CN113740795B - Misconnection judgment method for three-phase four-wire electric energy meter - Google Patents
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Abstract
The invention provides a misconnection judgment method for a three-phase four-wire electric energy meter, which comprises the following steps: s100, selecting an abnormal window with abnormal current; s200, respectively calculating a phase sequence current correlation coefficient in an abnormal window, a power factor corresponding to the abnormal phase sequence, and cosine similarity between an electric energy representation value and a horizontal line by using a cosine similarity calculation method; and S300, comparing the calculation result with a corresponding threshold value, and judging whether wrong wiring abnormality exists or not. The method fully uses a big data analysis means, uses 95 quantiles, selects an abnormal output window through high-load working current, utilizes a cosine similarity algorithm to carry out expansion analysis on the abnormal window, and solves the current similarity between phase sequences, the horizontal line similarity of electric energy representation values and the like, thereby judging the wrong wiring abnormality. The invention greatly reduces the manual workload and removes the influence of human factor judgment, thereby realizing intelligent and automatic quick judgment of wrong wiring abnormity and greatly reducing the work difficulty of field inspection.
Description
Technical Field
The invention relates to the technical field of electric energy meters, in particular to a misconnection judgment method for a three-phase four-wire electric energy meter.
Background
With the rapid development of the power industry, the demand of various industries on electric energy is increasing day by day, and the requirement on the accuracy of electric energy metering is higher and higher. For a three-phase meter, the wiring mode is complex, the three-phase meter is usually used for special transformer or industrial electricity, the power consumption is large, the metering is inaccurate due to wrong wiring, and great economic loss is caused to a power grid company.
At present, in the prior art, wrong wiring analysis of three-phase four-wire is not comprehensive, and manual correction is needed, for example, wiring diagrams and vector diagrams of three-phase four-wire electric energy metering devices corresponding to all kinds of voltage parameter and current parameter combinations are drawn in advance in related patents and stored in a preset memory. When receiving the voltage parameter and the current parameter input by the user, outputting a wiring diagram and a vector diagram corresponding to the voltage parameter and the current parameter, and giving a specific calculation process for obtaining the wiring diagram and the vector diagram according to the voltage parameter and the current parameter, and finally obtaining a correction coefficient.
With the development of the power industry, automation and intellectualization are natural trends of the development of the power industry in the future, a method for pre-drawing wiring diagrams and vector diagrams of three-phase four-wire electric energy metering devices corresponding to all kinds of voltage parameter and current parameter combinations needs to spend a large amount of time, errors caused by human errors are difficult to avoid, meanwhile, the method is poor in expansibility, and is difficult to deal with the current major trend of intellectualization and automation development facing to metering equipment. Therefore, starting from big data, the invention aims to solve the problem of quickly and automatically judging wrong wiring abnormity.
Disclosure of Invention
The invention provides a misconnection judgment method for a three-phase four-wire electric energy meter, and aims to solve the technical problem of how to quickly and automatically judge whether the three-phase four-wire electric energy meter is misconnected.
The misconnection judgment method for the three-phase four-wire electric energy meter according to the embodiment of the invention comprises the following steps:
selecting an abnormal window with abnormal current;
respectively calculating the phase sequence current correlation coefficient in the abnormal window, the power factor corresponding to the abnormal phase sequence and the cosine similarity between the electric energy representation value and the horizontal line by using a cosine similarity calculation method;
and comparing the calculation result with a corresponding threshold value, and judging whether wrong wiring abnormality exists or not.
According to some embodiments of the invention, the method further comprises:
and normalizing the power factor in the abnormal window to enable the numerical range of the power factor to be within 0-1.
In some embodiments of the present invention, selecting an anomaly window in which a current anomaly occurs includes:
collecting a plurality of current values of a preset time period window according to a preset time interval, wherein the minimum current value isI min The maximum current value isI max ；
If it isI min ＜-k 1 *I M And is andI max ＞k 1 *I M then selectI min 、I max The window is an abnormal window;
wherein, theI M Determined by a current specification, saidk 1 In order to be the current anomaly threshold value,k 1 ＞0.1。
according to some embodiments of the present invention, the method for determining the abnormal phase sequence in the abnormal window comprises:
and selecting any two-phase sequence from the three-phase sequence in the abnormal window, and determining the phase sequence with the detection current value being a negative value as the abnormal phase sequence.
In some embodiments of the invention, the method further comprises:
the operating current is determined using the following equation:I work = 95% quantile [ max (abs: (ab) (m))I A ),abs(I B ),abs(I C ))]WhereinI A 、I B 、I C Currents of three phase sequences respectively;
arbitrarily selecting two phase sequences, detecting the current if the phase sequenceI check ＜-k 2 *I work If so, judging the phase sequence to be an abnormal phase sequence; detecting current if phase sequenceI check ＞k 2 *I work Then the phase sequence is judged to be a normal phase sequence, wherein the threshold valuek 2 =0.4。
According to some embodiments of the invention, the phase-sequence current correlation coefficient cos is calculated (θ 1 ) Power factor cos (corresponding to abnormal phase sequence)φ) Cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) When cos (c) is satisfiedθ 1 )＜-k 3 ，cos(φ)≥k 4 And cos (c) ofθ 2 )＜k 5 When the three-phase four-wire electric energy meter is in fault connection, judging that the corresponding three-phase four-wire electric energy meter is in fault connection, wherein the threshold valuek 3 < 0.1, thresholdk 4 > 0.4, thresholdk 5 ＜0.8。
In some embodiments of the invention, the phase-sequence current correlation coefficient cos (c:)θ 1 ) Calculated using the formula:
wherein,I iis justIs as followsiThe normal phase-sequence current within the individual anomaly windows,I idifferent from each otherFor the abnormal phase-sequence current in the ith abnormal window,irepresents the firstiAn exception window is set in the memory of the computer,nthe total number of the abnormal windows;
power factor cos (corresponding to abnormal phase sequence)φ) The measured value is acquired by an ammeter;
cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) Calculated using the formula:
wherein,R i is a three-phase four-wire electric energy representation value,x i =c，cis an arbitrary constant, i.e.x i =cIs an arbitrary horizontal line.
The misconnection judgment method for the three-phase four-wire electric energy meter provided by the invention has the following advantages that:
the method fully uses a big data analysis means, uses 95 quantiles, selects an abnormal output window through high-load working current, utilizes a cosine similarity algorithm to carry out expansion analysis on the abnormal window, and solves the current similarity between phase sequences, the horizontal line similarity of electric energy representation values and the like, thereby judging the wrong wiring abnormality. The invention greatly reduces the manual workload and removes the influence of human factor judgment, thereby realizing intelligent and automatic quick judgment of wrong wiring abnormity and greatly reducing the work difficulty of field inspection.
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Fig. 1 is a flowchart of a method for determining a misconnection of a three-phase four-wire electric energy meter according to an embodiment of the invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the intended purpose, the present invention will be described in detail with reference to the accompanying drawings and preferred embodiments.
The description of the method flow in the present specification and the steps of the flow chart in the drawings of the present specification are not necessarily strictly performed by the step numbers, and the execution order of the method steps may be changed. Moreover, certain steps may be omitted, multiple steps may be combined into one step execution, and/or a step may be broken down into multiple step executions.
The invention provides a three-phase four-wire electric energy meter wrong wiring abnormity judging method based on cosine similarity analysis, aiming at the phenomenon of wrong wiring abnormity of a three-phase four-wire electric energy meter and avoiding the defects mentioned in the background technology, so that the wrong wiring abnormity can be judged effectively and quickly, and the judging accuracy is improved effectively.
As shown in fig. 1, the method for determining a misconnection of a three-phase four-wire electric energy meter according to an embodiment of the present invention includes:
s100, selecting an abnormal window with abnormal current;
s200, respectively calculating a phase sequence current correlation coefficient in an abnormal window, a power factor corresponding to the abnormal phase sequence, and cosine similarity between an electric energy representation value and a horizontal line by using a cosine similarity calculation method;
and S300, comparing the calculation result with a corresponding threshold value, and judging whether wrong wiring abnormality exists or not.
According to some embodiments of the invention, the method further comprises:
s150, normalizing the power factor in the abnormal window to enable the numerical range of the power factor to be within 0-1.
In some embodiments of the invention, step S100 comprises:
s110, collecting a plurality of current values of a preset time period window according to a preset time interval, wherein the minimum current value isI min The maximum current value isI max ；
S120, ifI min ＜-k 1 *I M And is andI max ＞k 1 *I M then selectI min 、I max The window is an abnormal window;
wherein,I M as determined by the current specification, the current,k 1 in order to be the current anomaly threshold value,k 1 ＞0.1。
according to some embodiments of the present invention, the method for determining the abnormal phase sequence in the abnormal window comprises:
and (4) arbitrarily selecting a two-phase sequence from the three-phase sequence in the abnormal window, and judging the phase sequence with the detected current value being a negative value as the abnormal phase sequence.
In some embodiments of the invention, the method further comprises:
the operating current is determined using the following equation:I work = 95% quantile [ max (abs: (ab) (m))I A ),abs(I B ),abs(I C ))]WhereinI A 、I B 、I C Currents of three phase sequences respectively;
arbitrarily selecting two phase sequences, detecting the current if the phase sequenceI check ＜-k 2 *I work If so, judging the phase sequence to be an abnormal phase sequence; detecting current if phase sequenceI check ＞k 2 *I work Then the phase sequence is judged to be a normal phase sequence, wherein the threshold valuek 2 =0.4。
According to some embodiments of the invention, the phase-sequence current correlation coefficient cos (is) is calculatedθ 1 ) Power factor cos (corresponding to abnormal phase sequence)φ) Cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) When cos (c) is satisfiedθ 1 )＜-k 3 ，cos(φ)≥k 4 And cos (c) ofθ 2 )＜k 5 When the three-phase four-wire electric energy meter is in fault connection, judging that the corresponding three-phase four-wire electric energy meter is in fault connection, wherein the threshold valuek 3 < 0.1, thresholdk 4 > 0.4, thresholdk 5 ＜0.8。
In some embodiments of the invention, the phase-sequence current correlation coefficient cos (C:)θ 1 ) Calculated using the formula:
wherein,I iis justIs as followsiThe normal phase-sequence current within the individual anomaly windows,I idifferent from each otherFor the abnormal phase-sequence current in the ith abnormal window,irepresenting the different windows of the anomaly,nthe total number of the abnormal windows;
power factor cos (corresponding to abnormal phase sequence)φ) The measured value is acquired by an ammeter;
cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) Calculated using the formula:
wherein,R i is a three-phase four-wire electric energy representation value,x i =c，cis an arbitrary constant, i.e.x i =cIs an arbitrary horizontal line, and the horizontal line is,irepresenting the different windows of the anomaly,nis the total number of the exception windows.
The misconnection judgment method for the three-phase four-wire electric energy meter provided by the invention has the following advantages that:
the method fully uses a big data analysis means, uses 95 quantiles, selects an abnormal output window through high-load working current, utilizes a cosine similarity algorithm to carry out expansion analysis on the abnormal window, and solves the current similarity between phase sequences, the horizontal line similarity of electric energy representation values and the like, thereby judging the wrong wiring abnormality. The invention greatly reduces the manual workload and removes the influence of human factor judgment, thereby realizing intelligent and automatic quick judgment of wrong wiring abnormity and greatly reducing the work difficulty of field inspection.
The misconnection determination method of the three-phase four-wire electric energy meter according to the present invention is described in detail below with reference to the accompanying drawings. It is to be understood that the following description is only exemplary in nature and should not be taken as a specific limitation on the invention.
The invention mainly uses a cosine similarity algorithm to calculate the current correlation coefficient in an abnormal window, the power factor corresponding to an abnormal phase sequence, and the cosine similarity between the electric energy representation value in the window and a horizontal plane, and compares the power factor and the electric energy representation value with corresponding thresholds so as to judge whether the wrong wiring abnormality exists. The method specifically comprises the following steps of judging the wrong wiring abnormality of the three-phase four-wire electric energy meter based on cosine similarity analysis:
a100, selecting a current window by a scribing method:
minimum value of all currentsI min And maximum valueI max If, ifI min ＜-k 1 *I M And isI max ＞k 1 *I M Then, the window is selected for subsequent abnormal judgment. For example, current acquisition may be set for one window every 15 minutes, and then current may be acquired for 96 windows per day.
Wherein,k 1 in order to be the current anomaly threshold value,I M for the current specification, through the statistics of network province and test point, the proposalk 1 ＞0.1。
A200, power factor normalization processing:
because the data ranges are not uniform and data in the ranges of 0-100 and 0-1 exist at the same time, the data in the range of 0-100 needs to be converted into the range of 0-1, and therefore normalization processing is carried out on the data, and errors are prevented.
A300, judging high load, determining working current:
I work = 95% quantile [ max (abs: (ab) (m))I A ),abs(I B ),abs(I C ))]
A400, selecting an abnormal window:
and (4) taking any two-phase sequence for judgment, and judging by combining the high load in the step A300:
if the phase detects the currentI check ＜-k 2 *I work The phase is abnormal phase sequence, and the other phase detects the currentI check ＞k 2 *I work Then the phase is the normal phase sequence. And outputting the window interval meeting the conditions as a wrong wiring abnormal window.
Wherein,I check in order to detect the current flow, it is,k 2 for phase sequence decision thresholds, it is proposed to choosek2 is more than 0.4, and the date of the trial and time of the network is just overk 2 When =0.3, the accuracy is only 35%, whenk 2 And the accuracy rate is improved to 80 percent by = 0.4.
A500, judging miswiring abnormity:
respectively obtaining the current correlation coefficient of the phase sequence in the output abnormal window of 4, namely the cosine similarity cos (between the phase sequences)θ 1 ) Power factor cos (corresponding to abnormal phase sequence in window)φ) Window electric energy indicating valueR i Cosine similarity to horizontal lines cos (θ 2 ). If the following conditions are met:
cos(θ 1 )＜-k 3 and cos (c) ofφ)≥k 4 And cos (c) ofθ 2 )＜k 5
It is determined to be miswired.
Wherein,k 3 for phase-sequence current correlation coefficient threshold, it is proposedk 3 ＜0.1，k 4 For abnormal phase sequence power factor threshold, suggestingk 4 ＞0.4，k 5 For the horizontal similarity threshold, suggestk 5 ＜0.8。
The cosine similarity calculation formula is as follows:
in the formula,θfor cosine similarity, A, B are the attribute vectors given the substituting formula,A i ，B ithe components of vectors a, B, respectively. The similarity range is [ -1,1]1 means that the vectors point exactly the same, and 0 means that the two vectors are completely independent.
Wherein, the phase-sequence current correlation coefficient cos (c:)θ 1 ) Calculated using the formula:
wherein,I iis justIs as followsiThe normal phase-sequence current within the individual anomaly windows,I idifferent from each otherFor the abnormal phase-sequence current in the ith abnormal window,irepresenting the different windows of the anomaly,nthe total number of the abnormal windows;
power factor cos (corresponding to abnormal phase sequence)φ) The measured value is acquired by an ammeter;
cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) Calculated using the formula:
wherein,R i is a three-phase four-wire electric energy representation value,x i =c，cis an arbitrary constant, i.e.x i =cIs an arbitrary horizontal line, and the horizontal line is,irepresenting the different windows of the anomaly,nis the total number of the exception windows.
A600, exception window deduplication:
and (3) taking two phases of A, B, C phase current, and sequentially repeating the steps A300-A500, namely calculating for 6 times in total, and after 6 results are accumulated, removing the weight of the repeated abnormal window to obtain a final result.
In conclusion, the invention fully applies a big data analysis means, applies 95 quantiles, selects an abnormal output window through high-load working current, utilizes a cosine similarity algorithm to carry out expansion analysis on the abnormal window, and solves the current similarity between phase sequences, the horizontal line similarity of electric energy representation values and the like, thereby judging the abnormal wrong wiring. The invention greatly reduces the manual workload and removes the influence of human factor judgment, thereby realizing intelligent and automatic quick judgment of wrong wiring abnormity and greatly reducing the work difficulty of field inspection.
While the invention has been described in connection with specific embodiments thereof, it is to be understood that it is intended by the appended drawings and description that the invention may be embodied in other specific forms without departing from the spirit or scope of the invention.
Claims (6)
1. A misconnection judgment method for a three-phase four-wire electric energy meter is characterized by comprising the following steps:
selecting an abnormal window with abnormal current;
respectively calculating the phase sequence current correlation coefficient in the abnormal window, the power factor corresponding to the abnormal phase sequence and the cosine similarity between the electric energy representation value and the horizontal line by using a cosine similarity calculation method;
comparing the calculation result with a corresponding threshold value, and judging whether wrong wiring abnormality exists or not;
calculating to obtain the phase sequence current correlation coefficient cos (c:)θ 1 ) Power factor corresponding to abnormal phase sequence
Cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) When cos (c) is satisfiedθ 1 )＜-k 3 ，
And cos (c) ofθ 2 )＜k 5 When the three-phase four-wire electric energy meter is in fault connection, judging that the corresponding three-phase four-wire electric energy meter is in fault connection, wherein the threshold valuek 3 < 0.1, thresholdk 4 > 0.4, thresholdk 5 ＜0.8。
2. The method of claim 1, further comprising:
and normalizing the power factor in the abnormal window to enable the numerical range of the power factor to be within 0-1.
3. The misconnection determination method of a three-phase four-wire electric energy meter according to claim 1, wherein selecting an abnormal window in which current abnormality occurs comprises:
collecting a plurality of current values of a preset time period window according to a preset time interval, wherein the minimum current value isI min The maximum current value isI max ；
If it isI min ＜-k 1 *I M And is andI max ＞k 1 *I M then selectI min 、I max The window is an abnormal window;
wherein, theI M Determined by a current specification, saidk 1 In order to be the current anomaly threshold value,k 1 ＞0.1。
4. the misconnection determination method of the three-phase four-wire electric energy meter according to claim 1, wherein the determination method of the abnormal phase sequence in the abnormal window is as follows:
and selecting any two-phase sequence from the three-phase sequence in the abnormal window, and determining the phase sequence with the detection current value being a negative value as the abnormal phase sequence.
5. The method of claim 4, further comprising:
the operating current is determined using the following equation:I work = 95% quantile [ max (abs: (ab) (m))I A ),abs(I B ),abs(I C ))]WhereinI A 、I B 、I C Currents of three phase sequences respectively;
arbitrarily selecting two phase sequences, detecting the current if the phase sequenceI check ＜-k 2 *I work If so, judging the phase sequence to be an abnormal phase sequence; detecting current if phase sequenceI check ＞k 2 *I work Then the phase sequence is judged to be a normal phase sequence, wherein the threshold valuek 2 =0.4。
6. The method of claim 1, wherein the phase sequence current correlation coefficient cos (c) is (c: (d))θ 1 ) Calculated using the formula:
wherein,I iis justIs as followsiThe normal phase-sequence current within the individual anomaly windows,I idifferent from each otherIs as followsiThe abnormal phase-sequence current within the abnormal window,irepresents the firstiAn exception window is set in the memory of the computer,nthe total number of the abnormal windows;
power factor corresponding to abnormal phase sequence
The measured value is acquired by an ammeter;
cosine similarity cos (of electric energy representation value and horizontal line)θ 2 ) Calculated using the formula:
wherein,R i is as followsiThe three-phase four-wire power representative values within the anomaly window,x i =c，cis an arbitrary constant, i.e.x i =cIs an arbitrary horizontal line, and the horizontal line is,irepresents the firstiAn exception window is set in the memory of the computer,nis the total number of the exception windows.
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| CN117150191B (en) * | 2023-10-30 | 2024-01-30 | 国网冀北电力有限公司 | Method and system for calculating miswiring power tracing and withdrawing power of digital ammeter |
| CN117150329B (en) * | 2023-10-30 | 2024-01-30 | 国网冀北电力有限公司 | Three-phase three-wire electric energy meter fault wiring research and judgment method based on long-term and short-term clustering similarity weighting |
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