CN111639141B - Data testing method and device and computer terminal - Google Patents
Data testing method and device and computer terminal Download PDFInfo
- Publication number
- CN111639141B CN111639141B CN202010455352.1A CN202010455352A CN111639141B CN 111639141 B CN111639141 B CN 111639141B CN 202010455352 A CN202010455352 A CN 202010455352A CN 111639141 B CN111639141 B CN 111639141B
- Authority
- CN
- China
- Prior art keywords
- data
- parameter
- substation
- track
- substation operation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2477—Temporal data queries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a data testing method, a device and a computer terminal, wherein the data testing method comprises the steps of firstly, after substation operation data are acquired, extracting a data tag sequence of the substation operation data, determining a plurality of groups of operation parameter sections, secondly, comparing each group of operation parameter sections of the substation operation data with each reference parameter section in a preset parameter set to obtain a comparison result, then determining a data state track of the substation operation data according to parameter characteristics corresponding to a target operation parameter section of which the comparison result meets a substation state stability condition, and finally, testing equipment loss data of the substation based on the substation operation data and the determined data state track of the substation operation data to obtain a testing result. Therefore, the accuracy and the reliability of the operation data test of the transformer substation can be improved, and whether the transformer substation fails or not can be accurately and reliably detected.
Description
Technical Field
The disclosure relates to the technical field of substation data processing, in particular to a data testing method, a data testing device and a computer terminal.
Background
With the development of technology, the types and the number of electric equipment are more and more, and the load demands of the electric equipment facing the power grid are also higher and higher. In this case, the grid may be in operation failure during operation, thereby causing production accidents. In the running process of the power grid, the running state of the transformer substation directly relates to safe and reliable running of the power grid, and in order to monitor the running state of the power grid, real-time test is required to be carried out on the running data of the transformer substation, so that whether the transformer substation has faults or not is detected. However, in practical application, the accuracy and reliability of the method for testing the data of the transformer substation are poor.
Disclosure of Invention
In order to improve the above technical problems in the related art, the present disclosure provides a data testing method, a data testing device and a computer terminal.
A data testing method applied to a computer terminal in communication with a substation, the method comprising:
after the substation operation data stored in real time by the substation are collected, extracting a data tag sequence of the substation operation data, and carrying out data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments; the data tag sequence is a sequence formed by equipment tags related to target electric equipment in the substation operation data;
comparing each group of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each level of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next level of comparison thread so as to be compared based on the next parameter weight;
Determining a data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter segment, the comparison result of which accords with the substation state stability condition, of the substation operation data;
testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a test result; the test result is used for representing the probability of faults of the transformer substation in a set period.
Optionally, extracting a data tag sequence of the substation operation data, and performing data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments, including:
listing data tags in the substation operation data, determining tag weights of the data tags, and sequencing the data tags according to the sequence of the tag weights from high to low to obtain the data tag sequence;
acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet;
Under the condition that a plurality of data sets are contained in the effective data packet corresponding to the substation operation data, determining authority contrast between the data sets of the substation operation data under the effective data packet according to the data sets of the substation operation data under the redundant data packet and authority information thereof, and splicing the data sets under the effective data packet based on the authority contrast between the data sets; setting adjustment priority for the target data set obtained by splicing according to the data set of the substation operation data under the redundant data packet and the authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority;
and carrying out segmentation processing on the data set under the effective data packet based on the node attribute of the target node with the segmentation mark corresponding to the sequence track in the data tag sequence to obtain a plurality of groups of operation parameter segments.
Optionally, determining the data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter segment, the comparison result of the substation operation data meets the substation state stability condition, includes:
Extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter section corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation;
extracting time sequence characteristics of the target operation parameter section according to a set time step;
generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to a target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights;
extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table, and determining the table object with the minimum table weight in the parameter table as a reference table object;
mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the time sequence feature and the target operation parameter segment based on the object attribute information and the mapping attribute information;
acquiring object track information in the reference table object by taking the mapping attribute information as an information template, mapping the object track information into the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining mapping track information corresponding to the object track information in the table object where the object attribute information is located;
And listing the track nodes and the connection information in the mapping track information, and generating a data state track of the substation operation data according to the track nodes and the connection information.
Optionally, testing the equipment loss data of the substation based on the substation operation data and the determined data state track of the substation operation data to obtain a test result, including:
determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data;
determining an update weight value of the current loss data in a preset time period based on a first update frequency of the current loss data in the preset time period and a second update frequency of each target loss data in the preset time period aiming at the current loss data in the target loss data;
and determining an updated risk coefficient of the current loss data between two adjacent set time periods according to updated weight values of the current loss data in two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
A data testing device for use with a computer terminal in communication with a substation, the device comprising:
the data segmentation module is used for extracting a data tag sequence of the substation operation data after the substation operation data stored in real time by the substation is acquired, and carrying out data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments; the data tag sequence is a sequence formed by equipment tags related to target electric equipment in the substation operation data;
the parameter comparison module is used for comparing each group of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each level of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next level of comparison thread so as to be compared based on the next parameter weight;
The track determining module is used for determining a data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter section, which accords with the substation state stability condition, of the comparison result of the substation operation data;
the data testing module is used for testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a testing result; the test result is used for representing the probability of faults of the transformer substation in a set period.
Optionally, the data segmentation module is configured to:
listing data tags in the substation operation data, determining tag weights of the data tags, and sequencing the data tags according to the sequence of the tag weights from high to low to obtain the data tag sequence;
acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet;
Under the condition that a plurality of data sets are contained in the effective data packet corresponding to the substation operation data, determining authority contrast between the data sets of the substation operation data under the effective data packet according to the data sets of the substation operation data under the redundant data packet and authority information thereof, and splicing the data sets under the effective data packet based on the authority contrast between the data sets; setting adjustment priority for the target data set obtained by splicing according to the data set of the substation operation data under the redundant data packet and the authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority;
and carrying out segmentation processing on the data set under the effective data packet based on the node attribute of the target node with the segmentation mark corresponding to the sequence track in the data tag sequence to obtain a plurality of groups of operation parameter segments.
Optionally, the track determining module is configured to:
extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter section corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation;
Extracting time sequence characteristics of the target operation parameter section according to a set time step;
generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to a target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights;
extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table, and determining the table object with the minimum table weight in the parameter table as a reference table object;
mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the time sequence feature and the target operation parameter segment based on the object attribute information and the mapping attribute information;
acquiring object track information in the reference table object by taking the mapping attribute information as an information template, mapping the object track information into the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining mapping track information corresponding to the object track information in the table object where the object attribute information is located;
And listing the track nodes and the connection information in the mapping track information, and generating a data state track of the substation operation data according to the track nodes and the connection information.
Optionally, the data testing module is configured to:
determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data;
determining an update weight value of the current loss data in a preset time period based on a first update frequency of the current loss data in the preset time period and a second update frequency of each target loss data in the preset time period aiming at the current loss data in the target loss data;
and determining an updated risk coefficient of the current loss data between two adjacent set time periods according to updated weight values of the current loss data in two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
A computer terminal comprising a processor and a memory in communication with each other, said processor being adapted to retrieve a computer program from said memory, said computer program being executed to implement the method as described above.
A computer readable storage medium having stored thereon a computer program which, when run, implements the method described above.
According to the technical scheme provided by the embodiment of the disclosure, firstly, a data tag sequence of the substation operation data is extracted after the substation operation data is acquired, a plurality of groups of operation parameter sections are determined, secondly, each group of operation parameter sections of the substation operation data is compared with each reference parameter section in a preset parameter set to obtain a comparison result, then, a data state track of the substation operation data is determined according to the comparison result which accords with the parameter characteristics corresponding to the target operation parameter sections of the substation state stable condition, and finally, the equipment loss data of the substation is tested based on the substation operation data and the determined data state track of the substation operation data to obtain a test result. Therefore, the accuracy and the reliability of the operation data test of the transformer substation can be improved, and whether the transformer substation fails or not can be accurately and reliably detected.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram of a data testing system according to the present disclosure.
FIG. 2 is a flow chart illustrating a method of data testing according to an exemplary embodiment.
Fig. 3 is a block diagram illustrating a data testing apparatus according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
In order to solve the technical problems of poor accuracy and reliability of a method for testing data of a transformer substation in the prior art, the embodiment of the application provides a data testing method, a data testing device and a computer terminal.
Referring first to fig. 1, a block diagram of a data testing system 100 according to an embodiment of the present application is provided, where the data testing system 100 may include a computer terminal 200 and a transformer substation 300, the computer terminal is in communication with the transformer substation 300, the transformer substation 300 is connected to a power grid transmission line in a target area, and the transformer substation 300 is configured to perform power interaction with electric equipment in the target area through the power grid transmission line.
Referring to fig. 2 in combination, a flowchart of a data testing method according to an embodiment of the present invention may be applied to the computer terminal 200 in fig. 1, and may specifically include the device tags described in the following steps.
Step 210, after collecting substation operation data stored in real time by the substation, extracting a data tag sequence of the substation operation data, and performing data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments; the data tag sequence is a sequence formed by device tags related to target electric equipment in the substation operation data.
Step 220, comparing each group of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each stage of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next stage of comparison thread so as to perform comparison based on the next parameter weight.
And 230, determining a data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter segment, which accords with the substation state stability condition, of the comparison result of the substation operation data.
Step 240, testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a test result; the test result is used for representing the probability of faults of the transformer substation in a set period.
When the method described in the step S210-step S240 is applied, firstly, after the substation operation data is collected, a data tag sequence of the substation operation data is extracted, a plurality of groups of operation parameter segments are determined, secondly, each group of operation parameter segments of the substation operation data is compared with each reference parameter segment in a preset parameter set to obtain a comparison result, then, a data state track of the substation operation data is determined according to the comparison result, which corresponds to a parameter feature corresponding to a target operation parameter segment of the substation state stability condition, and finally, the equipment loss data of the substation is tested based on the substation operation data and the determined data state track of the substation operation data to obtain a test result. Therefore, the accuracy and the reliability of the operation data test of the transformer substation can be improved, and whether the transformer substation fails or not can be accurately and reliably detected.
In an alternative embodiment, in order to accurately segment the substation operation data, in step S210, a data tag sequence of the substation operation data is extracted, and based on the data tag sequence, the substation operation data is subjected to data segmentation processing to obtain multiple sets of operation parameter segments, which may specifically include what is described in the following steps.
Step S211, listing the data tags in the substation operation data, determining the tag weight of each data tag, and sequencing the data tags according to the sequence of the tag weights from large to small to obtain the data tag sequence.
Step S212, acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; and adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet.
Step S213, when a plurality of data sets are included in the valid data packet corresponding to the substation operation data, determining authority contrast between each data set of the substation operation data under the valid data packet according to the data set of the substation operation data under the redundant data packet and authority information thereof, and splicing each data set under the valid data packet based on the authority contrast between each data set; and setting adjustment priority for the target data set obtained by splicing according to the data set of the substation operation data under the redundant data packet and the authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority.
Step S214, performing segment processing on the data set under the valid data packet based on the node attribute of the target node with the segment identifier corresponding to the sequence track in the data tag sequence to obtain multiple groups of operation parameter segments.
It can be understood that, through the steps S211 to S214, the valid data packet of the substation operation data and the data set under the redundant data packet can be adjusted and updated, so that the data set under the valid data packet can be segmented based on the node attribute of the target node with the segment identifier corresponding to the sequence track in the data tag sequence to obtain multiple groups of operation parameter segments, thereby accurately segmenting the substation operation data.
In an alternative embodiment, to ensure continuity of the data state track and avoid occurrence of faults in the data state track, in step S230, the data state track of the substation operation data is determined according to the parameter characteristics corresponding to the target operation parameter segment of the substation state stability condition according to the comparison result of the substation operation data, which may specifically include what is described in the following steps.
Step S231, extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter segment corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation.
Step S232, extracting the time sequence characteristics of the target operation parameter segment according to the set time step.
Step S233, generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to the target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights.
Step S234, extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table and determining the table object with the minimum table weight in the parameter table as a reference table object.
Step S235, mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the timing feature and the target operation parameter segment based on the object attribute information and the mapping attribute information.
Step S236, using the mapping attribute information as an information template to obtain object track information in the reference table object, mapping the object track information to the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining the mapping track information corresponding to the object track information in the table object where the object attribute information is located.
And step S237, the track nodes and the connection information in the mapping track information are listed, and the data state track of the substation operation data is generated according to the track nodes and the connection information.
It will be appreciated that, by the description of the above steps S231 to S237, continuity of the data state track can be ensured, and occurrence of faults in the data state track can be avoided.
In the implementation, in order to ensure the accuracy and reliability of the test result, in step S240, the device loss data of the substation is tested to obtain the test result based on the substation operation data and the determined data state track of the substation operation data, which may specifically include the following steps.
And step S241, determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data.
Step S242, for the current loss data in the target loss data, determines an update weight value of the current loss data in the preset period based on a first update frequency of the current loss data in the preset period and a second update frequency of each target loss data in the preset period.
Step S243, determining an updated risk coefficient of the current loss data between two adjacent set time periods according to the updated weight values of the current loss data in the two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
By the above-described contents of step S241 to step S243, the accuracy and reliability of the test result can be ensured.
Referring to fig. 3 in combination, there is provided a data testing apparatus 210 applied to a computer terminal in communication with a substation, the apparatus 210 including:
The data segmentation module 211 is configured to extract a data tag sequence of the substation operation data after collecting the substation operation data stored in real time in the substation, and perform data segmentation processing on the substation operation data based on the data tag sequence to obtain multiple groups of operation parameter segments; the data tag sequence is a sequence formed by equipment tags related to target electric equipment in the substation operation data;
the parameter comparison module 212 is configured to compare each set of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each level of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next level of comparison thread so as to be compared based on the next parameter weight;
The track determining module 213 is configured to determine a data state track of the substation operation data according to a parameter feature corresponding to a target operation parameter segment of the substation state stability condition according to a comparison result of the substation operation data;
the data testing module 214 is configured to test the equipment loss data of the substation based on the substation operation data and the determined data state track of the substation operation data to obtain a test result; the test result is used for representing the probability of faults of the transformer substation in a set period.
Optionally, the data segmentation module 211 is configured to:
listing data tags in the substation operation data, determining tag weights of the data tags, and sequencing the data tags according to the sequence of the tag weights from high to low to obtain the data tag sequence;
acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet;
Under the condition that a plurality of data sets are contained in the effective data packet corresponding to the substation operation data, determining authority contrast between the data sets of the substation operation data under the effective data packet according to the data sets of the substation operation data under the redundant data packet and authority information thereof, and splicing the data sets under the effective data packet based on the authority contrast between the data sets; setting adjustment priority for the target data set obtained by splicing according to the data set of the substation operation data under the redundant data packet and the authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority;
and carrying out segmentation processing on the data set under the effective data packet based on the node attribute of the target node with the segmentation mark corresponding to the sequence track in the data tag sequence to obtain a plurality of groups of operation parameter segments.
Optionally, the track determining module 213 is configured to:
extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter section corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation;
Extracting time sequence characteristics of the target operation parameter section according to a set time step;
generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to a target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights;
extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table, and determining the table object with the minimum table weight in the parameter table as a reference table object;
mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the time sequence feature and the target operation parameter segment based on the object attribute information and the mapping attribute information;
acquiring object track information in the reference table object by taking the mapping attribute information as an information template, mapping the object track information into the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining mapping track information corresponding to the object track information in the table object where the object attribute information is located;
And listing the track nodes and the connection information in the mapping track information, and generating a data state track of the substation operation data according to the track nodes and the connection information.
Optionally, the data testing module 214 is configured to:
determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data;
determining an update weight value of the current loss data in a preset time period based on a first update frequency of the current loss data in the preset time period and a second update frequency of each target loss data in the preset time period aiming at the current loss data in the target loss data;
and determining an updated risk coefficient of the current loss data between two adjacent set time periods according to updated weight values of the current loss data in two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
On the basis of the above, there is also provided a computer terminal comprising a processor and a memory in communication with each other, the processor being adapted to retrieve a computer program from the memory, the computer program being executed to implement the method as described above.
Further, a computer readable storage medium is provided, on which a computer program is stored, which computer program, when run, implements the above-mentioned method.
It is to be understood that the invention is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (6)
1. A data testing method, applied to a computer terminal in communication with a substation, the method comprising:
after the substation operation data stored in real time by the substation are collected, extracting a data tag sequence of the substation operation data, and carrying out data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments; the data tag sequence is a sequence formed by equipment tags related to target electric equipment in the substation operation data;
comparing each group of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each level of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next level of comparison thread so as to be compared based on the next parameter weight;
Determining a data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter segment, the comparison result of which accords with the substation state stability condition, of the substation operation data;
testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a test result; the test result is used for representing the probability of faults of the transformer substation in a set period;
the method for determining the data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter section, the comparison result of the substation operation data meets the substation state stability condition, comprises the following steps:
extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter section corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation;
extracting time sequence characteristics of the target operation parameter section according to a set time step;
generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to a target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights;
Extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table, and determining the table object with the minimum table weight in the parameter table as a reference table object;
mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the time sequence feature and the target operation parameter segment based on the object attribute information and the mapping attribute information;
acquiring object track information in the reference table object by taking the mapping attribute information as an information template, mapping the object track information into the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining mapping track information corresponding to the object track information in the table object where the object attribute information is located;
listing track nodes and connection information in the mapping track information and generating a data state track of the substation operation data according to the track nodes and the connection information;
the method for testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a test result comprises the following steps:
Determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data;
determining an update weight value of the current loss data in a preset time period based on a first update frequency of the current loss data in the preset time period and a second update frequency of each target loss data in the preset time period aiming at the current loss data in the target loss data;
and determining an updated risk coefficient of the current loss data between two adjacent set time periods according to updated weight values of the current loss data in two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
2. The method of claim 1, wherein extracting the data tag sequence of the substation operation data and performing data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments, comprises:
listing data tags in the substation operation data, determining tag weights of the data tags, and sequencing the data tags according to the sequence of the tag weights from high to low to obtain the data tag sequence;
Acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet;
under the condition that a plurality of data sets are contained in the effective data packet corresponding to the substation operation data, determining authority contrast between the data sets of the substation operation data under the effective data packet according to the data sets of the substation operation data under the redundant data packet and authority information thereof, and splicing the data sets under the effective data packet based on the authority contrast between the data sets; setting adjustment priority for a target data set obtained by splicing according to a data set of the substation operation data under the redundant data packet and authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority;
And carrying out segmentation processing on the data set under the effective data packet based on the node attribute of the target node with the segmentation mark corresponding to the sequence track in the data tag sequence to obtain a plurality of groups of operation parameter segments.
3. A data testing device for use with a computer terminal in communication with a substation, the device comprising:
the data segmentation module is used for extracting a data tag sequence of the substation operation data after the substation operation data stored in real time by the substation is acquired, and carrying out data segmentation processing on the substation operation data based on the data tag sequence to obtain a plurality of groups of operation parameter segments; the data tag sequence is a sequence formed by equipment tags related to target electric equipment in the substation operation data;
the parameter comparison module is used for comparing each group of operation parameter segments of the substation operation data with each reference parameter segment in a preset parameter set; the preset parameter set stores a plurality of groups of reference parameter segments and parameter weights corresponding to the reference parameter segments, wherein the reference parameter segments are state parameter sets of a power grid area where the target electric equipment is located; wherein if each set of operating parameter segments of the extracted substation operating data comprises a plurality of parameter weights, the comparison is made by: performing multi-level comparison according to priorities configured for the weights of the parameters in advance; in each level of comparison, only one parameter weight in each group of operation parameter segments is used for comparison, and the operation parameter segments meeting the preset conditions are input into a next level of comparison thread so as to be compared based on the next parameter weight;
The track determining module is used for determining a data state track of the substation operation data according to the parameter characteristics corresponding to the target operation parameter section, which accords with the substation state stability condition, of the comparison result of the substation operation data;
the data testing module is used for testing the equipment loss data of the transformer substation based on the transformer substation operation data and the determined data state track of the transformer substation operation data to obtain a testing result; the test result is used for representing the probability of faults of the transformer substation in a set period;
wherein, the orbit determination module is used for:
extracting a state evaluation coefficient of the comparison result, and determining a target operation parameter section corresponding to the state evaluation coefficient when the state evaluation coefficient reaches a preset state coefficient of the transformer substation;
extracting time sequence characteristics of the target operation parameter section according to a set time step;
generating a time sequence form corresponding to the time sequence feature and a parameter form corresponding to a target operation parameter segment, wherein the time sequence form and the parameter form respectively comprise a plurality of table objects with different form weights;
extracting object attribute information of the time sequence feature in one of the table objects of the time sequence table, and determining the table object with the minimum table weight in the parameter table as a reference table object;
Mapping the object attribute information into the reference table object to obtain mapping attribute information in the reference table object, and then generating a state switching list between the time sequence feature and the target operation parameter segment based on the object attribute information and the mapping attribute information;
acquiring object track information in the reference table object by taking the mapping attribute information as an information template, mapping the object track information into the table object where the object attribute information is located according to the logic information corresponding to the state switching list, and obtaining mapping track information corresponding to the object track information in the table object where the object attribute information is located;
listing track nodes and connection information in the mapping track information and generating a data state track of the substation operation data according to the track nodes and the connection information;
wherein, the data test module is used for:
determining loss coefficients corresponding to the equipment loss data, which are determined based on the substation operation data and the data state track, and weighting the equipment loss data by adopting the loss coefficients to obtain target loss data;
Determining an update weight value of the current loss data in a preset time period based on a first update frequency of the current loss data in the preset time period and a second update frequency of each target loss data in the preset time period aiming at the current loss data in the target loss data;
and determining an updated risk coefficient of the current loss data between two adjacent set time periods according to updated weight values of the current loss data in two adjacent preset time period intervals, and carrying out normalization processing on the updated risk coefficient to obtain the test result.
4. The apparatus of claim 3, wherein the data segmentation module is configured to:
listing data tags in the substation operation data, determining tag weights of the data tags, and sequencing the data tags according to the sequence of the tag weights from high to low to obtain the data tag sequence;
acquiring a sequence track of the data tag sequence and a plurality of data sets of the substation operation data; under the condition that the substation operation data contains redundant data groups according to the sequence track, determining authority contrast between each data set of the substation operation data under the effective data groups and each data set of the substation operation data under the redundant data groups according to the data sets of the substation operation data under the redundant data groups and authority information thereof; adjusting a data set with the minimum authority contrast of the substation operation data under the effective data packet and the data set under the redundant data packet to be under the redundant data packet;
Under the condition that a plurality of data sets are contained in the effective data packet corresponding to the substation operation data, determining authority contrast between the data sets of the substation operation data under the effective data packet according to the data sets of the substation operation data under the redundant data packet and authority information thereof, and splicing the data sets under the effective data packet based on the authority contrast between the data sets; setting adjustment priority for a target data set obtained by splicing according to a data set of the substation operation data under the redundant data packet and authority information thereof, and adjusting the target data set to a set position of the redundant data packet corresponding to the adjustment priority;
and carrying out segmentation processing on the data set under the effective data packet based on the node attribute of the target node with the segmentation mark corresponding to the sequence track in the data tag sequence to obtain a plurality of groups of operation parameter segments.
5. A computer terminal comprising a processor and a memory in communication with each other, said processor being adapted to retrieve a computer program from said memory, said computer program being executed to implement the method of any of the preceding claims 1-2.
6. A computer readable storage medium, characterized in that it has stored thereon a computer program, which, when run, implements the method of any of the preceding claims 1-2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010455352.1A CN111639141B (en) | 2020-05-26 | 2020-05-26 | Data testing method and device and computer terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010455352.1A CN111639141B (en) | 2020-05-26 | 2020-05-26 | Data testing method and device and computer terminal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111639141A CN111639141A (en) | 2020-09-08 |
| CN111639141B true CN111639141B (en) | 2023-08-15 |
Family
ID=72329948
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010455352.1A Active CN111639141B (en) | 2020-05-26 | 2020-05-26 | Data testing method and device and computer terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111639141B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115827453B (en) * | 2022-12-01 | 2023-09-08 | 中国兵器工业信息中心 | Reliability test section structure and test case generation method of networked software system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104361531A (en) * | 2014-11-14 | 2015-02-18 | 广东电网有限责任公司电力调度控制中心 | Identification method and system for high-risk failure equipment of substation automation system |
| CN105652113A (en) * | 2015-12-29 | 2016-06-08 | 安徽海兴泰瑞智能科技有限公司 | Power grid equipment performance perception and evaluation method |
| CN106528968A (en) * | 2016-10-31 | 2017-03-22 | 国网福建省电力有限公司 | Intelligent substation automatic dynamic simulation test method based on SSD file |
| CN107292490A (en) * | 2017-05-18 | 2017-10-24 | 国网浙江省电力公司杭州供电公司 | Trial operation substation operation risk evaluation system and appraisal procedure |
| CN108596459A (en) * | 2018-04-13 | 2018-09-28 | 广州供电局有限公司 | Substation's risk alarm method and system |
| CN109784777A (en) * | 2019-02-28 | 2019-05-21 | 西安交通大学 | Grid equipment state evaluating method based on timing information segment cloud measuring similarity |
| CN110110933A (en) * | 2019-05-10 | 2019-08-09 | 西南交通大学 | A kind of maintenance circle optimization method of intelligent substation protection system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7908357B2 (en) * | 2005-09-21 | 2011-03-15 | Battelle Memorial Institute | Methods and systems for detecting abnormal digital traffic |
| US9362746B2 (en) * | 2011-10-07 | 2016-06-07 | Cisco Technology, Inc. | Communication network topology management based on an associated electric grid topology |
| BR112015019262B8 (en) * | 2013-02-12 | 2022-07-05 | Headsight Inc | MOBILE MACHINE |
-
2020
- 2020-05-26 CN CN202010455352.1A patent/CN111639141B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104361531A (en) * | 2014-11-14 | 2015-02-18 | 广东电网有限责任公司电力调度控制中心 | Identification method and system for high-risk failure equipment of substation automation system |
| CN105652113A (en) * | 2015-12-29 | 2016-06-08 | 安徽海兴泰瑞智能科技有限公司 | Power grid equipment performance perception and evaluation method |
| CN106528968A (en) * | 2016-10-31 | 2017-03-22 | 国网福建省电力有限公司 | Intelligent substation automatic dynamic simulation test method based on SSD file |
| CN107292490A (en) * | 2017-05-18 | 2017-10-24 | 国网浙江省电力公司杭州供电公司 | Trial operation substation operation risk evaluation system and appraisal procedure |
| CN108596459A (en) * | 2018-04-13 | 2018-09-28 | 广州供电局有限公司 | Substation's risk alarm method and system |
| CN109784777A (en) * | 2019-02-28 | 2019-05-21 | 西安交通大学 | Grid equipment state evaluating method based on timing information segment cloud measuring similarity |
| CN110110933A (en) * | 2019-05-10 | 2019-08-09 | 西南交通大学 | A kind of maintenance circle optimization method of intelligent substation protection system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111639141A (en) | 2020-09-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111459700B (en) | Equipment fault diagnosis method, diagnosis device, diagnosis equipment and storage medium | |
| CN112731051B (en) | Single-ended fault positioning method and system for high-voltage direct-current transmission line of hybrid network | |
| CN111708785B (en) | Big data mining processing method and device and cloud platform | |
| US5627760A (en) | Method and apparatus for real time recursive parameter energy management system | |
| CN110601173B (en) | Distribution network topology identification method and device based on edge calculation | |
| CN111639141B (en) | Data testing method and device and computer terminal | |
| CN112330488A (en) | Power grid frequency situation prediction method based on transfer learning | |
| CN115345466A (en) | Power distribution network online evaluation system based on network frame topology and multi-source data fusion | |
| CN115618286A (en) | Transformer partial discharge type identification method, system, equipment, terminal and application | |
| CN112380340B (en) | Error data diagnosis method and system between main station, power plant and transformer substation | |
| CN111950448B (en) | High-voltage isolating switch fault state detection method and device based on machine vision | |
| CN114298188A (en) | Intelligent analysis method and system for power equipment faults | |
| CN110716101B (en) | Power line fault positioning method and device, computer and storage medium | |
| CN112685469A (en) | Business data analysis method and device based on Internet of things | |
| CN109299652B (en) | Model training method for image positioning, image positioning method and device | |
| CN112231981A (en) | Method for establishing large-scale electromagnetic transient simulation example | |
| CN117007912B (en) | Distribution network line power failure analysis method, device, equipment and storage medium | |
| CN115514621B (en) | Fault monitoring method, electronic device and storage medium | |
| CN116662060B (en) | Data processing method and system of sensor signal acquisition processing system | |
| CN112348282B (en) | Load prediction method and device | |
| CN110889613A (en) | Power grid system splitting risk analysis method based on SCADA big data | |
| JPH11252795A (en) | Power system condition determinator | |
| CN116467820A (en) | Automatic drawing method for power distribution grounding grid design diagram | |
| CN116821829A (en) | Transformer fault analysis method and device based on association rule analysis | |
| Gowtham et al. | Implementing Resiliency Upgrades on Power Distribution System Using Graph Theoretic Methods |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 650100 phase 4b, shenggaodacheng, Xishan District, Kunming City, Yunnan Province Applicant after: Li Yunxiang Address before: No. 206, Machang village, Machang village committee, Kuishan Town, Shizong County, Qujing City, Yunnan Province Applicant before: Li Yunxiang |
|
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230725 Address after: 430070 Hubei Province, Wuhan city Hongshan District Luoyu Road No. 546 Applicant after: HUBEI CENTRAL CHINA TECHNOLOGY DEVELOPMENT OF ELECTRIC POWER Co.,Ltd. Address before: 650100 phase 4b, shenggaodacheng, Xishan District, Kunming City, Yunnan Province Applicant before: Li Yunxiang |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |