CN113376564B - Smart electric meter metering correction method and device based on data analysis and terminal - Google Patents

Abstract

The present invention is applicable to the technical field of smart meters, and provides a method, device, terminal, and computer-readable storage medium for metering and correcting smart meters based on data analysis. The metering difference within a specified time period is obtained to obtain a target difference set; the metering difference of at least two smart meters corresponding to other meter boxes is obtained within the specified time period to obtain at least two comparison difference sets, wherein the target The meter box and at least two other meter boxes are respectively meter boxes on different low-voltage lines; the difference analysis is performed on the data group consisting of the target difference set and at least two comparison difference sets, and the target meter box is analyzed according to the analysis results. Each smart meter in the meter is calibrated. The invention can find the out-of-range measurement error of the smart electric meter in time, and perform relatively accurate measurement correction.

Description

Method, device and terminal for smart meter measurement and correction based on data analysis

technical field

The invention belongs to the technical field of smart meters, and in particular relates to a data analysis-based smart meter measurement correction method, a correction device, a terminal and a computer-readable storage medium.

Background technique

At present, the smart meter has become an important device in the load management of the smart grid. Its operating principle is to record the voltage U and current I information in the circuit through high sampling density. Information storage, information processing, automatic control, information interaction and other functions are driven by various needs such as electric energy metering, electric power marketing, customer service, etc., with the accuracy and stability of electric energy metering as the engineering purpose to realize the corresponding functions.

However, in the application of smart meters in electric energy metering work, unexpected metering failures may occur. For example, power data mutation failure. Power data mutation failure refers to the discrepancy between the metered power of the smart meter and the actual power consumption. After statistical verification, it was found that the program design of some smart meters was flawed. When the smart meter was disturbed, the relevant program could not effectively eliminate the interference, and the wrong data after the disturbance was directly recorded, resulting in a sudden change in the data of electric energy metering, forming a Out of range measurement error.

In addition, due to different application environments, there are measurement errors in the actual measurement of smart meters. For example, changes in voltage, current, and temperature will affect the measurement of smart meters. The measurement errors of normal smart meters are usually within the allowable range. Then, Due to some special reasons, the measurement error of some electric energy meters will exceed the allowable range, such as fast and slow characters, slow characters will cause losses to the power department, and fast characters will cause losses to users, causing user dissatisfaction. Such failures are usually difficult to detect in time.

Contents of the invention

In view of this, the present invention provides a smart meter calibration method, device, terminal and computer-readable storage medium based on data analysis, so as to solve the out-of-range measurement error of the smart meter in the prior art, which cannot be timely and accurately problems of discovery and metrological correction.

The first aspect of the embodiments of the present invention provides a smart meter meter correction method based on data analysis, the meter correction method includes:

Obtain the measurement difference value of each smart meter in the target meter box within a specified time period, and obtain the set of target difference values;

Obtain the metering difference of smart meters corresponding to at least two other meter boxes within the specified time period to obtain at least two comparison difference sets, wherein the target meter box and the at least two other meter boxes are respectively different low-voltage lines on the meter box;

Perform difference analysis on the data group composed of the target difference set and the at least two comparison difference sets, and perform measurement correction on each smart meter in the target meter box according to the analysis result.

In an optional embodiment, performing data analysis on the data group consisting of the target difference set and the at least two comparison difference sets, and performing metering on each smart meter in the target meter box according to the analysis result Corrections include:

calculating the arithmetic mean of the target difference set to obtain the target arithmetic mean;

Calculating the arithmetic mean of the at least two comparison difference sets respectively to obtain at least two comparison arithmetic mean;

Carrying out discrete clustering on the target arithmetic mean and the at least two comparative arithmetic means, if the target arithmetic mean does not belong to the central category, then determine that each smart meter in the target meter box needs to be metered Correction;

Based on the metering difference of the smart meters in the meter box corresponding to the center point of the central category, the metering correction is performed on the smart meters in the target meter box.

In a possible implementation manner, performing metering correction on the smart meters in the target meter box based on the metering difference of the smart meters in the meter box corresponding to the central point of the major category includes:

Calculate the average value of the metering difference of each smart meter in the meter box corresponding to the center point of the center category;

Perform measurement correction for each smart meter in the target meter box based on the average value.

In a possible implementation manner, the acquisition of the metering difference of each smart meter in the target meter box within a specified time period, and obtaining the target difference set includes:

Obtain the measurement value of each smart meter in the target meter box within a specified time period;

Obtain the calculated value of each smart meter in the target meter box within the specified time period;

The difference between the measured value and the calculated value of each smart meter is counted to form a target difference set.

In a possible implementation manner, performing measurement correction on each smart meter in the target meter box based on the average value includes:

Taking the average value as the first standard measurement error, perform measurement correction on the calculated values of the smart meters in the target meter box within the specified time period, and obtain metering data of the smart meters in the target meter box.

In a possible implementation manner, after obtaining the metering difference of each smart meter in the target meter box within a specified time period and obtaining the target difference set, it further includes:

Statistically calculate the deviation of the corresponding measurement difference of each smart meter in the target difference set;

Calibration is performed on target smart meters whose dispersion is greater than a preset threshold.

In a possible implementation manner, performing metering correction on the target smart meter whose dispersion is greater than a preset threshold includes:

The average value of the measurement difference corresponding to each smart meter in the statistical target difference set;

The target smart meter is calibrated with the average value of the metering difference corresponding to each smart meter in the statistical target difference set, and the metering data of the target meter is obtained.

The second aspect of the embodiment of the present invention provides a smart meter meter correction device based on data analysis, the meter correction device includes:

The first acquisition unit is configured to acquire the metering difference of each smart meter in the target meter box within a specified time period to obtain a target difference set;

The second acquisition unit is configured to acquire the metering difference of smart meters corresponding to at least two other meter boxes within the specified time period, and obtain at least two comparison difference sets, wherein the target meter box and at least two other meters The boxes are the meter boxes on different low-voltage lines;

The metering correction unit is configured to perform difference analysis on the data group composed of the target difference set and the at least two comparison difference sets, and perform metering correction on each smart meter in the target meter box according to the analysis result.

In a possible implementation manner, the measurement correction device further includes:

A target arithmetic mean calculation unit, configured to calculate the arithmetic mean of the target difference set to obtain the target arithmetic mean;

A comparison arithmetic mean calculation unit, configured to separately calculate the arithmetic mean of the at least two comparison difference sets to obtain at least two comparison arithmetic means;

a discrete clustering unit, configured to perform discrete clustering on the target arithmetic mean and the at least two comparison arithmetic mean; if the target arithmetic mean does not belong to the central category, then determine the target meter box Each smart meter needs to be calibrated;

Correspondingly, the metering correction unit is specifically configured to perform metering correction on each smart meter in the target meter box based on the metering difference of each smart meter in the meter box corresponding to the center point of the central category.

In a possible implementation manner, the measurement correction device further includes:

The first average value calculation unit is used to calculate the average value of the metering difference of each smart meter in the meter box corresponding to the center point of the center category;

Correspondingly, the metering correction unit is specifically configured to perform metering correction on each smart meter in the target meter box based on the average value calculated by the first average value calculation unit.

In a possible implementation manner, the measurement correction device further includes:

The measurement value acquisition unit is used to obtain the measurement value of each smart meter in the target meter box within a specified time period;

a calculated value acquisition unit, configured to acquire the calculated values of each smart meter in the target meter box within the specified time period;

Correspondingly, the first acquisition unit is specifically configured to count the difference between the measured value and the calculated value of each smart meter to form a target difference set.

In a possible implementation manner, the first acquisition unit is further configured to use the average value as the first standard measurement error to perform measurement correction on the calculated values of the smart meters in the target meter box within the specified time period , to obtain the metering data of each smart meter in the target meter box.

In a possible implementation manner, the measurement correction device further includes:

A dispersion statistics unit, used for statistically calculating the dispersion of the measurement difference corresponding to each smart meter in the target difference set;

Correspondingly, the metering correction unit is specifically further configured to perform metering correction on target smart meters whose dispersion is greater than a preset threshold.

In a possible implementation manner, the measurement correction device further includes:

The second average value statistical unit is used to count the average value of the measurement difference corresponding to each smart meter in the target difference set;

Correspondingly, the metering correction unit is also specifically used to perform metering correction on the target smart meter by using the average value of the metering difference corresponding to each smart meter in the target difference set counted by the second average value statistical unit to obtain the metering data of the target electric energy meter .

A third aspect of the embodiments of the present invention provides a terminal, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, the The steps of the smart meter measurement correction method based on data analysis as described in any one.

A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the data analysis-based Steps of a method for metering and calibrating a smart electric meter.

The beneficial effect that the present invention exists compared with prior art is:

The present invention obtains the measurement difference value of each smart meter in the target meter box within a specified time period to obtain a set of target difference values; obtains the measurement difference values of at least two smart meters corresponding to other meter boxes within the specified time period , to obtain at least two comparison difference sets; perform difference analysis on the data group consisting of the target difference set and the at least two comparison difference sets, and perform measurement correction on each smart meter in the target meter box according to the analysis results. Because usually the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line will be disturbed, and the target meter box and at least two other meter boxes are respectively meter boxes on different low-voltage lines, they will be interfered at the same time and are both The probability of sudden changes in metering data is extremely small, and out-of-range metering errors are usually reflected in the metering difference data of smart meters, so the data formed based on the metering differences of the target meter box and at least two other meter boxes Through comparative analysis, it is possible to find in time whether the smart meter in the target meter box has an out-of-range measurement error, and can refer to the meter error data of the meter box whose meter error does not exceed the range, and compare the meter errors of at least two smart meters corresponding to other meter boxes. The measurement data of the meter box is used for more accurate measurement correction. It can be seen that the present invention can detect the out-of-range measurement error of the smart meter in a timely manner, and perform relatively accurate measurement correction.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the descriptions of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only of the present invention. For some embodiments, those of ordinary skill in the art can also obtain other drawings based on these drawings without paying creative efforts.

Fig. 1 is a flow chart of the implementation of the smart meter meter calibration method based on data analysis provided by the embodiment of the present invention;

Fig. 2 is a schematic structural diagram of a smart meter meter correction device based on data analysis provided by an embodiment of the present invention;

Fig. 3 is a schematic diagram of a terminal provided by an embodiment of the present invention.

detailed description

In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

In order to make the purpose, technical solution and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

Referring to FIG. 1 , it shows a flow chart of the implementation of the data analysis-based smart meter measurement correction method provided by the embodiment of the present invention, which is described in detail as follows:

In step 101, the metering difference of each smart meter in the target meter box within a specified time period is obtained to obtain a target difference set;

In one application scenario, it can be applied to a cloud server, and the metering difference value of each smart meter in the target meter box within a specified time period is obtained through the cloud server through remote wireless communication, and a set of target difference values is obtained.

In another application scenario, calibration terminals can be set up for the meter boxes corresponding to different low-voltage lines. There are a number of smart meters in the meter box, and the calibration terminal communicates with the smart meters in the corresponding meter box. Calibration The terminals are connected by communication; the near-end calibration terminal takes the metering difference of each smart meter in the target meter box within a specified time period to obtain a target difference set.

In the embodiment of the present invention, the target difference set refers to the set of measurement differences of several smart meters in the target meter box within a specified time period. For example, if there are 9 smart meters in the target meter box, the obtained target difference The value set may be a set including 9 difference data.

In an implementation manner, the above step 101 may include:

Obtain the measurement value of each smart meter in the target meter box within a specified time period;

Obtain the calculated value of each smart meter in the target meter box within the specified time period;

The difference between the measured value and the calculated value of each smart meter is counted to form a target difference set.

In the embodiment of the present invention, the measurement difference may refer to the difference between the measurement value of the smart meter and the theoretical calculation value.

In the embodiment of the present invention, the reason why the data of the same specified time period is used is that within the same specified time period, the influence of environmental factors on the smart meters in the target meter box is relatively consistent, for example, at the same time, the target meter box The ambient temperature of each smart meter in the battery is consistent.

In step 102, the metering difference of the smart meters corresponding to at least two other meter boxes within the specified time period is obtained, and at least two comparison difference sets are obtained, wherein the target meter box and at least two other meter boxes are respectively It is the meter box on different low-voltage lines.

In the embodiment of the present invention, due to the analysis and comparison of data, it is also necessary to obtain the metering difference of at least two smart meters corresponding to other meter boxes within the specified time period, and obtain at least two comparison difference sets , and since the target meter box and at least two other meter boxes are respectively meter boxes on different low-voltage lines, it is impossible for these meter boxes to be affected by interference at the same time and produce data mutations, resulting in out-of-range errors. Therefore, assuming that the data of three meter boxes are collected in total, then at least two of the meter boxes have data within the normal error range, and at most there will only be one meter box with out-of-range error data. When comparing the data of the meter box of the low-voltage line, the comparison result will be more accurate.

In step 103, perform difference analysis on the data group consisting of the target difference set and the at least two comparison difference sets, and perform measurement correction on each smart meter in the target meter box according to the analysis result

In the embodiment of the present invention, by performing difference analysis on the data group consisting of the target difference set and at least two comparison difference sets, the data of the meter box where the smart meter with an out-of-range error will inevitably be reflected in the data analysis results In this way, the out-of-range error of each smart meter in the target meter box can be found in time and accurate measurement correction can be carried out according to the analysis results.

In an implementation manner, the above step 103 may include:

calculating the arithmetic mean of the target difference set to obtain the target arithmetic mean;

Calculating the arithmetic mean of the at least two comparison difference sets respectively to obtain at least two comparison arithmetic mean;

Carrying out discrete clustering on the target arithmetic mean and the at least two comparative arithmetic means, if the target arithmetic mean does not belong to the central category, then determine that each smart meter in the target meter box needs to be metered Correction;

Based on the metering difference of the smart meters in the meter box corresponding to the center point of the central category, the metering correction is performed on the smart meters in the target meter box.

In the embodiment of the present invention, the metering difference reflects the difference between the metering value and the calculated value of the smart meter, and the arithmetic mean of the metering difference set can evaluate the overall situation of the metering difference of the smart meter in the meter box. For example, if the target meter box If there is an error out of range smart meter, the arithmetic mean of the corresponding target difference set should be greater than the normal metering difference of the normal smart meter. After discrete clustering, the target arithmetic mean must not belong to the center category, but Dissociated from the central category; on the contrary, if there is no error out-of-range smart meter in the target meter box, the arithmetic mean of the corresponding target difference set should be approximately equal to the normal metering difference of the normal smart meter. After class, the target arithmetic mean must belong to the central class. Therefore, through the above-mentioned analysis method, the meter boxes with smart meters whose errors exceed the range can be found in time.

In an implementation manner, the measurement correction of the smart meters in the target meter box based on the metering difference of the smart meters in the meter box corresponding to the center point of the center category may include: calculating the center value The average value of the metering difference of each smart meter in the meter box corresponding to the center point of the class; based on the average value, meter correction is performed on each smart meter in the target meter box.

In the embodiment of the present invention, if it is found that there is an error out-of-range smart meter, it is necessary to perform metering correction on the error-out-of-range smart meter, so as to provide users with reasonable and correct metering results. The average value of the metering difference of each smart meter in the meter box corresponding to the center point of the center category belongs to the normal smart meter whose metering error is within the allowable range, and the average value of the metering difference of these normal smart meters can be used as the standard. Perform measurement calibration for each smart meter in the target meter box.

In an implementation manner, the above-mentioned metering correction of each smart meter in the target meter box based on the average value includes: taking the average value as the first standard metering error, and performing a measurement of each smart meter in the target meter box in the target meter box. The metering correction is performed on the calculated value within the specified time period, and the metering data of each smart meter in the target meter box is obtained.

In this embodiment, the calculated value is theoretical measurement data, and it is not suitable to use this value as the final measurement basis in practical applications. The calculated value will cause a deficit in the total table. Therefore, for a smart meter with an error out of range, the average value of its calculated value plus the measurement difference of a normal smart meter can be used as the final metering data.

In an implementation manner, after the above step 101, it may further include: counting the dispersion of the metering difference corresponding to each smart meter in the target difference set; performing metering correction on the target smart meter whose dispersion is greater than a preset threshold.

Dispersion is the difference between the average value and the true value of the observed value or estimated quantity, and is one of the measures to reflect the degree of dispersion of data distribution. In the embodiment of the present invention, the data index of the dispersion can accurately reflect the same meter box Whether there are smart meters with fast or slow characters in the meter and beyond the normal error range.

In the embodiment of the present invention, smart meters that go fast or slow and exceed the normal error range usually appear in the form of individual cases, and the reason is usually because of instantaneous high voltage breakdown smart meters caused by power grid fluctuations or lightning strikes Some devices (such as capacitors) lead to abnormal CPU power supply voltage, which causes abnormal reading and writing data of the PC loop. Therefore, through the data analysis of the measurement difference of the smart meters in the same time period in the same meter box, it is possible to accurately find the smart meters that go fast or slow and exceed the normal error range.

In an implementation manner, the above-mentioned measurement correction of the target smart electric meter whose deviation is greater than the preset threshold may include: counting the average value of the measurement difference corresponding to each smart electric meter in the target difference set; The smart meter performs measurement correction on the target smart meter corresponding to the average value of the metering difference, and obtains the metering data of the target meter.

In the embodiment of the present invention, after finding the smart meters with fast or slow characters and exceeding the normal error range, the average value of the corresponding measurement difference of other smart meters (normal smart meters) can be counted, and the average value can be compared with the target The smart meter performs measurement correction to obtain the final measurement data of the target electric energy meter. For example, the theoretical calculation value of the target electric energy meter plus the average value of the corresponding measurement difference of the normal smart electric meter in the meter box can be used as the final measurement value of the target electric energy meter .

As can be seen from the above, the present invention obtains the target difference set by obtaining the metering difference of each smart meter in the target meter box within the specified time period; obtains the smart meter corresponding to at least two other meter boxes within the specified time period At least two comparison difference sets are obtained; the difference analysis is performed on the data group consisting of the target difference set and at least two comparison difference sets, and each smart meter in the target meter box is analyzed according to the analysis results. Metrological correction. Because usually the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line will be disturbed, and the target meter box and at least two other meter boxes are respectively meter boxes on different low-voltage lines, they will be interfered at the same time and are both The probability of sudden changes in metering data is extremely small, and out-of-range metering errors are usually reflected in the metering difference data of smart meters, so the data formed based on the metering differences of the target meter box and at least two other meter boxes Through comparative analysis, it is possible to find in time whether the smart meter in the target meter box has an out-of-range measurement error, and can refer to the meter error data of the meter box whose meter error does not exceed the range, and compare the meter errors of at least two smart meters corresponding to other meter boxes. The measurement data of the meter box is used for more accurate measurement correction. It can be seen that the present invention can detect the out-of-range measurement error of the smart meter in a timely manner, and perform relatively accurate measurement correction.

It should be understood that the sequence numbers of the steps in the above embodiments do not mean the order of execution, and the execution order of each process should be determined by its functions and internal logic, and should not constitute any limitation to the implementation process of the embodiment of the present invention.

The following are device embodiments of the present invention. For details that are not exhaustively described therein, reference may be made to the corresponding method embodiments above.

Fig. 2 shows a schematic structural diagram of a data analysis-based smart meter metering correction device provided by an embodiment of the present invention. For the convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:

As shown in FIG. 2 , the measurement correction device 2 may include: a first acquisition unit 21 , a second acquisition unit 22 and a measurement correction unit 23 .

The first acquisition unit 21 is used to acquire the metering difference of each smart meter in the target meter box within a specified time period to obtain a target difference set;

The second acquiring unit 22 is configured to acquire the metering difference values of the smart meters corresponding to at least two other meter boxes within the specified time period, and obtain at least two comparison difference sets, wherein the target meter box and at least two other meter boxes The meter boxes are the meter boxes on different low-voltage lines;

The metering correction unit 23 is configured to perform difference analysis on the data group composed of the target difference set and the at least two comparison difference sets, and perform metering correction on each smart meter in the target meter box according to the analysis result.

In a possible implementation manner, the measurement calibration device 2 may also include:

A target arithmetic mean calculation unit, configured to calculate the arithmetic mean of the target difference set to obtain the target arithmetic mean;

A comparison arithmetic mean calculation unit, configured to separately calculate the arithmetic mean of the at least two comparison difference sets to obtain at least two comparison arithmetic means;

a discrete clustering unit, configured to perform discrete clustering on the target arithmetic mean and the at least two comparison arithmetic mean; if the target arithmetic mean does not belong to the central category, then determine the target meter box Each smart meter needs to be calibrated;

Correspondingly, the metering correction unit 23 is specifically configured to perform metering correction on each smart meter in the target meter box based on the metering difference of each smart meter in the meter box corresponding to the center point of the central category.

In a possible implementation manner, the measurement calibration device 2 may also include:

The first average value calculation unit is used to calculate the average value of the metering difference of each smart meter in the meter box corresponding to the center point of the center category;

Correspondingly, the metering correction unit 23 is specifically configured to perform metering correction on each smart meter in the target meter box based on the average value calculated by the first average value calculation unit.

In a possible implementation manner, the measurement calibration device 2 may also include:

The measurement value acquisition unit is used to obtain the measurement value of each smart meter in the target meter box within a specified time period;

a calculated value acquisition unit, configured to acquire the calculated values of each smart meter in the target meter box within the specified time period;

Correspondingly, the first acquiring unit 21 is specifically configured to count the difference between the measured value and the calculated value of each smart meter to form a target difference set.

In a possible implementation manner, the first acquisition unit 21 is further configured to use the average value as the first standard measurement error to measure the calculated value of each smart meter in the target meter box within the specified time period Calibrate to obtain the metering data of each smart meter in the target meter box.

In a possible implementation manner, the measurement calibration device 2 may also include:

A dispersion statistics unit, used for statistically calculating the dispersion of the measurement difference corresponding to each smart meter in the target difference set;

Correspondingly, the metering correction unit 23 is specifically further configured to perform metering correction on target smart meters whose dispersion is greater than a preset threshold.

In a possible implementation manner, the measurement calibration device 2 may also include:

The second average value statistical unit is used to count the average value of the measurement difference corresponding to each smart meter in the target difference set;

Correspondingly, the metering correction unit 23 is also specifically used to perform metering correction on the target smart meter with the average value of the metering difference corresponding to each smart meter in the target difference set counted by the second average value statistics unit, so as to obtain the metering value of the target electric energy meter. data.

As can be seen from the above, the present invention obtains the target difference set by obtaining the metering difference of each smart meter in the target meter box within the specified time period; obtains the smart meter corresponding to at least two other meter boxes within the specified time period At least two comparison difference sets are obtained; the difference analysis is performed on the data group consisting of the target difference set and at least two comparison difference sets, and each smart meter in the target meter box is analyzed according to the analysis results. Metrological correction. Because usually the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line will be disturbed, and the target meter box and at least two other meter boxes are respectively meter boxes on different low-voltage lines, they will be interfered at the same time and are both The probability of sudden changes in metering data is extremely small, and out-of-range metering errors are usually reflected in the metering difference data of smart meters, so the data formed based on the metering differences of the target meter box and at least two other meter boxes Through comparative analysis, it is possible to find in time whether the smart meter in the target meter box has an out-of-range measurement error, and can refer to the meter error data of the meter box whose meter error does not exceed the range, and compare the meter errors of at least two smart meters corresponding to other meter boxes. The measurement data of the meter box is used for more accurate measurement correction. It can be seen that the present invention can detect the out-of-range measurement error of the smart meter in a timely manner, and perform relatively accurate measurement correction.

Fig. 3 is a schematic diagram of a terminal provided by an embodiment of the present invention. As shown in FIG. 3 , the terminal 3 of this embodiment includes: a processor 30 , a memory 31 , and a computer program 32 stored in the memory 31 and operable on the processor 30 . When the processor 30 executes the computer program 32, it realizes the steps in the embodiments of the above-mentioned data aggregation methods of various civil affairs systems, such as steps 101 to 103 shown in FIG. 1 . Alternatively, when the processor 30 executes the computer program 32, the functions of the units in the above-mentioned device embodiments, such as the functions of the units 21 to 23 shown in FIG. 2 , are realized.

Exemplarily, the computer program 32 can be divided into one or more modules/units, and the one or more modules/units are stored in the memory 31 and executed by the processor 30 to complete this invention. The one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the terminal 3 . For example, the computer program 32 can be divided into a first acquisition unit, a second acquisition unit and a measurement correction unit, and the specific functions of each unit are as follows:

The first acquisition unit is configured to acquire the metering difference of each smart meter in the target meter box within a specified time period to obtain a target difference set;

The second acquisition unit is configured to acquire the metering difference of smart meters corresponding to at least two other meter boxes within the specified time period, and obtain at least two comparison difference sets, wherein the target meter box and at least two other meters The boxes are the meter boxes on different low-voltage lines;

The metering correction unit is configured to perform difference analysis on the data group composed of the target difference set and the at least two comparison difference sets, and perform metering correction on each smart meter in the target meter box according to the analysis result.

The terminal 3 may be a computing device such as a desktop computer, a notebook, a palmtop computer, or a cloud server. The terminal may include, but not limited to, a processor 30 and a memory 31 . Those skilled in the art can understand that FIG. 3 is only an example of the terminal 3 and does not constitute a limitation to the terminal 3. It may include more or less components than shown in the figure, or combine some components, or different components, such as The terminal may also include an input and output device, a network access device, a bus, and the like.

The so-called processor 30 may be a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

The storage 31 may be an internal storage unit of the terminal 3 , such as a hard disk or memory of the terminal 3 . The memory 31 may also be an external storage device of the terminal 3, such as a plug-in hard disk equipped on the terminal 3, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, Flash card (Flash Card), etc. Further, the memory 31 may also include both an internal storage unit of the terminal 3 and an external storage device. The memory 31 is used to store the computer program and other programs and data required by the terminal. The memory 31 can also be used to temporarily store data that has been output or will be output.

Those skilled in the art can clearly understand that for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units, Completion of modules means that the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist separately physically, or two or more units may be integrated into one unit, and the above-mentioned integrated units may adopt hardware It can also be implemented in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working process of the units and modules in the above system, reference may be made to the corresponding process in the foregoing method embodiments, and details will not be repeated here.

In the above-mentioned embodiments, the descriptions of each embodiment have their own emphases, and for parts that are not detailed or recorded in a certain embodiment, refer to the relevant descriptions of other embodiments.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed device/terminal and method may be implemented in other ways. For example, the device/terminal embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or Components may be combined or integrated into another system, or some features may be omitted, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

If the integrated module/unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention realizes all or part of the processes in the methods of the above embodiments, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable Excluding electrical carrier signals and telecommunication signals.

The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still carry out the foregoing embodiments Modifications to the technical solutions recorded in the examples, or equivalent replacement of some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should be included in within the protection scope of the present invention.

Claims (9)

1. A smart meter metering correction method based on data analysis is characterized by comprising the following steps:

acquiring a metering difference value of each intelligent electric meter in a target electric meter box in a specified time period to obtain a target difference value set, wherein the metering difference value represents the difference between a metering value and a theoretical calculation value of the intelligent electric meter;

acquiring the metering difference values of the intelligent electric meters corresponding to at least two other electric meter boxes in the specified time period to obtain at least two comparison difference value sets, wherein the target electric meter box and the at least two other electric meter boxes are electric meter boxes on different low-voltage lines respectively;

performing difference analysis on a data group consisting of the target difference set and the at least two comparison difference sets, and performing measurement correction on each intelligent ammeter in the target ammeter box according to an analysis result;

the difference analysis comprises discrete clustering of arithmetic mean, and the metering correction of each intelligent electric meter in the target electric meter box according to the analysis result comprises the following steps: if the clustering result of the target electric meter box does not belong to the central large class, metering and correcting each intelligent electric meter in the target electric meter box; if the clustering result of the target electric meter box belongs to the central large class, determining that each intelligent electric meter in the target electric meter box does not need to carry out metering correction;

the method comprises the following steps of obtaining the metering difference value of each intelligent electric meter in the target electric meter box in a specified time period, and after obtaining a target difference value set, further comprising: counting the dispersion of the corresponding metering difference of each intelligent electric meter in the target difference set; and carrying out measurement correction on the target intelligent electric meter with the dispersion larger than a preset threshold value.

2. The method for calibrating metering of smart meters based on data analysis of claim 1, wherein the analyzing the data of the data group consisting of the target difference set and the at least two comparison difference sets, and calibrating the metering of each smart meter in the target meter box according to the analysis result comprises:

calculating the arithmetic mean of the target difference set to obtain a target arithmetic mean;

respectively calculating the arithmetic mean of the at least two comparison difference sets to obtain at least two comparison arithmetic mean;

performing discrete clustering on the target arithmetic mean number and the at least two comparison arithmetic mean numbers, and if the target arithmetic mean number does not belong to a central large class, determining that each intelligent electric meter in the target electric meter box needs to perform metering correction;

and carrying out measurement correction on each intelligent electric meter in the target electric meter box based on the measurement difference value of each intelligent electric meter in the electric meter box corresponding to the central point of the central large class.

3. The method for smart meter metering correction based on data analysis according to claim 2, wherein the metering correction of the smart meters in the target meter box based on the metering difference values of the smart meters in the meter box corresponding to the central point of the central large category comprises:

calculating the average value of the metering difference values of the intelligent electric meters in the electric meter boxes corresponding to the central points of the central large categories;

and carrying out measurement correction on each intelligent electric meter in the target electric meter box based on the average value.

4. The method for calibrating metering of a smart meter based on data analysis of claim 3, wherein the obtaining the metering difference values of the smart meters in the target meter box within a specified time period to obtain the target difference value set comprises:

acquiring the metering value of each intelligent electric meter in the target electric meter box in a specified time period;

acquiring a calculated value of each intelligent ammeter in the target ammeter box in the appointed time period;

and counting the difference value between the metering value and the calculated value of each intelligent electric meter to form a target difference value set.

5. The method for smart meter metering correction based on data analysis of claim 4, wherein the metering correction of each smart meter in the target meter box based on the average value comprises:

and taking the average value as a first standard metering error, and metering and correcting the calculated value of each intelligent electric meter in the target electric meter box in the specified time period to obtain the metering data of each intelligent electric meter in the target electric meter box.

6. The method for smart meter metering correction based on data analysis of any one of claims 1 to 5, wherein the metering correction of the target smart meter with dispersion greater than a preset threshold value comprises:

counting the average value of the metering difference values corresponding to the intelligent electric meters in the target difference value set;

and carrying out measurement correction on the target intelligent electric meter by using the average value of the measurement difference value corresponding to each intelligent electric meter in the counted target difference value set to obtain the measurement data of the target electric energy meter.

7. A smart meter measurement correction device based on data analysis, characterized in that the measurement correction device comprises:

the system comprises a first obtaining unit, a second obtaining unit and a third obtaining unit, wherein the first obtaining unit is used for obtaining the metering difference value of each intelligent electric meter in a target electric meter box in a specified time period to obtain a target difference value set, and the metering difference value represents the difference between the metering value and the theoretical calculation value of the intelligent electric meter;

the second obtaining unit is used for obtaining the metering difference values of the intelligent electric meters corresponding to the at least two other electric meter boxes in the specified time period to obtain at least two comparison difference value sets, wherein the target electric meter box and the at least two other electric meter boxes are electric meter boxes on different low-voltage lines respectively;

the metering correction unit is used for carrying out difference analysis on a data group consisting of the target difference set and the at least two comparison difference sets and carrying out metering correction on each intelligent ammeter in the target ammeter box according to an analysis result;

the difference analysis comprises discrete clustering of arithmetic mean, and the metering correction of each intelligent electric meter in the target electric meter box according to the analysis result comprises the following steps: if the clustering result of the target electric meter box does not belong to the central large class, metering and correcting each intelligent electric meter in the target electric meter box; if the clustering result of the target electric meter box belongs to the central large class, determining that each intelligent electric meter in the target electric meter box does not need to carry out metering correction;

wherein the metering correction device further comprises: the dispersion counting unit is used for counting the dispersion of the metering difference corresponding to each intelligent electric meter in the target difference set; correspondingly, the metering correction unit is also used for metering and correcting the target intelligent electric meter with the dispersion larger than the preset threshold value.

8. A terminal comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor when executing the computer program implements the steps of the method for smart meter metering correction based on data analysis according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for correcting metering of a smart meter based on data analysis according to any one of claims 1 to 6.

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