Method and system for improving accuracy of clocked asynchronous power metering error estimation

Abstract

The application discloses a clock-asynchronous-oriented electric metering error estimation accuracy improving method and system, and the method comprises the following steps: screening target electric energy metering data with normal load from electric energy metering data; constructing a clock-asynchronous deviation suppression strategy based on metering interval expansion; constructing an expanded electric energy conservation equation according to the clock-asynchronous deviation suppression strategy based on metering interval expansion and the target electric energy metering data, constructing a numerical definition parameter of the expanded metering interval length according to the electric energy conservation equation, and collecting a plurality of numerical definition parameters to form a parameter distribution; determining the length of a minimum effective expanded metering interval according to the parameter distribution; constructing an energy conservation equation set according to the length of the minimum effective expanded metering interval, and obtaining user metering error by solving the energy conservation equation set by using a total least square method. Therefore, the application can reduce the solving deviation introduced by data asynchrony to user metering error estimation, and realizes accurate estimation of user metering error.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric energy meter, in particular to a clock-asynchronous-oriented electric metering error estimation accuracy improvement method and system. BACKGROUND

[0002] As the core equipment in the AMI (Advanced Metering Infrastructure) system, smart meters have been widely deployed in global power grids. The metering accuracy of smart meters is related to the interests of the general public and public service companies. In order to ensure the fairness of electric energy transactions, the metering error of smart meters needs to be obtained in time, and the operation and maintenance of abnormal electric energy meters needs to be carried out.

[0003] Public service companies usually use periodic sampling detection to test the metering accuracy of smart meters near the expiration date. The specific implementation form is field testing and laboratory testing after disassembly, which has the problems of poor timeliness and high cost. Due to the results of periodic sampling detection, the metering accuracy of smart meters cannot be reflected in real time and in full amount. The existing online estimation method of smart metering error fuses electrical topology constraints and electric energy metering data, constructs the energy conservation equation of the total metering value, the user smart metering value and the line loss in the same metering interval, and solves the metering error based on this. However, due to the communication time delay of multi-level communication in the district and the difference in the time keeping ability of the electric meter, the user meter clock cannot be completely synchronized, which leads to the fact that the metering intervals of each meter cannot be strictly aligned, thereby destroying the energy conservation condition, making it difficult to accurately obtain the metering error of the user meter, and reducing the targeting of operation and maintenance. Therefore, there is an urgent need for a clock-asynchronous-oriented electric metering error online estimation accuracy improvement method to reduce the solving deviation introduced by data asynchrony to user meter error estimation, and to realize accurate estimation of user metering error. SUMMARY

[0004] The present application provides a clock-asynchronous-oriented electric metering error estimation accuracy improvement method and system, which solves the problem of reduced error estimation accuracy based on energy conservation due to asynchronous measurement data of user meters in the district.

[0005] In a first aspect, a clock-asynchronous-oriented electric metering error estimation accuracy improvement method is provided, comprising:

[0006] Obtaining electric energy metering data of a district total meter and all user meters under all metering intervals, and screening target electric energy metering data with normal load from the electric energy metering data;

[0007] Constructing a clock-asynchronous deviation suppression strategy based on metering interval expansion;

[0008] construct an extended energy conservation equation according to the clock-asynchronous deviation suppression strategy of the extended metering interval and the target electric energy metering data, construct a numerical definition parameter of the length of the extended metering interval according to the extended energy conservation equation, and collect a plurality of the numerical definition parameters to form a parameter distribution;

[0009] determine the length of the minimum effective extended metering interval according to the parameter distribution;

[0010] construct an energy conservation equation group considering the metering deviation of the user meter and line loss according to the length of the minimum effective extended metering interval, solve the energy conservation equation group by using the total least squares method, and obtain the metering error of the user meter.

[0011] In a second aspect, a clock-asynchronous electric meter metering error estimation accuracy improvement system is provided, which comprises:

[0012] a data acquisition module configured to acquire electric energy metering data of a total meter of a transformer area and all user meters under the transformer area in all metering intervals, and to screen target electric energy metering data with normal load from the electric energy metering data;

[0013] a metering interval extension module configured to construct a clock-asynchronous deviation suppression strategy based on metering interval extension;

[0014] a parameter definition module in communication connection with the data acquisition module and the metering interval extension module, configured to construct an extended energy conservation equation according to the clock-asynchronous deviation suppression strategy of the extended metering interval and the target electric energy metering data, construct a numerical definition parameter of the length of the extended metering interval according to the extended energy conservation equation, and collect a plurality of the numerical definition parameters to form a parameter distribution;

[0015] an extended length determination module in communication connection with the parameter definition module, configured to determine the length of the minimum effective extended metering interval according to the parameter distribution; and

[0016] a metering error estimation module in communication connection with the extended length determination module, configured to construct an energy conservation equation group considering the metering deviation of the user meter and line loss according to the length of the minimum effective extended metering interval, solve the energy conservation equation group by using the total least squares method, and obtain the metering error of the user meter.

[0017] In a third aspect, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the clock-asynchronous electric meter metering error estimation accuracy improvement method as described above.

[0018] Compared with the prior art, the advantages of the present application are as follows: by acquiring the total metering data of the transformer area and the total metering data of all users under the transformer area at all metering intervals, and screening out target electric energy metering data with normal load from the electric energy metering data; then constructing a clock asynchronous deviation suppression strategy based on metering interval expansion; and constructing an expanded electric energy conservation equation according to the clock asynchronous deviation suppression strategy based on metering interval expansion and the target electric energy metering data, constructing a numerical definition parameter of the expanded metering interval length according to the electric energy conservation equation, and collecting a plurality of the numerical definition parameters to form a parameter distribution; then determining the length of the minimum effective expanded metering interval according to the parameter distribution; and finally constructing an energy conservation equation set considering the metering deviation of the user table and the line loss according to the length of the minimum effective expanded metering interval, solving the energy conservation equation set by using the total least squares method, and obtaining the metering error of the user table. Therefore, the solving deviation introduced by the data asynchrony to the user table error estimation can be reduced, and the accurate estimation of the metering error of the user table can be realized. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is an electrical connection topology diagram of the total metering table and the user metering table in the transformer area provided by an embodiment of the present application;

[0020] Figure 2 is a flowchart of a clock asynchronous electric metering error estimation accuracy improvement method provided by an embodiment of the present application;

[0021] Figure 3 is a structure diagram of a clock asynchronous electric metering error estimation accuracy improvement method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0022] Reference will now be made in detail to the present application, examples of which are illustrated in the accompanying drawings. While the present application will be described in conjunction with the specific embodiments, it will be understood that the present application is not limited to the specific embodiments. Rather, the present application is intended to cover any alternatives, modifications, and equivalents, which can be included within the spirit and scope of the present application as defined by the appended claims. It should be noted that the method steps described herein can all be realized by any functional block or functional arrangement, and any functional block or functional arrangement can be realized as a physical entity or a logical entity, or a combination of both.

[0023] In order for those skilled in the art to better understand the present application, the present application will be further described in detail below in conjunction with the drawings and specific embodiments.

[0024] Note: The examples described below are merely specific examples and are not intended to limit the embodiments of the present invention to the specific steps, values, conditions, data, order, etc. Those skilled in the art can utilize the concept of the present invention to construct more embodiments not mentioned herein by reading this specification.

[0025] Please see Figure 1 The user meter is the smart meter for the user in the distribution area, which records data such as the user's energy consumption. The master meter is the total energy meter under the transformer in the distribution area, which records data such as the total energy consumption of the distribution area. The line loss is the loss of the power supply line connecting the master meter and the user smart meters.

[0026] Please see Figure 2 The present invention provides a flowchart illustrating a method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters, comprising:

[0027] Step S100: Obtain the power metering data of the main meter of the distribution area and all user meters under the distribution area under all metering intervals, and filter out the target power metering data with normal load from the power metering data.

[0028] Specifically, the aforementioned electricity metering data should be the electricity metering data of the main meter of the distribution area and all user meters within the same metering interval, wherein in the first... i indivual Metering interval Below, the total electricity metering data is recorded as follows: , No. j The electricity metering data for each user's meter is recorded as follows: .

[0029] The definition of a normal load should be limited according to the actual specifications of the user's electricity meter. Optionally, when the user meter's accuracy class is preset level 2 and the connection method is direct connection, if the current in the current metering interval is greater than 10% of the reference current, then the load in the current metering interval is considered a normal load, and the electricity metering data of the corresponding main electricity meter and all user meters are retained. If the user meter's accuracy class is preset level 2 and the connection method is via a current transformer, if the current in the current metering interval is greater than 5% of the reference current, then the load in the current metering interval is considered a normal load, and the electricity metering data of the corresponding main electricity meter and all user meters are retained. Therefore, the target electricity metering dataset that can be used for user meter metering error estimation is... This is the electricity metering data under normal load.

[0030] Step S200: Construct a clock asynchronous deviation suppression strategy based on metering interval extension.

[0031] Specifically, in the i Each electricity metering interval Next, the When the clock of the user's electricity meter is asynchronous, it causes The electricity metering results have a time asynchronous deviation. The magnitude of its time asynchronous deviation depends on The proportion of single-time electricity metering intervals and the current load fluctuation situation. Among them, time asynchronous... The size depends on the delay caused by the master table hierarchical broadcast time synchronization and the first The timekeeping capability of the meter, during the period between two time calibrations... This can be considered a value with an upper limit; the load fluctuation curve has a predictable extreme value, which is related to the electricity consumption behavior of users in that area, therefore... There is an upper limit to the numerical variation. This can be achieved by extending the interval between single energy metering operations and reducing time-asynchronous... The proportion of single electricity metering intervals This reduces the time asynchrony deviation. The proportion of single-use electricity metering data This improves the accuracy of solving the following error estimation equations.

[0032] Step S300: Based on the clock asynchronous deviation suppression strategy of the metering interval extension and the target power metering data, construct the extended power conservation equation, construct the numerical definition parameter of the extended metering interval length based on the power conservation equation, and gather multiple numerical definition parameters to form a parameter distribution.

[0033] Specifically, based on the aforementioned metering interval expansion strategy, the original... Individual metering intervals are combined to form an extended single metering interval. That is, connected in the time dimension. The summation of individual electricity metering data forms the expanded electricity metering data.

[0034] The larger the value, the smaller the proportion of time-asynchronous error in the electricity metering data of a single interval. Considering the data accumulation time and the real-time nature of the error estimation results, The value cannot be infinitely large, therefore it needs to be properly controlled.

[0035] The energy conservation equation, which includes the energy from user metering errors, energy losses, and time-asynchronous deviations, can be expressed as follows:

[0036]

[0037] In the formula, For the extended equation of conservation of electrical energy, To reduce bus loss in the back-end area, to expand the power caused by the user table measurement deviation, to expand the power caused by the time asynchronous error, N is the number of user tables.

[0038] Since the value is related to the square of the consumed power, the value is related to the consumed power, and the the value of the definition parameter is as follows:

[0039]

[0040]

[0041]

[0042] In the formula, the value of the definition parameter of the expanded metering interval length, the expanded power conservation equation is a specific function relationship.

[0043] It can be seen that the value distribution of the definition parameter is consistent with the value distribution of the power consumed by the transformer area. And only related to the asynchronous time of the electric meter and the load fluctuation, can be regarded as a random disturbance quantity with an upper limit, the value of the definition parameter is negatively related to .

[0044] Collect the value definition parameters of different metering intervals to form the parameter value distribution as follows:

[0045]

[0046] In the formula, is the parameter distribution, is the number of expanded metering intervals, M is the number of metering intervals before expansion, and m is the number of metering intervals required to merge into a single expanded metering interval.

[0047] Step S400, according to the parameter distribution, determine the length of the minimum effective expanded metering interval.

[0048] Specifically, as the value of increases, the value distribution of the definition parameter is less disturbed by , that is, the variance of the distribution is smaller, and is more consistent with the value distribution of . Since the number of metering period mergers The limitedness of the time clock, for the balance between the accuracy and timeliness of the evaluation, introduces the time clock asynchronous deviation suppression diminishing marginal effect principle to determine the minimum effective expansion measurement interval length . The principle reveals that when The value of the step length increases, the measurement interval expansion shows a weakening trend in the variance reduction effect of the distribution If after a certain step change, the variance difference between adjacent distributions And The marginal benefit of variance suppression tends to zero, and the At this time is the minimum effective expansion measurement interval length.

[0049] The specific calculation formula is:

[0050] In the formula, The variance of the distribution The acceptable variance difference level.

[0051] The determination method of the minimum effective expansion measurement interval is as follows: according to the different values of Obtain the distribution And calculate the variance , and then draw the normalized The change curve of About Then use the change point detection method to determine the value of The specific steps are as follows:

[0052] If the curve has Change points, according to the change points, the entire curve is divided into Sections, and the data in each section is approximated by the mean value of the section, the goal is to minimize the error sum of squares in each section. The error sum of squares of a certain interval of

[0053]

[0054] In the formula, the interval Is a certain section of the curve.

[0055] If the change curve Has 1 change point, the curve can be divided into 2 sections, and the overall optimization goal is:

[0056]

[0057] According to the above optimization goal, the change point of the change curve can be obtained, and the minimum effective expansion measurement interval length . ​​

[0058] Step S500, according to the length of the minimum effective expansion metering interval, constructing an energy conservation equation set considering user metering error and line loss, using total least squares method to solve the energy conservation equation set to obtain user metering error.

[0059] Specifically, the method for constructing the energy conservation equation set considering user metering error and line loss is as follows:

[0060]

[0061] In the formula, is the metering error of the i-th user meter; is the loss coefficient; m is the length of the determined minimum effective expansion metering interval; is the total metering value of the transformer area in the M-th metering period after expansion; is the metering data of the i-th user meter in the M-th metering period after expansion;

[0062] Further, the energy conservation equation set is refined as:

[0063]

[0064] In the formula, is the coefficient matrix of the equation set;

[0065] is the electric energy metering data vector collected for the electric energy metering data of the i-th user meter in different periods;

[0066] , ;

[0067] is the line loss data vector collected for line loss in different periods;

[0068] ;

[0069] is the to-be-solved vector, containing the metering error of the user meter and the loss coefficient;

[0070] is the total metering value observation vector of the meter;

[0071] The total least squares method is used to solve the above energy conservation equation set to obtain accurate estimation of the user metering error.

[0072] First, the augmented matrix is constructed according to the formula:​​​ singular value decomposition is performed.

[0073] wherein, is a singular value matrix, , is a unitary matrix.

[0074] Further, the solution result is obtained according to the following formula.

[0075]

[0076] wherein, is the last column of .

[0077] The numerical results of the first represent the metering error estimation of the first smart meters, and then the metering performance evaluation result of the smart meter is formed according to the comparison result of the specific numerical value and the threshold value.

[0078] To sum up, the application first screens the preliminary data set that can be used for user metering error estimation;Develops the bias characteristic analysis of the error estimation introduced by the clock asynchronization of the user meter;Propose the clock asynchronization bias suppression strategy based on the metering interval expansion;Establish the energy conservation equation containing the user metering error electric energy, the loss electric energy and the data asynchronization bias electric energy, and propose the numerical definition parameter of the expanded metering interval length, and collect the parameter values of multiple metering intervals to form the parameter distribution;Propose the time clock asynchronization bias suppression marginal effect decreasing principle, determine the minimum effective expanded metering interval by calculating the variance reduction marginal benefit of the parameter distribution before and after expansion;With the help of the minimum effective expanded metering interval, the energy conservation equation set considering the user metering bias and line loss is established, and the total least square method is used to solve, so as to realize the accurate estimation of the user metering error.The application effectively improves the electric meter error estimation accuracy of the electric meter under the clock asynchronization of the transformer user, improves the intelligent operation and maintenance level of the metering out-of-tolerance electric meter, and ensures the accuracy and reliability of the charging pile electric energy metering.

[0079] Referring to FIG. 1, Figure 3 The application embodiment provides a clock asynchronization-oriented electric meter metering error estimation accuracy improvement system, which comprises:

[0080] A data acquisition module is configured to acquire electric energy metering data of a transformer total meter and all user meters under all metering intervals, and screen target electric energy metering data with normal load from the electric energy metering data.

[0081] A metering interval expansion module is configured to construct a clock asynchronization bias suppression strategy based on metering interval expansion.

[0082] ​The parameter definition module is in communication connection with the data acquisition module and the metering interval expansion module, configured to construct an expanded electrical energy conservation equation according to the clock asynchronous deviation suppression strategy of the metering interval expansion and the target electrical energy metering data, construct a numerical definition parameter of the expanded metering interval length according to the electrical energy conservation equation, and collect a plurality of the numerical definition parameters to form a parameter distribution;

[0083] The expansion length determination module is in communication connection with the parameter definition module, configured to determine the length of the minimum effective expanded metering interval according to the parameter distribution.

[0084] The metering error estimation module is in communication connection with the expansion length determination module, configured to construct an energy conservation equation group considering the user metering deviation and line loss according to the length of the minimum effective expanded metering interval, and solve the energy conservation equation group by using the total least squares method to obtain the user metering error.

[0085] Therefore, the smart metering error online estimation accuracy improvement scheme for clock asynchrony provided by the embodiment of the present application is used to solve the problem of reduced error estimation accuracy based on energy conservation due to asynchronous measurement data of the user meter in the transformer area, and can realize accurate estimation of the user metering error.

[0086] Specifically, the embodiment corresponds to the above method embodiment one by one, and the functions of each module have been described in detail in the corresponding method embodiment, and thus will not be described one by one.

[0087] Based on the same inventive concept, the embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize all method steps or part of the method steps of the above method.

[0088] The present application implements all or part of the processes in the above method, and can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0089] Based on the same inventive concept, the embodiments of the present application also provide an electronic device, including a memory and a processor, the memory stores a computer program running on the processor, and the processor implements all or part of the method steps of the above method when executing the computer program.

[0090] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the computer device, and connects all parts of the computer device through various interfaces and lines.

[0091] The memory can be used to store computer programs and / or modules, and the processor can realize various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application program required by a function (for example, a sound playing function, an image playing function, etc.); and the data storage area can store data created according to use of the mobile phone (for example, audio data, video data, etc.). In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0092] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, a server or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage, etc.) containing computer-usable program code.

[0093] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), server and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device implemented in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that implements the functions specified in the flow(s) or block(s).

[0094] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus, which realizes the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that implements the functions specified in the flow(s) or block(s).

[0095] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate computer-implemented processes, thus the instructions executed on the computer or other programmable devices provide processes for implementing the flow Figure 1 one or more flows and / or blocks Figure 1 one or more blocks or steps of functions specified in the flow

[0096] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method for improving the accuracy of metering error estimation in clock-asynchronous electricity meters, characterized in that, include: Obtain the power metering data of the main meter of the distribution area and all user meters under the distribution area under all metering intervals, and filter out the target power metering data with normal load from the power metering data; Construct a clock asynchronous deviation suppression strategy based on metering interval extension; Based on the clock asynchronous deviation suppression strategy of the metering interval extension and the target power metering data, the extended power conservation equation is constructed. Based on the power conservation equation, the numerical definition parameter of the extended metering interval length is constructed, and multiple numerical definition parameters are aggregated to form a parameter distribution. The length of the minimum effective extended metering interval is determined based on the parameter distribution. Based on the length of the minimum effective extended metering interval, an energy conservation equation system considering the metering deviation and line loss of the user meter is constructed. The energy conservation equation system is solved using the overall least squares method to obtain the metering error of the user meter. The proposed clock asynchronous skew suppression strategy based on metering interval extension includes: When asynchronous operation of the user meter clock is detected during a single metering interval, the asynchronous time value and the asynchronous time deviation of the energy metering data during the single metering interval are obtained. Multiple single metering intervals are then merged into a single extended metering interval to reduce the proportion of the time asynchronous value in the user table in a single metering interval, and the proportion of the time asynchronous deviation in the energy metering data in a single metering interval.

2. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 1, characterized in that, The step of filtering out target electricity metering data with normal load from the electricity metering data includes: When the accuracy level of the user meter is detected to be at the preset level and the access method is direct access, and the current in the current metering interval is greater than the first preset percentage of the reference current, the load of the current metering interval is determined to be a normal load. When the accuracy level of the user meter is detected to be at the preset level and the access method is via current transformer, and the current in the current metering interval is greater than the second preset percentage of the reference current, the load of the current metering interval is determined to be a normal load.

3. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 1, characterized in that, The step of constructing the extended energy conservation equation based on the clock asynchronous deviation suppression strategy extended according to the metering interval and the target energy metering data includes: Based on m single measurement intervals Merging to form a single extended metering interval Based on the target energy metering data, the extended energy conservation equation is constructed as follows: In the formula, This is the extended equation for the conservation of electrical energy. To reduce bus loss in the back-end area; To cover the electricity consumption caused by measurement deviations in the user's meter after expansion; To account for the power consumption caused by asynchronous time errors after expansion; Metering interval The corresponding number A logo, ; j For user table number, N is the number of user tables.

4. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 3, characterized in that, The process of constructing an extended metering interval length based on the energy conservation equation, and aggregating multiple numerically defined parameters to form a parameter distribution, includes: The numerical definition of the extended metering interval length, based on the aforementioned energy conservation equation, is shown in the following formula: In the formula, Define parameters for the extended measurement interval length; For the extended energy conservation equation A specific functional relationship; The numerically defined parameters are then aggregated to form a parameter distribution as shown in the following equation: In the formula, For parametric distribution; M represents the number of metering intervals after expansion; M represents the number of metering intervals before expansion; and m represents the number of metering intervals required to merge into a single expanded metering interval.

5. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 3, characterized in that, Determining the length of the minimum effective extended measurement interval based on the parameter distribution includes: Calculate the variance of the parameter distribution corresponding to the combination of m single measurement intervals into a single extended measurement interval, plot the normalized variance variation curve with respect to the number of measurement intervals m, and use the change point detection method to determine the value of the variation curve with respect to the number of measurement intervals m, so as to obtain the length m of the minimum effective extended measurement interval.

6. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 1, characterized in that, The method for constructing the energy conservation equations that take into account the metering deviation and line loss of user meters is shown in the following equation: In the formula, For the first Measurement error of user table number; is the loss coefficient; m is the length of the determined minimum effective extended metering interval; To extend the metering cycle to the Mth period, the total electricity meter reading for the distribution area; To extend the Mth measurement period, the first Electricity metering data for user number [number].

7. The method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in claim 6, characterized in that, The method of solving the energy conservation equations using the overall least squares method yields the user meter measurement error, including: The energy conservation equations are transformed into the following objective formula: In the formula, , is the coefficient matrix of the system of equations; For the first The electricity metering data vector is formed by aggregating the electricity metering data of user table No. 1 at different periods. ， ； This is a vector of line loss data collected from line loss data at different periods. ； Let be the vector to be solved; , is the observation vector of the total meter's electricity consumption value; T stands for transpose; The target formula is then solved using the overall least squares method to obtain the measurement error of the user table.

8. A system for improving the accuracy of metering error estimation in clock-asynchronous electricity meters, characterized in that, include: The data acquisition module is used to acquire the power metering data of the main meter of the distribution area and all user meters under the distribution area under all metering intervals, and to filter out the target power metering data with normal load from the power metering data; The metering interval extension module is used to construct a clock asynchronous deviation suppression strategy based on the metering interval extension. The parameter definition module is communicatively connected to the data acquisition module and the metering interval extension module. It is used to construct the extended energy conservation equation based on the clock asynchronous deviation suppression strategy of the metering interval extension and the target energy metering data, construct the numerical definition parameter of the extended metering interval length based on the energy conservation equation, and collect multiple numerical definition parameters to form a parameter distribution. The extension length determination module is communicatively connected to the parameter definition module and is used to determine the length of the minimum effective extension measurement interval based on the parameter distribution. as well as, The metering error estimation module is communicatively connected to the extension length determination module. It is used to construct a set of energy conservation equations that take into account the metering deviation and line loss of the user meter based on the length of the minimum effective extended metering interval, and solve the set of energy conservation equations using the overall least squares method to obtain the metering error of the user meter. The proposed clock asynchronous skew suppression strategy based on metering interval extension includes: When asynchronous operation of the user meter clock is detected during a single metering interval, the asynchronous time value and the asynchronous time deviation of the energy metering data during the single metering interval are obtained. Multiple single metering intervals are then merged into a single extended metering interval to reduce the proportion of the time asynchronous value in the user table in a single metering interval, and the proportion of the time asynchronous deviation in the energy metering data in a single metering interval.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for improving the accuracy of metering error estimation for clock-asynchronous electricity meters as described in any one of claims 1 to 7.

Images