CN115542236A - Method and device for estimating running error of electric energy meter - Google Patents
Method and device for estimating running error of electric energy meter Download PDFInfo
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Abstract
The invention relates to the technical field of data analysis, and provides a method and a device for estimating running errors of an electric energy meter, wherein the method comprises the following steps: establishing an error model of the electric energy meter; punishment is carried out on the error coefficient of each electric energy meter in the transformer area in the electric energy meter error model based on the regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the transformer area is obtained; determining a candidate over-tolerance meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area; punishment and solving are carried out on the error coefficients of other electric energy meters except for the candidate out-of-tolerance meter in the electric energy meter error model based on the regular coefficient, so as to obtain a second error coefficient of each electric energy meter in the distribution area; and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area. The method can screen out potential over-tolerance tables under the transformer area and reasonably distribute regular coefficients to the potential over-tolerance tables, so that the calculation quality of the error coefficients of the ammeter under the transformer area is improved, and the error estimation accuracy is improved.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a method and a device for estimating running errors of an electric energy meter.
Background
With the automatic collection mode of the electricity information collection system replacing the traditional manual meter reading mode, the online analysis method of the intelligent electric energy meter becomes a new means for evaluating and monitoring the operation quality of the intelligent electric energy meter. The existing online analysis method usually researches and calculates the operation errors of each intelligent electric energy meter under a distribution area by taking the distribution area as a unit through a big data technology, and needs to construct an operation error model of each intelligent electric energy meter under the distribution area to calculate the line loss item of the distribution area, so as to realize error estimation.
However, in an actual scene, the difference between the error coefficients of the abnormal meter and the normal meter is often not considered in calculating the line loss item, so that the error estimation of the electric energy meter in the transformer area is inaccurate, and the result that the accurate detection of the abnormal meter in the transformer area cannot be realized is caused.
Disclosure of Invention
The invention provides an electric energy meter operation error estimation method and device, which are used for solving the defect that error estimation is inaccurate due to the fact that the difference between an over-range meter and a normal meter is not considered in the prior art, and accurately estimating the electric energy meter operation error by finely expressing a line loss item of a distribution room.
The invention provides an electric energy meter operation error estimation method, which comprises the following steps:
establishing an error model of the electric energy meter;
punishment is carried out on the error coefficient of each electric energy meter in the distribution room in the electric energy meter error model based on a regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the distribution room is obtained;
determining a candidate over-differential meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area;
punishment and solution are carried out on the error coefficients of other electric energy meters except the candidate out-of-tolerance meter in the distribution room in the electric energy meter error model based on the regular coefficient, and second error coefficients of all the electric energy meters in the distribution room are obtained;
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
According to the method for estimating the running error of the electric energy meter, the method for determining the candidate over-differential meter of the distribution area based on the first error coefficient of each electric energy meter in the distribution area comprises the following steps:
determining the difference of error distribution between each electric energy meter in the distribution area and the distribution area based on the first error coefficient of each electric energy meter in the distribution area;
and determining the electric energy meters with the difference meeting a first preset condition as the candidate super-difference meters based on the difference of the error distribution of each electric energy meter and the distribution area in the distribution area.
According to the method for estimating the running error of the electric energy meter, provided by the invention, the first preset condition comprises any one or any combination of the following three conditions:
the absolute value of a first error coefficient of the electric energy meter meets a first threshold value;
the statistical test result of the first error coefficient of the electric energy meter meets a second threshold value;
the number of the candidate over-differential meters is L, L is a positive integer and is less than the total number of the electric energy meters in the transformer area.
According to the method for estimating the operation error of the electric energy meter provided by the invention, under the condition that the first preset condition comprises the three conditions, the electric energy meter with the determined difference meeting the first preset condition is the candidate over-differential meter, and the method comprises the following steps:
determining the electric energy meter of which the absolute value of the first error coefficient in the distribution area meets a first threshold value as a first preselected electric energy meter;
determining the electric energy meter with the statistical test result of the first error coefficient in the first preselected electric energy meter meeting a second threshold value as a second preselected electric energy meter;
and sequencing the second preselected electric energy meters according to the significance of the statistical test result, and determining the first L second preselected electric energy meters with significance sequencing as the candidate super-difference meters.
According to the method for estimating the running error of the electric energy meter, a ridge regression method is adopted for solving the error model of the electric energy meter.
According to the method for estimating the operation error of the electric energy meter, which is provided by the invention, the establishment of the error model of the electric energy meter comprises the following steps:
and establishing an electric energy meter error model by combining an energy conservation law based on the electricity consumption of the district electric energy meter and the line loss data of the district electric energy meter.
According to the method for estimating the operation error of the electric energy meter, the method for determining the operation error of the electric energy meter in the transformer district based on the second error coefficient of each electric energy meter in the transformer district comprises the following steps:
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area and the line loss data of the electric energy meters in the transformer area.
The invention also provides an electric energy meter operation error estimation device, which comprises:
the input module is used for establishing an electric energy meter error model;
the first solving module is used for punishing and solving the error coefficients of all the electric energy meters in the distribution room in the electric energy meter error model based on the regular coefficients to obtain first error coefficients of all the electric energy meters in the distribution room;
the screening module is used for determining candidate super-difference meters of the distribution area based on the first error coefficients of the electric energy meters in the distribution area;
the second solving module is used for punishing and solving the error coefficients of other electric energy meters except the candidate out-of-tolerance meter in the distribution room in the electric energy meter error model based on the regular coefficient to obtain second error coefficients of all the electric energy meters in the distribution room;
and the output module is used for determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the method for estimating the running error of the electric energy meter.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of estimating an operating error of an electric energy meter as in any one of the above.
The invention also provides a computer program product, which comprises a computer program, and when the computer program is executed by a processor, the method for estimating the running error of the electric energy meter is realized.
According to the method and the device for estimating the running errors of the electric energy meters, the first error coefficients of the electric energy meters are calculated through conventional regression, then the suspected out-of-tolerance candidate out-of-tolerance tables in the transformer area are determined through the first loss coefficients, when the error coefficients are calculated for the second time, punishment is not conducted on the candidate out-of-tolerance table coefficients based on the regular coefficients, then the improved second error coefficients can be obtained through solving, and accurate running errors are obtained. The invention ensures the calculation accuracy of the out-of-tolerance meter and can apply moderate regular work to other electric energy meters to control the overall overfitting degree, so that the error coefficient has the characteristic of composite distribution in the error model calculation, and the accuracy of error coefficient estimation is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for estimating an operating error of an electric energy meter according to the present invention;
FIG. 2 is a second schematic flow chart of the method for estimating the operating error of the electric energy meter according to the present invention;
FIG. 3 is a schematic structural diagram of an apparatus for estimating an operating error of an electric energy meter according to the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for estimating the operating error of the electric energy meter according to the present invention is described below with reference to fig. 1 to fig. 2, and as shown in fig. 1, the method for estimating the operating error of the electric energy meter according to the embodiment of the present invention at least includes the following steps:
102, punishing and solving error coefficients of all electric energy meters in a distribution room in an electric energy meter error model based on regular coefficients to obtain first error coefficients of all electric energy meters in the distribution room;
103, determining a candidate super-difference meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area;
104, punishing and solving error coefficients of other electric energy meters except for the candidate over-error meter in the transformer area in the electric energy meter error model based on a regular coefficient to obtain second error coefficients of all the electric energy meters in the transformer area;
and 105, determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
In step 101, it should be noted that the electric energy meter error model is a model for researching and calculating the operation error of each intelligent electric energy meter in the distribution area by taking the distribution area as a unit, the model includes a user power consumption item and a line loss item, and the line loss item is the operation error of the target solution. During construction, a relation model between the line loss and the power consumption of the user is constructed through an energy conservation law.
For step 102, it should be noted that the error coefficient is a key loop for solving the line loss term, and the error coefficients of different electric energy meters are often added with the same regular coefficient to control the degree of overfitting of the model to obtain a more accurate coefficient. In the embodiment, the electric energy meter error model is punished and solved by a conventional method to obtain a first error coefficient, the error coefficient does not need to be accurate, and only the error coefficient needs to be used for preliminarily screening out a possibly out-of-tolerance meter to lay a cushion for further optimizing the coefficient subsequently.
In step 103, it should be noted that, based on the first error coefficient of each electric energy meter in the distribution area, the embodiment of the present invention obtains a suspected super-difference table list by screening according to the difference significance between the error value and the error distribution. In an actual scene, the coefficients of a small part of abnormal meters which are out of tolerance and misaligned are often far from the distribution interval of normal meters, so that the use of the same regular coefficients for all the meters is no longer reasonable in the region where the out-of-tolerance meters exist.
With respect to step 104, it should be noted that, when the same regular coefficients are used, if the values are too large, the method is equivalent to assuming that the coefficients are from a prior distribution with smaller variance, the error of the calculated out-of-tolerance table may be small due to over-compression, and meanwhile, the error signal of the out-of-tolerance table that is not completely fitted may affect the accurate measurement of errors of other electric meters in the station area, and if the values are too small, the error calculation quality of the whole station area may be affected by over-fitting. Therefore, the method tries to improve the calculation quality of the error coefficient of the electric meter under the transformer area by identifying and judging the potential suspected over-error table under the transformer area and reasonably distributing the regular coefficient to the potential suspected over-error table.
For step 105, it should be noted that, after the operation error of the electric energy meter in the station area is determined, the electric energy meter with the operation error reaching the standard of the out-of-tolerance meter is used as the finally screened out-of-tolerance meter based on the preset out-of-tolerance meter standard, and the out-of-tolerance meter at this time is closer to the actual situation of the station area than the candidate out-of-tolerance meter obtained by calculating according to the first error coefficient in step 103, that is, the identification accuracy of the out-of-tolerance meter is improved.
According to the method for estimating the running errors of the electric energy meters, the first error coefficients of the electric energy meters are calculated through conventional regression, then the suspected out-of-tolerance candidate out-of-tolerance tables in the distribution area are determined through the first loss coefficients, when the error coefficients are calculated for the second time, punishment is not carried out on the candidate out-of-tolerance table coefficients based on the regular coefficients, then the improved second error coefficients can be obtained through solving, and the accurate running errors are obtained. The method ensures the calculation accuracy of the out-of-tolerance meter, and can also apply moderate regulation to other electric energy meters to control the overall overfitting degree, so that the error coefficients have the characteristic of composite distribution in the error model calculation, and the accuracy of error coefficient estimation is improved.
It can be understood that, establishing the error model of the electric energy meter includes:
and establishing an electric energy meter error model by combining an energy conservation law based on the electricity consumption of the district electric energy meter and the line loss data of the district electric energy meter.
It should be noted that, in the embodiment of the present invention, based on the law of conservation of energy, the line loss obtained by using kirchhoff's law and the power consumption of the user are in a quadratic function relationship, and a finally established model equation is as shown in formula 1:
wherein, the first and the second end of the pipe are connected with each other,
an electricity matrix in the shape of
，
The number of the time points is measured and corresponds to the total number of the equation, and each point is the electricity consumption in the measurement interval.
The electricity utilization matrix for all users (sub-tables) in the distribution area is in the shape of
The electricity consumption of each user in each behavior metering interval,
is the number of the user table.
Error of sub-table under table areaCoefficient of shape of
。
Expressing a line loss term matrix constructed in an energy conservation equation in the shape of
，
The number of line loss terms added to construct the equation.
The line loss coefficient corresponding to each line loss term is expressed in the shape of
The physical meaning is equivalent resistance.
The loss constant is represented, and the sum of the losses under the transformer area is represented, wherein the losses generally come from the losses of the intelligent electric meter.
It can be understood that the solving method for the error model of the electric energy meter adopts a ridge regression method.
It should be noted that, in the current online misalignment error monitoring model of the smart meter, the energy conservation equation is often solved by a ridge regression algorithm, and the optimization target is shown in formula 2:
wherein the content of the first and second substances,
representing regular coefficients, in which error coefficients are added to the same regular coefficients
The overfitting degree of the model is controlled to solve the overfitting degree to obtain a more accurate coefficient.
In addition, it should be noted that besides the ridge regression algorithm, other linear regression algorithms, such as Lasso regression algorithm, may be used to solve the error model of the electric energy meter.
It is understood that, based on the first error coefficients of the electric energy meters in the station area, determining the candidate over-error table of the station area includes:
determining the difference of error distribution between each electric energy meter in the distribution area and the distribution area based on the first error coefficient of each electric energy meter in the distribution area;
and determining the electric energy meters with the difference meeting the first preset condition as candidate over-differential meters based on the difference of the error distribution of each electric energy meter in the transformer area and the transformer area.
It should be noted that the first error coefficient is a basic error coefficient obtained by performing a first round of solution on the electric energy meter error model by using a common linear regression method, the distribution of the station area error specifically refers to the distribution of the error coefficients of the whole station area, and the difference between the distribution of the electric energy meters in the station area and the distribution of the station area error is the difference significance obtained by comparing the first error coefficient of each electric energy meter with the distribution of the error coefficients of the whole station area. The first preset condition is set for screening the electric energy meters with larger difference in overall error distribution in the distribution area, and because the coefficients of a small part of abnormal meters which are out of tolerance and out of alignment are often far from the distribution interval of normal electric meters, the step can effectively screen the meters which are out of tolerance possibly.
It is understood that the first preset condition includes any one or any combination of the following three conditions:
the absolute value of a first error coefficient of the electric energy meter meets a first threshold value;
the statistical test result of the first error coefficient of the electric energy meter meets a second threshold value;
the number of the candidate super-difference meters is L, L is a positive integer and is smaller than the total number of the electric energy meters in the transformer area.
For the first condition, it should be noted that the first error coefficient has a positive or negative value, and therefore needs to be compared with the absolute value thereof. The first threshold is a criterion for directly screening the calculated first error coefficient, and therefore, the magnitude of the first error coefficient is significantly different from the distribution of all the electricity meters under the district, i.e., the first threshold may be three times the standard deviation of the error calculated based on the first error coefficient.
For the second condition, it should be noted that the statistical test result of the first error coefficient of the electric energy meter means that the statistical test method is adopted to solve the significance of the distribution difference between the first error coefficient and all the electric energy meters in the distribution area, and the statistical test method can be t test, F test, chi-square test, and the like. Therefore, the second threshold is also a test value threshold that satisfies the corresponding confidence level set depending on the different and actual data of the statistical test manner.
With respect to the third condition, it should be noted that, because the distribution of the super difference table is sparse and the number is small, the number L of the candidate super difference tables does not need to be set to be large, for example, L is found to be enough to set to 3,3 candidate numbers for super difference table screening.
It is understood that, in a case that the first preset condition includes three conditions, determining the electric energy meter whose difference satisfies the first preset condition as a candidate over-tolerance meter includes:
and determining the electric energy meter of which the absolute value of the first error coefficient in the station area meets the first threshold value as a first preselected electric energy meter.
It should be noted that, the magnitude of the first error value is significantly different from the overall distribution of the station area errors, i.e. the first condition is as shown in equation 3:
wherein, the first and the second end of the pipe are connected with each other,
a first error coefficient representing an ith block table of the station area,
the standard deviation of error of all the meters under the station area is shown.
And determining the electric energy meter with the statistical test result of the first error coefficient in the first preselected electric energy meter meeting the second threshold value as a second preselected electric energy meter.
It should be noted that the embodiment of the present invention uses t-test to calculate the statistical test result. Specifically, the optimization objective of t-test for the embodiment of the present invention is shown in formula 4:
wherein the content of the first and second substances,
representation is based on
Regular terms added into the matrix, the expansion form of a general regular matrix,
is a part of the feature matrix in the linear regression model,
。
the t-test value of the first error coefficient is calculated by adopting an equation 5:
wherein the content of the first and second substances,
for the t-test value of the ith block of the first pre-selected power meter,
for the estimated coefficient-noise covariance matrix,
，
，
is the trace of the matrix and is the trace of the matrix,
，
is a mapping matrix from the fitted object to the fitted object.
Specifically, the second threshold is a condition for judging that the statistical test result is significant, and in the embodiment of the present invention, the second threshold is 3, that is, each first preselected electric energy meter needs to be calculated
Then, if
It is considered to be significantly different and judged as the second pre-selected power meter. 3 is a common threshold in statistical tests, corresponding to a 99.7% confidence level when assuming a normal/gaussian distribution.
And sorting the second preselected electric energy meters according to the significance of the statistical test result, and determining the second preselected electric energy meters with the first L ranked significance as candidate super-difference meters.
It should be noted that after the significance of the second preselected electric energy meter is ranked, the electric energy meter with the significance ranked in the first three digits is selected. Specifically, a method for sorting the significance degrees after t test in the first three digits is selected, as shown in formula 6:
and are in order to ensure that the water-soluble organic acid,
，
and
are respectively the first
And a first
The block second preselects the t-test value of the electric energy meter.
It can be understood that punishment and solution are performed on the error coefficients of the electric energy meters except the candidate over-tolerance meter in the electric energy meter error model based on the regular coefficient, which means that the suspected over-tolerance meter relaxation regular coefficient is subjected to the second round of calculation to obtain the second error coefficient of each electric energy meter in the improved distribution room.
Specifically, the optimization goal shown in formula 2 is changed to the optimization goal shown in formula 7:
wherein, the first and the second end of the pipe are connected with each other,
indicating that the error coefficients of the preselected super-difference meter are no longer penalized based on regular coefficients, i.e. only regular terms of the electrical energy meter are calculated except for the preselected super-difference meter comprised by L. And then solving to obtain the improved second error coefficient.
According to the electric energy meter operation error estimation method, through two rounds of ridge regression calculation and the solving mode of adjusting the regular coefficient to adapt to the distribution of the composite coefficient, the method is similar to the method of carrying out unbiased least square estimation between suspected out-of-tolerance electric meters, so that the accuracy of out-of-tolerance electric meter calculation is guaranteed, and meanwhile, proper regular patterns can be applied to other electric meters to control the overall overfitting degree.
It can be understood that, determining the operation error of the electric energy meter in the distribution area based on the second error coefficient of each electric energy meter in the distribution area includes:
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficients of the electric energy meters in the transformer area and the line loss data of the electric energy meters in the transformer area.
It should be noted that, in the following description,
it can be understood that, as shown in fig. 2, an embodiment of the present invention discloses a method for estimating an operating error of an electric energy meter, which at least includes the following steps:
1) The magnitude of the error value of the first error coefficient is obviously different from the integral distribution of the station area errors;
2) The t test value of the first error coefficient is judged to be significant through statistical test;
3) The significant electric meter coefficients are arranged at the front, and the significance is sorted in the first three digits;
and step 205, determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
According to the electric energy meter operation error estimation method, the regular coefficients are adjusted in the second round of calculation, and the method is similar to the method of performing one-time unbiased least square estimation between suspected out-of-tolerance electric meters, so that the accuracy of calculation of the out-of-tolerance electric meters is guaranteed, and meanwhile, proper regular patterns can be applied to other electric meters to control the overall overfitting degree, and therefore the error coefficients have the characteristic of composite distribution in the misalignment model calculation, and the accuracy of error coefficient estimation is improved. In addition, compared with a method for directly adding a composite prior in an optimized target, the method only solves a simple ridge regression problem in two steps of separate solution, has an analytic solution which is easy to calculate, and avoids the problem of difficult convergence in the process of optimizing the complex target.
The following describes the operation error estimation device of the electric energy meter provided by the present invention, and the operation error estimation device of the electric energy meter described below and the operation error estimation method of the electric energy meter described above may be referred to each other correspondingly.
As shown in fig. 3, the device for estimating the operating error of the electric energy meter according to the embodiment of the present invention includes:
the input module 301 is used for establishing an electric energy meter error model;
the first solving module 302 is configured to punish and solve error coefficients of each electric energy meter in the distribution room in the electric energy meter error model based on a regular coefficient to obtain first error coefficients of each electric energy meter in the distribution room;
the screening module 303 is configured to determine a candidate super-difference meter of the distribution room based on the first error coefficient of each electric energy meter in the distribution room;
the second solving module 304 is configured to punish and solve error coefficients of other electric energy meters in the distribution room except for the candidate out-of-tolerance meter based on a regular coefficient in the electric energy meter error model to obtain second error coefficients of each electric energy meter in the distribution room;
and the output module 305 is configured to determine an operation error of the electric energy meters in the transformer district based on the second error coefficient of each electric energy meter in the transformer district.
According to the electric energy meter operation error estimation device provided by the embodiment of the invention, the first solving module 302 calculates the first error coefficient of each electric energy meter through conventional regression, then the screening module 303 determines the suspected out-of-tolerance candidate out-of-tolerance tables in the distribution room through the first loss coefficient, the second solving module 304 does not punish the candidate out-of-tolerance table coefficients based on the regular coefficient when calculating the error coefficients for the second time, and then the improved second error coefficient can be obtained through solving, so that the accurate operation error is obtained. The device provided by the invention ensures the calculation accuracy of the out-of-tolerance meter, and can also apply moderate regulation to other electric energy meters to control the overall overfitting degree, so that the error coefficient has the characteristic of composite distribution in the error model calculation, and the accuracy of error coefficient estimation is improved.
It is understood that, based on the first error coefficients of the electric energy meters in the station area, determining the candidate over-error table of the station area includes:
determining the difference of error distribution between each electric energy meter in the distribution area and the distribution area based on the first error coefficient of each electric energy meter in the distribution area;
and determining the electric energy meters with the difference meeting the first preset condition as candidate over-differential meters based on the difference of the error distribution of each electric energy meter in the transformer area and the transformer area.
It is understood that the first preset condition includes any one or any combination of the following three conditions:
the absolute value of a first error coefficient of the electric energy meter meets a first threshold value;
the statistical test result of the first error coefficient of the electric energy meter meets a second threshold value;
the number of the candidate over-differential meters is L, L is a positive integer and is less than the total number of the electric energy meters in the transformer area.
It is understood that, in a case that the first preset condition includes three conditions, determining the electric energy meter whose difference satisfies the first preset condition as a candidate over-tolerance meter includes:
determining the electric energy meter of which the absolute value of the first error coefficient in the distribution area meets a first threshold value as a first preselected electric energy meter;
determining the electric energy meter with the statistical test result of the first error coefficient in the first preselected electric energy meter meeting the second threshold value as a second preselected electric energy meter;
and sorting the second preselected electric energy meters according to the significance of the statistical test result, and determining the second preselected electric energy meters with the first L ranked significance as candidate super-difference meters.
It can be understood that the solving method for the error model of the electric energy meter adopts a ridge regression method.
It can be understood that, establishing the error model of the electric energy meter includes:
and establishing an electric energy meter error model by combining an energy conservation law based on the electricity consumption of the district electric energy meter and the line loss data of the district electric energy meter.
It can be understood that, determining the operation error of the electric energy meters in the district based on the second error coefficient of each electric energy meter in the district includes:
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficients of the electric energy meters in the transformer area and the line loss data of the electric energy meters in the transformer area.
Fig. 4 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 4: a processor (processor) 410, a communication Interface 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a method of power meter run error estimation, the method comprising:
establishing an error model of the electric energy meter;
punishment is carried out on the error coefficient of each electric energy meter in the distribution room in the electric energy meter error model based on the regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the distribution room is obtained;
determining a candidate over-differential meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area;
punishment and solving are carried out on the error coefficients of other electric energy meters except for the candidate out-of-tolerance meter in the electric energy meter error model based on the regular coefficient, so as to obtain a second error coefficient of each electric energy meter in the distribution area;
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer readable storage medium, when the computer program is executed by a processor, the computer can execute the method for estimating the operation error of the electric energy meter provided by the above methods, and the method includes:
establishing an error model of the electric energy meter;
punishment is carried out on the error coefficient of each electric energy meter in the transformer area in the electric energy meter error model based on the regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the transformer area is obtained;
determining a candidate over-tolerance meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area;
punishment and solving are carried out on the error coefficients of other electric energy meters except for the candidate out-of-tolerance meter in the electric energy meter error model based on the regular coefficient, so as to obtain a second error coefficient of each electric energy meter in the distribution area;
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements a method for estimating an operating error of an electric energy meter provided by the above methods, the method comprising:
establishing an error model of the electric energy meter;
punishment is carried out on the error coefficient of each electric energy meter in the transformer area in the electric energy meter error model based on the regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the transformer area is obtained;
determining a candidate over-differential meter of the transformer area based on the first error coefficient of each electric energy meter in the transformer area;
punishment and solving are carried out on the error coefficients of other electric energy meters except for the candidate out-of-tolerance meter in the electric energy meter error model based on the regular coefficient, so as to obtain a second error coefficient of each electric energy meter in the distribution area;
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
The above-described embodiments of the apparatus are merely illustrative, and units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An electric energy meter operation error estimation method is characterized by comprising the following steps:
establishing an error model of the electric energy meter;
punishment is carried out on the error coefficient of each electric energy meter in the distribution room in the electric energy meter error model based on a regular coefficient, and solution is carried out, so that a first error coefficient of each electric energy meter in the distribution room is obtained;
determining a candidate super-difference meter of the distribution area based on the first error coefficient of each electric energy meter in the distribution area;
punishment is carried out on the error coefficients of other electric energy meters except the candidate out-of-tolerance meter in the electric energy meter error model based on the regular coefficient, and solution is carried out, so that second error coefficients of all the electric energy meters in the station area are obtained;
and determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
2. The method of claim 1, wherein determining the candidate over-error table for the region based on the first error coefficients of the power meters in the region comprises:
determining the difference of error distribution between each electric energy meter in the distribution area and the distribution area based on the first error coefficient of each electric energy meter in the distribution area;
and determining the electric energy meters with the difference meeting a first preset condition as the candidate super-difference meters based on the difference of the error distribution of each electric energy meter and the distribution area in the distribution area.
3. The method according to claim 2, wherein the first preset condition comprises any one of the following three conditions or any combination of the three conditions:
the absolute value of a first error coefficient of the electric energy meter meets a first threshold value;
the statistical test result of the first error coefficient of the electric energy meter meets a second threshold value;
the number of the candidate super-differential meters is L, L is a positive integer and is smaller than the total number of the electric energy meters in the transformer area.
4. The method according to claim 3, wherein in the case that the first preset condition includes the three conditions, the determining that the electric energy meter whose difference satisfies the first preset condition is the candidate over-tolerance meter includes:
determining the electric energy meter of which the absolute value of the first error coefficient in the distribution area meets a first threshold value as a first preselected electric energy meter;
determining the electric energy meter with the statistical test result of the first error coefficient in the first preselected electric energy meter meeting a second threshold value as a second preselected electric energy meter;
and sorting the second preselected electric energy meters according to the significance of the statistical test result, and determining the second preselected electric energy meters with the significance sorted in the first L numbers as the candidate super-difference meters.
5. The method for estimating the running error of the electric energy meter according to any one of claims 1 to 4, wherein a ridge regression method is adopted as a solving method for the error model of the electric energy meter.
6. The method for estimating the operating error of the electric energy meter according to any one of claims 1 to 4, wherein the establishing an error model of the electric energy meter comprises the following steps:
and establishing an electric energy meter error model by combining an energy conservation law based on the electricity consumption of the district electric energy meter and the line loss data of the district electric energy meter.
7. The method of claim 6, wherein determining the operation error of the power meters in the district based on the second error coefficients of the power meters in the district comprises:
and determining the operation error of the distribution area electric energy meter based on the second error coefficient of each electric energy meter in the distribution area and the line loss data of the distribution area electric energy meter.
8. An electric energy meter operation error estimation device, comprising:
the input module is used for establishing an electric energy meter error model;
the first solving module is used for punishing and solving the error coefficients of all the electric energy meters in the distribution room in the electric energy meter error model based on regular coefficients to obtain first error coefficients of all the electric energy meters in the distribution room;
the screening module is used for determining candidate over-error meters of the transformer area based on the first error coefficients of the electric energy meters in the transformer area;
the second solving module is used for punishing and solving the error coefficients of other electric energy meters except the candidate out-of-tolerance meter in the station area in the electric energy meter error model based on the regular coefficient to obtain second error coefficients of all the electric energy meters in the station area;
and the output module is used for determining the operation error of the electric energy meters in the transformer area based on the second error coefficient of each electric energy meter in the transformer area.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the method of estimating an operating error of an electric energy meter according to any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for estimating an operating error of a power meter according to any of claims 1 to 7.
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