CN104537271B - A kind of power distribution network bad data recognition method based on quality tab - Google Patents
A kind of power distribution network bad data recognition method based on quality tab Download PDFInfo
- Publication number
- CN104537271B CN104537271B CN201510030386.5A CN201510030386A CN104537271B CN 104537271 B CN104537271 B CN 104537271B CN 201510030386 A CN201510030386 A CN 201510030386A CN 104537271 B CN104537271 B CN 104537271B
- Authority
- CN
- China
- Prior art keywords
- score
- measurement
- rule
- voltage
- current
- 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
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000005259 measurement Methods 0.000 claims abstract description 60
- 230000005611 electricity Effects 0.000 claims abstract description 27
- 238000004364 calculation method Methods 0.000 claims abstract description 12
- 238000011156 evaluation Methods 0.000 claims abstract description 5
- 230000000737 periodic effect Effects 0.000 claims description 13
- 238000012795 verification Methods 0.000 claims description 9
- 238000003066 decision tree Methods 0.000 claims description 3
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 2
- 230000011664 signaling Effects 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 238000006424 Flood reaction Methods 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- JEIPFZHSYJVQDO-UHFFFAOYSA-N ferric oxide Chemical compound O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000010937 topological data analysis Methods 0.000 description 1
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The present invention discloses a kind of power distribution network bad data recognition method based on quality tab, belong to power system computation analysis field, under conditions of multi-source data is obtained, corresponding quality of data fraction score is evaluated using the constraint rule of 6 voltage measurement U, magnitude of current measurement I, active measurement P, active electrical degree amount and idle electricity factors of influence, after evaluation the calculating of quality tab value is carried out using the mass fraction score values of each measurement, according to result of calculation, bad data is picked out.Overcome the drawbacks of traditional data identification method is divided the error in data of part on whole nodes, and comprehensively utilize the redundancy metric data of voltage class up and down, bond quality label, is recognized to bad data, improves power distribution network virtual measurement and the quality of state estimation input data.
Description
Technical field
The present invention relates to a kind of power distribution network bad data recognition method based on quality tab, belongs to power system computation point
Analysis field.More specifically, by a kind of power distribution network data identification method based on quality tab, to the umber of defectives of power distribution network
According to being detected and being recognized, it is a kind of practical data identification method, can be provided for power distribution network virtual measurement with state estimation
Data supporting.
Background technology
Conventional power distribution network lacks data measurement equipment and monitoring means, and in this case, the power distribution network quality of data recognizes past
It is past that trend matching problem is converted into based on a series of assumed condition.With the continuous implementation of Automation of Electric Systems, to
The identification of electric network data quality has new requirement again.The power distribution network quality of data identification need two major class data, i.e., metric data and
Line parameter circuit value data.Metric data includes remote signalling data and telemetry, and the former mostlys come from distribution remote signalling information, and it is to match somebody with somebody
The basis of electric network topological analysis, the latter mostly come from distribution telemetry, also need to be based on other data acquisition systems in addition
The redundant datas such as the historical data and electricity data of system recognize foundation as the quality of data, to reach to data redudancy
It is required that.Because the metric data amount of power distribution network is huge, and contain bad data, it is therefore desirable to which corresponding data filtering techniques enter
Line number Data preprocess, that is, a kind of practical power distribution network bad data recognition method is realized, thinks power distribution network virtual measurement and state
Estimation provides data supporting.
In view of this, the present inventor is studied this, and it is bad specially to develop a kind of power distribution network based on quality tab
Thus data identification method, this case produce.
The content of the invention
It is an object of the invention to provide a kind of power distribution network bad data recognition method based on quality tab, for matching somebody with somebody at present
The measure configuration situation and multi-data source present situation in electric automation pilot region, power distribution network metric data is carried out to estimate preceding identification,
The drawbacks of traditional data identification method is divided the error in data of part on whole nodes are overcome, and are comprehensively utilized up and down
The redundancy metric data of voltage class, bond quality label, is recognized to bad data, improves power distribution network virtual measurement and shape
State estimates the quality of input data.
To achieve these goals, solution of the invention is：
A kind of power distribution network bad data recognition method based on quality tab, comprises the following steps：
1) multi-data source obtains:Under the conditions of full electric network network structure CIM is known, obtained with reference to from feeder line FTU and bus RTU
The realtime power and voltage arrived, from marketing system (CIS), the load data of centralized meter-reading system export different type user, including electricity
Pressure, electric current, instantaneous active, instantaneous reactive, active electrical degree amount and idle electricity, form the data that postorder quality tab is formulated
Source；
2) each measurement mass fraction evaluation：Under conditions of multi-source data is obtained, voltage measurement U, the magnitude of current are utilized
I, active measurement P, the constraint rule of 6 factors of influence of active electrical degree amount and idle electricity are measured to the corresponding quality of data
Fraction score is evaluated；
3) quality tab is formulated:The calculating of quality tab value, root are carried out using the mass fraction score values of each measurement
According to result of calculation, bad data is picked out, the value being calculated is bigger, illustrates that the data are better, conversely, then poorer.
Above-mentioned steps 2) described in constraint rule be specially：
I. voltage U is constrained：︱
Rule 1：Data continuity：Current voltage and the voltage ratio of first 15 minutes and latter 15 minutes are relatively no more than threshold value, i.e. ︱
U-U-15︱≤δ, and ︱ U-U+15︱≤δ；
Rule 2：Periodic law：Synchronization compares no more than threshold value (current voltage and synchronization in one week in one week
Average voltage error no more than threshold value), i.e.,
Rule 3：The range of nominal tension compares：Meet that (this ratio can basis within the setting ratio of rated voltage
Actual conditions adjust, and generally meet within the 10% of rated voltage), i.e. U ∈ [a, b]；
Rule 4：With the voltage ratio of previous equipment compared with：Whole voltages are less than busbar voltage, i.e. ︱ U-Ub︱≤σ；
Ii. electric current I is constrained：
Rule 1：Data continuity：Current flow is compared with the electric current of first 15 minutes and latter 15 minutes no more than threshold value, ︱ I-
I-15︱≤δ, and ︱ I-I+15︱≤δ；
Rule 2：Periodic law：Synchronization compares no more than threshold value (current flow and synchronization in one week in one week
Current average error no more than threshold value), i.e.,
Rule 3：Compared with outlet breaker：Current value on each switch is less than the current value of outlet breaker, i.e. ︱ I-
Ib︱≤σ；
Rule 4：The KCL rules verification of electric current, it is that every circuit assigns current value I, access line is adjacent after topology is shunk
Switch (being no more than T nodes) current value, travel through afterwards each CN node carry out KCL verifications, two are judged to each electric current I
It is secondary, this twice between if be all twice to, then be entered as 1, one-to-one mistake is entered as 0.5, and all mistakes are entered as 0；
Iii. active-power P constrains：
Rule 1：Data continuity：Current active power is no more than compared with the active power of first 15 minutes and latter 15 minutes
Threshold value, i.e. ︱ P-P-15︱≤δ, and ︱ P-P+15︱≤δ；
Rule 2：Periodic law：In one week synchronization compare no more than threshold value (current active power with one week in it is same
The active power mean value error at moment is no more than threshold value), i.e.,
Iv. active electrical degree amount constrains：
Rule 1：| m- electricity during active electrical degree amount * |≤δ；
V. reactive power Q constrains：
Rule 1：Data continuity：Current reactive power is no more than compared with the reactive power of first 15 minutes and latter 15 minutes
Threshold value, i.e. ︱ Q-Q-15︱≤δ, and ︱ Q-Q+15︱≤δ；
Rule 2：Periodic law：In one week synchronization compare no more than threshold value (current reactive power with one week in it is same
The reactive power average value error at moment is no more than threshold value), i.e.,
Vi. idle electricity constraint：
Rule 1：| m- electricity during idle electricity * |≤δ；
The constraint rule classification of 6 factors is judged more than, and different quality is calculated to different measuring meters
Fraction score, the mass fraction score that each constraint rule obtains is 0~1, and specific formula for calculation is：
[1] data continuity calculates fraction
Formula：Score=1- (| measurement-preceding 15 minutes measurements |/preceding 15 minutes measurement * threshold values+| measurement-after
15 minutes measurements |/rear 15 minutes measurement * threshold values)/2；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
Wherein, threshold value 0.5；
[2] historical law calculates fraction：
Formula：Score=1- | measurement-average value |/(average value * threshold values)；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
Wherein, active-power P, reactive power Q, electric current I threshold value is all taken as 0.5, and voltage U is 0.1.
[3] voltage reduces along circuit and calculates fraction：
Formula：Score=1- | the voltage of measurement-previous equipment |/(the voltage * threshold values of previous equipment)；
Wherein, threshold value 0.1, previous equipment may be considered in radial net closer to the equipment of power supply；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
[4] voltage calculating fraction compared with rated voltage：
Formula：Score=1- | measurement-rated voltage |/(rated voltage * threshold values)；
Wherein, threshold value 0.1, the rated voltage of voltage class of the rated voltage where this measurement；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
[5] electric current (scope) compared with outlet breaker calculates fraction：
Formula：0 is scored at more than outlet breaker, 1 is scored at less than outlet breaker.
[6] the KCL rule master gage point counting numbers of electric current：
Explanation：The KCL rules of each magnitude of current need to detect twice, so the upper limit of score is 0.5 point every time；
The calculation formula of each KCL verifications：Mark=0.5- | electric current-reference current |/(reference current * threshold values)；
The fraction of calculating is not in the range of [0,0.5], then score calculates according to 0；
Then the score of both sides is added to obtain the score of KCL rules；
Reference current is calculated as follows：If measurement to be checked is maximum among all measurements of node, benchmark
Electric current is the sum of other all electric currents；If not maximum, reference current=maximum current-other all electric currents and (remove
Electric current to be checked)；
Threshold value is 0.1.
[7] electricity of active reactive calculates fraction：
Formula：Score=1- | m- there is (no) work(electric degree during P (Q) * |/(there is (no) work(electric degree) * threshold values)；
Wherein, threshold value 0.2, time are different according to the number of the measuring point of each hour；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0.
Above-mentioned steps 3) described in the calculation formula of quality tab value be：
The mass fraction score that span is [0,1] is obtained by each constraint rule, each rule that constrains is by ID3
Decision Tree Algorithm obtains its weight according to sample, and each constraint rule weight sum of same measurement is 1, measurement
Quality tab value：Q (X)=∑ is each (weight corresponding to mass fraction score*), and its score is also in the range of [0,1].
Power distribution network bad data recognition method of the present invention based on quality tab, obtaining the condition of multi-source data
Under, measure 6 I, active measurement P, active electrical degree amount and idle electricity factors of influence using voltage measurement U, the magnitude of current
Constraint rule corresponding quality of data fraction score is evaluated, after evaluation utilize each measurement mass fraction
Score values carry out the calculating of quality tab value, according to result of calculation, pick out bad data, the value being calculated is bigger, explanation
The data are better, conversely, then poorer.Have the following advantages that：
1) residual error for overcoming existing bad data detection and identification floods problem, and the erroneous judgement for greatly reducing data is general
Rate；
2) the drawbacks of traditional data identification method is divided the error in data of part on whole nodes are overcome, and it is comprehensive
The redundancy metric data for utilizing voltage class up and down is closed, bond quality label, bad data is recognized, greatly improves distribution
Net virtual measurement and the quality of state estimation input data.
Embodiment
A kind of power distribution network bad data recognition method based on quality tab, comprises the following steps：
Step 1：Multi-data source obtains:Under the conditions of full electric network network structure CIM is known, with reference to from feeder line FTU and bus
The realtime power P and voltage U that RTU is obtained, the load data of different type user is exported from marketing system (CIS), centralized meter-reading system,
Including voltage U, electric current I, instantaneous active P, instantaneous reactive Q, active electrical degree amount and idle electricity, postorder quality tab system is formed
Fixed data source；
Step 2：Each measurement mass fraction evaluation：Under conditions of multi-source data is obtained, voltage measurement U, electricity are utilized
Flow measurement I, active measurement P, the constraint rule of 6 factors of influence of active electrical degree amount and idle electricity are to corresponding data
Mass fraction score is evaluated；
The constraint rule is specially：
I. voltage U is constrained：
Rule 1：Data continuity：Current voltage and the voltage ratio of first 15 minutes and latter 15 minutes are relatively no more than threshold value, i.e. ︱
U-U-15︱≤δ, and ︱ U-U+15︱≤δ；
Rule 2：Periodic law：Synchronization compares no more than threshold value (current voltage and synchronization in one week in one week
Average voltage error no more than threshold value), i.e.,
Rule 3：The range of nominal tension compares：Meet that (this ratio can basis within the setting ratio of rated voltage
Actual conditions adjust, and generally meet within the 10% of rated voltage), i.e. U ∈ [a, b]；
Rule 4：With the voltage ratio of previous equipment compared with：Whole voltages are less than busbar voltage, i.e. ︱ U-Ub︱≤σ；
Ii. electric current I is constrained：
Rule 1：Data continuity：Current flow is compared with the electric current of first 15 minutes and latter 15 minutes no more than threshold value, i.e. ︱
I-I-15︱≤δ, and ︱ I-I+15︱≤δ；
Rule 2：Periodic law：Synchronization compares no more than threshold value (current flow and synchronization in one week in one week
Current average error no more than threshold value), i.e.,
Rule 3：Compared with outlet breaker：Current value on each switch is less than the current value of outlet breaker, i.e. ︱ I-
Ib︱≤σ；
Rule 4：The KCL rules verification of electric current, it is that every circuit assigns current value I, access line is adjacent after topology is shunk
Switch (being no more than T nodes) current value, travel through afterwards each CN node carry out KCL verifications, two are judged to each electric current I
It is secondary, this twice between if be all twice to, then be entered as 1, one-to-one mistake is entered as 0.5, and all mistakes are entered as 0；
Iii. active-power P constrains：
Rule 1：Data continuity：Current active power is no more than compared with the active power of first 15 minutes and latter 15 minutes
Threshold value, i.e. ︱ P-P-15︱≤δ, and ︱ P-P+15︱≤δ；
Rule 2：Periodic law：In one week synchronization compare no more than threshold value (current active power with one week in it is same
The active power mean value error at moment is no more than threshold value), i.e.,
Iv. active electrical degree amount constrains：
Rule 1：| m- electricity during active electrical degree amount * |≤δ；
V. reactive power Q constrains：
Rule 1：Data continuity：Current reactive power is no more than compared with the reactive power of first 15 minutes and latter 15 minutes
Threshold value, i.e. ︱ Q-Q-15︱≤δ, and ︱ Q-Q+15︱≤δ；
Rule 2：Periodic law：In one week synchronization compare no more than threshold value (current reactive power with one week in it is same
The reactive power average value error at moment is no more than threshold value), i.e.,
Vi. idle electricity constraint：
Rule 1：| m- electricity during idle electricity * |≤δ
The constraint rule classification of 6 factors is judged more than, and different quality is calculated to different measuring meters
Fraction score, the mass fraction score that each constraint rule obtains is 0~1, and specific formula for calculation is：
[1] data continuity calculates fraction
Formula：Score=1- (| measurement-preceding 15 minutes measurements |/preceding 15 minutes measurement * threshold values+| measurement-after
15 minutes measurements |/rear 15 minutes measurement * threshold values)/2；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
Wherein, threshold value 0.5.
[2] historical law calculates fraction：
Formula：Score=1- | measurement-average value |/(average value * threshold values)；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
Wherein, active-power P, reactive power Q, electric current I threshold value is all taken as 0.5, and voltage U threshold values is 0.1.
[3] voltage reduces along circuit and calculates fraction：
Formula：Score=1- | the voltage of measurement-previous equipment |/(the voltage * threshold values of previous equipment)；
Wherein, threshold value 0.1, previous equipment may be considered in radial net closer to the equipment of power supply；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
[4] voltage calculating fraction compared with rated voltage：
Formula：Score=1- | measurement-rated voltage |/(rated voltage * threshold values)；
Wherein, threshold value 0.1, the rated voltage of voltage class of the rated voltage where this measurement；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
[5] electric current (scope) compared with outlet breaker calculates fraction：
Formula：0 is scored at more than outlet breaker, 1 is scored at less than outlet breaker.
[6] the KCL rule master gage point counting numbers of electric current：
Explanation：The KCL rules of each magnitude of current need to detect twice, so the upper limit of score is 0.5 point every time；
Calculation formula after each KCL verifications：Mark=0.5- | electric current-reference current |/(reference current * threshold values)；
The fraction of calculating is not in the range of [0,0.5], then score calculates according to 0；
Then the score of both sides is added to obtain the score of KCL rules；
Reference current is calculated as follows：If measurement to be checked is maximum among all measurements of node, benchmark
Electric current is the sum of other all electric currents；If not maximum, reference current=maximum current-other all electric currents and (remove
Electric current to be checked)；
Threshold value is 0.1.
[7] electricity of active reactive calculates fraction：
Formula：Score=1- | m- there is (no) work(electric degree during P (Q) * |/(there is (no) work(electric degree) * threshold values)；
Threshold value is 0.2, and the time is different according to the number of the measuring point of each hour；
If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；
Step 3：Quality tab is formulated:The calculating of quality tab value is carried out using the mass fraction score of each measurement,
According to result of calculation, bad data is picked out, the value being calculated is smaller, illustrates that the data are poorer.The present embodiment is with voltage
Exemplified by measuring U, the calculating of quality tab value is carried out：
The mass fraction score that 4 spans are [0,1] is obtained by voltage measurement U 4 detected rules, often
Individual rule obtains its weight a1, a2, a3, a4, wherein a1+a2+a3+a4=1 by ID3 Decision Tree Algorithms according to sample,
Voltage measurement U quality tab value：3 score * a3+ of the score * a1+ of Q (U)=rule 1 rule 2 score * a2+ rules
4 score * a4 of rule.Voltage measurement U quality tab value is also in the range of [0,1], for that can set judge as requested
Standard, as shown in table 1, quality tab value are bigger, illustrate that the measurement Value Data is better, conversely, then poorer.
Table 1：The voltage measurement U quality tab value judgment criteria of the present embodiment：
| It is outstanding | Well | Typically | It is poor | Extreme difference |
| 0.8-1.0 | 0.6-0.8 | 0.4-0.6 | 0.2-0.4 | 0.0-0.2 |
The quality tab value of remaining measurement can similarly obtain according to above-mentioned steps.
Above-described embodiment and non-limiting product form of the invention and style, the ordinary skill people of any art
The appropriate change or modification that member is done to it, it all should be regarded as not departing from the patent category of the present invention.
Claims (3)
- A kind of 1. power distribution network bad data recognition method based on quality tab, it is characterised in that comprise the following steps：1) multi-data source obtains:Under the conditions of full electric network network structure CIM is known, with reference to what is obtained from feeder line FTU and bus RTU Realtime power and voltage, from marketing system, the load data of centralized meter-reading system export different type user, including voltage, electric current, wink Shi Yougong, instantaneous reactive, active electrical degree amount and idle electricity, form the data source that postorder quality tab is formulated；2) each measurement mass fraction evaluation：Under conditions of multi-source data is obtained, measured using voltage measurement U, the magnitude of current I, active measurement P, active electrical degree amount, the constraint rule of 6 factors of influence of idle measurement Q and idle electricity are to corresponding Quality of data fraction score is evaluated；3) quality tab is formulated：The calculating of quality tab value is carried out using the mass fraction score values of each measurement, according to meter Result is calculated, picks out bad data, the value being calculated is bigger, and measurement corresponding to explanation is better, conversely, then poorer；Above-mentioned steps 2) described in constraint rule be specially：Voltage measurement U is constrained：Rule 1：Data continuity：Current voltage and the voltage ratio of first 15 minutes and latter 15 minutes are relatively no more than threshold value, i.e., | U- U-15|≤δU, and | U-U+15|≤δU；Rule 2：Periodic law：Current voltage and in one week the comparison of the average voltage of synchronization be no more than threshold value, i.e.,Rule 3：The range of nominal tension compares：Meet within the setting ratio of rated voltage, i.e. U ∈ [a, b]；Rule 4：With the voltage ratio of previous equipment compared with：Whole voltages are less than busbar voltage；Magnitude of current measurement I constraints：Rule 1：Data continuity：Current flow compared with the electric current of first 15 minutes and latter 15 minutes no more than threshold value, | I-I-15| ≤δI, and | I-I+15|≤δI；Rule 2：Periodic law：Current flow and in one week the comparison of the average current of synchronization be no more than threshold value, i.e.,Rule 3：Compared with outlet breaker：Current value on each switch is less than the current value of outlet breaker；Rule 4：The KCL rules verification of electric current, it is that every circuit assigns current value I, access line is adjacent to open after topology is shunk The current value of pass, travel through afterwards each CN node carry out KCL verifications, to each electric current I judge twice, this twice between such as Fruit be all twice to, then be entered as 1, one-to-one mistake is entered as 0.5, and all mistakes are entered as 0, and the CN nodes refer to by topology The equivalent node in Distribution Network Frame after shrink process；Active measurement P constraints：Rule 1：Data continuity：Current active power is compared with the active power of first 15 minutes and latter 15 minutes no more than threshold Value, i.e., | P-P-15|≤δP, and | P-P+15|≤δP；Rule 2：Periodic law：Active power with one week in the comparison of average active power of synchronization be no more than threshold value, i.e.,Active electrical degree amount constrains：Rule 1：| m- active electrical degree amount during active electrical degree amount * |≤δActive electrical degree；Idle measurement Q constraints：Rule 1：Data continuity：Current reactive power is compared with the reactive power of first 15 minutes and latter 15 minutes no more than threshold Value, i.e., | Q-Q-15|≤δQ, and | Q-Q+15|≤δQ；Rule 2：Periodic law：Reactive power with one week in the comparison of average reactive power of synchronization be no more than threshold value, i.e.,Idle electricity constraint：Rule 1：| m- idle electricity during idle electricity * |≤δIdle electric degree；The constraint rule classification of 6 factors is judged more than, and different mass fractions is calculated to different measuring meters Score, the mass fraction score that each constraint rule obtains is 0~1, and specific formula for calculation is：[1] data continuity calculates fractionFormula：Score=1- (| measurement-preceding 15 minutes measurements |/preceding 15 minutes measurement * threshold values+| measurement-latter 15 points Clock measurement |/rear 15 minutes measurement * threshold values)/2；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；Wherein, threshold value 0.5；[2] periodic law calculates fraction：Formula：Score=1- | measurement-average value |/(average value * threshold values)；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；Wherein, active-power P, reactive power Q, electric current I threshold value is all taken as 0.5, and voltage U threshold values are 0.1；[3] voltage reduces along circuit and calculates fraction：Formula：Score=1- | the voltage of measurement-previous equipment |/(the voltage * threshold values of previous equipment)；Wherein, threshold value 0.1, previous equipment are closer to the equipment of power supply in radial net；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；[4] voltage calculating fraction compared with rated voltage：Formula：Score=1- | measurement-rated voltage |/(rated voltage * threshold values)；Here wherein, threshold value 0.1, the rated voltage of voltage class of the rated voltage where this measurement；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；[5] electric current calculating fraction compared with outlet breaker：Explanation：0 is scored at more than outlet breaker, 1 is scored at less than outlet breaker；[6] the KCL rule master gage point counting numbers of electric current：Explanation：The KCL rules of each magnitude of current need to detect twice, so the upper limit of score is 0.5 point every time；Calculation formula after each KCL verifications：Mark=0.5- | electric current-reference current |/(reference current * threshold values)；The fraction of calculating is not in the range of [0,0.5], then score calculates according to 0；Then the score of both sides is added to obtain the score of KCL rules；Reference current is calculated as follows：If measurement to be checked is maximum among all measurements of node, reference current For the sum of other all electric currents；If measurement to be checked is not to be maximum among all measurements of node, reference current= The sum of maximum current-other all electric currents；Threshold value is 0.1；[7] the calculating fraction of active electrical degree amount：Formula：Score=1- | m- active electrical degree amount during P* |/(active electrical degree amount * threshold values)；Wherein, threshold value 0.2, time are different according to the number of the measuring point of each hour；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0；[8] the calculating fraction of idle electricity：Formula：Score=1- | m- idle electricity during Q* |/(idle electricity * threshold values)；Wherein, threshold value 0.2, time are different according to the number of the measuring point of each hour；If the mass fraction score being calculated not in the range of [0,1], then score calculates according to 0.
- A kind of 2. power distribution network bad data recognition method based on quality tab as claimed in claim 1, it is characterised in that：Step The calculation formula of rapid 3) described quality tab value is：Each constraint rule obtains the mass fraction score that span is [0,1], and each rule that constrains is by ID3 decision trees point Class algorithm obtains its weight according to sample, and each constraint rule weight sum of same measurement is 1, the quality mark of measurement Label value：Weight corresponding to the mass fraction score* constraint rules of Q (X)=∑ constraint rule, its score are also in [0,1] scope It is interior.
- A kind of 3. power distribution network bad data recognition method based on quality tab as claimed in claim 1, it is characterised in that：Institute The range of nominal tension for stating voltage U constraint rules 3 more specific is：Meet within the 10% of rated voltage.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510030386.5A CN104537271B (en) | 2015-01-21 | 2015-01-21 | A kind of power distribution network bad data recognition method based on quality tab |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510030386.5A CN104537271B (en) | 2015-01-21 | 2015-01-21 | A kind of power distribution network bad data recognition method based on quality tab |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104537271A CN104537271A (en) | 2015-04-22 |
| CN104537271B true CN104537271B (en) | 2018-01-02 |
Family
ID=52852797
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510030386.5A Active CN104537271B (en) | 2015-01-21 | 2015-01-21 | A kind of power distribution network bad data recognition method based on quality tab |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104537271B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104794206B (en) * | 2015-04-23 | 2017-09-19 | 国网山东省电力公司 | A kind of substation data QA system and method |
| CN105391062B (en) * | 2015-12-07 | 2017-12-22 | 国网浙江省电力公司宁波供电公司 | A kind of active bad data recognition method based on DC flow model |
| CN106022972B (en) * | 2016-06-30 | 2022-10-21 | 中国电力科学研究院 | Power distribution network abnormal data identification method based on state matrix symmetry |
| CN106408204B (en) * | 2016-09-30 | 2019-11-22 | 许继电气股份有限公司 | A kind of plant stand bad data detection and device based on multisource data fusion |
| CN107239848A (en) * | 2017-04-14 | 2017-10-10 | 国网福建省电力有限公司泉州供电公司 | Bad data recognition method based on load prediction |
| CN110232061A (en) * | 2019-06-20 | 2019-09-13 | 国网上海市电力公司 | A kind of power distribution network multi-source data method of quality control |
| CN111881124A (en) * | 2020-07-24 | 2020-11-03 | 贵州电网有限责任公司 | Data processing method and system based on state estimation of improved algorithm |
| CN111860899A (en) * | 2020-08-06 | 2020-10-30 | 上海电机系统节能工程技术研究中心有限公司 | Motor operation and maintenance method, device, electronic equipment and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400310A (en) * | 2013-08-08 | 2013-11-20 | 华北电力大学（保定） | Method for evaluating power distribution network electrical equipment state based on historical data trend prediction |
| CN103618385A (en) * | 2013-12-03 | 2014-03-05 | 国家电网公司 | State estimation data correction system and method for improving accuracy |
| CN104134999A (en) * | 2014-08-06 | 2014-11-05 | 国家电网公司 | Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources |
-
2015
- 2015-01-21 CN CN201510030386.5A patent/CN104537271B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400310A (en) * | 2013-08-08 | 2013-11-20 | 华北电力大学（保定） | Method for evaluating power distribution network electrical equipment state based on historical data trend prediction |
| CN103618385A (en) * | 2013-12-03 | 2014-03-05 | 国家电网公司 | State estimation data correction system and method for improving accuracy |
| CN104134999A (en) * | 2014-08-06 | 2014-11-05 | 国家电网公司 | Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources |
Non-Patent Citations (1)
| Title |
|---|
| 考虑质量标签的多数据源配电网状态估计算法;徐玮韡 等;《电力自动化设备》;20110410;第31卷(第4期);78-81，86 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104537271A (en) | 2015-04-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104537271B (en) | A kind of power distribution network bad data recognition method based on quality tab | |
| CN110516912B (en) | Method for identifying household transformer relation of distribution station | |
| WO2021043317A1 (en) | Transformer area identification method and method for constructing transformer area line topography | |
| CN107508297B (en) | A kind of verification of distribution topological structure and maintaining method | |
| CN107340492A (en) | Electric power meter failure analysis methods with scene anticipation are excavated based on big data | |
| CN107453484B (en) | SCADA data calibration method based on WAMS information | |
| CN107069721A (en) | A kind of electric power system operation risk assessment method theoretical based on random set | |
| CN103617568A (en) | Setting method for abnormal data determination threshold in steady-state power quality early-warning mechanism | |
| CN112329806B (en) | Ammeter clustering method for topology identification of low-voltage transformer area | |
| CN108492043A (en) | A kind of power consumer load prediction method based on clustering algorithm | |
| CN110580387B (en) | DC protection system mixed Weibull reliability evaluation method based on entropy weight method | |
| CN112688428B (en) | 10-kilovolt power grid synchronous line loss treatment method based on Internet of things technology | |
| CN101499659B (en) | Transforming plant distributed state estimation method based on Kirchhoff's current law | |
| CN109842122A (en) | A kind of low-voltage platform area low-voltage administering method | |
| CN113159488B (en) | Low-voltage distribution area topology identification method | |
| CN109164319A (en) | A kind of building user power utilization abnormality determination method | |
| CN116845971A (en) | Automatic identification method for topological structure of photovoltaic grid-connected low-voltage transformer area | |
| CN108919044A (en) | A kind of unit style distribution network failure active identification method based on mutual verification scheme | |
| CN112510817A (en) | Intelligent identification method for low-voltage topological relation of transformer area | |
| CN110232061A (en) | A kind of power distribution network multi-source data method of quality control | |
| CN102636706B (en) | Method for identifying branches with parameter errors in power grid | |
| CN116203351A (en) | Method and system for detecting abnormal line impedance | |
| CN109784777B (en) | Power grid equipment state evaluation method based on time sequence information fragment cloud similarity measurement | |
| CN105701265A (en) | Double-fed wind generator modeling method and apparatus | |
| CN111178679A (en) | Phase identification method based on clustering algorithm and network search |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |