CN113376564A - Smart electric meter metering correction method and device based on data analysis and terminal - Google Patents
Smart electric meter metering correction method and device based on data analysis and terminal Download PDFInfo
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- CN113376564A CN113376564A CN202110610835.9A CN202110610835A CN113376564A CN 113376564 A CN113376564 A CN 113376564A CN 202110610835 A CN202110610835 A CN 202110610835A CN 113376564 A CN113376564 A CN 113376564A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention is suitable for the technical field of intelligent electric meters, and provides a method, a device, a terminal and a computer readable storage medium for metering correction of an intelligent electric meter based on data analysis, wherein the metering correction method comprises the following steps: acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set; 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; and 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 electric meter in the target electric meter box according to an analysis result. The invention can find out the over-range metering error of the intelligent ammeter in time and carry out more accurate metering correction.
Description
Technical Field
The invention belongs to the technical field of intelligent electric meters, and particularly relates to a method, a device, a terminal and a computer readable storage medium for metering correction of an intelligent electric meter based on data analysis.
Background
At present, a smart meter becomes important equipment in load management of a smart grid, the operation principle of the smart meter is that the voltage U and the current I information in a loop are recorded by high sampling density, on the basis of the principle of electric energy metering, functions of information storage, information processing, automatic control, information interaction and the like are realized by embedded computing resources, and under the drive of various requirements of electric energy metering, electric power marketing, customer service and the like, the corresponding functions are realized by taking the accuracy and the stability of the electric energy metering as engineering purposes.
However, in the application of the smart meter to the electric energy metering work, unexpected metering failure may occur. Such as a sudden electrical data failure. The sudden change fault of the electric quantity data means that the measured electric quantity of the intelligent electric meter is not consistent with the actual electric quantity. After statistics and verification, the program design of part of the intelligent electric meters has defects, when the intelligent electric meters are interfered, the related programs cannot effectively eliminate the interference, and error data after the interference is directly recorded, so that the data mutation of the electric energy metering is caused, and an over-range metering error is formed.
In addition, due to different application environments, a smart meter has a metering error in actual metering, for example, voltage, current and temperature changes all affect the metering of the smart meter, the metering error of a normal smart meter is usually within an allowable range, and then, due to some special reasons, part of the metering error of the smart meter exceeds the allowable range, for example, fast-moving words and slow-moving words cause losses to an electric power department, and fast-moving words cause losses to a user, causing discontentment of the user, and for such faults, it is usually difficult to find in time.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a terminal and a computer readable storage medium for metering correction of a smart meter based on data analysis, so as to solve the problem in the prior art that an out-of-range metering error of a smart meter cannot be timely and accurately found and metered and corrected.
The first aspect of the embodiment of the invention provides a smart meter metering correction method based on data analysis, which comprises the following steps:
acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set;
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;
and 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 electric meter in the target electric meter box according to an analysis result.
In an optional embodiment, the analyzing the data of the data group composed of the target difference set and the at least two comparison difference sets, and performing measurement correction on each smart meter in the target meter box according to the analysis result includes:
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 and the at least two comparison arithmetic means, and if the target arithmetic mean does not belong to the 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.
In a possible implementation manner, the performing measurement correction on each smart meter in the target meter box based on the measurement difference value of each smart meter in the meter box corresponding to the central point of the central category includes:
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.
In a possible implementation manner, the obtaining a metering difference value of each smart meter in a target meter box within a specified time period to obtain a target difference value set includes:
acquiring the metering values of the intelligent electric meters in the target electric meter box in a specified time period;
acquiring a calculated value of each intelligent electric meter in the target electric meter box in the specified 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.
In one possible implementation manner, performing metering correction on each smart meter in the target meter box based on the average value includes:
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.
In a possible implementation manner, after the obtaining of 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, the method further includes:
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.
In a possible implementation manner, the performing measurement correction on the target smart meter whose dispersion is greater than the preset threshold includes:
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.
A second aspect of an embodiment of the present invention provides a smart meter metering correction apparatus based on data analysis, where the metering correction apparatus includes:
the first acquisition unit is used for acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set;
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;
and the metering correction unit is used for performing difference analysis on a data group consisting of the target difference set and the at least two comparison difference sets and performing metering correction on each intelligent electric meter in the target electric meter box according to an analysis result.
In one possible implementation, the metering correction apparatus further includes:
the target arithmetic mean calculating unit is used for calculating the arithmetic mean of the target difference set to obtain a target arithmetic mean;
the comparison arithmetic mean calculating unit is used for calculating the arithmetic mean of the at least two comparison difference sets respectively to obtain at least two comparison arithmetic means;
the discrete clustering unit is used for performing discrete clustering on the target arithmetic mean and the at least two comparison arithmetic means, and if the target arithmetic mean does not belong to the central large class, determining that each intelligent ammeter in the target ammeter box needs to be subjected to metering correction;
correspondingly, the metering correction unit is specifically used for carrying out metering correction on each intelligent electric meter in the target electric meter box based on the metering difference value of each intelligent electric meter in the electric meter box corresponding to the central point of the central large class.
In one possible implementation, the metering correction apparatus further includes:
the first average value calculating unit is used for 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 class;
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 one possible implementation, the metering correction apparatus further includes:
the metering value acquisition unit is used for acquiring the metering values of the intelligent electric meters in the target electric meter box in a specified time period;
the calculation value acquisition unit is used for acquiring calculation values of all the intelligent electric meters in the target electric meter box in the specified time period;
correspondingly, the first obtaining unit is specifically configured to count differences between the metering value and the calculated value of each smart electric meter, so as to form a target difference set.
In a possible implementation manner, the first obtaining unit is further specifically configured to perform measurement correction on the calculated value of each smart meter in the target meter box in the specified time period by using the average value as a first standard measurement error, so as to obtain measurement data of each smart meter in the target meter box.
In one possible implementation, the metering correction apparatus further includes:
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 specifically further used for metering and correcting the target intelligent electric meter with the dispersion larger than the preset threshold value.
In one possible implementation, the metering correction apparatus further includes:
the second average value statistical unit is used for calculating the average value of the metering difference values corresponding to the intelligent electric meters in the target difference value set;
correspondingly, the metering correction unit is further specifically configured to perform metering correction on the target smart electric meter by using the average value of the metering difference value corresponding to each smart electric meter in the target difference value set counted by the second average value counting unit, so as 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 executable on the processor, where the processor implements the steps of any one of the data analysis-based smart meter metering correction methods when executing the computer program.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method for correcting metering of a smart meter based on data analysis according to any one of the above-mentioned embodiments.
Compared with the prior art, the invention has the following beneficial effects:
according to the method, a target difference value set is obtained by obtaining the metering difference value of each intelligent ammeter in a target ammeter box in a specified time period; 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; and 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 electric meter in the target electric meter box according to an analysis result. Since the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line are usually interfered, the target electric meter box and at least two other electric meter boxes are electric meter boxes on different low-voltage lines respectively, the probability that the target electric meter box and the at least two other electric meter boxes are interfered simultaneously and all cause sudden change of metering data is extremely low, the over-range metering error is usually reflected on the metering difference value data of the intelligent ammeter, so that the data formed by the metering difference values of the intelligent ammeter corresponding to the target ammeter box and at least two other ammeter boxes are compared and analyzed, whether the over-range metering error exists in the intelligent ammeter in the target ammeter box can be found in time, and the metering error data of the ammeter boxes with the metering errors not exceeding the range can be referred to accurately meter and correct the metering data of the ammeter boxes of the intelligent ammeter corresponding to at least two other ammeter boxes with the metering errors. Therefore, the method and the device can find out the over-range metering error of the intelligent ammeter in time and carry out accurate metering correction.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of an implementation of a method for calibrating metering of a smart meter based on data analysis according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a smart meter metering correction device based on data analysis according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from 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 objects, technical solutions and advantages of the present invention more apparent, the following description is made by way of specific embodiments with reference to the accompanying drawings.
Referring to fig. 1, it shows a flowchart of an implementation of the method for correcting metering of a smart meter based on data analysis according to an embodiment of the present invention, which is detailed as follows:
in step 101, acquiring a metering difference value of each intelligent electric meter in a target electric meter box within a specified time period to obtain a target difference value set;
in an application scenario, the method can be applied to a cloud server, and a metering difference value of each intelligent electric meter in a target electric meter box in a specified time period is obtained through the cloud server in a remote wireless communication mode, so that a target difference value set is obtained.
In another application scenario, correction terminals can be respectively arranged on ammeter boxes corresponding to different low-voltage lines, a plurality of intelligent ammeters are arranged in the ammeter boxes, the correction terminals are in communication connection with the intelligent ammeters in the ammeter boxes corresponding to the correction terminals, and the correction terminals are in communication connection; and a near-end correction terminal is used for acquiring the metering difference value of each intelligent electric meter in the target electric meter box in a specified time period to obtain a target difference value set.
In the embodiment of the present invention, the target difference set refers to a set of metering differences of a plurality of smart meters in the target meter box in a specified time period, for example, if 9 smart meters are arranged in the target meter box, the obtained target difference set may be a set including 9 difference data.
In one implementation, the step 101 may include:
acquiring the metering values of the intelligent electric meters in the target electric meter box in a specified time period;
acquiring a calculated value of each intelligent electric meter in the target electric meter box in the specified 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.
In the embodiment of the present invention, the metering difference value may be a difference between a metering value of the smart meter and a theoretical calculation value.
In the embodiment of the present invention, the data of the same designated time period is used because the influence of the environmental factors on each smart meter in the target meter box is relatively consistent in the same designated time period, for example, the environmental temperature of each smart meter in the target meter box is consistent at the same time.
In step 102, the metering difference values of the smart meters corresponding to the at least two other electric meter boxes in the specified time period are obtained, and at least two comparison difference value sets are obtained, 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.
In the embodiment of the present invention, since data analysis and comparison are performed, it is further necessary to obtain the metering difference values of the smart meters corresponding to at least two other meter boxes in the specified time period to obtain at least two comparison difference value sets, and since the target meter box and the at least two other meter boxes are respectively meter boxes on different low-voltage lines, the meter boxes are unlikely to be simultaneously affected by interference to generate data mutation, thereby causing an out-of-range error. Therefore, the data of the three electric meter boxes are collected, the data of at least two electric meter boxes are the data within the normal error range, at most, one electric meter box can have out-of-range error data, and the comparison result can be more accurate when more electric meter box data of different low-voltage lines are obtained.
In step 103, performing difference analysis on the data group composed of the target difference set and the at least two comparison difference sets, and performing measurement correction on each smart meter in the target meter box according to the analysis result
In the embodiment of the invention, the difference analysis is carried out on the data group consisting of the target difference set and the at least two comparison difference sets, the electric meter box data of the intelligent electric meter with the out-of-range error is inevitably reflected in the analysis result of the data, so that the out-of-range error of each intelligent electric meter in the target electric meter box can be timely found and accurately measured and corrected according to the analysis result.
In one implementation, the step 103 may include:
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 and the at least two comparison arithmetic means, and if the target arithmetic mean does not belong to the 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.
In the embodiment of the invention, the metering difference value reflects the difference between the metering value and the calculated value of the intelligent electric meter, and the arithmetic mean of the metering difference value set can evaluate the overall situation of the metering difference of the intelligent electric meter in the electric meter box, for example, if the error of the intelligent electric meter exceeds the range of the target electric meter box, the corresponding arithmetic mean of the target difference value set is larger than the normal metering difference value of the normal intelligent electric meter, and after the discrete clustering is carried out, the target arithmetic mean is not necessarily in the central class but is free outside the central class; on the contrary, if the target ammeter box does not have the intelligent ammeter with the error exceeding the range, the arithmetic mean of the corresponding target difference set is about equal to the normal metering difference of the normal intelligent ammeter, and after the discrete clustering is carried out, the target arithmetic mean inevitably belongs to the central large category. Therefore, the ammeter box of the intelligent ammeter with the error exceeding the range can be found in time through the analysis mode.
In one implementation, the performing measurement correction on each smart meter in the target meter box based on the measurement difference value of each smart meter in the meter box corresponding to the central point of the central large category may include: 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.
In the embodiment of the invention, if the error out-of-range smart meter is found, the error out-of-range smart meter needs to be measured and corrected so as to provide a reasonable and correct measurement result for a user. And the average value of the metering difference values of the intelligent electric meters in the electric meter boxes corresponding to the central point of the central large category belongs to normal intelligent electric meters with the metering errors within an allowable range, and the metering correction can be carried out on the intelligent electric meters in the target electric meter box by taking the average value of the metering difference values of the normal intelligent electric meters as a standard.
In one implementation, the performing, based on the average value, a metering correction on each smart meter in the target meter box includes: 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.
In this embodiment, the calculated value is theoretical metering data, and it is not suitable to use the value as a final metering basis in practical applications because the metering data has a score between the general table and the sub-table, and if the theoretical calculated value is used for the sub-table, the general table will be empty. Therefore, for the intelligent electric meter with the error exceeding the range, the calculated value and the average value of the metering difference values of the normal intelligent electric meter can be used as final metering data.
In one implementation, after the step 101, the method may further include: 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.
In the embodiment of the invention, the data index of the dispersion can accurately reflect whether fast-moving words or slow-moving words exist in the same electric meter box and exceed the intelligent electric meter outside a normal error range.
In the embodiment of the invention, the smart meter which moves fast words or slow words and exceeds the normal error range usually appears in the form of a single example, and the reason is that the CPU power supply voltage is abnormal because the instantaneous high voltage caused by power grid fluctuation or lightning strike breaks down devices (such as capacitors) of the smart meter, so that the read-write data of the PC loop is abnormal. Therefore, the intelligent electric meters with the fast words or the slow words exceeding the normal error range can be accurately found through data analysis of the metering difference values of the intelligent electric meters in the same electric meter box in the same time period.
In one implementation, the performing measurement correction on the target smart meter whose dispersion is greater than the preset threshold may include: 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.
In the embodiment of the present invention, after finding out the smart meter that moves fast words or slow words and exceeds the normal error range, the average value of the corresponding metering difference values of other smart meters (normal smart meters) may be counted, and the target smart meter may be subjected to metering correction by using the average value, so as to obtain the final metering data of the target power meter, for example, the theoretical calculation value of the target power meter and the average value of the corresponding metering difference values of the normal smart meters in the meter box may be used as the final metering value of the target power meter.
According to the method, the target difference value set is obtained by obtaining the metering difference values of the intelligent electric meters in the target electric meter box within the specified time period; 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; and 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 electric meter in the target electric meter box according to an analysis result. Since the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line are usually interfered, the target electric meter box and at least two other electric meter boxes are electric meter boxes on different low-voltage lines respectively, the probability that the target electric meter box and the at least two other electric meter boxes are interfered simultaneously and all cause sudden change of metering data is extremely low, the over-range metering error is usually reflected on the metering difference value data of the intelligent ammeter, so that the data formed by the metering difference values of the intelligent ammeter corresponding to the target ammeter box and at least two other ammeter boxes are compared and analyzed, whether the over-range metering error exists in the intelligent ammeter in the target ammeter box can be found in time, and the metering error data of the ammeter boxes with the metering errors not exceeding the range can be referred to accurately meter and correct the metering data of the ammeter boxes of the intelligent ammeter corresponding to at least two other ammeter boxes with the metering errors. Therefore, the method and the device can find out the over-range metering error of the intelligent ammeter in time and carry out accurate metering correction.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The following are embodiments of the apparatus of the invention, reference being made to the corresponding method embodiments described above for details which are not described in detail therein.
Fig. 2 is a schematic structural diagram of a smart meter metering correction device based on data analysis according to an embodiment of the present invention, and for 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 metering correction apparatus 2 may include: a first acquisition unit 21, a second acquisition unit 22 and a metrology correction unit 23.
The first obtaining unit 21 is configured to obtain a metering difference value of each smart meter in a target meter box within a specified time period to obtain a target difference value set;
the second obtaining unit 22 is configured to obtain the metering difference values of the smart meters corresponding to the at least two other meter boxes in the specified time period to obtain at least two comparison difference value sets, where the target meter box and the at least two other meter boxes are meter boxes on different low-voltage lines respectively;
and the metering correction unit 23 is configured to perform difference analysis on a data set formed by 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 an analysis result.
In a possible implementation, the metering correction device 2 may further include:
the target arithmetic mean calculating unit is used for calculating the arithmetic mean of the target difference set to obtain a target arithmetic mean;
the comparison arithmetic mean calculating unit is used for calculating the arithmetic mean of the at least two comparison difference sets respectively to obtain at least two comparison arithmetic means;
the discrete clustering unit is used for performing discrete clustering on the target arithmetic mean and the at least two comparison arithmetic means, and if the target arithmetic mean does not belong to the central large class, determining that each intelligent ammeter in the target ammeter box needs to be subjected to metering correction;
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 value of each smart meter in the meter box corresponding to the central point of the central large category.
In a possible implementation, the metering correction device 2 may further include:
the first average value calculating unit is used for 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 class;
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, the metering correction device 2 may further include:
the metering value acquisition unit is used for acquiring the metering values of the intelligent electric meters in the target electric meter box in a specified time period;
the calculation value acquisition unit is used for acquiring calculation values of all the intelligent electric meters in the target electric meter box in the specified time period;
correspondingly, the first obtaining unit 21 is specifically configured to count differences between the metering value and the calculated value of each smart meter, so as to form a target difference set.
In a possible implementation manner, the first obtaining unit 21 is further specifically configured to use the average value as a first standard metering error, and perform metering correction on a calculated value of each smart meter in the target meter box in the specified time period, so as to obtain metering data of each smart meter in the target meter box.
In a possible implementation, the metering correction device 2 may further include:
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 23 is further specifically configured to perform metering correction on the target smart meter whose dispersion is greater than the preset threshold.
In a possible implementation, the metering correction device 2 may further include:
the second average value statistical unit is used for calculating the average value of the metering difference values corresponding to the intelligent electric meters in the target difference value set;
correspondingly, the metering correction unit 23 is further specifically configured to perform metering correction on the target smart meter by using the average value of the metering difference value corresponding to each smart meter in the target difference value set counted by the second average value counting unit, so as to obtain the metering data of the target electric energy meter.
According to the method, the target difference value set is obtained by obtaining the metering difference values of the intelligent electric meters in the target electric meter box within the specified time period; 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; and 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 electric meter in the target electric meter box according to an analysis result. Since the smart meters in the same meter box or the smart meters corresponding to the same low-voltage line are usually interfered, the target electric meter box and at least two other electric meter boxes are electric meter boxes on different low-voltage lines respectively, the probability that the target electric meter box and the at least two other electric meter boxes are interfered simultaneously and all cause sudden change of metering data is extremely low, the over-range metering error is usually reflected on the metering difference value data of the intelligent ammeter, so that the data formed by the metering difference values of the intelligent ammeter corresponding to the target ammeter box and at least two other ammeter boxes are compared and analyzed, whether the over-range metering error exists in the intelligent ammeter in the target ammeter box can be found in time, and the metering error data of the ammeter boxes with the metering errors not exceeding the range can be referred to accurately meter and correct the metering data of the ammeter boxes of the intelligent ammeter corresponding to at least two other ammeter boxes with the metering errors. Therefore, the method and the device can find out the over-range metering error of the intelligent ammeter in time and carry out accurate metering correction.
Fig. 3 is a schematic diagram of a terminal according to 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 said memory 31 and executable on said processor 30. The processor 30 executes the computer program 32 to implement the steps in the data aggregation method embodiments of the above-mentioned respective civil systems, such as the steps 101 to 103 shown in fig. 1. Alternatively, the processor 30, when executing the computer program 32, implements the functions of the units in the above-described device embodiments, such as the functions of the units 21 to 23 shown in fig. 2.
Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 32 in the terminal 3. For example, the computer program 32 may be divided into a first acquisition unit, a second acquisition unit and a metrology correction unit, each unit functioning specifically as follows:
the first acquisition unit is used for acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set;
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;
and the metering correction unit is used for performing difference analysis on a data group consisting of the target difference set and the at least two comparison difference sets and performing metering correction on each intelligent electric meter in the target electric meter box according to an analysis result.
The terminal 3 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is only an example of a terminal 3 and does not constitute a limitation of the terminal 3 and may comprise more or less components than those shown, or some components may be combined, or different components, e.g. the terminal may further comprise input output devices, network access devices, buses, etc.
The Processor 30 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or a 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, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like provided on the terminal 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal 3. The memory 31 is used for storing the computer program and other programs and data required by the terminal. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The 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 place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; 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; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A smart meter metering correction method based on data analysis is characterized by comprising the following steps:
acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set;
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;
and 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 electric meter in the target electric meter box according to an analysis result.
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 and the at least two comparison arithmetic means, and if the target arithmetic mean does not belong to the 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 calibrating metering of smart meters based on data analysis of claim 2, wherein the calibrating of the metering 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 central point of the central 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 values of the intelligent electric meters in the target electric meter box in a specified time period;
acquiring a calculated value of each intelligent electric meter in the target electric meter box in the specified 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 correcting metering of the smart electric meter based on the data analysis as claimed in any one of claims 1 to 5, wherein after obtaining the metering difference values of the smart electric meters in the target electric meter box within a specified time period and obtaining the target difference value set, the method further comprises:
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.
7. The method for metering and correcting the smart meters based on the data analysis of claim 6, wherein the metering and correcting the target smart meters with the dispersion larger than the preset threshold value comprises the following steps:
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.
8. A smart meter metering correction device based on data analysis, characterized in that the metering correction device comprises:
the first acquisition unit is used for acquiring the metering difference value of each intelligent ammeter in the target ammeter box in a specified time period to obtain a target difference value set;
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;
and the metering correction unit is used for performing difference analysis on a data group consisting of the target difference set and the at least two comparison difference sets and performing metering correction on each intelligent electric meter in the target electric meter box according to an analysis result.
9. 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 7.
10. 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 7.
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