A method, device and storage medium for solving electric meter errors

Abstract

The present invention relates to an electric meter error solving method, device and storage medium. The method comprises the following steps: obtaining data of a measuring switch in a meter box and all corresponding sub-meters thereof, and preprocessing the data of all sub-meters; constructing a phase-separated energy conservation equation group and a total energy conservation equation group based on the preprocessed data of all sub-meters; establishing a simultaneous equation group of the phase-separated energy conservation equation group and the total energy conservation equation group, and solving them by a BFGS quasi-Newton method to obtain an initial fitting residual sequence; after filtering out metering period data based on the data in the initial fitting residual sequence, obtaining an optimal data set, solving the optimal data set again by a BFGS quasi-Newton method, repeating iterations until the iteration stops when a stopping condition is reached, and obtaining a final optimal data set; and calculating the error of each sub-meter of the measuring switch based on the final optimal data set.

Description

Technical Field

[0001] The invention relates to an electric meter error solving method, equipment and storage medium, belonging to the technical field of electric energy measurement. Background Art

[0002] In recent years, smart meters have replaced traditional meters, greatly reducing the workload of meter reading and manual inspections. At the same time, a large number of smart meters are running on the network, which makes people pay special attention to smart meter error monitoring.

[0003] In the online monitoring model of smart meter misalignment error (hereinafter referred to as misalignment model), the energy conservation relationship between the total meter and the household meter is used to establish a model to solve the error coefficient of the meter. In the area where the smart measurement switch is installed, the misalignment model will have further room for development. The smart measurement switch is a low-voltage switch electrical appliance that combines a high-precision current sensor and a measurement unit, which can be installed in environments such as low-voltage metering boxes. It not only has basic connection, disconnection and short-circuit overload protection functions, but also can monitor the electrical quantity of the distribution line in real time, and support advanced applications such as edge management, topology identification, and power consumption analysis.

[0004] How to establish a model based on the phase information of the measuring switch, effectively utilize the phase information, and improve the calculation accuracy of the sub-meter error in the meter box equipped with the measuring switch is a problem to be solved.

[0005] The invention patent with publication number "CN110673081A" discloses an online estimation method for smart meter errors based on edge computing. The invention is based on the principle of energy conservation in the meter box, and uses the smart circuit breaker meter power equal to the power of each sub-meter and the line loss to construct a group of energy conservation equations, and obtains the error parameters through the least squares method, and calculates the error of each sub-meter based on the error parameters; this scheme reduces the energy conservation of the substation area to the meter box, and establishes a group of equations based on the total-split relationship in the meter box. The number of sub-meters is greatly reduced, which is expected to improve the accuracy of error calculation.

[0006] However, the above scheme only builds the model based on the conservation relationship of the total and divided electricity in the meter box, which is an insufficient use of information. Abandoning additional information will lead to the loss of part of the data, so that the room for improvement in improving the accuracy of the model is also abandoned; secondly, the line loss is regarded as a fixed quantity to build the model, but in reality the line loss is related to the user's electricity consumption behavior, and the line loss rate of the meter box and the allowable range of the meter error are at the same order of magnitude. Due to the constraint of energy conservation, if the line loss calculation is inaccurate, the error of the electricity meter will definitely be estimated inaccurately. Summary of the invention

[0007] In order to solve the above problems in the prior art, a method, device and storage medium for solving electric meter errors are proposed.

[0008] The technical solution of the present invention is as follows:

[0009] In one aspect, the present invention provides a method for solving an electric meter error, comprising the following steps:

[0010] Obtain the data of the measuring switch in the meter box and all its corresponding sub-meters, and pre-process the data of all sub-meters;

[0011] Based on the pre-processed data of all sub-tables, the phase-separated energy conservation equations and the total energy conservation equations are constructed;

[0012] The simultaneous equations of phase energy conservation equations and total energy conservation equations are established, and the initial fitting residual sequence is obtained by solving them using the BFGS quasi-Newton method;

[0013] After screening out the metering period data based on the data in the initial fitting residual sequence, the optimal data set is obtained, and the optimal data set is solved again by the BFGS quasi-Newton method, and the iteration is repeated until the iteration condition is reached to stop the iteration and obtain the final optimal data set;

[0014] The error of each sub-meter of the measuring switch is calculated based on the final optimal data set.

[0015] As a preferred embodiment of the present invention, the pretreatment step is:

[0016] After filtering the abnormal data in the sub-meter data, the phase of any sub-meter is identified based on the data of the sub-meter to obtain the phase information of each sub-meter, and at the same time, the sub-meter index of the measurement switch on the three phases is constructed.

[0017] As a preferred embodiment of the present invention, the phase-separated energy conservation equations are specifically shown as follows:

[0018] ;

[0019] ;

[0020] ;

[0021] in: , , Respectively indicate the measurement switch A, B, C phase in the first The amount of electricity in a metering cycle; Indicates Table No. The amount of electricity in a metering cycle; Indicates Error parameters of each sub-table; , , Respectively represent the equivalent resistance of the A, B, and C phases of the measurement switch; , , Respectively represent the fixed losses of the measured switch phases A, B, and C; , , Respectively represent the sub-table index list of the measurement switch A, B, and C phases; Indicates the total number of metering cycles; Indicates A sub-table; Indicates A measurement cycle.

[0022] As a preferred embodiment of the present invention, the total energy conservation equations are specifically shown as follows:

[0023] ;

[0024] in: Indicates the measurement switch Total power consumption in a measurement cycle; Represents the total fixed loss of the measured switch; Indicates the equivalent resistance of the first branch of the measuring switch; Indicates the total number of sub-meters measuring switches.

[0025] As a preferred embodiment of the present invention, the specific steps of solving the simultaneous equations by the BFGS quasi-Newton method are as follows:

[0026] The simultaneous equations are expressed as ,in: represents the power of the A, B, and C phases of the measurement switch and the total power in the simultaneous equations. represents the coefficient matrix in the system of simultaneous equations, represents the vector of unknowns in the system of simultaneous equations;

[0027] Setting the weight matrix , calculate the weight matrix corresponding to The weighted least squares solution of is equivalent to the minimization problem of the following formula:

[0028] ;

[0029] but

[0030] ;

[0031] in: express The gradient of Represents the transpose of a matrix;

[0032] The BFGS quasi-Newton method is used to solve the above nonlinear problem. The specific steps are as follows:

[0033] Initialize the unknown vector , threshold , the initial approximation matrix , the initial number of iterations , represents the identity matrix;

[0034] Calculate the The search direction of the iteration ,in, Indicates The approximate matrix of the iterations, Indicates The gradient of the iteration, ;

[0035] Determine The search step size of the iteration , so that , i.e. using:

[0036] ;

[0037] Find:

[0038] ;

[0039] make , ;

[0040] calculate:

[0041] ;

[0042] like , then calculate , and then calculate:

[0043] ;

[0044] make , calculate the search direction again, and repeat the above steps until , the calculation is stopped and an approximate solution is obtained ;

[0045] The approximate solution Substituting into the original equation, we get the initial fitting residual sequence, as shown below:

[0046] ;

[0047] in: represents the initial fit residual sequence.

[0048] As a preferred embodiment of the present invention, the steps for determining the final preferred data set are:

[0049] pass The point deletion method removes the initial fitting residual sequence that is greater than or less than The corresponding metering cycle data is deleted, where: represents the initial fitting residual sequence The first quantile corresponding value of express The third quantile corresponding value is , the remaining measurement period data are used as the final preferred data set;

[0050] The BFGS quasi-Newton method is used again to solve the optimal data set after data screening based on the initial fitting residual sequence, and the iteration is repeated until the iteration condition is reached to stop the iteration and obtain the final approximate solution. The final preferred dataset.

[0051] As a preferred embodiment of the present invention, The unknown vector contained in includes the error parameters of each sub-table. The error value is calculated by the following formula:

[0052] ;

[0053] in: Indicates The error value of each subtable.

[0054] On the other hand, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any embodiment of the present invention is implemented.

[0055] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0056] The present invention has the following beneficial effects:

[0057] 1. The present invention introduces line loss in the meter box model by combining the phase energy conservation relationship to make the model expression more accurate. The added additional phase conservation relationship includes additional data information. From the number of equation groups, it can be simply understood that the amount of data has been increased, thereby improving the effectiveness and stability of the model calculation.

[0058] 2. The present invention adopts a dynamic weighted least squares method based on the model fitting residual and uses the BFGS quasi-Newton method to solve the model. On the one hand, it avoids the problem of needing to solve the second-order derivative (Hessian matrix) in the Newton method. On the other hand, it avoids the matrix inversion problem through the Sherman-Morrison formula, making the model solution more stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0062] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0063] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0064] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0065] Embodiment 1:

[0066] See also Figure 1 , a method for solving an electric meter error, comprising the following steps:

[0067] Obtain the data of the measuring switch in the meter box and all its corresponding sub-meters, and pre-process the data of all sub-meters;

[0068] Based on the pre-processed data of all sub-tables, the phase-separated energy conservation equations and the total energy conservation equations are constructed;

[0069] The simultaneous equations of phase energy conservation equations and total energy conservation equations are established, and the initial fitting residual sequence is obtained by solving them using the BFGS quasi-Newton method;

[0070] After screening out the metering period data based on the data in the initial fitting residual sequence, the optimal data set is obtained, and the optimal data set is solved again by the BFGS quasi-Newton method, and the iteration is repeated until the iteration condition is reached to stop the iteration and obtain the final optimal data set;

[0071] The error of each sub-meter of the measuring switch is calculated based on the final optimal data set.

[0072] As a preferred implementation of this embodiment, the preprocessing steps are:

[0073] After filtering out abnormal data in the sub-meter data, phase identification is performed on any sub-meter based on the data of the sub-meter (there are many known methods for phase identification, which will not be repeated here), and the phase information of each sub-meter is obtained. At the same time, the sub-meter index of the measurement switch on the three phases is constructed.

[0074] As a preferred implementation of this embodiment, the phase-separated energy conservation equations are specifically shown as follows:

[0075] ;

[0076] ;

[0077] ;

[0078] in: , , Respectively indicate the measurement switch A, B, C phase in the first The amount of electricity in a metering cycle; Indicates Table No. The amount of electricity in a metering cycle; Indicates Error parameters of each sub-table; , , Respectively represent the equivalent resistance of the A, B, and C phases of the measurement switch; , , Respectively represent the fixed losses of the measured switch phases A, B, and C; , , Respectively represent the sub-table index list of the measurement switch A, B, and C phases; Indicates the total number of metering cycles; Indicates A sub-table; Indicates A measurement cycle.

[0079] As a preferred implementation of this embodiment, the total energy conservation equations are specifically shown as follows:

[0080] ;

[0081] in: Indicates the measurement switch Total power consumption in a measurement cycle; Represents the total fixed loss of the measured switch; Indicates the equivalent resistance of the first branch of the measuring switch; Indicates the total number of sub-meters measuring switches.

[0082] As a preferred implementation of this embodiment, the specific steps of solving the simultaneous equations by the BFGS quasi-Newton method are as follows:

[0083] The simultaneous equations are expressed as ,in: represents the power of the A, B, and C phases of the measurement switch and the total power in the simultaneous equations. represents the coefficient matrix in the system of simultaneous equations, represents the vector of unknowns in the system of simultaneous equations;

[0084] Setting the weight matrix , calculate the weight matrix corresponding to The weighted least squares solution of is equivalent to the minimization problem of the following formula:

[0085] ;

[0086] but

[0087] ;

[0088] in: express The gradient of Represents the transpose of a matrix; Indicates that Defined as ;

[0089] The BFGS quasi-Newton method is used to solve the above nonlinear problem. The specific steps are as follows:

[0090] Initialize the unknown vector , threshold , the initial approximation matrix , the initial number of iterations , represents the identity matrix;

[0091] Calculate the The search direction of the iteration ,in, Indicates The approximate matrix of the iterations, Indicates The gradient of the iteration, ;

[0092] Determine The search step size of the iteration , so that , i.e. using:

[0093] ;

[0094] Find:

[0095] ;

[0096] make , ;

[0097] calculate:

[0098] ;

[0099] like , then calculate , and then calculate:

[0100] ;

[0101] make , calculate the search direction again, and repeat the above steps until , the calculation is stopped and an approximate solution is obtained ;

[0102] The approximate solution Substituting into the original equation, we get the initial fitting residual sequence, as shown below:

[0103] ;

[0104] in: represents the initial fit residual sequence.

[0105] In this embodiment, the weight matrix Through the forgetting factor The settings are as follows:

[0106]

[0107] As a preferred implementation of this embodiment, the steps for determining the final preferred data set are:

[0108] pass The point deletion method removes the initial fitting residual sequence that is greater than or less than The corresponding metering cycle data is deleted, where: represents the initial fitting residual sequence The first quantile corresponding value of express The third quantile corresponding value is , the remaining measurement period data are used as the final preferred data set;

[0109] The BFGS quasi-Newton method is used again to solve the optimal data set after data screening based on the initial fitting residual sequence, and the iteration is repeated until the iteration condition is reached to stop the iteration and obtain the final approximate solution. The final preferred dataset.

[0110] At each iteration, the weight matrix Also through The point deletion method is used to filter out data.

[0111] As a preferred implementation of this embodiment, The unknown vector contained in includes the error parameters of each sub-table. The error value is calculated by the following formula:

[0112] ;

[0113] in: Indicates The error value of each subtable.

[0114] Embodiment 2:

[0115] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0116] Embodiment three:

[0117] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0118] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0119] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0120] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0121] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, 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, which is stored in a storage medium and includes 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 method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0122] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for solving an electric meter error, characterized in that: The following steps are involved: Obtain the data of the measuring switch in the meter box and all its corresponding sub-meters, and pre-process the data of all sub-meters; Based on the pre-processed data of all sub-tables, the phase-separated energy conservation equations and the total energy conservation equations are constructed; The phase-separated energy conservation equations are specifically shown in the following formula: ； ； ； in: , , Respectively indicate the measurement switch A, B, C phase in the first The amount of electricity in a metering cycle; Indicates Table No. The amount of electricity in a metering cycle; Indicates Error parameters of each sub-table; , , Respectively represent the equivalent resistance of the A, B, and C phases of the measurement switch; , , Respectively represent the fixed losses of the measured switch phases A, B, and C; , , Respectively represent the sub-table index list of the measurement switch A, B, and C phases; Indicates the total number of metering cycles; Indicates A sub-table; Indicates Metering cycle; The total energy conservation equations are specifically shown in the following formula: ； in: Indicates the measurement switch Total power consumption in a measurement cycle; Represents the total fixed loss of the measured switch; Indicates the equivalent resistance of the first branch of the measuring switch; Indicates the total number of sub-meters measuring switches; The simultaneous equations of phase energy conservation equations and total energy conservation equations are established, and the initial fitting residual sequence is obtained by solving them using the BFGS quasi-Newton method; After screening out the metering period data based on the data in the initial fitting residual sequence, the optimal data set is obtained, and the optimal data set is solved again by the BFGS quasi-Newton method, and the iteration is repeated until the iteration stop condition is reached to obtain the final optimal data set; The error of each sub-meter of the measuring switch is calculated based on the final optimal data set.

2. The method for solving an electric meter error according to claim 1, characterized in that: The pre-processing steps are: After filtering the abnormal data in the sub-meter data, the phase of any sub-meter is identified based on the data of the sub-meter to obtain the phase information of each sub-meter, and at the same time, the sub-meter index of the measurement switch on the three phases is constructed.

3. The method for solving an electric meter error according to claim 1, characterized in that: The specific steps for solving the simultaneous equations by the BFGS quasi-Newton method are: The simultaneous equations are expressed as ,in: represents the power of the A, B, and C phases of the measurement switch and the total power in the simultaneous equations. represents the coefficient matrix in the system of simultaneous equations, represents the vector of unknowns in the system of simultaneous equations; Setting the weight matrix , calculate the weight matrix corresponding to The weighted least squares solution of is equivalent to the minimization problem of the following formula: ； but ； in: express The gradient of Represents the transpose of a matrix; The BFGS quasi-Newton method is used to solve the above minimization problem. The specific steps are: Initialize the unknown vector , threshold , the initial approximation matrix , the initial number of iterations , represents the identity matrix; Calculate the The search direction of the iteration ,in, Indicates The approximate matrix of the iterations, Indicates The gradient of the iteration, ; Determine The search step size of the iteration , so that , i.e. using: ； Find: ； make , ; calculate: ； like , then calculate , and then calculate: ； make , calculate the search direction again, and repeat the above steps until , the calculation is stopped and an approximate solution is obtained ; The approximate solution Substituting into the original equation, we get the initial fitting residual sequence, as shown below: ； in: represents the initial fit residual sequence.

4. The method for solving an electric meter error according to claim 3, characterized in that: The steps for determining the final optimal data set are: pass The point deletion method removes the initial fitting residual sequence that is greater than or less than The corresponding metering cycle data is deleted, where: represents the initial fitting residual sequence The first quantile corresponding value of express The third quantile corresponding value is , the remaining measurement period data are used as the final preferred data set; The BFGS quasi-Newton method is used again to solve the optimal data set after data screening based on the initial fitting residual sequence, and the iteration is repeated until the iteration condition is reached to stop the iteration and obtain the final approximate solution. The final preferred dataset.

5. The method for solving an electric meter error according to claim 4, characterized in that: The unknown vector contained in includes the error parameters of each sub-table. The error value is calculated by the following formula: ； in: Indicates The error value of each subtable.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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