High-precision electric energy meter error correction method and system

Abstract

The invention discloses a high-precision electric energy meter error correction method and system, and relates to the technical field of electric power measurement and metrology, and the method comprises the steps: collecting the operation data of a three-phase electric energy meter, and calling the historical operation data; error verification is carried out on the three-phase electric energy meter, verification pulses and multifunctional pulses are used for automatic switching, and whether errors are within a specified range or not is verified and judged; carrying out error detection, monitoring the false detection rate, detecting the reject ratio of data, tracing historical judgment errors, carrying out automatic short circuit, and carrying out error correction after short circuit; error correction is carried out, rechecking is carried out after correction, errors are made to return to an allowable range, data detected and corrected each time are recorded, and a correction database is established for historical data tracing. Through comprehensive monitoring, accurate error detection and classification, automatic short circuit processing and error correction and big data analysis, a correction database is established, efficient and accurate error correction of the electric energy meter is realized, and the measurement accuracy and reliability of the electric energy meter are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power measurement and metering, and in particular to a high-precision electric energy meter error correction method and system. Background Art

[0002] In the field of electric energy measurement, the accuracy and stability of electric energy meters as key measuring equipment are directly related to the normal operation of the power system and the fairness of power trading. With the development of the power system and the improvement of the level of intelligence, the application of high-precision electric energy meters is becoming more and more extensive. However, the existing electric energy meter error correction technology still has certain limitations.

[0003] In recent years, although the error correction technology of three-phase electricity meters has made certain progress, the existing technology generally has the following shortcomings: First, the existing technology does not collect and analyze the operation data of the electricity meter comprehensively, and often ignores the influence of environmental parameters, load characteristics, etc. on the error of the electricity meter; second, the error verification method is relatively single, and fails to switch flexibly according to different working conditions and external conditions, resulting in inaccurate error verification results; third, during the error correction process, the monitoring and diagnosis of the error are not detailed enough, and there is a lack of consideration of the false detection rate, resulting in poor correction effect; finally, after the error correction of the electricity meter, the existing technology lacks an effective re-inspection and data traceability mechanism, making it difficult to ensure the durability and reliability of the correction effect.

[0004] In response to the above problems, we have invented a high-precision electric energy meter error correction method for three-phase electric energy meters, which has significant advantages in improving the error correction accuracy of electric energy meters and optimizing the correction process. Summary of the invention

[0005] In view of the above-mentioned existing problems, the present invention aims to solve technical problems and technical difficulties such as accurately collecting and analyzing the operating data of electric energy meters, automatically switching error verification methods for different working conditions, performing effective error correction, and utilizing big data analysis and correction strategy optimization. Through this method, high-precision electric energy meter error detection and correction is achieved, which effectively improves the measurement accuracy and operating stability of the electric energy meter and reduces the metering loss caused by errors.

[0006] In order to solve the above technical problems, a high-precision electric energy meter error correction method is proposed, including:

[0007] Collect the operating data of the three-phase energy meter and call the historical operating data; perform error verification on the three-phase energy meter, use the verification pulse and the multi-function pulse for automatic switching, verify and determine whether the error is within the specified range; perform error detection, monitor the false detection rate, the unqualified rate of the detection data and trace the historical judgment error to automatically short-circuit, and perform error correction after short-circuiting; perform error correction and re-inspect after correction to return the error to the allowable range, record the data of each detection and correction, and establish a correction database for historical data tracing.

[0008] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, wherein: the operating data includes electrical parameters, environmental parameters, load characteristics, power supply parameters and sampling frequency;

[0009] The electrical parameters include current, voltage, power and power factor, and the power includes active power, reactive power and apparent power;

[0010] The environmental parameters include temperature and humidity;

[0011] The load characteristics include load changes and maximum demand, and the load changes include periodic fluctuations and sudden increases;

[0012] The power supply parameters include grid voltage fluctuation and harmonic content;

[0013] The corresponding historical operating data is called for the collected operating data, and the electric energy meter is statically tested under no-load and specified load conditions, and the difference between the operating data output and input is recorded. The specified range is set according to the geographical location and power consumption characteristics of the three-phase electric energy meter: the test voltage value is within ±3%, the leakage current is within ±5%, the timing time is set to 60 seconds and cannot exceed ±20 milliseconds.

[0014] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, the error verification includes using a check pulse and a multi-function pulse to perform error verification on a three-phase electric energy meter, and the system automatically switches between the two pulses:

[0015] When the system is under current loading and the equipment enters nonlinear load state, multi-function pulse verification is used;

[0016] When the system is not loaded with current and the temperature is below 20°C, use the calibration pulse test to perform small signal testing;

[0017] When it is detected that the equipment meets the requirements of maintaining a current conversion rate greater than 2A / millisecond and a load conversion rate greater than 15% within 10 milliseconds, the calibration pulse and multi-function pulse verification are used at the same time;

[0018] Real-time monitoring of the energy meter status, automatic switching of pulse types when any of the conditions are met, the system keeps a record of the previous pulse response when switching, the conditions include:

[0019] Condition 1 is that the current working state switches irregularly;

[0020] Condition 2: Current variation exceeds ±10%

[0021] Condition three is that the system detects that the jump rate of the pulse signal changes by more than 0.1 Hz.

[0022] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, the determination of whether the error is within the specified range includes the preliminary calculation of the measurement error C u -C a , conduct a comprehensive evaluation of the error to determine whether the error of the three-phase electric energy meter is within the specified range or standard range:

[0023]

[0024] Among them, E t is the total error assessment, K is the dynamic adjustment coefficient, Acc i is the accidental error value of each test data, L i is the importance weight of the data, C u is the ideal value of the energy meter, C a is the calculated value obtained from actual measurement, n is the total amount of verified data, i is the variable index, D i is the error value of each verification data, E th is the set error threshold;

[0025] When E t <E th When , it is judged to be within the normal range, the measurement is accurate, and normal operation is maintained;

[0026] When E th ≤E t <2E th When , it is judged as the alarm range, a warning is output, and the error difference trend is judged. According to the trend judgment result, it is determined whether to convert to the abnormal range. When the trend judgment result shows that the error difference trend is increasing as a whole and there is no downward fluctuation, it is converted to the abnormal range for intervention error correction;

[0027] When the trend evaluation results show that the error difference trend has downward fluctuations but has not increased overall, error detection is performed, and intervention error correction is performed after the cause of the error anomaly is determined;

[0028] When the trend evaluation results show that the error difference trend has an upward fluctuation but is overall downward, or is overall downward without any upward fluctuation, it is considered not to be caused by the equipment, and the time for the overall decline to the normal range is predicted. If the time does not exceed 5 minutes, the system automatically finds the influencing factors and makes corrections. If the time exceeds 5 minutes, error detection is performed, environmental parameters are analyzed, and automatic correction of the error correction auxiliary system is performed;

[0029] When E t ≥2E th When it is detected, it is judged as an abnormal range and immediate intervention error correction is required.

[0030] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, the error detection includes detecting error data by loop open detection, and when it is necessary to analyze environmental parameters, loop open detection and temperature detection are used;

[0031] The loop open detection includes setting the actual voltage V actual , and record the initial measurement value, trace the impact of historical data and the deviation of real-time measurement, and calculate the error as:

[0032]

[0033] Among them, E open is the error percentage during the open circuit detection phase, M open is the measured value of the electric energy meter under open circuit, α is the coefficient reflecting the relationship between the measured value and historical data, H open Bias correction factors based on historical data;

[0034] Define a new failure rate when |E open |>E th，1 When |E open |≤E th，1 When , it is considered that the current data failure rate is low, among which, E th，1 is the defined error threshold, used to determine whether it exceeds the acceptable range;

[0035] The two methods of loop open detection and temperature detection include recording the current ambient temperature of the electric energy meter, calculating the temperature-related error and the comprehensive error E total , confirm the total data failure rate, when |E total |>E th，2 When |E total |≤E th，2 When , it is considered that the current data failure rate is low, among which, E th，2 is the defined error threshold, which is used to determine whether the total data exceeds the acceptable range;

[0036] At the same time, the false detection rate diagnosis is carried out. When the data with high unqualified rate and low false detection rate are short-circuited and error corrected, the error correction is carried out after short-circuiting.

[0037] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, wherein: the monitoring of the false detection rate includes simultaneously performing false detection rate diagnosis to identify accidental errors;

[0038] The number of electric energy meters with high failure rate is counted by historical statistics, and the false detection rate E is calculated. detect , when E detect >E detect_th When E detect ≤E detect_th When , it is considered that there is a low false positive rate, which is an accidental error;

[0039] When the data failure rate is high and there is a high false detection rate, the system automatically performs short-circuit processing and error correction, and calculates all short-circuited meters according to the cause-and-effect relationship of the error correction increase:

[0040] E corrected =E total -γD decision

[0041] Among them, E corrected is the error correction parameter, D decision is a decision variable, indicating whether it is judged as a false positive; γ is a loss correction factor.

[0042] As a preferred solution of the high-precision electric energy meter error correction method described in the present invention, the error correction includes collecting operation data including voltage, current, power factor and power consumption time information through a three-phase electric energy meter, and counting the historical data of each electric energy meter including the verification results and correction records;

[0043] Using big data analysis, we can obtain the geographical location information of the energy meter and collect the electricity consumption characteristic data of each area. We can extract the operating characteristics of similar energy meters through data mining technology, identify the error distribution law, analyze the overall trend and individual differences of similar energy meters, and identify the errors caused by commonality and individuality.

[0044] Through cluster analysis, the electric energy meters are divided into y groups with similar characteristics. When the operating error of the same type of electric energy meters exceeds ±2%, they are marked as high-error meters. The high-error meters are corrected first and then the remaining electric energy meters are corrected.

[0045] When the average error of any type of electric energy meter exceeds ±3% of the global standard deviation of the type, a cost-optimized individual correction is performed to reduce the error to within ±1% of the group average.

[0046] Evaluate the behavior model of the energy meter and set different correction strategies based on regional power grid characteristics, seasonal fluctuations and historical power consumption patterns. When the location characteristics of the energy meter do not match the power consumption characteristics, the corresponding correction parameters and correction strategies are called; when the geographical location of the energy meter matches the location characteristics in the database by more than 85%, only the corresponding correction parameters are adjusted to adapt to the local power grid characteristics;

[0047] When the operation time of the electricity meter exceeds 3 years and the frequency fluctuation of the power grid in the geographical area exceeds 5Hz, the correction algorithm upgrade is triggered, and a location-related correction database is established to trace the historical data. When the correction parameter adjustment number of the electricity meter exceeds 5 times, the historical data analysis is automatically started to trace the operating status and correction changes of the historical data, and provide improvement suggestions. If the historical correction failure rate exceeds 10%, the system will issue an alarm to the maintenance team.

[0048] Another object of the present invention is to provide a high-precision electric energy meter error correction system, which solves the error problems that may occur in the actual operation of the high-precision electric energy meter. Through real-time data acquisition, precise error detection and evaluation, and intelligent error correction and optimization, it ensures that the measurement accuracy of the electric energy meter is always maintained within the specified range, thereby improving the accuracy and reliability of electric energy metering and meeting the requirements of the power system for the performance of high-precision electric energy meters.

[0049] As a preferred solution of the high-precision electric energy meter error correction system described in the present invention, it is characterized by comprising an error verification module, an error detection module, and an error correction module;

[0050] The error detection module includes an operation data acquisition unit and a verification unit. The operation data acquisition unit is responsible for collecting real-time operation data of the three-phase electric energy meter, including electrical parameters, environmental parameters, and load characteristics; the verification unit is responsible for calling historical operation data, analyzing the operation trend and abnormal conditions of the electric energy meter, and inputting the results into the error detection module;

[0051] The error detection module includes a detection unit and an error evaluation unit. The detection unit receives data from the error verification module and performs error detection, including loop open detection and temperature detection. The error evaluation unit performs a comprehensive evaluation on the error of the electric energy meter according to the error detection result, determines whether the error is within a specified range, and sends the error detection result and the evaluation result to the error correction module.

[0052] The error correction module includes a correction unit and a strategy optimization unit. The correction unit performs error correction on the electric energy meter according to the error evaluation result, including automatic short-circuit processing and error correction; the strategy optimization unit adjusts the correction strategy according to the geographical location, power consumption characteristics and operating time information of the electric energy meter, optimizes the correction effect, and feeds back to the error detection module.

[0053] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that the processor implements the steps of a high-precision electric energy meter error correction method when executing the computer program.

[0054] A computer-readable storage medium stores a computer program thereon, characterized in that when the computer program is executed by a processor, the steps of the high-precision electric energy meter error correction method are implemented.

[0055] Beneficial effects of the present invention: The present invention realizes comprehensive monitoring of the operating status of the electric energy meter by collecting the operating data of the three-phase electric energy meter and calling the historical operating data, provides detailed data support for subsequent error verification and correction, and ensures the accuracy and comprehensiveness of the error analysis; performs error verification on the electric energy meter and uses the verification pulse and the multi-function pulse to automatically switch, realizes the accurate detection and classification of errors, improves the flexibility and accuracy of detection, reduces human intervention, and improves the detection efficiency; performs error detection and monitors the false detection rate, effectively identifies and corrects accidental errors through automatic short-circuit processing and error correction, improves the reliability of error detection, and enhances the automation degree of the system; finally, performs error correction and re-inspection to ensure that the error returns to the allowable range, records the data and establishes a correction database, identifies the error distribution law through big data analysis and cluster analysis, and provides a scientific basis for the accurate operation and maintenance of the electric energy meter, thereby improving the overall performance and reliability of the electric energy meter. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0057] Figure 1 An overall flow chart of a high-precision electric energy meter error correction method provided by an embodiment of the present invention.

[0058] Figure 2 A system solution module diagram of a high-precision electric energy meter error correction system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0062] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0063] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0064] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0065] Example 1, reference Figure 1, which is the first embodiment of the present invention, provides a high-precision electric energy meter error correction method, comprising:

[0066] S1: Collect the operating data of the three-phase electric energy meter and call the historical operating data.

[0067] Furthermore, the operating data includes electrical parameters, environmental parameters, load characteristics, power supply parameters and sampling frequency;

[0068] The electrical parameters include current, voltage, power and power factor, and the power includes active power, reactive power and apparent power;

[0069] The environmental parameters include temperature and humidity;

[0070] The load characteristics include load changes and maximum demand, and the load changes include periodic fluctuations and sudden increases;

[0071] The power supply parameters include grid voltage fluctuation and harmonic content;

[0072] The corresponding historical operating data is called for the collected operating data, and the electric energy meter is statically tested under no-load and specified load conditions, and the difference between the operating data output and input is recorded. The specified range is set according to the geographical location and power consumption characteristics of the three-phase electric energy meter: the test voltage value is within ±3%, the leakage current is within ±5%, the timing time is set to 60 seconds and cannot exceed ±20 milliseconds.

[0073] S2: Perform error verification on the three-phase electric energy meter, use the verification pulse and multi-function pulse for automatic switching, verify and determine whether the error is within the specified range.

[0074] Furthermore, the three-phase energy meter is error-checked using the calibration pulse and the multi-function pulse. The system automatically switches between the two pulses:

[0075] When the system is under current loading and the equipment enters nonlinear load state, multi-function pulse verification is used;

[0076] When the system is not loaded with current and the temperature is below 20°C, use the calibration pulse test to perform small signal testing;

[0077] When it is detected that the equipment meets the requirements of maintaining a current conversion rate greater than 2A / millisecond and a load conversion rate greater than 15% within 10 milliseconds, the calibration pulse and multi-function pulse verification are used at the same time;

[0078] Real-time monitoring of the energy meter status, automatic switching of pulse types when any of the conditions are met, the system keeps a record of the previous pulse response when switching, the conditions include:

[0079] Condition 1 is that the current working state switches irregularly;

[0080] Condition 2: Current variation exceeds ±10%

[0081] Condition three is that the system detects that the jump rate of the pulse signal changes by more than 0.1 Hz.

[0082] It should be noted that the initial calculation of the measurement error C u -C a , conduct a comprehensive evaluation of the error to determine whether the error of the three-phase electric energy meter is within the specified range or standard range:

[0083]

[0084] Among them, E t is the total error assessment, K is the dynamic adjustment coefficient, Acc i is the accidental error value of each test data, L i is the importance weight of the data, C u is the ideal value of the energy meter, C a is the calculated value obtained from actual measurement, n is the total amount of verified data, i is the variable index, D i is the error value of each verification data, E th is the set error threshold;

[0085] When E t <E th When , it is judged to be within the normal range, the measurement is accurate, and normal operation is maintained;

[0086] When E th ≤E t <2E th When , it is judged as the alarm range, a warning is output, and the error difference trend is judged. According to the trend judgment result, it is determined whether to convert to the abnormal range. When the trend judgment result shows that the error difference trend is increasing as a whole and there is no downward fluctuation, it is converted to the abnormal range for intervention error correction;

[0087] When the trend evaluation results show that the error difference trend has downward fluctuations but has not increased overall, error detection is performed, and intervention error correction is performed after the cause of the error anomaly is determined;

[0088] When the trend evaluation results show that the error difference trend has an upward fluctuation but is overall downward, or is overall downward without any upward fluctuation, it is considered not to be caused by the equipment, and the time for the overall decline to the normal range is predicted. If the time does not exceed 5 minutes, the system automatically finds the influencing factors and makes corrections. If the time exceeds 5 minutes, error detection is performed, environmental parameters are analyzed, and automatic correction of the error correction auxiliary system is performed;

[0089] When Et ≥2E th When it is detected, it is judged as an abnormal range and immediate intervention error correction is required.

[0090] S3: Perform error detection, monitor the false detection rate, detect the unqualified rate of data, and trace the historical judgment error to automatically short-circuit, and perform error correction after short-circuiting.

[0091] Furthermore, the error data is detected by using open circuit detection. When it is necessary to analyze environmental parameters, both open circuit detection and temperature detection are used;

[0092] The loop open detection includes setting the actual voltage V actual , and record the initial measurement value, trace the impact of historical data and the deviation of real-time measurement, and calculate the error as:

[0093]

[0094] Among them, E open is the error percentage during the open circuit detection phase, M open is the measured value of the electric energy meter under open circuit, α is the coefficient reflecting the relationship between the measured value and historical data, H open Bias correction factors based on historical data;

[0095] Define a new failure rate when |E open |>E th，1 When |E open |≤E th，1 When , it is considered that the current data failure rate is low, among which, E th，1 is the defined error threshold, used to determine whether it exceeds the acceptable range;

[0096] The two methods of loop open detection and temperature detection include recording the current ambient temperature T of the electric energy meter. measure , calculate the temperature-dependent error E temp :

[0097] E temp =T measure ·k temp +E open

[0098] Among them, k temp Indicates the influence coefficient of temperature change on the measured value,

[0099] Calculate the comprehensive error:

[0100]

[0101] Confirm the total data failure rate, when |E total|>E th，2 When |E total |≤E th，2 When , it is considered that the current data failure rate is low, among which, E th，2 is the defined error threshold, which is used to determine whether the total data exceeds the acceptable range;

[0102] At the same time, the false detection rate diagnosis is carried out. When the data with high unqualified rate and low false detection rate are short-circuited and error corrected, the error correction is carried out after short-circuiting.

[0103] It should be noted that false positive rate diagnosis is also performed to identify accidental errors;

[0104] The number of electric energy meters with high failure rate through historical statistics:

[0105]

[0106] in, is the comprehensive failure rate of the i-th electric energy meter, m is the number of electric energy meters, x i is the status of the i-th electric energy meter, i.e. qualified or unqualified;

[0107] Calculate the false positive rate:

[0108]

[0109] Among them, E detect is the percentage of false positive rate, N total is the total number of electric energy meters in the historical data, C detect In order to balance the deviation constant caused by false detection, the electric energy meter that finally performs short circuit is determined. detect >E detect_th When E detect ≤E detect_th When , it is considered that there is a low false positive rate, which is an accidental error;

[0110] When the data failure rate is high and there is a high false detection rate, the system automatically performs short-circuit processing and error correction, and calculates all short-circuited meters according to the cause-and-effect relationship of the error correction increase:

[0111] E corrected =E total -γD decision

[0112] Among them, E corrected is the calibration parameter, D decision is a decision variable, indicating whether it is judged that there is an error; γ is the loss correction factor.

[0113] S4: Perform error correction and re-inspection after correction to return the error to the allowable range, record the data of each test and correction, and establish a correction database for historical data tracing.

[0114] Furthermore, the operating data including voltage, current, power factor and power usage time information are collected through three-phase energy meters, and the historical data of each energy meter including the verification results and correction records are counted;

[0115] Using big data analysis, we can obtain the geographical location information of the energy meter and collect the electricity consumption characteristic data of each area. We can extract the operating characteristics of similar energy meters through data mining technology, identify the error distribution law, analyze the overall trend and individual differences of similar energy meters, and identify the errors caused by commonality and individuality.

[0116] Through cluster analysis, the electric energy meters are divided into y groups with similar characteristics. When the operating error of the same type of electric energy meters exceeds ±2%, they are marked as high-error meters. The high-error meters are corrected first and then the remaining electric energy meters are corrected.

[0117] When the average error of any type of electric energy meter exceeds ±3% of the global standard deviation of the type, a cost-optimized individual correction is performed to reduce the error to within ±1% of the group average.

[0118] Evaluate the behavior model of the energy meter and set different correction strategies based on regional power grid characteristics, seasonal fluctuations and historical power consumption patterns. When the location characteristics of the energy meter do not match the power consumption characteristics, the corresponding correction parameters and correction strategies are called; when the geographical location of the energy meter matches the location characteristics in the database by more than 85%, only the corresponding correction parameters are adjusted to adapt to the local power grid characteristics;

[0119] When the operation time of the electricity meter exceeds 3 years and the frequency fluctuation of the power grid in the geographical area exceeds 5Hz, the correction algorithm upgrade is triggered, and a location-related correction database is established to trace the historical data. When the correction parameter adjustment number of the electricity meter exceeds 5 times, the historical data analysis is automatically started to trace the operating status and correction changes of the historical data, and provide improvement suggestions. If the historical correction failure rate exceeds 10%, the system will issue an alarm to the maintenance team.

[0120] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0121] Embodiment 2, the second embodiment of the present invention, is different from the first two embodiments in that:

[0122] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0123] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0124] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0125] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0126] Example 3, reference Figure 2 , which is the third embodiment of the present invention, and provides a high-precision electric energy meter error correction system, including an error verification module 10, an error detection module 20, and an error correction module 30;

[0127] The error detection module 10 includes an operation data acquisition unit 101 and a verification unit 102. The operation data acquisition unit 101 is responsible for collecting real-time operation data of the three-phase electric energy meter, including electrical parameters, environmental parameters, and load characteristics; the verification unit 102 is responsible for calling historical operation data, analyzing the operation trend and abnormal conditions of the electric energy meter, and inputting the results into the error detection module 20;

[0128] The error detection module 20 includes a detection unit 201 and an error evaluation unit 202. The detection unit 201 receives data from the error verification module 10 and performs error detection, including loop open detection and temperature detection. The error evaluation unit 202 performs a comprehensive evaluation on the error of the electric energy meter according to the error detection result, determines whether the error is within a specified range, and sends the error detection result and the evaluation result to the error correction module 30.

[0129] The error correction module 30 includes a correction unit 301 and a strategy optimization unit 302. The correction unit 301 performs error correction on the electric energy meter according to the error evaluation result, including automatic short-circuit processing and error correction; the strategy optimization unit 302 adjusts the correction strategy according to the geographical location, power consumption characteristics and operating time information of the electric energy meter, optimizes the correction effect, and feeds back to the error detection module 20.

[0130] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A high-precision electric energy meter error correction method, characterized in that: include, Collect the operating data of three-phase electric energy meters and call historical operating data; To conduct error verification on three-phase electric energy meters, use the verification pulse and multi-function pulse for automatic switching, verify and determine whether the error is within the specified range; Perform error detection, monitor the false detection rate, detect the unqualified rate of data, and trace the historical judgment error to automatically short-circuit, and perform error correction after short-circuiting; Perform error correction and re-inspect after correction to return the error to the allowable range, record the data of each test and correction, and establish a correction database for historical data tracing.

2. A high-precision electric energy meter error correction method as claimed in claim 1, characterized in that: The operating data includes electrical parameters, environmental parameters, load characteristics, power supply parameters and sampling frequency; The electrical parameters include current, voltage, power and power factor, and the power includes active power, reactive power and apparent power; The environmental parameters include temperature and humidity; The load characteristics include load changes and maximum demand, and the load changes include periodic fluctuations and sudden increases; The power supply parameters include grid voltage fluctuation and harmonic content; The corresponding historical operating data is called for the collected operating data, and the electric energy meter is statically tested under no-load and specified load conditions, and the difference between the operating data output and input is recorded. The specified range is set according to the geographical location and power consumption characteristics of the three-phase electric energy meter: the test voltage value is within ±3%, the leakage current is within ±5%, the timing time is set to 60 seconds and cannot exceed ±20 milliseconds.

3. A high-precision electric energy meter error correction method as claimed in claim 2, characterized in that: The error verification includes using a check pulse and a multi-function pulse to perform error verification on a three-phase electric energy meter, and the system automatically switches between the two pulses: When the system is under current loading and the equipment enters nonlinear load state, multi-function pulse verification is used; When the system is not loaded with current and the temperature is below 20°C, use the calibration pulse test to perform small signal testing; When it is detected that the equipment meets the requirements of maintaining a current conversion rate greater than 2A / millisecond and a load conversion rate greater than 15% within 10 milliseconds, the calibration pulse and multi-function pulse verification are used at the same time; Real-time monitoring of the energy meter status, automatic switching of pulse types when any of the conditions are met, the system keeps a record of the previous pulse response when switching, the conditions include: Condition 1 is that the current working state switches irregularly; Condition 2: Current variation exceeds ±10% Condition three is that the system detects that the jump rate of the pulse signal changes by more than 0.1 Hz.

4. A high-precision electric energy meter error correction method as claimed in claim 3, characterized in that: The determination of whether the error is within the specified range includes the preliminary calculation of the measurement error C u -C a , conduct a comprehensive evaluation of the error to determine whether the error of the three-phase electric energy meter is within the specified range or standard range: Among them, E t is the total error assessment, K is the dynamic adjustment coefficient, Acc i is the accidental error value of each test data, L i is the importance weight of the data, C u is the ideal value of the energy meter, C a is the calculated value obtained from actual measurement, n is the total amount of verified data, i is the variable index, D i is the error value of each verification data, E th is the set error threshold; When E t <E th When , it is judged to be within the normal range, the measurement is accurate, and normal operation is maintained; When E th ≤E t <2E th When the error difference trend is , it is judged as the alarm range, a warning is output, and the error difference trend is judged. According to the trend judgment result, it is judged whether to convert it to the abnormal range. When the trend judgment result shows that the error difference trend is increasing as a whole and there is no downward fluctuation, it is converted to the abnormal range for intervention error correction; When the trend evaluation results show that the error difference trend has downward fluctuations but has not increased overall, error detection is performed, and intervention error correction is performed after the cause of the error anomaly is determined; When the trend evaluation results show that the error difference trend has an upward fluctuation but is overall downward, or is overall downward without any upward fluctuation, it is considered not to be caused by the equipment, and the time for the overall decline to the normal range is predicted. If the time does not exceed 5 minutes, the system automatically finds the influencing factors and makes corrections. If the time exceeds 5 minutes, error detection is performed, environmental parameters are analyzed, and automatic correction of the error correction auxiliary system is performed; When E t ≥2E th When it is detected, it is judged as an abnormal range and immediate intervention error correction is required.

5. A high-precision electric energy meter error correction method as claimed in claim 4, characterized in that: The error detection includes detecting error data by using open circuit detection. When it is necessary to analyze environmental parameters, two methods, open circuit detection and temperature detection, are used. The loop open detection includes setting the actual voltage V actual , and record the initial measurement value, trace the impact of historical data and the deviation of real-time measurement, and calculate the error as: Among them, E open is the error percentage during the open circuit detection phase, M open is the measured value of the electric energy meter under open circuit, α is the coefficient reflecting the relationship between the measured value and historical data, H open Bias correction factors based on historical data; Define a new failure rate when |E open |>E th,1 When |E open |≤E th,1 When , it is considered that the current data failure rate is low, among which, E th,1 is the defined error threshold, used to determine whether it exceeds the acceptable range; The two methods of loop open detection and temperature detection include recording the current ambient temperature of the electric energy meter, calculating the temperature-related error and the comprehensive error E total , confirm the total data failure rate, when |E total |>E th,2 When |E total |≤E th,2 When , it is considered that the current data failure rate is low, among which, E th,2 is the defined error threshold, which is used to determine whether the total data exceeds the acceptable range; At the same time, the false detection rate diagnosis is carried out. When the data with high unqualified rate and low false detection rate are short-circuited and error corrected, the error correction is carried out after short-circuiting.

6. A high-precision electric energy meter error correction method as claimed in claim 5, characterized in that: The monitoring of the false detection rate includes simultaneously performing false detection rate diagnosis to identify accidental errors; The number of electric energy meters with high failure rate is counted by historical statistics, and the false detection rate E is calculated. detect , when E detect >E detect_th When E detect ≤E detect_th When , it is considered that there is a low false positive rate, which is an accidental error; When the data failure rate is high and there is a high false detection rate, the system automatically performs short-circuit processing and error correction, and calculates all short-circuited meters according to the cause-and-effect relationship of the error correction increase: AND corrected =And total -γD decision Among them, E corrected is the error correction parameter, D decision is a decision variable, indicating whether it is judged as a false positive; γ is a loss correction factor.

7. A high-precision electric energy meter error correction method as claimed in claim 6, characterized in that: The error correction includes collecting operation data including voltage, current, power factor and power usage time information through three-phase electric energy meters, and counting the historical data of each electric energy meter including verification results and correction records; Using big data analysis, we can obtain the geographical location information of the energy meter and collect the electricity consumption characteristic data of each area. We can extract the operating characteristics of similar energy meters through data mining technology, identify the error distribution law, analyze the overall trend and individual differences of similar energy meters, and identify the errors caused by commonality and individuality. Through cluster analysis, the electric energy meters are divided into y groups with similar characteristics. When the operating error of the same type of electric energy meters exceeds ±2%, they are marked as high-error meters. The high-error meters are corrected first and then the remaining electric energy meters are corrected. When the average error of any type of electric energy meter exceeds ±3% of the global standard deviation of the type, a cost-optimized individual correction is performed to reduce the error to within ±1% of the group average. Evaluate the behavior model of the energy meter and set different correction strategies based on regional power grid characteristics, seasonal fluctuations and historical power consumption patterns. When the location characteristics of the energy meter do not match the power consumption characteristics, the corresponding correction parameters and correction strategies are called; when the geographical location of the energy meter matches the location characteristics in the database by more than 85%, only the corresponding correction parameters are adjusted to adapt to the local power grid characteristics; When the operation time of the electricity meter exceeds 3 years and the frequency fluctuation of the power grid in the geographical area exceeds 5Hz, the correction algorithm upgrade is triggered, and a location-related correction database is established to trace the historical data. When the correction parameter adjustment number of the electricity meter exceeds 5 times, the historical data analysis is automatically started to trace the operating status and correction changes of the historical data, and provide improvement suggestions. If the historical correction failure rate exceeds 10%, the system will issue an alarm to the maintenance team.

8. A system using a high-precision electric energy meter error correction method as claimed in any one of claims 1 to 7, characterized in that: It includes an error verification module, an error detection module, and an error correction module; The error detection module includes an operation data acquisition unit and a verification unit. The operation data acquisition unit is responsible for collecting real-time operation data of the three-phase electric energy meter, including electrical parameters, environmental parameters, and load characteristics; the verification unit is responsible for calling historical operation data, analyzing the operation trend and abnormal conditions of the electric energy meter, and inputting the results into the error detection module; The error detection module includes a detection unit and an error evaluation unit. The detection unit receives data from the error verification module and performs error detection, including loop open detection and temperature detection. The error evaluation unit performs a comprehensive evaluation on the error of the electric energy meter according to the error detection result, determines whether the error is within a specified range, and sends the error detection result and the evaluation result to the error correction module. The error correction module includes a correction unit and a strategy optimization unit. The correction unit performs error correction on the electric energy meter according to the error evaluation result, including automatic short-circuit processing and error correction; the strategy optimization unit adjusts the correction strategy according to the geographical location, power consumption characteristics and operating time information of the electric energy meter, optimizes the correction effect, and feeds back to the error detection module.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a high-precision electric energy meter error correction method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a high-precision electric energy meter error correction method described in any one of claims 1 to 7 are implemented.

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