data is determined according to the instruction parsing parameters, and the data fields of the processed heterogeneous data and the third-party shared system are mapped and configured according to the data integration method.

[0009] As an optional implementation, in the first aspect of the present invention, the calling parameters of the processed heterogeneous data include calling subject parameters, calling content, calling status parameters, calling frequency parameters, and calling response parameters; The step of generating monitoring information for the processed heterogeneous data based on the calling parameters includes: Obtain the shared system resource status parameters of the processed heterogeneous data; the shared system resource status parameters include server CPU utilization, memory utilization, network bandwidth utilization, database connection count, and interface gateway request forwarding efficiency parameters; Obtain the shared quality parameters of the processed heterogeneous data; the shared quality parameters include data integrity compliance rate, data timeliness compliance rate, and abnormal data processing progress parameters. Based on the calling parameters, the shared system resource status parameters, and the shared quality parameters, monitoring information for the processed heterogeneous data is generated.

[0010] As an optional implementation, in the first aspect of the present invention, generating monitoring information for the processed heterogeneous data based on the calling parameters, the shared system resource status parameters, and the shared quality parameters includes: Obtain preset monitoring dimension configuration parameters, and based on the monitoring dimension configuration parameters, perform correlation and integration operations on the calling parameters, the shared system resource status parameters, and the shared quality parameters to obtain multi-dimensional integrated parameters; Obtain preset monitoring threshold parameters, and perform anomaly identification operation on the multidimensional integrated parameters according to the monitoring threshold parameters to obtain the anomaly identification result of the multidimensional integrated parameters; the anomaly identification result includes anomaly type parameters, anomaly level parameters, and anomaly associated node parameters; Based on the multidimensional integration parameters and the anomaly identification results, multi-type monitoring information of the multidimensional integration parameters is generated as monitoring information of the processed heterogeneous data; the multi-type monitoring information includes at least one of global overview monitoring information, traceability monitoring information, anomaly early warning monitoring information, and trend statistics monitoring information.

[0011] A second aspect of this invention discloses a method and apparatus for power grid data sharing and real-time monitoring, the apparatus comprising: The acquisition module is used to acquire multi-source heterogeneous data under a preset power grid business scenario; the multi-source heterogeneous data includes power grid operation data, equipment status data, user behavior data, and system operation data; The target processing module is used to perform target processing operations on the multi-source heterogeneous data to obtain processed heterogeneous data. A sharing processing module is used to perform sharing processing on the processed heterogeneous data according to the sharing instruction when a sharing instruction for the processed heterogeneous data is received. The monitoring module is used to monitor the calling parameters of the processed heterogeneous data in real time during the shared processing process of the shared processing module, and generate monitoring information of the processed heterogeneous data according to the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

[0012] As an optional implementation, in the second aspect of the present invention, the target processing module performs target processing operations on the multi-source heterogeneous data to obtain processed heterogeneous data in the following specific ways: The system acquires anomalies in the multi-source heterogeneous data and performs cleaning operations on the multi-source heterogeneous data based on the anomalies to obtain cleaned heterogeneous data. The anomalies include at least one of fluctuation anomalies, field missing anomalies, and data duplication anomalies. The cleaning operations include at least one of data filtering operations, data interpolation and completion operations, and deduplication and merging operations. The scene access parameters of the cleaned heterogeneous data are obtained, and the cleaned heterogeneous data is standardized according to the scene access parameters to obtain standardized heterogeneous data; the scene access parameters include at least one of scene access type parameters, scene access time parameters, and scene access unit parameters. Obtain the desensitization information of the standardized heterogeneous data, and desensitize the standardized heterogeneous data according to the desensitization information to obtain desensitized heterogeneous data; The desensitized heterogeneous data is subjected to a target enhancement operation to obtain enhanced heterogeneous data, which is used as processed heterogeneous data.

[0013] As an optional implementation, in a second aspect of the present invention, the target processing module performs target enhancement operations on the de-identified heterogeneous data to obtain enhanced heterogeneous data, specifically including: The target link parameters of the desensitized heterogeneous data are obtained, and based on the target link parameters, forward and reverse lineage penetration operations are performed on the desensitized heterogeneous data to obtain the forward and reverse lineage relationship parameters of the desensitized heterogeneous data; the target link parameters include generation link parameters, processing link parameters, flow link parameters and application link parameters; The lineage extension element parameters of the anonymized heterogeneous data are obtained, and lineage extension operations are performed on the anonymized heterogeneous data according to the forward and reverse lineage relationship parameters and the lineage extension element parameters to obtain the extended lineage relationship parameters of the anonymized heterogeneous data; the lineage extension element parameters include at least one of the following: business scenario element parameters, data governance requirement element parameters, security requirement element parameters, system operation and maintenance element parameters, and value mining element parameters; Based on the extended bloodline parameters, a multi-dimensional association operation is performed on the desensitized heterogeneous data to obtain associated heterogeneous data. Then, based on the preset quality inspection requirements parameters, the associated heterogeneous data is inspected to obtain the quality inspection results of the associated heterogeneous data. When the quality inspection result indicates that the correlated heterogeneous data has passed the quality inspection, the correlated heterogeneous data is identified as enhanced heterogeneous data. When the quality inspection result indicates that the associated heterogeneous data fails the quality inspection, the associated heterogeneous data is identified as the de-identified heterogeneous data, and the operation of obtaining the target link parameters of the de-identified heterogeneous data is triggered.

[0014] As an optional implementation, in a second aspect of the present invention, the method by which the sharing processing module performs sharing processing on the processed heterogeneous data according to the sharing instruction specifically includes: The shared instruction is parsed to obtain the instruction parsing parameters corresponding to the shared instruction; the instruction parsing parameters include at least one of the following: shared data identifier parameters, shared object parameters, shared scope parameters, shared duration parameters, and shared purpose parameters; Based on the instruction parsing parameters, the sharing type of the processed heterogeneous data is determined, and according to the sharing type, matching permission control operations are performed on the processed heterogeneous data; the sharing type includes internal platform sharing type or cross-system integration sharing type; After completing the access control operation, the security protection requirements parameters of the processed heterogeneous data are determined according to the instruction parsing parameters, and the security protection processing operation is performed on the processed heterogeneous data according to the security protection requirements parameters; the security protection requirements parameters include at least one of the following: data transmission encryption requirements parameters, access control hardening requirements parameters, and sensitive field protection requirements parameters. After completing the security protection processing operation, the processed heterogeneous data is shared and transmitted.

[0015] As an optional implementation, in the second aspect of the present invention, the method by which the sharing processing module performs matching permission control operations on the processed heterogeneous data according to the sharing type specifically includes: When the sharing type includes the internal platform sharing type, determine the unit-level permission parameters and role-level permission parameters of the processed heterogeneous data, and determine the accessible data range of the processed heterogeneous data based on the unit-level permission parameters and role-level permission parameters. Based on the instruction parsing parameters and the accessible data range, determine the usage permission display parameters that match the sharing type of the internal platform, and perform differentiated display control operations on the processed heterogeneous data according to the usage permission display parameters; the usage permission display parameters include at least one of scenario development permission display parameters, report generation permission display parameters, and business decision-making permission display parameters. When the sharing type includes the cross-system integration sharing type, a temporary access permission parameter for the processed heterogeneous data is determined, and a temporary access token for the processed heterogeneous data is generated based on the temporary access permission parameter, so as to bind the temporary access token to the access authorization credential of the third-party sharing system of the processed heterogeneous data; the temporary access permission parameter includes at least one of a temporary access duration parameter, a temporary access data range parameter, and a temporary access operation permission parameter. After the binding is completed, the data integration method of the processed heterogeneous data is determined according to the instruction parsing parameters, and the data fields of the processed heterogeneous data and the third-party shared system are mapped and configured according to the data integration method.

[0016] As an optional implementation, in the second aspect of the present invention, the calling parameters of the processed heterogeneous data include calling subject parameters, calling content, calling status parameters, calling frequency parameters, and calling response parameters; Specifically, the monitoring module generates monitoring information for the processed heterogeneous data based on the calling parameters in the following ways: Obtain the shared system resource status parameters of the processed heterogeneous data; the shared system resource status parameters include server CPU utilization, memory utilization, network bandwidth utilization, database connection count, and interface gateway request forwarding efficiency parameters; Obtain the shared quality parameters of the processed heterogeneous data; the shared quality parameters include data integrity compliance rate, data timeliness compliance rate, and abnormal data processing progress parameters. Based on the calling parameters, the shared system resource status parameters, and the shared quality parameters, monitoring information for the processed heterogeneous data is generated.

[0017] As an optional implementation, in a second aspect of the present invention, the monitoring module generates monitoring information for the processed heterogeneous data based on the calling parameters, the shared system resource status parameters, and the shared quality parameters, specifically including: Obtain preset monitoring dimension configuration parameters, and based on the monitoring dimension configuration parameters, perform correlation and integration operations on the calling parameters, the shared system resource status parameters, and the shared quality parameters to obtain multi-dimensional integrated parameters; Obtain preset monitoring threshold parameters, and perform anomaly identification operation on the multidimensional integrated parameters according to the monitoring threshold parameters to obtain the anomaly identification result of the multidimensional integrated parameters; the anomaly identification result includes anomaly type parameters, anomaly level parameters, and anomaly associated node parameters; Based on the multidimensional integration parameters and the anomaly identification results, multi-type monitoring information of the multidimensional integration parameters is generated as monitoring information of the processed heterogeneous data; the multi-type monitoring information includes at least one of global overview monitoring information, traceability monitoring information, anomaly early warning monitoring information, and trend statistics monitoring information.

[0018] A third aspect of the present invention discloses another method and apparatus for power grid data sharing and real-time monitoring, the apparatus comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute a power grid data sharing and real-time monitoring method disclosed in the first aspect of the present invention.

[0019] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute a power grid data sharing and real-time monitoring method disclosed in the first aspect of the present invention.

[0020] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: In this embodiment of the invention, target processing is performed on the acquired multi-source heterogeneous data to obtain processed heterogeneous data. When a sharing instruction for the processed heterogeneous data is received, sharing processing is performed on the processed heterogeneous data according to the sharing instruction. During the sharing processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated based on the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data. In this way, target processing of multi-source heterogeneous data can be performed first, and then the sharing and monitoring process of processed heterogeneous data can be realized, which improves the reliability and accuracy of processing multi-source heterogeneous data, thereby improving the timeliness and accuracy of transmission of multi-source heterogeneous data, and thus helping to improve the adaptability of multi-source heterogeneous data with multiple terminals. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used 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 those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a power grid data sharing and real-time monitoring method disclosed in an embodiment of the present invention; Figure 2 This is a flowchart illustrating another power grid data sharing and real-time monitoring method disclosed in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a power grid data sharing and real-time monitoring method and apparatus disclosed in an embodiment of the present invention; Figure 4 This is a schematic diagram of another power grid data sharing and real-time monitoring method and apparatus disclosed in an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] This invention discloses a method and apparatus for power grid data sharing and real-time monitoring, which improves the reliability and accuracy of processing multi-source heterogeneous data, thereby improving the timeliness and accuracy of multi-source heterogeneous data transmission, and thus helps to improve the adaptability of multi-source heterogeneous data with multiple terminals.

[0027] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating a power grid data sharing and real-time monitoring method disclosed in an embodiment of the present invention. Optionally, this method can be implemented by a data sharing and monitoring device, which can be integrated into a host computer (such as a smart computer, smartphone, data sharing and monitoring platform, etc.), or it can be a local server or cloud server used to process the power grid data sharing and real-time monitoring process, etc. The embodiments of the present invention do not impose limitations. Figure 1 As shown, this method for power grid data sharing and real-time monitoring may include the following operations: 101. Obtain multi-source heterogeneous data under preset power grid business scenarios.

[0028] In this embodiment of the invention, the multi-source heterogeneous data specifically includes power grid operation data, equipment status data, user behavior data, and system operation data. Specifically, power grid operation data includes at least one of the following: power load data, power transmission data, power quality data, and dispatch operation data; equipment status data includes at least one of the following: transmission and transformation equipment data, distribution equipment data, equipment maintenance data, and infrared temperature measurement data; user behavior data includes at least one of the following: login access data (such as user ID, login time, login IP, login terminal, etc.), scenario operation data, data interaction data (such as the type of data called, frequency of indicator viewing, data download volume, sharing application records, etc.), and feedback behavior data; and system operation data includes at least one of the following: hardware resource data, software service data, security operation data, and log monitoring data.

[0029] 102. Perform target processing operations on multi-source heterogeneous data to obtain processed heterogeneous data.

[0030] In this embodiment of the invention, further, target processing operations are performed on the multi-source heterogeneous data to obtain processed heterogeneous data, including: Obtain anomalies in multi-source heterogeneous data, and perform cleaning operations on the multi-source heterogeneous data based on the anomalies to obtain cleaned heterogeneous data; Obtain the scene access parameters of the cleaned heterogeneous data, and perform standardization operations on the cleaned heterogeneous data according to the scene access parameters to obtain standardized heterogeneous data. Obtain the anonymization information of the standardized heterogeneous data, and anonymize the standardized heterogeneous data according to the anonymization information to obtain the anonymized heterogeneous data; Target augmentation is performed on the desensitized heterogeneous data to obtain augmented heterogeneous data, which is then used as processed heterogeneous data.

[0031] In this optional embodiment, the abnormal situation may include at least one of the following: fluctuation abnormal situation, field missing situation, and data duplication situation; and the cleaning operation may include at least one of the following: data filtering operation, data interpolation and completion operation, and deduplication and merging operation.

[0032] Further optionally, the scene access parameters include at least one of the following: scene access type parameter, scene access time parameter, and scene access unit parameter.

[0033] In this optional embodiment, further, a target augmentation operation is performed on the desensitized heterogeneous data to obtain augmented heterogeneous data, including: Obtain the target link parameters of the desensitized heterogeneous data, and perform forward and reverse lineage penetration operations on the desensitized heterogeneous data based on the target link parameters to obtain the forward and reverse lineage relationship parameters of the desensitized heterogeneous data. Obtain the bloodline extension element parameters of the desensitized heterogeneous data, and perform bloodline extension operation on the desensitized heterogeneous data based on the forward and reverse bloodline relationship parameters and the bloodline extension element parameters to obtain the extended bloodline relationship parameters of the desensitized heterogeneous data. Based on the extended bloodline parameters, multi-dimensional association operations are performed on the desensitized heterogeneous data to obtain the associated heterogeneous data. Then, based on the preset quality inspection requirements parameters, the quality inspection results of the associated heterogeneous data are obtained. When the quality inspection results indicate that the correlated heterogeneous data has passed the quality inspection, the correlated heterogeneous data will be identified as the enhanced heterogeneous data. When the quality inspection result indicates that the associated heterogeneous data fails the quality inspection, the associated heterogeneous data is identified as de-identified heterogeneous data, and the operation of obtaining the target link parameters of the de-identified heterogeneous data is triggered.

[0034] In this optional embodiment, specifically, the target link parameters include generating link parameters, processing link parameters, transferring link parameters, and applying link parameters.

[0035] Optionally, the lineage extension element parameters include at least one of the following: business scenario element parameters (such as the business scenarios involved in data monitoring and display, assessment and evaluation, digital innovation, etc.), data governance requirement element parameters (such as the verification rules that data must follow, the anomaly handling process, etc.), security requirement element parameters (such as permission and access control requirements, compliance audit requirements, and responsibility traceability requirements, etc.), system operation and maintenance element parameters (such as the data flow relationship between the cloud platform and third-party systems (4A system, IOS work order system), the servers, network resources, microservice modules that the data depends on, and the operation and maintenance work orders and rectification records corresponding to data anomalies, etc.), and value mining element parameters (such as data reuse requirements (citation frequency, reuse effect, etc.), optimization decision requirements (such as optimizing the correlation logic between line loss rate data and equipment failure rate, power supply data, etc.).

[0036] Optionally, the quality inspection requirement parameters may include at least one of the following: data integrity requirement parameters, data accuracy requirement parameters, data compliance requirement parameters, and data availability requirement parameters.

[0037] The lineage extension operation can be understood as follows: by using the lineage extension element parameters of anonymized heterogeneous data (which cover five dimensions: business scenarios, data governance, security requirements, system operation and maintenance, and value mining, clarifying the business purpose, compliance rules, permission requirements, technical dependencies, and reuse value of the data), and combining them with existing positive and negative lineage relationship parameters (such as the source, flow, and destination of the data), the extended elements are bound to the lineage link to complete the lineage extension operation. The final extended lineage relationship parameters not only contain the entire data flow trajectory but also associate multi-dimensional information such as business, security, and operation and maintenance, providing accurate basis for subsequent data sharing permission control, compliance verification, and anomaly tracing, thereby improving the refinement and compliance of power grid data management.

[0038] 103. When a sharing instruction for processed heterogeneous data is received, the processed heterogeneous data is shared according to the sharing instruction.

[0039] 104. During the shared processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated based on the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

[0040] In this embodiment of the invention, the calling parameters of the processed heterogeneous data specifically include calling subject parameters, calling content, calling status parameters, calling frequency parameters, and calling response parameters.

[0041] For example, firstly, the system acquires multi-source heterogeneous data under the preset "provincial power grid real-time monitoring" business scenario. Among them, power grid operation data includes 500kV line power flow distribution, line loss rate, etc.; equipment status data includes transmission line infrared temperature measurement data, transformer oil temperature and defect records, etc.; user behavior data includes the platform login trajectory and monitoring dashboard operation records of maintenance personnel at the municipal level; system operation data includes hardware resource status such as server CPU utilization and interface response time.

[0042] Then, the multi-source heterogeneous data is cleaned (e.g., removing abnormal fluctuation values ​​in load data), standardized (e.g., unifying timestamp format), de-identified (e.g., hiding sensitive information of operation and maintenance personnel), and enhanced: such as clarifying the collection source and downstream reporting application of multi-source heterogeneous data through forward and reverse lineage penetration, as well as related business scenarios, security permissions and other extended elements, so as to obtain qualified processed heterogeneous data after quality inspection.

[0043] Subsequently, upon receiving a "load data sharing application" instruction from the municipal power supply company, the system parses the instruction parameters, matches them with the municipal unit's permissions, and generates a temporary access token to complete the data field mapping, enabling shared data transmission. Simultaneously, during the sharing process, parameters such as the calling entity, calling content, calling status, calling frequency, and response time are monitored in real time, and information such as server CPU utilization and data integrity compliance rate are synchronously correlated, thereby generating a "Provincial Load Data Sharing Monitoring Briefing" and pushing it to the provincial company's operation and maintenance monitoring center, achieving traceability and monitoring of the entire data sharing process.

[0044] As can be seen, implementing the embodiments of the present invention can first perform target processing on multi-source heterogeneous data, and then realize the sharing and monitoring process of the processed heterogeneous data, thereby improving the reliability and accuracy of processing multi-source heterogeneous data, and further improving the timeliness and accuracy of transmission of multi-source heterogeneous data, which is conducive to improving the adaptability between multi-source heterogeneous data and multiple terminals.

[0045] Example 2 Please see Figure 2 , Figure 2 This is a flowchart illustrating another power grid data sharing and real-time monitoring method disclosed in an embodiment of the present invention. Optionally, this method can be implemented by a data sharing and monitoring device, which can be integrated into a host computer (such as a smart computer, smartphone, data sharing and monitoring platform, etc.), or it can be a local server or cloud server used to process the power grid data sharing and real-time monitoring process, etc. The embodiments of the present invention do not impose limitations. Figure 2 As shown, this method for power grid data sharing and real-time monitoring may include the following operations: 201. Obtain multi-source heterogeneous data under the preset power grid business scenario.

[0046] 202. Perform target processing operations on multi-source heterogeneous data to obtain processed heterogeneous data.

[0047] 203. When a shared instruction for processed heterogeneous data is received, the shared instruction is parsed to obtain the instruction parsing parameters corresponding to the shared instruction.

[0048] In this embodiment of the invention, optionally, the sharing instruction can be initiated manually by the user within the platform, triggered by an interface call, or requested through a third-party system integration request. Further optionally, the instruction parsing parameters include at least one of the following: shared data identifier parameters (such as data ID, data type identifier, business domain identifier, etc.), shared object parameters (such as the unit level initiating the sharing, third-party system, role, etc.), shared scope parameters (such as sharing all data, some fields, etc.), shared duration parameters (such as initiating permanent sharing, temporary sharing, etc.), and shared purpose parameters (such as initiating sharing for business decision-making, report generation, scenario development, etc.).

[0049] 204. Based on the command parsing parameters, determine the sharing type of the processed heterogeneous data, and perform matching permission control operations on the processed heterogeneous data according to the sharing type.

[0050] In this embodiment of the invention, the sharing type includes internal platform sharing type or cross-system integration sharing type.

[0051] 205. After completing the access control operation, determine the security protection requirements parameters of the processed heterogeneous data based on the instruction parsing parameters, and perform security protection processing operations on the processed heterogeneous data according to the security protection requirements parameters.

[0052] In this embodiment of the invention, the security protection requirements parameters may optionally include at least one of the following: data transmission encryption requirements parameters (such as using SSL / TLS protocol for encrypted transmission, encrypting data files for storage, etc.), access control hardening requirements parameters (such as implementing IP / URL access restrictions, allowing only authorized IP addresses or business modules to access shared data, so as to block unauthorized access), and sensitive field protection requirements parameters.

[0053] 206. After completing the security protection process, perform a shared transmission operation on the processed heterogeneous data.

[0054] 207. During the shared processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated based on the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

[0055] In this embodiment of the invention, for other descriptions of steps 201, 202 and 207, please refer to the detailed description of steps 101, 102 and 104 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0056] As can be seen, implementing the embodiments of the present invention enables the parsing of sharing instructions to determine the sharing type of processed heterogeneous data based on the instruction parsing parameters. Then, based on the sharing type, access control is applied to the processed heterogeneous data. After access control is completed, further security protection processing is applied to the processed heterogeneous data to achieve data sharing and transmission. This improves the reliability and accuracy of access control for processed heterogeneous data, and further enhances the security of shared transmission of processed heterogeneous data through data security protection processing, thereby effectively reducing the risk of data leakage and improving the precision of power grid operation management.

[0057] In an optional embodiment, step 204 above, which involves performing matching permission control operations on the processed heterogeneous data based on the sharing type, includes: When the sharing type includes the internal platform sharing type, determine the unit-level permission parameters and role-level permission parameters of the processed heterogeneous data, and determine the accessible data range of the processed heterogeneous data based on the unit-level permission parameters and role-level permission parameters. Based on the command parsing parameters and the range of accessible data, determine the usage permission display parameters that match the sharing type of the internal platform, and perform differentiated display control operations on the processed heterogeneous data according to the usage permission display parameters. When the sharing type includes cross-system integration sharing type, determine the temporary access permission parameters for the processed heterogeneous data, and generate a temporary access token for the processed heterogeneous data based on the temporary access permission parameters, so as to bind the temporary access token to the access authorization credential of the third-party sharing system for the processed heterogeneous data. After binding is completed, the data integration method of the processed heterogeneous data is determined according to the command parsing parameters, and the data fields of the processed heterogeneous data and the third-party shared system are mapped and configured according to the data integration method.

[0058] In this optional embodiment, the usage permission display parameters may optionally include at least one of scenario development permission display parameters, report generation permission display parameters, and business decision permission display parameters. Further optionally, the temporary access permission parameters may include at least one of temporary access duration parameters, temporary access data range parameters, and temporary access operation permission parameters.

[0059] For example, regarding internal platform sharing types, this differentiated display control operation can be understood as follows: If the permission display parameters for this purpose include scenario development permission display parameters, then the processed heterogeneous data will be mounted to the authorized dataset list of the platform's scenario development center, and data interface call permissions will be opened. Simultaneously, a data lineage graph, field description documents, and example call code will be provided, thereby supporting developers to directly customize business scenario development based on this data, while retaining data usage traceability identifiers to ensure the data source of the development scenario is traceable. If the permission display parameters for this purpose include report generation permission display parameters, then according to the sharing scope parameter in the instruction parsing parameters, export permissions for the corresponding data fields will be opened to support... It supports exporting data in multiple formats such as CSV, Excel, and JSON, and automatically generates report templates to adapt to the data structure. For example, it adapts load data into daily / weekly / monthly report templates and limits the maximum amount of data exported in a single batch (default ≤ 100,000 records) to reduce the consumption of system resources by exporting large amounts of data. If the permission display parameters for this purpose include business decision permission display parameters, only data visualization viewing permissions are enabled, and the raw data export function is not provided. It only supports multi-dimensional filtering of data by unit level, time dimension, and business scenario, and automatically generates decision support charts, such as load trend charts and line loss rate comparison charts, and marks the data source, update time, and quality verification results to provide a reliable basis for business decisions.

[0060] For cross-system integration and sharing, this mapping configuration operation can be understood as follows: If the data integration method is JADP single sign-on integration, the standard field mapping relationship between the two systems will be automatically matched. For example, the "power supply" field of the power grid operation data will be mapped to the "total power supply" field of the third-party system, and a visual mapping configuration interface will be provided to support users to manually adjust the mapping relationship. If the data integration method is 4A security management integration or national cryptographic encryption integration, the fields of the processed heterogeneous data will be standardized and encoded first, and then mapped and converted according to the field encoding rules of the third-party system. At the same time, a field mapping relationship table will be generated and archived to support subsequent data flow traceability and format verification.

[0061] As can be seen, this optional embodiment can determine the usage permission display parameters that match the internal platform sharing type, and perform differentiated display control on the processed heterogeneous data according to the usage permission display parameters; and for cross-system integration sharing type, it generates temporary access tokens for the processed heterogeneous data, and after binding the temporary access tokens with the access authorization credentials of the third-party sharing system for the processed heterogeneous data, it determines the data integration method of the processed heterogeneous data according to the instruction parsing parameters, realizing the mapping configuration process between the processed heterogeneous data and the data fields of the third-party sharing system. In this way, it is beneficial to perform targeted permission control on the processed heterogeneous data, thereby improving the reliability and accuracy of differentiated display control and mapping configuration of the processed heterogeneous data, ensuring accurate data acquisition for users of different levels and roles, and blocking unauthorized access from illegal systems from the source, thereby improving the accuracy and security of subsequent shared transmission of processed heterogeneous data, improving user experience and business collaboration efficiency; at the same time, it also realizes the compliance and traceability process of data.

[0062] In another optional embodiment, step 207 above, generating monitoring information for the processed heterogeneous data based on the calling parameters, includes: Obtain the shared system resource status parameters of the processed heterogeneous data; Obtain shared quality parameters of the processed heterogeneous data; Based on the call parameters, shared system resource status parameters, and shared quality parameters, monitoring information for the processed heterogeneous data is generated.

[0063] In this optional embodiment, specifically, the shared system resource status parameters include server CPU utilization, memory utilization, network bandwidth utilization, number of database connections, and interface gateway request forwarding efficiency parameters; and the shared quality parameters include data integrity compliance rate, data timeliness compliance rate, and abnormal data processing progress parameters.

[0064] Furthermore, based on the call parameters, shared system resource status parameters, and shared quality parameters, monitoring information for the processed heterogeneous data is generated, including: Obtain the preset monitoring dimension configuration parameters, and based on the monitoring dimension configuration parameters, perform correlation and integration operations on the call parameters, shared system resource status parameters, and shared quality parameters to obtain multi-dimensional integrated parameters; Obtain the preset monitoring threshold parameters, and perform anomaly identification operation on the multidimensional integrated parameters based on the monitoring threshold parameters to obtain the anomaly identification results of the multidimensional integrated parameters; Based on the multidimensional integrated parameters and anomaly identification results, multi-type monitoring information of the multidimensional integrated parameters is generated as monitoring information for the processed heterogeneous data.

[0065] In this optional embodiment, the anomaly identification result includes anomaly type parameters, anomaly level parameters, and anomaly association node parameters. Optionally, the multi-type monitoring information includes at least one of global overview monitoring information, traceability monitoring information, anomaly early warning monitoring information, and trend statistics monitoring information.

[0066] For example, during the data sharing process, the system synchronously collects three types of core monitoring parameters: First, call parameters, which cover the calling entity information of each business department and its subordinate units, the data type of the call, the call execution status, the call frequency per unit time, and the call response status; second, shared system resource status parameters, which monitor in real time the server hardware resource usage supporting data sharing, the operating efficiency of the data transmission link, and the database connection status; and third, shared quality parameters, which are the completeness and real-time performance of statistical data in the shared transmission, as well as the progress of handling abnormal data.

[0067] Next, the system configures parameters according to preset monitoring dimensions, and integrates the call parameters, shared system resource status parameters, and shared quality parameters to form multi-dimensional linked integrated data. At the same time, combined with the dynamic monitoring threshold standards of the power grid dispatching business scenario, the integrated data is used to identify anomalies, so as to accurately locate the anomaly type, classify the anomaly level, and pinpoint the related nodes that caused the anomaly.

[0068] Subsequently, based on the integrated data and anomaly identification results, the system automatically generates multiple types of monitoring information. Among them, the global overview monitoring information can intuitively present the overall operational status of data sharing across the entire network, making it easy for managers to quickly grasp the core situation; the traceability monitoring information can build a full-link relationship view from the calling entity to the shared data and then to the system resources, supporting accurate tracing of problems; the anomaly early warning monitoring information can push the corresponding monitoring objects in an appropriate manner for different levels of anomalies, and simultaneously include directional suggestions for anomaly handling; the trend statistics monitoring information can predict the operational trend of subsequent data sharing based on historical operational data, providing support for the early deployment of countermeasures.

[0069] In this way, through this monitoring scheme, power grid managers can promptly identify potential problems in the data sharing process, quickly take optimization measures, ensure the stability and efficiency of data sharing for core dispatching operations, and provide strong data support for the safe operation of the power grid.

[0070] As can be seen, this optional embodiment can correlate and integrate the shared system resource status parameters, shared quality parameters, and call parameters of the processed heterogeneous data. Based on monitoring threshold parameters, it can identify anomalies in the multi-dimensional integrated parameters, obtaining anomaly identification results and generating multi-type monitoring information for these parameters. Thus, by constructing a three-dimensional linkage monitoring system of "call-resource-quality," it not only breaks through the limitations of traditional monitoring that only focuses on call behavior, but also achieves comprehensive monitoring of the entire data sharing chain. This improves the accuracy of identifying potential problems such as resource overload and substandard data quality, reducing missed or false judgments caused by single-dimensional monitoring. Furthermore, it meets the differentiated needs of monitoring objects at different levels, facilitating power grid managers to grasp the overall situation and support rapid problem location, thereby contributing to the refined management process of power grid data sharing.

[0071] Example 3 Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a power grid data sharing and real-time monitoring method and apparatus disclosed in an embodiment of the present invention. Figure 3 As shown, the apparatus for a power grid data sharing and real-time monitoring method may include: The acquisition module 301 is used to acquire multi-source heterogeneous data under a preset power grid business scenario; The target processing module 302 is used to perform target processing operations on multi-source heterogeneous data to obtain processed heterogeneous data; The shared processing module 303 is used to perform shared processing on the processed heterogeneous data according to the shared instruction when a shared instruction for the processed heterogeneous data is received. The monitoring module 304 is used to monitor the call parameters of the processed heterogeneous data in real time during the shared processing process of the shared processing module 303, and generate monitoring information of the processed heterogeneous data according to the call parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

[0072] In this embodiment of the invention, the multi-source heterogeneous data includes power grid operation data, equipment status data, user behavior data, and system operation data; the calling parameters of the processed heterogeneous data include calling subject parameters, calling content, calling status parameters, calling frequency parameters, and calling response parameters.

[0073] Furthermore, the target processing module 302 performs target processing operations on the multi-source heterogeneous data to obtain the processed heterogeneous data in the following ways: Obtain anomalies in multi-source heterogeneous data, and perform cleaning operations on the multi-source heterogeneous data based on the anomalies to obtain cleaned heterogeneous data; Obtain the scene access parameters of the cleaned heterogeneous data, and perform standardization operations on the cleaned heterogeneous data according to the scene access parameters to obtain standardized heterogeneous data. Obtain the anonymization information of the standardized heterogeneous data, and anonymize the standardized heterogeneous data according to the anonymization information to obtain the anonymized heterogeneous data; Target augmentation is performed on the desensitized heterogeneous data to obtain augmented heterogeneous data, which is then used as processed heterogeneous data.

[0074] In this optional embodiment, the abnormal situation includes at least one of the following: fluctuation abnormal situation, field missing situation, and data duplication situation; the cleaning operation includes at least one of the following: data filtering operation, data interpolation and completion operation, and deduplication and merging operation; the scene access parameter includes at least one of the following: scene access type parameter, scene access time parameter, and scene access unit parameter.

[0075] Furthermore, the target processing module 302 performs target enhancement operations on the de-identified heterogeneous data, and the specific methods for obtaining the enhanced heterogeneous data include: Obtain the target link parameters of the desensitized heterogeneous data, and perform forward and reverse lineage penetration operations on the desensitized heterogeneous data based on the target link parameters to obtain the forward and reverse lineage relationship parameters of the desensitized heterogeneous data. Obtain the bloodline extension element parameters of the desensitized heterogeneous data, and perform bloodline extension operation on the desensitized heterogeneous data based on the forward and reverse bloodline relationship parameters and the bloodline extension element parameters to obtain the extended bloodline relationship parameters of the desensitized heterogeneous data. Based on the extended bloodline parameters, multi-dimensional association operations are performed on the desensitized heterogeneous data to obtain the associated heterogeneous data. Then, based on the preset quality inspection requirements parameters, the quality inspection results of the associated heterogeneous data are obtained. When the quality inspection results indicate that the correlated heterogeneous data has passed the quality inspection, the correlated heterogeneous data will be identified as the enhanced heterogeneous data. When the quality inspection result indicates that the associated heterogeneous data fails the quality inspection, the associated heterogeneous data is identified as de-identified heterogeneous data, and the operation of obtaining the target link parameters of the de-identified heterogeneous data is triggered.

[0076] In this optional embodiment, the target link parameters include generation link parameters, processing link parameters, flow link parameters, and application link parameters; the lineage extension element parameters include at least one of business scenario element parameters, data governance requirement element parameters, security requirement element parameters, system operation and maintenance element parameters, and value mining element parameters.

[0077] It is evident that implementation Figure 3The described power grid data sharing and real-time monitoring method and device can first perform target processing on multi-source heterogeneous data, and then realize the sharing and monitoring of the processed heterogeneous data. This improves the reliability and accuracy of processing multi-source heterogeneous data, thereby improving the timeliness and accuracy of transmission of multi-source heterogeneous data, which is conducive to improving the adaptability between multi-source heterogeneous data and multiple terminals.

[0078] In an optional embodiment, the sharing processing module 303 performs sharing processing on the processed heterogeneous data according to the sharing instruction in the following specific ways: Perform parsing operations on shared instructions to obtain the instruction parsing parameters corresponding to the shared instructions; Based on the command parsing parameters, determine the sharing type of the processed heterogeneous data, and perform matching permission control operations on the processed heterogeneous data according to the sharing type; After completing the access control operation, the security protection requirements parameters of the processed heterogeneous data are determined according to the command parsing parameters, and the security protection processing operation is performed on the processed heterogeneous data according to the security protection requirements parameters. After completing the security protection process, the processed heterogeneous data is shared and transmitted.

[0079] In this optional embodiment, the instruction parsing parameters include at least one of the following: shared data identifier parameters, shared object parameters, shared scope parameters, shared duration parameters, and shared purpose parameters; the sharing type includes internal platform sharing type or cross-system integration sharing type; and the security protection requirement parameters include at least one of the following: data transmission encryption requirement parameters, access control hardening requirement parameters, and sensitive field protection requirement parameters.

[0080] It is evident that implementation Figure 3 The described power grid data sharing and real-time monitoring method and device can parse sharing instructions to determine the sharing type of processed heterogeneous data based on the instruction parsing parameters. Then, based on the sharing type, it performs access control on the processed heterogeneous data. After completing access control, it further performs security protection processing on the processed heterogeneous data to achieve data sharing and transmission. This improves the reliability and accuracy of access control for processed heterogeneous data, and further enhances the security of shared transmission of processed heterogeneous data through data security protection processing, thereby effectively reducing the risk of data leakage and improving the precision of power grid operation and management.

[0081] In another optional embodiment, the sharing processing module 303 performs matching permission control operations on the processed heterogeneous data according to the sharing type, specifically including: When the sharing type includes the internal platform sharing type, determine the unit-level permission parameters and role-level permission parameters of the processed heterogeneous data, and determine the accessible data range of the processed heterogeneous data based on the unit-level permission parameters and role-level permission parameters. Based on the command parsing parameters and the range of accessible data, determine the usage permission display parameters that match the sharing type of the internal platform, and perform differentiated display control operations on the processed heterogeneous data according to the usage permission display parameters. When the sharing type includes cross-system integration sharing type, determine the temporary access permission parameters for the processed heterogeneous data, and generate a temporary access token for the processed heterogeneous data based on the temporary access permission parameters, so as to bind the temporary access token to the access authorization credential of the third-party sharing system for the processed heterogeneous data. After binding is completed, the data integration method of the processed heterogeneous data is determined according to the command parsing parameters, and the data fields of the processed heterogeneous data and the third-party shared system are mapped and configured according to the data integration method.

[0082] In this optional embodiment, the usage permission display parameters include at least one of scenario development permission display parameters, report generation permission display parameters, and business decision permission display parameters; the temporary access permission parameters include at least one of temporary access duration parameters, temporary access data range parameters, and temporary access operation permission parameters.

[0083] It is evident that implementation Figure 3 The described power grid data sharing and real-time monitoring method and device can determine usage permission display parameters matching the internal platform sharing type, and perform differentiated display control of processed heterogeneous data according to the usage permission display parameters. Furthermore, for cross-system integration sharing types, it generates temporary access tokens for processed heterogeneous data. After binding the temporary access tokens with the access authorization credentials of the third-party sharing system for the processed heterogeneous data, it determines the data integration method of the processed heterogeneous data according to the instruction parsing parameters, realizing the mapping configuration process between the processed heterogeneous data and the data fields of the third-party sharing system. This facilitates targeted permission control of processed heterogeneous data, thereby improving the reliability and accuracy of differentiated display control and mapping configuration of processed heterogeneous data. It ensures accurate data acquisition for users at different levels and with different roles, and blocks unauthorized access from illegal systems at the source. This improves the accuracy and security of subsequent shared transmission of processed heterogeneous data, enhancing user experience and improving business collaboration efficiency. Simultaneously, it also achieves a compliant and traceable data process.

[0084] In yet another optional embodiment, the monitoring module 304 generates monitoring information for the processed heterogeneous data according to the calling parameters in the following specific ways: Obtain the shared system resource status parameters of the processed heterogeneous data; Obtain shared quality parameters of the processed heterogeneous data; Based on the call parameters, shared system resource status parameters, and shared quality parameters, monitoring information for the processed heterogeneous data is generated.

[0085] In this optional embodiment, the shared system resource status parameters include server CPU utilization, memory utilization, network bandwidth utilization, number of database connections, and interface gateway request forwarding efficiency parameters; the shared quality parameters include data integrity compliance rate, data timeliness compliance rate, and abnormal data processing progress parameters.

[0086] Furthermore, the monitoring module 304 generates monitoring information for the processed heterogeneous data based on the calling parameters, shared system resource status parameters, and shared quality parameters in the following specific ways: Obtain the preset monitoring dimension configuration parameters, and based on the monitoring dimension configuration parameters, perform correlation and integration operations on the call parameters, shared system resource status parameters, and shared quality parameters to obtain multi-dimensional integrated parameters; Obtain the preset monitoring threshold parameters, and perform anomaly identification operation on the multidimensional integrated parameters based on the monitoring threshold parameters to obtain the anomaly identification results of the multidimensional integrated parameters; Based on the multidimensional integrated parameters and anomaly identification results, multi-type monitoring information of the multidimensional integrated parameters is generated as monitoring information for the processed heterogeneous data.

[0087] In this optional embodiment, the anomaly identification result includes anomaly type parameters, anomaly level parameters, and anomaly associated node parameters; the multi-type monitoring information includes at least one of global overview monitoring information, traceability monitoring information, anomaly early warning monitoring information, and trend statistics monitoring information.

[0088] It is evident that implementation Figure 3The described power grid data sharing and real-time monitoring method and device can correlate and integrate the resource status parameters, sharing quality parameters, and call parameters of the shared system for processed heterogeneous data. Based on monitoring threshold parameters, it identifies anomalies in the multi-dimensional integrated parameters, obtaining anomaly identification results and generating multi-type monitoring information for these parameters. By constructing a three-dimensional linkage monitoring system of "call-resource-quality," it not only overcomes the limitations of traditional monitoring that only focuses on call behavior, but also achieves comprehensive monitoring of the entire data sharing chain. This improves the accuracy of identifying potential problems such as resource overload and substandard data quality, reducing missed or false judgments caused by single-dimensional monitoring. Furthermore, it meets the differentiated needs of monitoring objects at different levels, facilitating power grid managers to grasp the overall situation and support rapid problem localization, thus contributing to the refined management process of power grid data sharing.

[0089] Example 4 Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of another power grid data sharing and real-time monitoring method and apparatus disclosed in an embodiment of the present invention. Figure 4 As shown, the apparatus for a power grid data sharing and real-time monitoring method may include: Memory 401 storing executable program code; Processor 402 coupled to memory 401; The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the power grid data sharing and real-time monitoring method described in Embodiment 1 or Embodiment 2 of the present invention.

[0090] Example 5 This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute the steps in a power grid data sharing and real-time monitoring method described in Embodiment 1 or Embodiment 2 of this invention.

[0091] Example 6 This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in a power grid data sharing and real-time monitoring method described in Embodiment 1 or Embodiment 2.

[0092] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0093] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0094] Finally, it should be noted that the power grid data sharing and real-time monitoring method and apparatus disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for power grid data sharing and real-time monitoring, characterized in that, The method includes: Acquire multi-source heterogeneous data under preset power grid business scenarios; the multi-source heterogeneous data includes power grid operation data, equipment status data, user behavior data, and system operation data; The multi-source heterogeneous data is subjected to target processing operations to obtain processed heterogeneous data; When a sharing instruction for the processed heterogeneous data is received, the processed heterogeneous data is shared according to the sharing instruction; During the shared processing, the calling parameters of the processed heterogeneous data are monitored in real time, and monitoring information of the processed heterogeneous data is generated based on the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

2. The method for power grid data sharing and real-time monitoring according to claim 1, characterized in that, The target processing operation on the multi-source heterogeneous data to obtain processed heterogeneous data includes: The system acquires anomalies in the multi-source heterogeneous data and performs cleaning operations on the multi-source heterogeneous data based on the anomalies to obtain cleaned heterogeneous data. The anomalies include at least one of fluctuation anomalies, field missing anomalies, and data duplication anomalies. The cleaning operations include at least one of data filtering operations, data interpolation and completion operations, and deduplication and merging operations. The scene access parameters of the cleaned heterogeneous data are obtained, and the cleaned heterogeneous data is standardized according to the scene access parameters to obtain standardized heterogeneous data; the scene access parameters include at least one of scene access type parameters, scene access time parameters, and scene access unit parameters. Obtain the desensitization information of the standardized heterogeneous data, and desensitize the standardized heterogeneous data according to the desensitization information to obtain desensitized heterogeneous data; The desensitized heterogeneous data is subjected to a target enhancement operation to obtain enhanced heterogeneous data, which is used as processed heterogeneous data.

3. The method for power grid data sharing and real-time monitoring according to claim 2, characterized in that, The step of performing target augmentation on the desensitized heterogeneous data to obtain augmented heterogeneous data includes: The target link parameters of the desensitized heterogeneous data are obtained, and based on the target link parameters, forward and reverse lineage penetration operations are performed on the desensitized heterogeneous data to obtain the forward and reverse lineage relationship parameters of the desensitized heterogeneous data; the target link parameters include generation link parameters, processing link parameters, flow link parameters and application link parameters; The lineage extension element parameters of the anonymized heterogeneous data are obtained, and lineage extension operations are performed on the anonymized heterogeneous data according to the forward and reverse lineage relationship parameters and the lineage extension element parameters to obtain the extended lineage relationship parameters of the anonymized heterogeneous data; the lineage extension element parameters include at least one of the following: business scenario element parameters, data governance requirement element parameters, security requirement element parameters, system operation and maintenance element parameters, and value mining element parameters; Based on the extended bloodline parameters, a multi-dimensional association operation is performed on the desensitized heterogeneous data to obtain associated heterogeneous data. Then, based on the preset quality inspection requirements parameters, the associated heterogeneous data is inspected to obtain the quality inspection results of the associated heterogeneous data. When the quality inspection result indicates that the correlated heterogeneous data has passed the quality inspection, the correlated heterogeneous data is identified as enhanced heterogeneous data. When the quality inspection result indicates that the associated heterogeneous data fails the quality inspection, the associated heterogeneous data is identified as the de-identified heterogeneous data, and the operation of obtaining the target link parameters of the de-identified heterogeneous data is triggered.

4. A method for power grid data sharing and real-time monitoring according to any one of claims 1-3, characterized in that, The step of sharing the processed heterogeneous data according to the sharing instruction includes: The shared instruction is parsed to obtain the instruction parsing parameters corresponding to the shared instruction; the instruction parsing parameters include at least one of the following: shared data identifier parameters, shared object parameters, shared scope parameters, shared duration parameters, and shared purpose parameters; Based on the instruction parsing parameters, the sharing type of the processed heterogeneous data is determined, and according to the sharing type, a matching permission control operation is performed on the processed heterogeneous data; the sharing type includes internal platform sharing type or cross-system integration sharing type; After completing the access control operation, the security protection requirements parameters of the processed heterogeneous data are determined according to the instruction parsing parameters, and the security protection processing operation is performed on the processed heterogeneous data according to the security protection requirements parameters; the security protection requirements parameters include at least one of the following: data transmission encryption requirements parameters, access control hardening requirements parameters, and sensitive field protection requirements parameters. After completing the security protection processing operation, the processed heterogeneous data is shared and transmitted.

5. The method for power grid data sharing and real-time monitoring according to claim 4, characterized in that, The step of performing matching permission control operations on the processed heterogeneous data according to the sharing type includes: When the sharing type includes the internal platform sharing type, determine the unit level permission parameters and role permission parameters of the processed heterogeneous data, and determine the accessible data range of the processed heterogeneous data based on the unit level permission parameters and the role permission parameters. Based on the instruction parsing parameters and the accessible data range, determine the usage permission display parameters that match the sharing type of the internal platform, and perform differentiated display control operations on the processed heterogeneous data according to the usage permission display parameters; the usage permission display parameters include at least one of scenario development permission display parameters, report generation permission display parameters, and business decision-making permission display parameters. When the sharing type includes the cross-system integration sharing type, a temporary access permission parameter for the processed heterogeneous data is determined, and a temporary access token for the processed heterogeneous data is generated based on the temporary access permission parameter, so as to bind the temporary access token to the access authorization credential of the third-party sharing system of the processed heterogeneous data; the temporary access permission parameter includes at least one of a temporary access duration parameter, a temporary access data range parameter, and a temporary access operation permission parameter. After the binding is completed, the data integration method of the processed heterogeneous data is determined according to the instruction parsing parameters, and the data fields of the processed heterogeneous data and the third-party shared system are mapped and configured according to the data integration method.

6. The method for power grid data sharing and real-time monitoring according to claim 1, characterized in that, The call parameters for the processed heterogeneous data include call subject parameters, call content, call status parameters, call frequency parameters, and call response parameters; The step of generating monitoring information for the processed heterogeneous data based on the calling parameters includes: Obtain the shared system resource status parameters of the processed heterogeneous data; the shared system resource status parameters include server CPU utilization, memory utilization, network bandwidth utilization, database connection count, and interface gateway request forwarding efficiency parameters; Obtain the shared quality parameters of the processed heterogeneous data; the shared quality parameters include data integrity compliance rate, data timeliness compliance rate, and abnormal data processing progress parameters. Based on the calling parameters, the shared system resource status parameters, and the shared quality parameters, monitoring information for the processed heterogeneous data is generated.

7. The method for power grid data sharing and real-time monitoring according to claim 6, characterized in that, The step of generating monitoring information for the processed heterogeneous data based on the calling parameters, the shared system resource status parameters, and the shared quality parameters includes: Obtain preset monitoring dimension configuration parameters, and based on the monitoring dimension configuration parameters, perform correlation and integration operations on the calling parameters, the shared system resource status parameters, and the shared quality parameters to obtain multi-dimensional integrated parameters; Obtain preset monitoring threshold parameters, and perform anomaly identification operation on the multidimensional integrated parameters according to the monitoring threshold parameters to obtain the anomaly identification result of the multidimensional integrated parameters; the anomaly identification result includes anomaly type parameters, anomaly level parameters, and anomaly associated node parameters; Based on the multidimensional integration parameters and the anomaly identification results, multi-type monitoring information of the multidimensional integration parameters is generated as monitoring information of the processed heterogeneous data; the multi-type monitoring information includes at least one of global overview monitoring information, traceability monitoring information, anomaly early warning monitoring information, and trend statistics monitoring information.

8. A method and apparatus for power grid data sharing and real-time monitoring, characterized in that, The device includes: The acquisition module is used to acquire multi-source heterogeneous data under a preset power grid business scenario; the multi-source heterogeneous data includes power grid operation data, equipment status data, user behavior data, and system operation data; The target processing module is used to perform target processing operations on the multi-source heterogeneous data to obtain processed heterogeneous data. A sharing processing module is used to perform sharing processing on the processed heterogeneous data according to the sharing instruction when a sharing instruction for the processed heterogeneous data is received. The monitoring module is used to monitor the calling parameters of the processed heterogeneous data in real time during the shared processing process of the shared processing module, and generate monitoring information of the processed heterogeneous data according to the calling parameters, so as to send the monitoring information to the monitoring object of the processed heterogeneous data.

9. A method and apparatus for power grid data sharing and real-time monitoring, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute a power grid data sharing and real-time monitoring method as described in any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute a power grid data sharing and real-time monitoring method as described in any one of claims 1-7.

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