Data verification method and device, equipment and storage medium
By determining the relationship between candidate business in the power system and performing data verification, the problem of ignoring the inherent correlation of data in traditional methods is solved, and the refined management and quality improvement of timing measurement point data is achieved.
Patent Information
- Application Number
- CN202510544243.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-28
- Publication Date
- 2025-08-08
AI Technical Summary
Traditional time-series data governance methods lack consideration of the inherent correlation and constraint relationship between different measurement points data in the power system, making it difficult to find contradictions or unreasonable data quality problems at the business logic level, and cannot meet the deep and refined management needs of power generation companies for production data quality.
By determining the data to be verified and the candidate business relationship of the power system, using the power capacity and the number of equipment, and combining the business logic relationship, the timing measurement point data is verified, including determining the matching business relationship and performing data verification.
It improves the pertinence and effectiveness of data management of time-sequence measurement points in the power system, can detect and correct abnormalities in the data, and meets the in-depth management needs of power generation companies for data quality.
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Figure CN120448759A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of data processing technology, and in particular to a data verification method, device, equipment and storage medium. Background Art
[0002] During the production process of power generation companies, a large amount of time-series data is generated, such as generator operating parameters and equipment status monitoring data. The accuracy and reliability of this data are crucial for production management and decision-making. Traditional time-series data governance methods primarily perform single-point verification based on the six properties of data: accuracy, completeness, consistency, timeliness, uniqueness, and traceability. Common verification tasks include detecting anomalies in the data stream at a single measurement point, such as data interruptions, dead values, and jumps.
[0003] However, these traditional methods are often limited to evaluating individual data sequences in isolation, lacking consideration of the underlying business logic and physical processes, and overlooking the inherent correlations and constraints between data at different measurement points. Consequently, these methods struggle to identify data quality issues that may appear "normal" at a single point but are inconsistent or illogical at the business logic level. This makes it difficult for traditional methods to fully meet the in-depth and refined management needs of power generation companies for production data quality. Summary of the Invention
[0004] The present invention provides a data verification method, device, equipment and storage medium to achieve data verification management of power system time series measurement point data.
[0005] In a first aspect, an embodiment of the present invention provides a data verification method, the method comprising:
[0006] Determining data to be verified and candidate business association relationships of a target power system, wherein the data to be verified is time-series measurement point data of the power system; the candidate business association relationships are determined based on power capacity and the number of devices related to the business in the power system; the candidate business association relationships include a business logic relationship between a first parameter to be verified and a second parameter to be verified;
[0007] Determining at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships;
[0008] The data to be verified is verified according to the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
[0009] In a second aspect, an embodiment of the present invention further provides a data verification device, the device comprising:
[0010] A data determination module is configured to determine data to be verified and candidate business association relationships of a target power system, wherein the data to be verified is time-series measurement point data of the power system; the candidate business association relationships are determined based on the power capacity and number of devices related to the business in the power system; the candidate business association relationships include a business logic relationship between a first parameter to be verified and a second parameter to be verified;
[0011] a business association relationship determination module, configured to determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships;
[0012] The verification result determination module is used to verify the data to be verified based on the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
[0013] In a third aspect, an embodiment of the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the data verification method as described in any one of the embodiments of the present invention is implemented.
[0014] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, are used to execute the data verification method as described in any one of the embodiments of the present invention.
[0015] The technical solution of the embodiment of the present invention combines the time series measurement point data with the business association relationship of the power system, verifies and manages the time series measurement point data of the power system according to the business association relationship, and improves the pertinence and effectiveness of the management of the time series measurement point data of the power system.
[0016] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0018] Figure 1 This is a flow chart of a data verification method provided by Example 1 of the present invention;
[0019] Figure 2This is a flow chart of a data verification method provided by Embodiment 2 of the present invention;
[0020] Figure 3 This is a schematic diagram of the structure of a data verification device provided by Embodiment 3 of the present invention;
[0021] Figure 4 It is a structural diagram of an electronic device for implementing the data verification method according to an embodiment of the present invention. DETAILED DESCRIPTION
[0022] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.
[0023] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0024] Example 1
[0025] Figure 1 A flowchart of a data verification method is provided for the first embodiment of the present invention. This embodiment is applicable to data verification situations. The method can be executed by a data verification device. The data verification device can be implemented in the form of hardware and / or software. The data verification device can be configured in any electronic device with network communication and computing capabilities. Figure 1 As shown, the method includes:
[0026] S110: Determine the association between the data to be verified and the candidate services of the target power system.
[0027] In this embodiment, the target power system can be the power system of a certain region, which can be a province, city, district, county, or street. The data to be verified is the time-series measurement point data of the target power system. The time-series measurement point data refers to the data obtained by monitoring and recording various measurement points in the power system in chronological order. This data has time stamps and can reflect the operating status and characteristics of the power system at different times. The time-series measurement point data of the power system may come from power plants, substations, transmission lines, or power loads.
[0028] The candidate business association relationships are determined based on the power capacity and number of devices related to the business in the power system. Alternatively, candidate business association relationships can generally be determined based on the business logic of the power system, such as the relationship between the power capacity of each measurement point or the relationship between the number of operating / out-of-service devices at each measurement point.
[0029] Among them, the candidate business association relationship includes the business logic relationship between the first parameter to be verified and the second parameter to be verified, and the business logic relationship can be predetermined. The candidate business association relationship is a preset logical relationship formed by the first parameter to be verified and the second parameter to be verified, and this logical relationship is determined in advance based on the business level. For example, in the power system, the first parameter to be verified may be "total power generation in the region", and the second parameter to be verified is "the sum of power generation of each power plant". The preset logical relationship is "the two are equal". This relationship can constitute a candidate business association relationship for the power system for data verification.
[0030] It should be noted that the technical method of this embodiment is used to verify and manage the time-series measurement point data of the power system.
[0031] In practical applications, the data to be verified for the target power system can be obtained through the following methods.
[0032] There are many automated devices in the power system, such as substation telecontrol terminals and distribution automation terminals. These devices can collect various operating data of the power system in real time, including voltage, current, power, frequency, etc., and upload the data to the dispatching control center or other data processing platforms according to certain communication protocols.
[0033] In addition, smart meters can collect real-time user load data, such as active power, reactive power, voltage, and current, and upload this data to metering automation systems or other data platforms via power line carrier communication or wireless communication. By analyzing large amounts of smart meter data, it is possible to obtain time-series measurement point data, such as the load distribution of the power system at different times.
[0034] SCADA (Supervisory Control and Data Acquisition) is a crucial system for data collection, monitoring, and control in power systems. It collects real-time data from sensors, transmitters, and other devices distributed throughout the power system and transmits this data to a control center for processing, display, and storage. The SCADA system collects a large amount of time-series data from measurement points throughout the power system, including grid operating status and equipment parameters, providing a crucial basis for power system operation, scheduling, and management.
[0035] In addition, the target power system can be modeled and simulated using power system simulation software. During the simulation process, different operating conditions and time steps can be set to simulate the dynamic operation of the target power system, thereby obtaining various time-series measurement point data of the target power system.
[0036] The above method can be used to obtain the time series measurement point data of the target power system. In practical applications, the accuracy of the time series measurement point data of the target power system can be verified in a variety of ways.
[0037] Furthermore, the candidate business association relationships of the target power system may be determined according to the power business rules of the target power system.
[0038] In practical applications, the historical time-series measurement point data of the target power system can be obtained first. It should be noted that the historical time-series measurement point data may come from different data sources such as SCADA systems, smart meters, and power statistical reports. They need to be obtained and organized into the same data format through corresponding data interfaces and data processing processes.
[0039] Then, according to the specific characteristics of different regions, different time periods and the target power system, the value of the error range is flexibly adjusted to determine different candidate business association relationships between the data of each time series measurement point to adapt to the actual power business rules, such as the candidate business association relationship being the size relationship between the data of two time series measurement points.
[0040] In actual applications, candidate business association relationships can usually be appropriately adjusted and optimized based on specific business scenarios and data conditions.
[0041] As an optional but non-limiting implementation method, the data to be verified include the total operating power capacity of the target power system, the total power capacity of the connected equipment, the total power load, the equipment outage capacity, the number of connected equipment, the number of operating equipment, the number of outage equipment, the number of standby equipment, the number of communication interrupted equipment, the number of normally operating equipment, the number of load-limited operating equipment, the number of fault-shutdown equipment, and the number of shut-down equipment.
[0042] In this embodiment, the total operating power capacity refers to the sum of the rated power capacities of all operating power generation equipment (such as generators and generator sets) in the power system. The total connected equipment power capacity refers to the sum of the rated capacities of all power generation equipment connected to the power system. The total power load refers to the total power actually consumed by all power-consuming equipment in the power system at a given moment. The outage capacity refers to the sum of the capacities of power generation equipment that has ceased operation due to equipment failure, overhaul, maintenance, or other reasons.
[0043] In this embodiment, the data to be verified may also include the number of wind turbine scheduling load limits, the number of wind turbines' own load limits, as well as the number of wind turbines on standby at the same time, the number of wind turbines operating at load limits, the number of wind turbines shut down due to faults, the number of wind turbines generally shut down, the number of wind turbines in operation, the proportion of wind turbines in operation, the proportion of wind turbine capacity, the photovoltaic capacity in operation, the number of photovoltaic units in operation, the proportion of photovoltaic units in operation, the proportion of photovoltaic capacity, etc.
[0044] It should be noted that the data to be verified may be different in different power systems.
[0045] As an optional but non-limiting implementation, the candidate business association relationship includes:
[0046] If the first parameter to be verified is the total power capacity of the access device, and the second parameter to be verified is the sum of the total operating power capacity and the equipment outage capacity, then the candidate service association relationship is that the total power capacity of the access device is greater than the sum of the total operating power capacity and the equipment outage capacity;
[0047] If the first parameter to be verified is the total power capacity in operation and the second parameter to be verified is the total power load, then the candidate business association relationship is that the total power capacity in operation is greater than the total power load;
[0048] If the first parameter to be verified is the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment, and the second parameter to be verified is the number of connected devices, then the candidate service association relationship is that the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment is equal to the number of connected devices;
[0049] If the first parameter to be verified is the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment, and the second parameter to be verified is the number of in-operation devices, then the candidate service association relationship is that the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment is equal to the number of in-operation devices;
[0050] If the first parameter to be verified is the sum of the number of faulty and shut down devices and the number of shut down devices of the same type, and the second parameter to be verified is the number of shut down devices, then the candidate business association relationship is that the sum of the number of faulty and shut down devices and the number of shut down devices of the same type is equal to the number of shut down devices;
[0051] If the first parameter to be verified is the difference between the average device power capacity and the device power capacity, and the second parameter to be verified is a preset threshold, then the candidate business association relationship is that the difference between the average device power capacity and the device power capacity is less than the preset threshold, and the average device power capacity is the ratio of the total operating power capacity to the number of operating devices.
[0052] It should be noted that this data verification method can be applied to power systems to verify and manage time-series measurement point data in power systems.
[0053] In addition to the candidate business association relationships listed above, candidate business association relationships may also include that the ratio of total electricity load to total operating power capacity (total load rate) should be maintained within a reasonable threshold range, or when an increase in the number of communication interruptions of a certain type of equipment (such as wind turbines) is monitored, the corresponding operating power capacity is reduced or the equipment outage capacity is increased at the associated timing measurement point.
[0054] It should be noted that the candidate business association relationships of different target power systems are specifically limited according to actual conditions and are not limited to the candidate business association relationships listed above.
[0055] S120: Determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices in the candidate business association relationships.
[0056] In this embodiment, the business association relationship is an association relationship among candidate business association relationships that matches the data to be verified.
[0057] Furthermore, in this embodiment, the data to be verified is usually a specific data content field and its field value or a data set, etc., and the candidate business association relationship is in the form of business rules, logical relationships or conditional expressions, etc. The data to be verified may be related to power capacity or the number of devices. Then, the business association relationship that matches the data to be verified can be determined based on the specific description content of the power capacity or the number of devices in the candidate business association relationship.
[0058] For example, if a candidate business association relationship describes the power capacity of the target power line system, and the data to be verified is related to the number of devices, then the candidate business association relationship and the data to be verified will not match. If a candidate business association relationship describes the power capacity of the target power line system, and the data to be verified is related to power capacity, then the candidate business association relationship and the data to be verified may match.
[0059] In addition, the degree of matching between the data to be verified and the candidate business association relationship can be further confirmed. Based on whether the degree of matching between the data to be verified and the candidate business association relationship is greater than a set threshold, or the maximum degree of matching between the data to be verified and the candidate business association relationship, the corresponding candidate business association relationship is used as the business association relationship that matches the data to be verified.
[0060] For example, if the data to be verified is the total operating power capacity and the total power load, candidate business association relationship one is that the total operating power capacity is greater than the total power load, and candidate business association relationship two is that the total power capacity of the access equipment is greater than the sum of the total operating power capacity and the equipment outage capacity, then the degree of matching between candidate business association relationship one and the data to be verified should be greater than the degree of matching between candidate business association relationship two and the data to be verified.
[0061] Specifically, the degree of match can be determined by checking whether candidate business association relationship 1 and candidate business association relationship 2 contain the same fields as the data to be verified, and whether the field values are equal. The more fields in a candidate business association relationship that are identical to the data to be verified, and the more identical the field values are, the greater the degree of match between the candidate business association relationship and the data to be verified.
[0062] Furthermore, in this embodiment, the candidate business association relationship 1 may be used as a business association relationship that matches the data to be verified (the total capacity of the operating power and the total power load).
[0063] As an optional but non-limiting implementation, determining at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices in the candidate business association relationships includes steps A1-A2:
[0064] Step A1: Determine a correlation coefficient based on a matching result between the content field of the candidate business association relationship and the content field of the data to be verified.
[0065] Step A2: Determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the correlation coefficient.
[0066] In this embodiment, the correlation coefficient is a matching result between the content field of the candidate business association relationship and the content field of the data to be verified.
[0067] It should be noted that before performing content field matching, the data must be preprocessed first, the data to be verified and the candidate business association relationship must be converted into strings, spaces removed, case converted, etc., to avoid matching failures due to formatting issues.
[0068] Furthermore, a string matching algorithm such as the KMP (Knuth-Morris-Pratt) algorithm or the Boyer-Moore algorithm may be used to perform string matching on the content fields of the candidate business association relationships and the content fields of the data to be verified, and at least one business association relationship that matches the data to be verified may be determined from the candidate business association relationships.
[0069] In practical applications, string exact matching, fuzzy matching, regular expression matching, etc. can be performed. If exact matching is performed, multiple candidate business association relationships can be stored in a list, each candidate business association relationship can be represented by a dictionary, and the dictionary can be used to store the data to be verified.
[0070] Next, a matching algorithm may be used to traverse each field of the data to be verified, and check whether the candidate business association relationship contains the same field as the data to be verified and the field value is equal, thereby determining the correlation coefficient.
[0071] It should be noted that the greater the correlation coefficient, the more likely the candidate business association relationship contains the same fields as the data to be verified and the same field values. Further, based on the correlation coefficient, it is determined whether a candidate business association relationship matches the data to be verified, and the business association relationship that matches the data to be verified is added to the list for output.
[0072] In this embodiment, the candidate business association relationships corresponding to correlation coefficients greater than a preset threshold, or the candidate business association relationships corresponding to the maximum correlation coefficient, can be used as the business association relationships that match the data to be verified. In this embodiment, the specific content of the business association relationship that matches the data to be verified is determined from the candidate business association relationships based on the correlation coefficient is not limited.
[0073] In actual applications, if fuzzy matching or regular expression matching is used, the matching function may be modified. This embodiment does not describe the modification process of the matching function in detail.
[0074] S130: Verify the data to be verified according to the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
[0075] In this embodiment, after determining the business association relationship matching the data to be verified, the data to be verified may be calculated and logically judged based on the first parameter to be verified and the second parameter to be verified of the business association relationship to determine a verification result of the data to be verified.
[0076] In actual applications, the "normal / abnormal" mark of the verification result of the data to be verified can be directly output, and the abnormal data to be verified that does not conform to the business association relationship can be highlighted.
[0077] Furthermore, if the data verification process is executed at a certain frequency, an exception list including the time when the exception occurred, the specific time series measurement point data involved, and the description of the relationship between the verification business is generated based on the exception identification.
[0078] In actual applications, the exception list can also be pushed to the relevant responsible units of each target power system. The responsible unit verifies the abnormal situation based on the abnormal data to be verified, and determines whether it is a real production operation abnormality event or a problem in the data collection, transmission, storage or processing link itself. And based on the verification results, take corresponding corrective measures, such as correcting the incorrect data source configuration, adjusting the data reporting logic, troubleshooting and repairing equipment communication failures, etc. After the rectification is completed, the responsible unit can feedback the processing results, and if necessary, update the baseline data (such as the aforementioned business association relationship) to ensure its accuracy. Furthermore, based on continuous data anomaly monitoring, rectification feedback and effect evaluation, the validity and coverage of the data to be verified and the business association relationship during the data verification process are continuously reviewed and optimized, thereby forming a data verification improvement closed-loop mechanism based on business logic, continuous operation and continuous optimization, and realizing the data governance process of the power system time series measurement point data.
[0079] The technical solution of the embodiment of the present invention combines the time series measurement point data with the business association relationship of the power system, verifies the time series measurement point data of the power system according to the business association relationship, and improves the pertinence and effectiveness of the time series measurement point data management of the power system.
[0080] Example 2
[0081] Figure 2 This is a flow chart of a data verification method provided in the second embodiment of the present invention. This embodiment of the present invention is further specified based on the above embodiment. This embodiment is applicable to data verification situations. The method can be executed by a data verification device. The data verification device can be implemented in the form of hardware and / or software. The data verification device can be configured in any electronic device with network communication and computing capabilities. Figure 2 As shown, the method includes:
[0082] S210. Determine the data to be verified and candidate business association relationships of the target power system, where the data to be verified is the time-series measurement point data of the power system; the candidate business association relationship is determined based on the power capacity and the number of equipment related to the business in the power system; the candidate business association relationship includes a business logic relationship between a first parameter to be verified and a second parameter to be verified.
[0083] S220: Determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships.
[0084] S230: Determine a first value of a first parameter to be verified of the service association relationship according to the data to be verified.
[0085] In this embodiment, the first value is a calculation result of substituting the data to be verified into the first parameter to be verified of the business association relationship.
[0086] In this embodiment, the data to be verified is usually related to power capacity or the number of devices. The data to be verified is the numerical value of each parameter related to power capacity or the number of devices in the power system. The business association relationship can be expressed by a logical relationship.
[0087] Therefore, according to the value of the data to be verified and the corresponding logical relationship in the business association relationship, the calculation result of the first parameter to be verified of the business association relationship, that is, the size of the first value, can be determined.
[0088] In this embodiment, the first value is determined based on data in the data to be verified that is associated with the first parameter to be verified in the service association relationship. For example, if the service association relationship is that the sum of the number of communication-disconnected devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment is equal to the number of connected devices, the first parameter to be verified is the sum of the number of communication-disconnected devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment, and the second parameter to be verified is the number of connected devices.
[0089] Furthermore, the first numerical value can be determined based on data related to the first parameter to be verified in the business association relationship, and the data related to the first parameter to be verified include the number of communication interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-shutdown devices, and the number of shut-down devices of the same type of equipment.
[0090] Furthermore, by calculating the sum of the number of communication interrupted devices, standby devices, normal operating devices, load-limited operating devices, fault-shutdown devices, and shutdown devices of the same type of devices, the first value of the service association relationship can be obtained.
[0091] S240: Determine a second value of a second parameter to be verified of the business association relationship according to the data to be verified.
[0092] In this embodiment, the second value is the result of substituting the data to be verified into the second parameter to be verified of the business association relationship. Based on the value of the data to be verified and the corresponding logical relationship in the business association relationship, the calculation result of the second parameter to be verified of the business association relationship, i.e., the magnitude of the second value, can be determined.
[0093] In this embodiment, taking the example of a service association where the sum of the number of communication-disconnected devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-shutdown devices, and the number of shut-down devices of the same type of device is equal to the number of connected devices, the second parameter to be verified is the number of connected devices. Based on the number of connected devices associated with the second parameter to be verified in the service association, the value of the number of connected devices is used as the second value of the service association.
[0094] S250: Determine a verification result of the data to be verified according to the first value and the second value.
[0095] In this embodiment, the verification result can be the accuracy of the data to be verified, or the abnormal state or normal state of the data to be verified. The first value and the second value are specific values, and the relationship between the first value and the second value can reflect the logical relationship between the first parameter to be verified and the second parameter to be verified.
[0096] In this embodiment, the logical relationship between the first value and the second value can be used to determine whether the logical relationship of the data to be verified in the target power system meets the preset business association relationship, thereby determining the verification result of the data to be verified.
[0097] Through the first value and the second value, the accuracy of the data to be verified can be quickly judged, which helps to improve the efficiency of data verification. At the same time, according to the corresponding business association relationship, the time series measurement point data corresponding to the data to be verified in the power system is verified, which can improve the pertinence and effectiveness of the time series measurement point data management of the power system.
[0098] As an optional but non-limiting implementation, determining the verification result of the data to be verified according to the first value and the second value includes steps B1-B2:
[0099] Step B1: Perform logical judgment based on the first value and the second value to determine a size comparison relationship.
[0100] Step B2: Determine the verification result of the data to be verified based on the size comparison relationship and the business association relationship.
[0101] In this embodiment, when performing logical judgment to determine the size comparison relationship between the first value and the second value, common size comparison relationships include equal, greater than, less than, greater than or equal to, less than or equal to, and not equal to.
[0102] In this embodiment, the size comparison relationship can be specifically divided into the following categories: the first value is greater than the second value, the first value is less than the second value, and the first value is equal to the second value.
[0103] Furthermore, the business association relationship is a logical relationship or conditional expression, which can be expressed as a set of business rules in the power system, each business rule including a first parameter to be verified, a second parameter to be verified, and a preset association relationship between the first parameter to be verified and the second parameter to be verified.
[0104] The size comparison relationship in this embodiment represents a logical relationship between the calculation result of the first parameter to be verified and the calculation result of the second parameter to be verified.
[0105] Furthermore, the accuracy and abnormality of the data to be verified are judged based on the logical relationship between the calculation result of the first parameter to be verified and the calculation result of the second parameter to be verified, and the preset association relationship between the first parameter to be verified and the second parameter to be verified.
[0106] In this embodiment, the verification result of the data to be verified is determined by comparing the size relationship and the business association relationship, which can improve the pertinence and effectiveness of the power system time series measurement point data management.
[0107] As an optional but non-limiting implementation, determining the verification result of the data to be verified based on the size comparison relationship and the business association relationship includes steps C1-C2:
[0108] Step C1: If the size comparison relationship and the business association relationship are consistent, it is determined that the verification result of the data to be verified is normal.
[0109] Step C2: If the size comparison relationship and the business association relationship are inconsistent, it is determined that the verification result of the data to be verified is abnormal.
[0110] In this embodiment, the verification result includes whether the data to be verified is normal or abnormal.
[0111] It can be understood that if the size comparison relationship and the business association relationship are consistent, it means that the logical relationship between the data to be verified conforms to the preset business association relationship, then it can be determined that the data to be verified is normal and the data collected from the target power system is accurate.
[0112] If the comparison relationship and the business association relationship are inconsistent, it means that the logical relationship between the data to be verified does not conform to the preset business association relationship. It can be determined that the data to be verified is abnormal and the data collected from the target power system is inaccurate.
[0113] In this embodiment, by determining the consistency of the size comparison relationship and the business association relationship, the accuracy of the data to be verified can be quickly verified.
[0114] As an optional but non-limiting implementation, if the comparison relationship and the business association relationship are inconsistent, after determining that the verification result of the data to be verified is abnormal, steps D1-D2 are included:
[0115] Step D1: trigger a data anomaly warning based on the abnormal verification result.
[0116] Step D2: Visually display the verification results on the front-end page.
[0117] In this embodiment, if the verification result of the data to be verified is abnormal, it means that the logical relationship between the data to be verified does not conform to the preset business association relationship, and the data collected from the target power system is inaccurate.
[0118] In actual applications, the data anomaly warning can be triggered based on the abnormal verification result, and the verification result can be visualized on the front-end page to remind the responsible units related to the target power system to verify the abnormal data and check the causes of the data anomaly, which is conducive to improving the data governance efficiency of the target power coefficient.
[0119] The technical solution of the embodiment of the present invention combines the time-series measurement point data with the business association relationship of the power system, determines the calculation results of the first parameter to be verified and the second parameter to be verified of the business association relationship based on the data to be verified, and verifies the time-series measurement point data of the power system based on the calculation results of the first parameter to be verified and the second parameter to be verified, so as to improve the pertinence and effectiveness of the management of the time-series measurement point data of the power system.
[0120] Example 3
[0121] Figure 3 This is a schematic diagram of the structure of a data verification device provided by the third embodiment of the present invention. This embodiment is applicable to data verification situations. The data verification device can be implemented in the form of hardware and / or software. The data verification device can be configured in any electronic device with network communication and computing capabilities. Figure 3 As shown, the device includes:
[0122] The data determination module 310 is configured to determine the target power system's data to be verified and candidate business association relationships, wherein the data to be verified is time-series measurement point data of the power system; the candidate business association relationships are determined based on the power capacity and number of devices related to the business in the power system; and the candidate business association relationships include a business logic relationship between a first parameter to be verified and a second parameter to be verified;
[0123] A business association relationship determination module 320 is configured to determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships;
[0124] The verification result determination module 330 is configured to verify the data to be verified based on the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
[0125] Optionally, verifying the data to be verified based on the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result includes:
[0126] Determining a first value of a first parameter to be verified of the business association relationship according to the data to be verified;
[0127] Determining a second value of a second parameter to be verified of the business association relationship according to the data to be verified;
[0128] A verification result of the data to be verified is determined according to the first value and the second value.
[0129] Optionally, determining a verification result of the data to be verified according to the first value and the second value includes:
[0130] Performing a logical judgment based on the first value and the second value to determine a size comparison relationship;
[0131] The verification result of the data to be verified is determined based on the size comparison relationship and the business association relationship.
[0132] Optionally, determining a verification result of the data to be verified based on the size comparison relationship and the business association relationship includes:
[0133] If the size comparison relationship and the business association relationship are consistent, then the verification result of the data to be verified is determined to be normal;
[0134] If the size comparison relationship and the business association relationship are inconsistent, it is determined that the verification result of the data to be verified is abnormal.
[0135] Optionally, if the size comparison relationship and the business association relationship are inconsistent, after determining that the verification result of the data to be verified is abnormal, the method includes:
[0136] According to the abnormal verification result, a data abnormality warning is triggered;
[0137] The verification results are visually displayed on the front-end page.
[0138] Optionally, determining at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships includes:
[0139] Determine a correlation coefficient based on a matching result between the content field of the candidate business association relationship and the content field of the data to be verified;
[0140] At least one business association relationship matching the data to be verified is determined from the candidate business association relationships according to the correlation coefficient.
[0141] Optionally, the candidate business association relationship includes:
[0142] If the first parameter to be verified is the total power capacity of the access device, and the second parameter to be verified is the sum of the total operating power capacity and the equipment outage capacity, then the candidate service association relationship is that the total power capacity of the access device is greater than the sum of the total operating power capacity and the equipment outage capacity;
[0143] If the first parameter to be verified is the total power capacity in operation and the second parameter to be verified is the total power load, then the candidate business association relationship is that the total power capacity in operation is greater than the total power load;
[0144] If the first parameter to be verified is the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment, and the second parameter to be verified is the number of connected devices, then the candidate service association relationship is that the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment is equal to the number of connected devices;
[0145] If the first parameter to be verified is the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment, and the second parameter to be verified is the number of in-operation devices, then the candidate service association relationship is that the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment is equal to the number of in-operation devices;
[0146] If the first parameter to be verified is the sum of the number of faulty and shut down devices and the number of shut down devices of the same type, and the second parameter to be verified is the number of shut down devices, then the candidate business association relationship is that the sum of the number of faulty and shut down devices and the number of shut down devices of the same type is equal to the number of shut down devices;
[0147] If the first parameter to be verified is the difference between the average device power capacity and the device power capacity, and the second parameter to be verified is a preset threshold, then the candidate business association relationship is that the difference between the average device power capacity and the device power capacity is less than the preset threshold, and the average device power capacity is the ratio of the total operating power capacity to the number of operating devices.
[0148] The technical solution of the embodiment of the present invention combines the time series measurement point data with the business association relationship of the power system to verify and manage the time series measurement point data of the power system, thereby improving the pertinence and effectiveness of the management of the time series measurement point data of the power system.
[0149] The data verification device provided in the embodiment of the present invention can execute the data verification method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.
[0150] Example 4
[0151] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.
[0152] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0153] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.
[0154] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the data verification method.
[0155] In some embodiments, the data verification method can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data verification method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the data verification method in any other suitable manner (e.g., by means of firmware).
[0156] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product that includes a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication unit 19, or installed from the storage unit 18, or installed from the ROM 12. When the computer program is executed by the processor 11, the above-mentioned functions defined in the method of the embodiment of the present invention are performed.
[0157] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0158] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.
[0159] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0160] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
[0161] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.
[0162] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.
[0163] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.
[0164] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.
Claims
1. A data verification method, characterized in that: include: Determine the association between the data to be verified and the candidate business of the target power system, wherein the data to be verified is the time-series measurement point data of the power system; The candidate business association relationship is determined based on the power capacity and the number of devices related to the business in the power system; the candidate business association relationship includes a business logic relationship between a first parameter to be verified and a second parameter to be verified; Determining at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships; The data to be verified is verified according to the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
2. The method according to claim 1, characterized in that Verifying the data to be verified based on the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result, including: Determining a first value of a first parameter to be verified of the business association relationship according to the data to be verified; Determining a second value of a second parameter to be verified of the business association relationship according to the data to be verified; A verification result of the data to be verified is determined according to the first value and the second value.
3. The method according to claim 2, characterized in that Determining a verification result of the data to be verified according to the first value and the second value includes: Performing a logical judgment based on the first value and the second value to determine a size comparison relationship; The verification result of the data to be verified is determined based on the size comparison relationship and the business association relationship.
4. The method according to claim 3, characterized in that Determining the verification result of the data to be verified based on the size comparison relationship and the business association relationship includes: If the size comparison relationship and the business association relationship are consistent, then the verification result of the data to be verified is determined to be normal; If the size comparison relationship and the business association relationship are inconsistent, it is determined that the verification result of the data to be verified is abnormal.
5. The method according to claim 4, characterized in that If the size comparison relationship and the business association relationship are inconsistent, then after determining that the verification result of the data to be verified is abnormal, the method includes: According to the abnormal verification result, a data abnormality warning is triggered; The verification results are visually displayed on the front-end page.
6. The method according to claim 1, characterized in that Determining at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships includes: Determine a correlation coefficient based on a matching result between the content field of the candidate business association relationship and the content field of the data to be verified; At least one business association relationship matching the data to be verified is determined from the candidate business association relationships according to the correlation coefficient.
7. The method according to claim 1, characterized in that The candidate business association relationships include: If the first parameter to be verified is the total power capacity of the access device, and the second parameter to be verified is the sum of the total operating power capacity and the equipment outage capacity, then the candidate service association relationship is that the total power capacity of the access device is greater than the sum of the total operating power capacity and the equipment outage capacity; If the first parameter to be verified is the total power capacity in operation and the second parameter to be verified is the total power load, then the candidate business association relationship is that the total power capacity in operation is greater than the total power load; If the first parameter to be verified is the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment, and the second parameter to be verified is the number of connected devices, then the candidate service association relationship is that the sum of the number of communication-interrupted devices, the number of standby devices, the number of normally operating devices, the number of load-limited operating devices, the number of fault-stopped devices, and the number of stopped devices of the same type of equipment is equal to the number of connected devices; If the first parameter to be verified is the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment, and the second parameter to be verified is the number of in-operation devices, then the candidate service association relationship is that the sum of the number of standby devices, the number of normal operating devices, and the number of load-limited operating devices of the same type of equipment is equal to the number of in-operation devices; If the first parameter to be verified is the sum of the number of faulty and shut down devices and the number of shut down devices of the same type, and the second parameter to be verified is the number of shut down devices, then the candidate business association relationship is that the sum of the number of faulty and shut down devices and the number of shut down devices of the same type is equal to the number of shut down devices; If the first parameter to be verified is the difference between the average device power capacity and the device power capacity, and the second parameter to be verified is a preset threshold, then the candidate business association relationship is that the difference between the average device power capacity and the device power capacity is less than the preset threshold, and the average device power capacity is the ratio of the total operating power capacity to the number of operating devices.
8. A data verification device, characterized in that: include: A data determination module is used to determine the association relationship between the data to be verified and the candidate services of the target power system, wherein the data to be verified is the time-series measurement point data of the power system; The candidate business association relationship is determined based on the power capacity and the number of devices related to the business in the power system; the candidate business association relationship includes a business logic relationship between a first parameter to be verified and a second parameter to be verified; a business association relationship determination module, configured to determine at least one business association relationship that matches the data to be verified from the candidate business association relationships based on the power capacity and the number of devices of the candidate business association relationships; The verification result determination module is used to verify the data to be verified based on the first parameter to be verified and the second parameter to be verified of the business association relationship to obtain a verification result.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the data verification method according to any one of claims 1 to 7 is implemented.
10. A storage medium storing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to perform the data verification method according to any one of claims 1 to 7.