CN113484819B - Method for diagnosing metering faults of electric energy meter in limited range based on high-frequency current sampling - Google Patents
Method for diagnosing metering faults of electric energy meter in limited range based on high-frequency current sampling Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
The invention discloses a method for diagnosing metering faults of an electric energy meter in a limited range based on high-frequency current sampling, relates to the technical field of electric energy metering, and solves the problem that the error estimation precision or hit rate of the electric energy meter in the prior art is severely limited by the loss estimation precision, and the technical scheme is as follows: collecting the current instantaneous values of the total table and the sub-table, and obtaining a total sample space after multiple collection; establishing a coefficient matrix, an augmentation matrix and judging whether the ranks of the coefficient matrix and the augmentation matrix are equal; if the acquired data are invalid, re-acquiring at least one group of data, discarding the data with the same group number to obtain a new overall sample space until the ranks of the coefficient matrix and the augmentation matrix are equal; and establishing an error calculation model, solving the error calculation model, and comparing the error calculation model with the precision level threshold of the electric energy meter to obtain a fault diagnosis result. The invention can realize accurate calculation of the error of the electric energy meter, effectively improve the estimation precision and hit rate of the error of the electric energy meter and effectively eliminate the interference of human factors.
Description
Technical Field
The invention relates to the technical field of electric energy metering, in particular to a metering fault diagnosis method of an electric energy meter in a limited range based on high-frequency current sampling.
Background
Along with the continuous promotion of global energy transformation process, especially the carbon neutralization and the carbon peak proposal, the efficient energy technology is an important development direction in a long time in the future, and the efficient energy technology is used as important equipment for trade settlement of customers and electric power companies, and the electric energy meter plays a more important role. Therefore, how to ensure the quality of the electric energy meter to be in a good state all the time is a problem to be solved in front of the power company and the quality management department.
In view of this, it has been proposed to construct an equation set with total electric quantity equal to the sum of the electric quantities of the sub-meters by collecting the total electric energy information of the sub-meters and the total table and introducing error coefficients based on the principle of conservation of energy, and finally solve the errors of the electric energy meters by calculating the equation set. The method has better results to a great extent. However, in practical situations, the loss exists in the circuit and is far higher than the electricity consumption of the household user in general, so that the error estimation of each electric energy meter has larger deviation or the error out-of-tolerance electric energy meter cannot be effectively hit. It should be noted here in particular that the error of an electric energy meter, in particular an error-out-of-tolerance electric energy meter, exceeds a threshold value specified by the country or industry, which value generally does not exceed the accuracy class of the electric energy meter. For example, the error of a 2-stage single-phase electric energy meter should not exceed 2%.
Therefore, how to study and design a method for diagnosing metering faults of an electric energy meter in a limited range based on high-frequency current sampling, which can solve the problems, is a problem which needs to be solved urgently at present.
Disclosure of Invention
In order to solve the problem that the error estimation precision or hit rate of the electric energy meter is severely limited by the loss estimation precision in the prior art, the invention aims to provide the electric energy meter metering fault diagnosis method in a limited range based on high-frequency current sampling, the calculation model is in common high fit with the actual application, the problem of line loss is avoided, and the error estimation precision and hit rate of the electric energy meter can be effectively improved.
The technical aim of the invention is realized by the following technical scheme: the method for diagnosing the metering faults of the electric energy meter in a limited range based on high-frequency current sampling comprises the following steps:
collecting the current instantaneous values of the total table and each sub table in the limited range at the same time, and obtaining a total sample space composed of a plurality of groups of data after multiple times of collection;
establishing a coefficient matrix according to the acquired data of each sub-table in the overall sample space, establishing an augmentation matrix according to all the data in the overall sample space, and judging whether the ranks of the coefficient matrix and the augmentation matrix are equal; if the acquired data are equal, the acquired data are valid; if the acquired data are not equal, the acquired data are invalid;
if the acquired data are invalid, performing a supplementary acquisition operation to acquire at least one group of data again, discarding the data with the same group number from the original total sample space to obtain a new total sample space, and obtaining a final total sample space until the ranks of the coefficient matrix and the augmentation matrix are equal;
and establishing an error calculation model according to the final total sample space, solving the error calculation model to obtain error data of the electric energy meter, and comparing the error data of the electric energy meter with a precision grade threshold value of the electric energy meter to obtain a fault diagnosis result.
Further, the limited range includes a set of a station area, a meter box, and a plurality of meters suspended under the same transformer.
Further, the installation position of the summary is specifically:
the total surface of the transformer area is arranged on the low-voltage side of the transformer;
or, when the total table of the transformer area is installed on the high-voltage side or the total table of the transformer area collects the current data of the high-voltage side, the current of the high-voltage side is converted into the accurate current of the low-voltage side by taking compensation measures.
Further, the collecting process of the plurality of groups of data specifically includes:
determining the total table number and the sub-table number in the limited range;
collecting all total tables and current instantaneous values of all sub tables at the same time to obtain a group of initial collection data;
judging whether the initial acquisition data are valid data or not, and if so, marking the initial acquisition data as a primary valid acquisition group;
and repeating the collection at preset time intervals until the number of the effective collection groups is not lower than the number of the sub-tables.
Further, if any group of the initial acquisition data satisfies the effective judgment formula, judging that the corresponding initial acquisition data is effective data, wherein the effective judgment formula specifically comprises:
wherein x is ij The current instantaneous value acquired by the ith electric energy meter at the jth time is represented; n represents the sum of the total number and the sub-number.
Further, the preset time interval is a minute-level interval and an hour-level interval, and each acquired data is independent and linearly independent.
Further, the coefficient matrix specifically includes:
wherein A represents a coefficient matrix; x is x (N-1)(N-1) Indicating the current instantaneous value acquired by the N-1 th sub-table in the N-1 th time;
the augmentation matrix specifically comprises:
representing an augmentation matrix; x is x N(N-1) Indicating the instantaneous value, X, of the current collected from the N-1 th time of the total table N The table total number is 1.
Further, the specific process of discarding data from the original total sample space is as follows:
setting a discard threshold delta according to the instantaneous current sampling precision;
counting the number C of not more than the discard threshold delta in each group of acquired data j J represents the collection data collected at the j-th time;
reject max (C j ) All data of the group.
Further, the rejection threshold value is consistent with the instantaneous current sampling precision or is in a multiple relationship, and the multiple is an integer of 1-10.
Further, the calculation formula of the error calculation model specifically includes:
AX＝B
wherein A represents a coefficient matrix; x represents an error matrix; b represents a result matrix;
the error matrix specifically comprises:
wherein ε N-1 Error data of the N-1 electric energy meter are represented;
the result matrix specifically comprises:
wherein x is N(N-1) Indicating the instantaneous value of the current at the nth-1 th acquisition of the nth summary.
Compared with the prior art, the invention has the following beneficial effects:
1. all information required by the electric energy meter metering fault diagnosis method in a limited range based on high-frequency current sampling can be accurately measured through the sensor, the acquisition is easy, factors affecting the accuracy of a model, such as line loss and the like, can be avoided, and accurate calculation can be realized;
2. the electric energy meter metering fault diagnosis model based on the limited range of high-frequency current sampling can realize accurate calculation of the operation error of the electric energy meter, effectively prolong the service life of the electric energy meter and avoid resource waste and electronic waste;
3. the invention is based on the electric energy meter metering fault diagnosis in the limited range of the high-frequency current sampling, does not need to add extra hardware equipment, and has small investment;
4. the invention can realize the metering fault diagnosis of the electric energy meter in a limited range based on high-frequency current sampling through software, does not need manual intervention in the whole process, can effectively eliminate the interference of human factors and ensures the fairness and fairness of the result.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
FIG. 1 is a schematic diagram of a current balance principle sampling based on a total current equal to the sum of the currents of the branches;
fig. 2 is a flow chart of an embodiment of the present invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Fig. 1 is a schematic diagram of sampling based on the current balance principle where the total current is equal to the sum of the currents of the branches, and it can be seen from the circuit principle that i=i A +I B +I C Always hold.
Examples: the method for diagnosing the metering faults of the electric energy meter in a limited range based on high-frequency current sampling is specifically realized by the following steps as shown in fig. 2.
Step one: collecting the current instantaneous values of the total table and each sub-table in the limited range at the same time, and obtaining a total sample space composed of a plurality of groups of data after multiple times of collection.
The limited range comprises a range such as a platform area, a meter box, a set formed by a plurality of meters hung under the same transformer, and the like.
It is noted that the summary of the transformer area is typically mounted on the low voltage side of the transformer. If the total table of the transformer area is installed on the high-voltage side or the total table of the transformer area collects the current data of the high-voltage side, the current of the high-voltage side needs to be converted into the accurate current of the low-voltage side by taking compensation measures.
The acquisition process of the plurality of groups of data comprises the following steps: determining the total number of tables and the number of sub-tables in a limited range, for example, assuming that the number of sub-tables is N-1 and the total number of tables is 1; collecting current instantaneous values of N electric energy meters at the same moment to obtain a group of initial collection data; judging whether the initial acquisition data are valid data or not, and if so, marking the initial acquisition data as a primary valid acquisition group; and repeating the collection at preset time intervals until the number of the effective collection groups is not lower than the number of the sub-tables.
If any group of initial acquisition data meets the effective judgment formula, judging the corresponding initial acquisition data as effective data, wherein the effective judgment formula specifically comprises:wherein x is ij The current instantaneous value acquired by the ith electric energy meter at the jth time is represented; n represents the sum of the total number and the sub-number.
It should be noted that the preset time interval is a minute-level interval and an hour-level interval, and each acquired data is independent and linearly independent.
Step two: establishing a coefficient matrix according to the acquired data of each sub-table in the overall sample space, establishing an augmentation matrix according to all the data in the overall sample space, and judging whether the ranks of the coefficient matrix and the augmentation matrix are equal; if the acquired data are equal, the acquired data are valid; if not, the acquired data is invalid.
The coefficient matrix is specifically:
wherein A represents a coefficient matrix; x is x (N-1)(N-1) Represent the firstN-1 is only divided into instantaneous values of current acquired in the N-1 time.
The augmentation matrix is specifically:
representing an augmentation matrix; x is x N(N-1) Indicating the instantaneous value, X, of the current collected from the N-1 th time of the total table N The table total number is 1.
Step three: and if the acquired data are invalid, performing a supplementary acquisition operation to acquire a group of data again, discarding the data with the same group number from the original total sample space to obtain a new total sample space, and obtaining a final total sample space until the ranks of the coefficient matrix and the augmentation matrix are equal.
The specific process of discarding data from the original total sample space is as follows: setting a discard threshold delta according to the instantaneous current sampling precision; counting the number C of not more than the discard threshold delta in each group of acquired data j J represents the collection data collected at the j-th time; reject max (C j ) All data of the group.
It should be noted that the reject threshold and the instantaneous current sampling precision are kept consistent or in a multiple relationship, the multiple is an integer of 1-10, and the reject threshold and the instantaneous current sampling precision can be selected according to actual needs. If the sampling accuracy is 1mA, δ=3ma.
Step four: and establishing an error calculation model according to the final total sample space, solving the error calculation model to obtain error data of the electric energy meter, and comparing the error data of the electric energy meter with a precision grade threshold value of the electric energy meter to obtain a fault diagnosis result.
The calculation formula of the error calculation model is specifically as follows:
AX＝B
wherein A represents a coefficient matrix; x represents an error matrix; b represents the result matrix.
The error matrix is specifically:
wherein ε N-1 And the error data of the N-1 electric energy meter are shown.
The result matrix is specifically:
wherein x is N(N-1) Indicating the instantaneous value, X, of the current collected from the N-1 th time of the total table N The table total number is 1.
For example, assume that the acquired data is as shown in table 1.
| Sample numbering | Acquisition time | Summary sheet | User A | User B | User C |
| 1 | t1 | X N1 | X A1 | X B1 | X C1 |
| 2 | t2 | X N2 | X A2 | X B2 | X C2 |
| 3 | t3 | X N3 | X A3 | X B3 | X C3 |
The coefficient matrix a and the constant term B can be established by the sampling data of table 1 and the calculation model ax=b is established.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing detailed description of the invention has been presented for purposes of illustration and description, and it should be understood that the invention is not limited to the particular embodiments disclosed, but is intended to cover all modifications, equivalents, alternatives, and improvements within the spirit and principles of the invention.
Claims (8)
1. The method for diagnosing the metering faults of the electric energy meter in a limited range based on high-frequency current sampling is characterized by comprising the following steps of:
collecting the current instantaneous values of the total table and each sub table in the limited range at the same time, and obtaining a total sample space composed of a plurality of groups of data after multiple times of collection;
establishing a coefficient matrix according to the acquired data of each sub-table in the overall sample space, establishing an augmentation matrix according to all the data in the overall sample space, and judging whether the ranks of the coefficient matrix and the augmentation matrix are equal; if the acquired data are equal, the acquired data are valid; if the acquired data are not equal, the acquired data are invalid;
if the acquired data are invalid, performing a supplementary acquisition operation to acquire at least one group of data again, discarding the data with the same group number from the original total sample space to obtain a new total sample space, and obtaining a final total sample space until the ranks of the coefficient matrix and the augmentation matrix are equal;
establishing an error calculation model according to the final overall sample space, solving the error calculation model to obtain electric energy meter error data, and comparing the electric energy meter error data with an accuracy grade threshold value of the electric energy meter to obtain a fault diagnosis result;
the calculation formula of the error calculation model is specifically as follows:
AX＝B
wherein A represents a coefficient matrix; x represents an error matrix; b represents a result matrix;
the error matrix specifically comprises:
wherein ε N-1 Error data of the N-1 electric energy meter are represented;
the result matrix specifically comprises:
wherein x is N(N-1) Indicating the current instantaneous value of the Nth total table acquired at the N-1 th time;
the coefficient matrix specifically comprises:
wherein A represents a coefficient matrix; x is x (N-1)(N-1) Indicating the current instantaneous value acquired by the N-1 th sub-table in the N-1 th time;
the augmentation matrix specifically comprises:
wherein,representing an augmentation matrix; x is x N(N-1) Indicating the instantaneous value, X, of the current collected from the N-1 th time of the total table N The table total number is 1.
2. The method for diagnosing metering faults of an electric energy meter in a limited range based on high-frequency current sampling as claimed in claim 1, wherein the limited range comprises a set of a platform area, a meter box and a plurality of meter hanging under the same transformer.
3. The method for diagnosing metering faults of the electric energy meter in a limited range based on high-frequency current sampling as claimed in claim 1, wherein the installation position of the summary is specifically as follows:
the total surface of the transformer area is arranged on the low-voltage side of the transformer;
or, when the total table of the transformer area is installed on the high-voltage side or the total table of the transformer area collects the current data of the high-voltage side, the current of the high-voltage side is converted into the accurate current of the low-voltage side by taking compensation measures.
4. The method for diagnosing metering faults of the electric energy meter in a limited range based on high-frequency current sampling as claimed in claim 1, wherein the collecting process of the plurality of groups of data is specifically as follows:
determining the total table number and the sub-table number in the limited range;
collecting all total tables and current instantaneous values of all sub tables at the same time to obtain a group of initial collection data;
judging whether the initial acquisition data are valid data or not, and if so, marking the initial acquisition data as a primary valid acquisition group;
and repeating the collection at preset time intervals until the number of the effective collection groups is not lower than the number of the sub-tables.
5. The method for diagnosing a metering fault of an electric energy meter within a limited range based on high-frequency current sampling as claimed in claim 4, wherein if any one group of the initial collected data satisfies an effective judgment formula, the corresponding initial collected data is judged to be effective data, and the effective judgment formula is specifically:
wherein x is ij The current instantaneous value acquired by the ith electric energy meter at the jth time is represented; n represents the sum of the total number and the sub-number.
6. The method for diagnosing metering faults of an electric energy meter in a limited range based on high frequency current sampling as claimed in claim 4, wherein the preset time interval is a minute-level interval and an hour-level interval, and each acquired data is independent and linearly independent.
7. The method for diagnosing metering faults of the electric energy meter in a limited range based on high-frequency current sampling as claimed in claim 1, wherein the specific process of discarding data from the original total sample space is as follows:
setting a discard threshold delta according to the instantaneous current sampling precision;
counting the number C of not more than the discard threshold delta in each group of acquired data j J represents the collection data collected at the j-th time;
reject max (C j ) All data of the group.
8. The method for diagnosing metering faults of an electric energy meter in a limited range based on high frequency current sampling as claimed in claim 7, wherein the rejection threshold is consistent with or in a multiple relationship with the instantaneous current sampling precision, and the multiple is an integer of 1-10.
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| CN114280527A (en) * | 2021-12-21 | 2022-04-05 | 青岛鼎信通讯股份有限公司 | Electric energy meter misalignment analysis method based on low-voltage Internet of things sensing terminal |
| CN115542236B (en) * | 2022-11-24 | 2023-06-06 | 北京志翔科技股份有限公司 | Electric energy meter operation error estimation method and device |
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