CN108022046A - A kind of electric power system data method for evaluating quality, storage medium and equipment - Google Patents
A kind of electric power system data method for evaluating quality, storage medium and equipment Download PDFInfo
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- CN108022046A CN108022046A CN201711265908.5A CN201711265908A CN108022046A CN 108022046 A CN108022046 A CN 108022046A CN 201711265908 A CN201711265908 A CN 201711265908A CN 108022046 A CN108022046 A CN 108022046A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a kind of electric power system data method for evaluating quality, storage medium and equipment, the described method includes：Obtain the metric data in the data window of preset time period；Calculate the variance of the metric data in the preset time period；The variance and the first predetermined threshold value are contrasted, obtain comparing result；According to comparing result, the quality of the metric data is assessed.The present invention effectively can assess the quality of electric power data, prevent residual error is flooded from being shifted with residual error.
Description
Technical field
The present invention relates to technical field of electric power, more particularly to a kind of method for evaluating quality of metric data, storage medium and
Equipment.
Background technology
The quality of the electric power data of electric system especially metric data, is effective reference index of Operation of Electric Systems,
The quality height of metric data directly affects Power system state estimation efficiency and as a result, the quality of assessment metric data is electricity
The important component of Force system state estimation.
The detection to metric data mainly has two methods at present：When detected after estimation, after completion status estimation
To metric data residual error, and it is detected after carrying out proper treatment to the residual error, but this method calculation amount is larger, and there are residual error
The phenomenon flooded, can reduce the sensitivity of detection；Second, detection before estimation, the value of metric data is predicted to obtain measure it is residual
Difference, is detected according to the dependency relation of the measurement residuals, but this method detection difficult, and believing redundancy in a dynamic system
Breath is under-utilized.
The content of the invention
For in the prior art the defects of, the present invention provides a kind of electric power system data method for evaluating quality, storage medium
And equipment, effectively the quality of electric power data can be assessed, prevent residual error is flooded from being shifted with residual error.
In a first aspect, the present invention provides a kind of electric power system data method for evaluating quality, the described method includes：
Obtain the metric data in the data window of preset time period；
Calculate the variance of the metric data in the preset time period；
The variance and the first predetermined threshold value are contrasted, obtain comparing result；
According to comparing result, the quality of the metric data is assessed.
Further, it is described according to comparing result, the quality of the metric data is assessed, is specifically included：If comparing result
Show that the variance is more than the first predetermined threshold value, then it is quality data to assess the metric data.
Further, it is described according to comparing result, the quality of the metric data is assessed, is further included：
If comparing result shows that the variance is not more than the first predetermined threshold value, by no more than the measurement of the first predetermined threshold value
Data are as suspicious data；
Suspicious data is stored in suspicious data storehouse, and detects the correlation between each suspicious data and other data；
If correlation is big, the suspicious data is quality data, if correlation is small, the suspicious data is low-quality
Measure data.
Further, the correlation detected between each suspicious data and other data, specifically includes：
Calculate the related coefficient between each suspicious data and other data；
Compare the size of related coefficient absolute value and the second predetermined threshold value, and then judge each suspicious data and other data
Between correlation size.
Further, according to comparing result, judge the size of the correlation between each suspicious data and other data, have
Body includes：
If related coefficient absolute value is not less than the second predetermined threshold value, judge between the suspicious data and other data
Correlation is big；
If related coefficient absolute value is less than the second predetermined threshold value, the phase between the suspicious data and other data is judged
Guan Xing little.
Second aspect, present invention also offers a kind of computer-readable recording medium, is stored thereon with computer program, should
Following steps are realized when program is executed by processor：
Obtain the metric data in the data window of preset time period；
Calculate the variance of the metric data in the preset time period；
The variance and the first predetermined threshold value are contrasted, obtain comparing result；
According to comparing result, the quality of the metric data is assessed.
The third aspect, present invention also offers a kind of computer equipment, including memory, processor and is stored in memory
Computer program that is upper and can running on a processor, the processor realize following steps when performing described program：
Obtain the metric data in the data window of preset time period；
Calculate the variance of the metric data in the preset time period；
The variance and the first predetermined threshold value are contrasted, obtain comparing result；
According to comparing result, the quality of the metric data is assessed.
As shown from the above technical solution, the present invention provide a kind of electric power system data method for evaluating quality, storage medium and
Equipment, the variance based on metric data carry out quality evaluation, effectively the quality of electric power data can be assessed, prevented residual
Difference is flooded to be shifted with residual error.
Brief description of the drawings
Fig. 1 shows the flow diagram of electric power system data method for evaluating quality provided by the invention.
Embodiment
The embodiment of technical solution of the present invention is described in detail below in conjunction with attached drawing.Following embodiments are only used for
Clearly illustrate technical scheme, therefore be intended only as example, and the protection of the present invention cannot be limited with this
Scope.
Embodiment one
Fig. 1 shows the flow diagram for the electric power system data method for evaluating quality that the embodiment of the present invention one provides.Such as
Shown in Fig. 1, the described method includes：
Step S1, obtains the metric data in the data window of preset time period (time window).
The time series set of electrical power system metric data is represented by：
Z=[zi(k)]+[vi(k)] (i, j=1,2 ..., M)
Wherein, k is markers, zi(k) it is i-th of measurement time series, vi(k) it is measurement noise.
Certain traveling time window is chosen, the covariance matrix for calculating each variable in above formula is：
Q=cov (Z)=E [Z, ZT]
Each element is in n moment covariance matrixes：
Wherein, N is length of time series,For average value of i-th of measurement in time window, qii(n) it is i-th
A measurement is in the auto-variance at n moment, qij(n) it is the covariance of i-th of measurement and j-th of measurement at the n moment.
Step S2, calculates the variance of the metric data in the preset time period.
The variance of metric data is that detection measures the quality of data and abnormal efficiency index, its calculation formula is：
Step S3, by the variances sigmaiContrasted with the first predetermined threshold value, obtain comparing result.
For the measurement of each metric data, a threshold value is pre-set as the first predetermined threshold value, by step S2
The variance being calculated is contrasted with first predetermined threshold value, compares both sizes, can evaluation quantity according to both sizes
Survey the quality of data.
First predetermined threshold value can be set according to actual conditions.
Step S4, according to comparing result, assesses the quality of the metric data.
Step S4 is specifically included：If comparing result shows that the variance is more than the first predetermined threshold value, the measurement is assessed
Data are quality data；If comparing result shows that the variance is not more than the first predetermined threshold value, will be preset no more than first
The metric data of threshold value is as suspicious data；Suspicious data is stored in suspicious data storehouse, and detects each suspicious data and its
Correlation between its data；If correlation is big, the suspicious data is quality data, if correlation is small, it is described can
It is low quality data to doubt data.
Wherein, the correlation between each suspicious data and other data is detected, is detected especially by related coefficient, is had
Body includes：The related coefficient of each suspicious data and other suspicious datas in suspicious data storehouse is calculated, by related coefficient absolute value
Contrasted with the second predetermined threshold value；According to comparing result, correlation between each suspicious data and other data is judged
Size.
Wherein related coefficient is represented by：
Wherein, qij(k) be metric data covariance matrix in each element the k moment value (i, j=1,2 ..., M, j ≠
i)。
Wherein, the second predetermined threshold value is preferably 1.
Specifically, if related coefficient absolute value is greater than or equal to 1, judge between the suspicious data and other data
Correlation is big, and such case is typically as caused by measurement rough error；If related coefficient absolute value is less than 1, judge described suspicious
Correlation between data and other data is small, and such case is typically as caused by changing operation states of electric power system.
Based on above content, the technique effect that the embodiment of the present invention one can be realized is：Pass through metric data auto-variance
The change of related system between change and multiple metric data, can more accurately assess the quality of data of electric system,
Prevent residual error is flooded from being shifted with residual error.
Embodiment two
To the embodiment of the present invention one accordingly, the embodiment of the present invention two provides a kind of computer-readable recording medium, thereon
Computer program (instruction) is stored with, which realizes following steps when being executed by processor：
Obtain the metric data in the data window of preset time period；
Calculate the variance of the metric data in the preset time period；
The variance and the first predetermined threshold value are contrasted, obtain comparing result；
According to comparing result, the quality of the metric data is assessed.
Above-mentioned storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), deposit at random
Access to memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.
Above-mentioned specific limit on computer-readable recording medium may refer to embodiment one, and details are not described herein.
Embodiment three
To the embodiment of the present invention one accordingly, the embodiment of the present invention three provides a kind of computer equipment, including memory, place
The computer program managed device and storage on a memory and can run on a processor, the processor perform real during described program
Existing following steps：
Obtain the metric data in the data window of preset time period；
Calculate the variance of the metric data in the preset time period；
The variance and the first predetermined threshold value are contrasted, obtain comparing result；
According to comparing result, the quality of the metric data is assessed.
Above-mentioned specific limit on computer equipment may refer to embodiment one, and details are not described herein.
Without conflicting with each other, those skilled in the art can be by the different embodiments described in this specification
Or example and different embodiments or exemplary feature are combined and combine.
It should be noted that the present invention Figure of description in block diagram and/or flow chart in each square frame and frame
The combination of figure and/or the square frame in flow chart, can use function or the dedicated hardware based system of action as defined in performing
To realize, or can be realized with the combination that specialized hardware is instructed with acquisition machine.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Pipe is described in detail the present invention with reference to foregoing embodiments, it will be understood by those of ordinary skill in the art that：Its according to
Can so modify to the technical solution described in foregoing embodiments, either to which part or all technical characteristic into
Row equivalent substitution；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme, it should all cover among the claim of the present invention and the scope of specification.
Claims (7)
- A kind of 1. electric power system data method for evaluating quality, it is characterised in that the described method includes：Obtain the metric data in the data window of preset time period；Calculate the variance of the metric data in the preset time period；The variance and the first predetermined threshold value are contrasted, obtain comparing result；According to comparing result, the quality of the metric data is assessed.
- 2. Data Quality Assessment Methodology according to claim 1, it is characterised in that it is described according to comparing result, assess institute The quality of metric data is stated, is specifically included：If comparing result shows that the variance is more than the first predetermined threshold value, the amount is assessed Survey data are quality data.
- 3. Data Quality Assessment Methodology according to claim 2, it is characterised in that it is described according to comparing result, assess institute The quality of metric data is stated, is further included：If comparing result shows that the variance is not more than the first predetermined threshold value, by no more than the metric data of the first predetermined threshold value As suspicious data；Suspicious data is stored in suspicious data storehouse, and detects the correlation between each suspicious data and other data；If correlation is big, the suspicious data is quality data, if correlation is small, the suspicious data is low quality number According to.
- 4. Data Quality Assessment Methodology according to claim 3, it is characterised in that described to detect each suspicious data and its Correlation between its data, specifically includes：Calculate the related coefficient between each suspicious data and other data；Compare the size of related coefficient absolute value and the second predetermined threshold value, and then judge between each suspicious data and other data Correlation size.
- 5. Data Quality Assessment Methodology according to claim 4, it is characterised in that according to comparing result, judgement each may be used The size of the correlation between data and other data is doubted, is specifically included：If related coefficient absolute value is not less than the second predetermined threshold value, judge related between the suspicious data and other data Property is big；If related coefficient absolute value is less than the second predetermined threshold value, the correlation between the suspicious data and other data is judged It is small.
- 6. a kind of computer-readable recording medium, is stored thereon with computer program, it is characterised in that the program is held by processor Following steps are realized during row：Obtain the metric data in the data window of preset time period；Calculate the variance of the metric data in the preset time period；The variance and the first predetermined threshold value are contrasted, obtain comparing result；According to comparing result, the quality of the metric data is assessed.
- 7. a kind of computer equipment, including memory, processor and storage are on a memory and the meter that can run on a processor Calculation machine program, it is characterised in that the processor realizes following steps when performing described program：Obtain the metric data in the data window of preset time period；Calculate the variance of the metric data in the preset time period；The variance and the first predetermined threshold value are contrasted, obtain comparing result；According to comparing result, the quality of the metric data is assessed.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109308589A (en) * | 2018-11-20 | 2019-02-05 | 国网山西省电力公司 | Grid automation data quality monitoring method, storage medium, terminal device and system |
| CN109800191A (en) * | 2019-01-25 | 2019-05-24 | 中科驭数（北京）科技有限公司 | The method and device of covariance for sequence of calculation data |
| CN110889650A (en) * | 2019-12-16 | 2020-03-17 | 国网青海省电力公司经济技术研究院 | Quantitative evaluation method and device for output stationarity of multi-element new energy power system |
| CN111797088A (en) * | 2020-09-10 | 2020-10-20 | 智者四海（北京）技术有限公司 | Data quality inspection method and device |
| CN112101447A (en) * | 2020-09-10 | 2020-12-18 | 北京百度网讯科技有限公司 | Data set quality evaluation method, device, equipment and storage medium |
| CN113779150A (en) * | 2021-09-14 | 2021-12-10 | 杭州数梦工场科技有限公司 | Data quality evaluation method and device |
| CN116505976A (en) * | 2023-06-29 | 2023-07-28 | 无锡量子感知研究所 | Data transmission parameter determining method and device and electronic equipment |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109308589A (en) * | 2018-11-20 | 2019-02-05 | 国网山西省电力公司 | Grid automation data quality monitoring method, storage medium, terminal device and system |
| CN109308589B (en) * | 2018-11-20 | 2021-09-21 | 国网山西省电力公司 | Power grid automation data quality monitoring method, storage medium, terminal equipment and system |
| CN109800191A (en) * | 2019-01-25 | 2019-05-24 | 中科驭数（北京）科技有限公司 | The method and device of covariance for sequence of calculation data |
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| CN110889650A (en) * | 2019-12-16 | 2020-03-17 | 国网青海省电力公司经济技术研究院 | Quantitative evaluation method and device for output stationarity of multi-element new energy power system |
| CN111797088A (en) * | 2020-09-10 | 2020-10-20 | 智者四海（北京）技术有限公司 | Data quality inspection method and device |
| CN112101447A (en) * | 2020-09-10 | 2020-12-18 | 北京百度网讯科技有限公司 | Data set quality evaluation method, device, equipment and storage medium |
| CN112101447B (en) * | 2020-09-10 | 2024-04-16 | 北京百度网讯科技有限公司 | Quality evaluation method, device, equipment and storage medium for data set |
| CN113779150A (en) * | 2021-09-14 | 2021-12-10 | 杭州数梦工场科技有限公司 | Data quality evaluation method and device |
| CN116505976A (en) * | 2023-06-29 | 2023-07-28 | 无锡量子感知研究所 | Data transmission parameter determining method and device and electronic equipment |
| CN116505976B (en) * | 2023-06-29 | 2024-02-13 | 无锡量子感知研究所 | Data transmission parameter determining method and device and electronic equipment |
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Application publication date: 20180511 |