A method and system for remotely monitoring the operation error of a gateway electric energy meter

Abstract

This invention provides a method and system for remote monitoring of the operating error of energy meters at key points. The method acquires the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point equipped with main and auxiliary meters. After calculating the energy difference between the main and auxiliary meters at each line metering point, it calculates the operating error of the energy meter at each line metering point based on a pre-established metering point error model, a metering point error conversion formula, and an energy meter error model. Based on the operating error and accuracy level of the energy meter at each line metering point, the operating status of the energy meter at each line metering point is determined. This method, based on the conservation of bus energy and the conservation of energy between the main and auxiliary meters, achieves the monitoring of the operating error of energy meters at key points without the addition of additional standard devices. It can achieve full coverage of key points where main and auxiliary meters are installed, effectively improving the quality and efficiency of energy meter operating error detection.

Description

Technical Field

[0001] This invention relates to the field of electricity metering and monitoring technology, and more specifically, to a method and system for remote monitoring of operational errors of a gate electricity meter. Background Technology

[0002] Gateway electricity meters refer to electricity meters installed and operated at gateways such as power generation enterprises' grid connection, inter-regional interconnection lines, provincial grid interconnection lines, and intra-provincial power supply. They are used for trade settlement and internal economic indicator assessment and play an important role in the electricity metering of the entire power grid. It is necessary to ensure the normal and stable operation of gateway electricity meters.

[0003] Energy meters at the junction point require the connection of primary voltage and current to secondary voltage and current via current transformers and their secondary circuits. Currently, the assessment of the operational error of these meters is primarily achieved through manual on-site inspections or remote monitoring using standard devices. Manual on-site inspections are conducted twice a year, acquiring errors specific to a given load point. Remote monitoring of these meters mainly involves remote error acquisition based on on-site inspection comparisons and status evaluation based on data analysis. For remote error acquisition, standard energy meters or high-accuracy voltage and current sampling devices are installed in the monitored junction meter circuit. Comparison data transmission is achieved through the acquisition equipment, and error calculation and analysis are performed at a remote master station. Status evaluation based on data analysis currently primarily utilizes weighted scoring techniques for energy meter status inspection. This involves establishing multi-dimensional indicators such as metering performance, acquisition functions, and operational risks, assigning weights, and calculating a score based on the meter's indicator data to determine its operational status. In addition, for the inaccuracy analysis of the electricity meters on the transformer side, the energy conservation method is used. The electricity meter error is treated as an unknown quantity in a multivariate non-homogeneous equation, and the electricity meter error is solved by information such as energy and line loss over multiple time periods. The main problems with the above two methods are: the on-site detection obtains intermittent and local errors, making it difficult to detect the inaccuracy of the electricity meters at the gateway under other load points and between two detection cycles in a timely manner; the remote comparison method requires the installation of standard devices, which requires modification of the circuit where the electricity meter is located, which is difficult and will change the parameters of the secondary circuit. The standard device still needs to be disassembled and tested periodically; the weighted electricity meter condition inspection technology has high requirements for multidimensional data and relies on batch data and family information of electricity meters. However, there are many types of electricity meters at the gateway, and the lack of relevant information leads to insufficient evaluation items. The energy conservation-based method uses the main meter of the transformer substation as a standard energy meter with two higher accuracy levels to detect energy meter errors. However, the gate contains current transformers and their secondary circuits and does not have a standard energy meter with a high accuracy level. In the absence of current transformer errors, it is difficult to decompose the energy meter errors. Summary of the Invention

[0004] To address the technical problems in existing technologies, such as the need to install standard devices for remote monitoring of the operating error of metering at key points, the difficulty in modifying the circuit where the meter is located, the high demand for multi-dimensional data, and the inability to obtain transformer errors when using the main meter of the distribution area as a standard meter with two higher accuracy levels based on the energy conservation method to detect meter errors, thus making it difficult to decompose the operating error of the meter, this invention provides a method and system for remote monitoring of the operating error of metering at key points.

[0005] According to one aspect of the present invention, a method for remote monitoring of the operating error of a gated energy meter is provided, the method comprising:

[0006] The daily cumulative energy consumption of the main meter and the daily cumulative energy consumption of the auxiliary meter are obtained at the line metering point where the main and auxiliary meters are installed. The energy meter at the gateway includes the main meter and the auxiliary meter at the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point.

[0007] Calculate the energy difference between the main and auxiliary meters at each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point;

[0008] Based on the pre-established metering point error model, the main metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the main meter of all line metering points, and the secondary metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the secondary meter of all line metering points.

[0009] Based on the pre-established metering point error conversion formula, the main metering point error of all line metering points is calculated according to the main metering point error conversion value of all line metering points, and the secondary metering point error of all line metering points is calculated according to the secondary metering point error conversion value of all line metering points.

[0010] Based on the pre-established energy meter error model, the operating error of the gate energy meter at each line metering point is calculated according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters.

[0011] Based on the operating error and accuracy class of the energy meter at each line metering point, determine the operating status of the energy meter at each line metering point.

[0012] According to another aspect of the present invention, the present invention provides a remote monitoring system for the operating error of a gate electricity meter, the system comprising:

[0013] The data acquisition module is used to acquire the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at the line metering point where the main and auxiliary meters are installed. The energy meter at the gateway includes the main meter and the auxiliary meter at the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point.

[0014] The first calculation module is used to calculate the difference in energy between the main and auxiliary meters for each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter for each line metering point.

[0015] The second calculation module is used to calculate the main metering point error conversion value of all line metering points based on the pre-established metering point error model and the daily cumulative electricity energy of the main meters of all line metering points, and to calculate the secondary metering point error conversion value of all line metering points based on the daily cumulative electricity energy of the secondary meters of all line metering points.

[0016] The third calculation module is used to calculate the main metering point error of all line metering points based on the pre-established metering point error conversion formula and the main metering point error conversion value of all line metering points, and to calculate the secondary metering point error of all line metering points based on the secondary metering point error conversion value of all line metering points.

[0017] The fourth calculation module is used to calculate the operating error of the gate energy meter at each line metering point based on the pre-established energy meter error model, according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters.

[0018] The results output module is used to determine the operating status of the energy meter at each line metering point based on the operating error and accuracy level of the energy meter at each line metering point.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0020] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0021] The present invention discloses a remote monitoring method and system for the operating error of a gated energy meter. The method includes: acquiring the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point equipped with a main and auxiliary meter, and calculating the energy difference between the main and auxiliary meters at each line metering point; calculating the conversion value of the main and auxiliary metering point errors for all line metering points based on a pre-established metering point error model and the daily cumulative energy of the main and auxiliary meters at all line metering points; calculating the main and auxiliary metering point errors for all line metering points based on a pre-established metering point error conversion formula and the conversion values ​​of the main and auxiliary metering point errors for all line metering points; calculating the operating error of the gated energy meter at each line metering point based on a pre-established energy meter error model, the main and auxiliary metering point errors, the daily cumulative energy of the main and auxiliary meters, and the energy difference between the main and auxiliary meters at each line metering point; and determining the operating status of the gated energy meter at each line metering point based on the operating error and accuracy level of the gated energy meter at each line metering point. The method described above is based on the conservation of bus energy and the conservation of energy in the main and auxiliary meters to remotely monitor the operating error of the gate energy meter. The operating error of the gate energy meter is decomposed by the consistency of the error of the current transformer under the main and auxiliary meters. The method can monitor the operating error of the gate energy meter without the addition of additional standard devices, and can achieve full coverage of the gate where the main and auxiliary energy meters are installed. It combines periodic inspection with remote monitoring, promotes the transformation of periodic inspection to condition inspection, improves the pertinence and timeliness of on-site inspection, and reduces the personnel and equipment investment for on-site inspection, thereby improving quality and efficiency. Attached Figure Description

[0022] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0023] Figure 1 This is a flowchart illustrating a remote monitoring method for the operating error of a gate energy meter according to a preferred embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the structure of a remote monitoring system for the operating error of a gate energy meter according to a preferred embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of the structure of an electronic device according to a preferred embodiment of the present invention. Detailed Implementation

[0026] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0027] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0028] Exemplary methods

[0029] Figure 1 This is a flowchart illustrating a remote monitoring method for the operating error of a gated energy meter according to a preferred embodiment of the present invention. Figure 1 As shown, the remote monitoring method for the operating error of the gate electricity meter in this preferred embodiment starts from step 101.

[0030] In step 101, the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter of the line metering point are obtained. The gate energy meter includes the main meter and the auxiliary meter of the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point.

[0031] In this preferred embodiment, all line metering points with relevant metering stations are considered as the research object. Based on the daily cumulative energy of the main and auxiliary meters at all line metering points, and grounded in the energy conservation of the bus and the energy conservation of the main and auxiliary meters, the operating status of the relevant metering station at each line metering point is determined. Specifically, the daily cumulative energy of the main meter at each line metering point is the difference between the positive and negative daily cumulative energy of the main meter, and the daily cumulative energy of the auxiliary meter is the difference between the positive and negative daily cumulative energy of the auxiliary meter. Assuming there are I incoming line metering points and J outgoing line metering points, there are corresponding I+J relevant metering stations. The conversion relationship between the metering error ε and the converted metering error β for each line metering point is given by the following formula:

[0032]

[0033] The reasoning process for determining the metering point error model based on the conservation equation of the bus electrical energy in this preferred embodiment is as follows:

[0034] Based on the conservation equation established for the electric energy of the bus, we have: W 1进 *(1-β 1进 )+…+W i进 *(1-β i进 )+…+W I进 *(1-β I进 )

[0035] =W 1出 *(1-β 1出 )+…+W j出 *(1-β j出)+…+W J出 *(1-β J出 )

[0036] In the formula, 1≤i≤I, 1≤j≤J, J is the total number of outgoing metering points, and W i进 and β i进 These are the daily cumulative energy consumption of the meter at the i-th incoming line metering point and the corresponding error conversion value of the main / auxiliary metering point, W. j出 and β j出 These are the daily cumulative energy of the meter at the j-th outgoing metering point and the corresponding error conversion value of the main / auxiliary metering point;

[0037] Transforming the above equation, we get:

[0038]

[0039] According to the above formula, let

[0040]

[0041] X = [-W] 1进 … -W i进 … -W I进 W 1出 … W j出 … W J出 ]

[0042]

[0043] Then there is

[0044] X*β=Y

[0045] However, due to the high collinearity of matrix X, the equation X*β=Y obtained based on the conservation of bus electrical energy cannot be solved directly. Therefore, it is necessary to introduce the ridge regression equation to establish the metering point error model. Thus, the expression of the metering point error model established in this preferred embodiment is as follows:

[0046] β(k)=(X T X+kI)- 1 X T Y

[0047] In the formula, k is the ridge parameter, k > 0, and I is the identity matrix.

[0048] Similarly, the reasoning process for establishing the energy meter error model based on the energy conservation of the energy meter in this preferred embodiment is as follows:

[0049] Based on the energy conservation principle of the electricity meters at each metering point of the line, the following equation can be obtained:

[0050] W 主 e副 -W 副 e 主 ≈W 副 -W 主 +W 副截断 -W 主截断

[0051] In the formula, e 主 e 副 W 主 and W 副 These represent the main meter error, auxiliary meter error, daily cumulative energy consumption of the main meter, and daily cumulative energy consumption of the auxiliary meter for each metering point on the line.

[0052] In this preferred embodiment, there is also the difference W between the main and auxiliary energy meters at each line metering point. 主副差 The calculation formula is as follows:

[0053] W 主副差 ≈W 副 -W 主 +W 副截断 -W 主截断

[0054] Therefore, for each metering point's energy meter, the following conservation equation can be established:

[0055] e 主 +e 互 =ε 主

[0056] e 副 +e 互 =ε 副

[0057] W 主 e 副 -W 副 e 主 =W 主副差

[0058] In the formula, e 互 , ε 主 , ε 副 These are the instrument transformer errors at each line metering point, the main metering point errors, and the secondary metering point errors, respectively.

[0059] Based on the above three conservation equations, we can obtain:

[0060] A*e=B

[0061] in,

[0062]

[0063] Similar to establishing a metering point error model, this preferred embodiment establishes an energy meter error model based on the equation A*e=B by introducing a ridge regression equation. Therefore, the expression for the energy meter error model established in this preferred embodiment is:

[0064] e(k)=(A T A+kI) -1 A T B

[0065] In the formula, k is the ridge parameter, k > 0, and I is the identity matrix.

[0066] In step 102, the energy difference between the main and auxiliary meters at each line metering point is calculated based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point.

[0067] Preferably, the calculation of the energy difference between the main and auxiliary meters at each line metering point, based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter, is performed using the following formula:

[0068] W 主副差 =W 副 -W 主 +W 副截断 -W 主截断

[0069] In the formula, W 主副差 W 副 W 主 W 副截断 and W 主截断 These represent the energy difference between the main and auxiliary meters at any given line metering point, the daily cumulative energy of the auxiliary meter, the daily cumulative energy of the main meter, the energy cut-off of the auxiliary meter, and the energy cut-off of the main meter. The energy cut-off for each meter at each point is determined based on the decimal point multiple of that meter, and its calculation formula is as follows:

[0070] W 截断 =10 -(电能表小数位数) *rand(0,1).

[0071] In step 103, based on the pre-established metering point error model, the main metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the main meters of all line metering points, and the secondary metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the secondary meters of all line metering points.

[0072] Preferably, the step of calculating the main metering point error conversion value of all line metering points based on the pre-established metering point error model, according to the daily cumulative energy of the main meters of all line metering points, and calculating the secondary metering point error conversion value of all line metering points based on the daily cumulative energy of the secondary meters of all line metering points, includes:

[0073] A ridge regression equation is introduced to establish a measurement point error model, wherein the expression of the measurement point error model is:

[0074] β(k)=(X T X+kI) -1 X T Y

[0075]

[0076] X = [-W] 1进 … -W i进 … -W I进 W 1出 … W j出 … W J出 ]

[0077]

[0078] In the formula, k>0, k is the ridge parameter, I is the identity matrix, and X T It is the transpose of matrix X, 1≤i≤I, where I is the total number of incoming line metering points, 1≤j≤J, where J is the total number of outgoing line metering points, where W i进 and W j出 β represents the daily cumulative energy consumption of the main meters at the incoming and outgoing metering points, respectively. j进 and β j出 These are the main metering point error conversion values ​​for the i-th incoming metering point and the j-th outgoing metering point, respectively. The elements of matrix β(k) are the main metering point error conversion values ​​for all line metering points when matrix β takes the value k. When W 进 and W 出 β represents the cumulative daily electricity consumption of the secondary meters at the i-th incoming metering point and the j-th outgoing metering point, respectively. i进 and β j出 These are the converted error values ​​of the secondary metering points of the i-th incoming metering point and the j-th outgoing metering point, respectively. Matrix β(k) is the converted error value of the secondary metering points of all line metering points when matrix β takes the value k.

[0079] Based on the aforementioned measurement point error model, a first L-curve is obtained by curve fitting using the L-curve method. The expression for the first curvature model of the first L-curve is:

[0080]

[0081] ρ1(k)=||β(k)||

[0082] η1(k)=||Xβ(k)-Y||

[0083] In the formula, ρ1(k) and η1(k) are the second norms of β(k) and Xβ(k)-Y, respectively; ρ′1(k) and η′1(k) are the first derivatives of ρ1(k) and η1(k), respectively; ρ″1(k) and v″1(k) are the second derivatives of ρ1(k) and η1(k), respectively; and ζ1(k) is the first curvature of the first L-curve.

[0084] Based on the daily cumulative electricity of the main meters of all line metering points, the value of the ridge parameter k0 when the curvature value is the maximum is determined according to the first curvature model, and the value of k0 is substituted into the metering point error model to calculate the main metering point error conversion value of all line metering points.

[0085] Based on the cumulative daily electricity consumption of all line metering points, the value of the ridge parameter k1 when the curvature value is maximum is determined according to the first curvature model, and the value of k1 is substituted into the metering point error model to calculate the converted value of the sub-metering point error of all line metering points.

[0086] In step 104, based on the pre-established metering point error conversion formula, the main metering point error of all line metering points is calculated according to the main metering point error conversion value of all line metering points, and the secondary metering point error of all line metering points is calculated according to the secondary metering point error conversion value of all line metering points.

[0087] Preferably, the step of calculating the main metering point error of all line metering points based on the pre-established metering point error conversion formula, and calculating the secondary metering point error of all line metering points based on the secondary metering point error conversion values ​​of all line metering points, is as follows:

[0088]

[0089] In the formula, when β is the converted value of the main metering point error of the line metering point, ε is the corresponding main metering point error of the line metering point; when β is the converted value of the secondary metering point error of the line metering point, ε is the corresponding secondary metering point error of the line metering point.

[0090] In step 105, based on the pre-established energy meter error model, the operating error of the gate energy meter at each line metering point is calculated according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters.

[0091] Preferably, based on the pre-established energy meter error model, the gate energy meter error for each line metering point is calculated according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters, wherein:

[0092] A ridge regression equation is introduced to establish an error model for the electricity meter at each line metering point. The expression for the electricity meter error model is as follows:

[0093] e(k)=(A T A+kI) -1 A T B

[0094]

[0095] In the formula, k > 0, k is the ridge parameter, I is the identity matrix, and A T It is the transpose of matrix A, where the elements e in matrix e are... 主 e 副 e 互 The element W in matrix A 副 W 主 and the element ε in matrix B 主 , ε 副 and W 主副差 These are the main meter error, secondary meter error, transformer error, daily cumulative energy of the secondary meter, daily cumulative energy of the main meter, main meter error, secondary meter error, and main and secondary meter energy difference for each line metering point. The elements of matrix e(k) are the main meter error, secondary meter error, and transformer error for a single line metering point when matrix e takes the value k.

[0096] Based on the aforementioned energy meter error model, a second L-curve is obtained by curve fitting using the L-curve method. The expression for the second curvature model of the second L-curve is as follows:

[0097]

[0098] ρ2(k)=||e(k)||

[0099] η2(k)=||Ae(k)-B||

[0100] In the formula, ρ2(k) and η2(k) are the L2 norms of e(k) and Ae(k)-B, respectively; ρ′2(k) and η′2(k) are the first derivatives of ρ2(k) and η2(k), respectively; ρ″2(k) and η″2(k) are the second derivatives of ρ2(k) and η2(k), respectively; and ζ2(k) is the second curvature of the second L-curve.

[0101] Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k2 when the curvature value is maximized is determined according to the second curvature model.

[0102] Based on the given value k2 and the energy meter error model, matrix C is constructed, where the expression for matrix C is:

[0103] C=η2(k2)(A T A+e(k2)I) -1

[0104] Based on matrix C, a generalized ridge regression equation is introduced to establish an energy meter operation error model for each line metering point. The expression for this energy meter operation error model is as follows:

[0105] e R (k)=(A T A+kR)- 1 A T S

[0106]

[0107] R = diagC- 1

[0108] In the formula, matrix e R element e in 主R e 副R and e 互R These represent the main meter operating error, the secondary meter operating error, and the current transformer operating error corresponding to a single line metering point, respectively, matrix e. R The elements in (k) are matrix e R When taking the value of k, the operating error of the main meter, the operating error of the auxiliary meter, and the operating error of the current transformer are corresponding to a single line metering point; R is a matrix C -1 a diagonal matrix;

[0109] Based on the aforementioned energy meter error operation model, a third L-curve is obtained by curve fitting using the L-curve method. The expression for the third curvature model of the third L-curve is as follows:

[0110]

[0111] ρ3(k)=||e R (k)||

[0112] η3(k)=||Ae R (k)-B||

[0113] In the formula, ρ3(k) and η3(k) are respectively e R (k) and Ae R The second norm of (k)-B, ρ′3(k) and η′3(k) are the first derivatives of ρ3(k) and η3(k) respectively, ρ″3(k) and η″3(k) are the second derivatives of ρ3(k) and η3(k) respectively, and ζ3(k) is the third curvature of the third L curve;

[0114] Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k3 when the curvature value is maximum is determined according to the third curvature model. The value of k3 is then substituted into the energy meter operation error model to calculate the operating error of the primary meter, the operating error of the secondary meter, and the operating error of the transformer for each line metering point. The operating error of the energy meter at each line metering point includes the operating error of the primary meter and the operating error of the secondary meter.

[0115] In step 106, the operating status of the energy meter at each line metering point is determined based on the operating error and accuracy class of the energy meter at each line metering point.

[0116] Preferably, the operating status of the energy meter at each line metering point is determined based on the operating error and accuracy class of the energy meter at each line metering point, including:

[0117] When the absolute value of the operating error of the meter at a line metering point is less than or equal to the error limit corresponding to its accuracy class, the operating status of the meter is determined to be normal.

[0118] When the operating error of a meter at a line metering point is less than x times the error limit corresponding to its accuracy class and greater than the error limit corresponding to its accuracy class, the operating status of the meter is determined to be a warning state, where x is a positive number.

[0119] When the absolute value of the operating error of the meter at a line metering point is greater than or equal to x times the error limit corresponding to its accuracy class, the operating status of the meter is determined to be abnormal.

[0120] The remote monitoring method for the operating error of the gate energy meter described in this preferred embodiment is based on the conservation of bus energy and the conservation of energy of the main and auxiliary meters. It remotely monitors the operating error of the gate energy meter by decomposing the error consistency of the current transformers under the main and auxiliary meters. It can monitor the operating error of the gate energy meter without adding additional standard devices, and can achieve full coverage of the gate where the main and auxiliary energy meters are installed. It combines periodic inspection with remote monitoring, promotes the transformation of periodic inspection to condition inspection, improves the pertinence and timeliness of on-site inspection, and can reduce the personnel and equipment investment for on-site inspection, thereby improving quality and efficiency.

[0121] Exemplary System

[0122] Figure 2 This is a schematic diagram of the structure of a remote monitoring system for the operating error of a gated energy meter according to a preferred embodiment of the present invention. Figure 2 As shown, the remote monitoring system for the operating error of the energy meter at the junction of the two terminals according to this preferred embodiment includes:

[0123] The data acquisition module 201 is used to acquire the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at the line metering point where the main and auxiliary meters are installed. The energy meter at the gateway includes the main meter and the auxiliary meter at the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point.

[0124] The first calculation module 202 is used to calculate the difference in energy between the main and auxiliary meters at each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point.

[0125] The second calculation module 203 is used to calculate the main metering point error conversion value of all line metering points based on the pre-established metering point error model and the daily cumulative electricity energy of the main meter of all line metering points, and to calculate the secondary metering point error conversion value of all line metering points based on the daily cumulative electricity energy of the secondary meter of all line metering points.

[0126] The third calculation module 204 is used to calculate the main metering point error of all line metering points based on the pre-established metering point error conversion formula and the main metering point error conversion value of all line metering points, and to calculate the secondary metering point error of all line metering points based on the secondary metering point error conversion value of all line metering points.

[0127] The fourth calculation module 205 is used to calculate the operating error of the gate energy meter at each line metering point based on the pre-established energy meter error model, according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters.

[0128] The result output module 206 is used to determine the operating status of the energy meter at each line metering point based on the operating error and accuracy level of the energy meter at each line metering point.

[0129] Preferably, the first calculation module 202 calculates the energy difference between the main and auxiliary meters at each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point. The calculation formula is as follows:

[0130] W 主副差 =W 副 -W 主 +W 副截断 -W 主截断

[0131] In the formula, W 主副差 W 副 W 主 W 副截断 and W 主截断These represent the energy difference between the main and auxiliary meters at any given line metering point, the daily cumulative energy of the auxiliary meter, the daily cumulative energy of the main meter, the energy cut-off of the auxiliary meter, and the energy cut-off of the main meter. The energy cut-off for each meter at each point is determined based on the decimal point multiple of that meter, and its calculation formula is as follows:

[0132] W 截断 =10 -(电能表小数位数)*rand(0,1) .

[0133] Preferably, the second calculation module 203, based on a pre-established metering point error model, calculates the main metering point error conversion value for all line metering points according to the daily cumulative energy of the main meters of all line metering points, and calculates the secondary metering point error conversion value for all line metering points according to the daily cumulative energy of the secondary meters of all line metering points, including:

[0134] A ridge regression equation is introduced to establish a measurement point error model, wherein the expression of the measurement point error model is:

[0135] β(k)=(X T X+kI) -1 X T Y

[0136]

[0137] X = [-W] 1进 … -W i进 … -W I进 W 1出 … W j出 … W J出 ]

[0138]

[0139] In the formula, k>0, k is the ridge parameter, I is the identity matrix, and X T It is the transpose of matrix X, 1≤i≤I, where I is the total number of incoming line metering points, 1≤j≤J, where J is the total number of outgoing line metering points, where W i进 and W j出 β represents the daily cumulative energy consumption of the main meters at the incoming and outgoing metering points, respectively. j进 and β j出 These are the main metering point error conversion values ​​for the i-th incoming metering point and the j-th outgoing metering point, respectively. The elements of matrix β(k) are the main metering point error conversion values ​​for all line metering points when matrix β takes the value k. When W 进 and W 出 β represents the cumulative daily electricity consumption of the secondary meters at the i-th incoming metering point and the j-th outgoing metering point, respectively. i进 and β j出These are the converted error values ​​of the secondary metering points of the i-th incoming metering point and the j-th outgoing metering point, respectively. Matrix β(k) is the converted error value of the secondary metering points of all line metering points when matrix β takes the value k.

[0140] Based on the aforementioned measurement point error model, a first L-curve is obtained by curve fitting using the L-curve method. The expression for the first curvature model of the first L-curve is:

[0141]

[0142] ρ1(k)=||β(k)||

[0143] η1(k)=||Xβ(k)-Y||

[0144] In the formula, ρ1(k) and η1(k) are the L2 norms of β(k) and Xβ(k)-Y, respectively; ρ′1(k) and η′1(k) are the first derivatives of ρ1(k) and η1(k), respectively; ρ″1(k) and η″1(k) are the second derivatives of ρ1(k) and η1(k), respectively; and ζ1(k) is the first curvature of the first L curve.

[0145] Based on the daily cumulative electricity of the main meters of all line metering points, the value of the ridge parameter k0 when the curvature value is the maximum is determined according to the first curvature model, and the value of k0 is substituted into the metering point error model to calculate the main metering point error conversion value of all line metering points.

[0146] Based on the cumulative daily electricity consumption of all line metering points, the value of the ridge parameter k1 when the curvature value is maximum is determined according to the first curvature model, and the value of k1 is substituted into the metering point error model to calculate the converted value of the sub-metering point error of all line metering points.

[0147] Preferably, the third calculation module 204 calculates the main metering point error of all line metering points based on a pre-established metering point error conversion formula, according to the main metering point error conversion value of all line metering points, and calculates the secondary metering point error of all line metering points based on the secondary metering point error conversion value of all line metering points. The calculation formula is as follows:

[0148]

[0149] In the formula, when β is the converted value of the main metering point error of the line metering point, ε is the corresponding main metering point error of the line metering point; when β is the converted value of the secondary metering point error of the line metering point, ε is the corresponding secondary metering point error of the line metering point.

[0150] Preferably, the fourth calculation module 205, based on a pre-established energy meter error model, calculates the gate energy meter error for each line metering point according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters, wherein:

[0151] A ridge regression equation is introduced to establish an error model for the electricity meter at each line metering point. The expression for the electricity meter error model is as follows:

[0152] e(k)=(A T A+kI) -1 A T B

[0153]

[0154]

[0155] In the formula, k > 0, k is the ridge parameter, I is the identity matrix, and A T It is the transpose of matrix A, where the elements e in matrix e are... 主 e 副 e 互 The element W in matrix A 副 W 主 and the element ε in matrix B 主 , ε 副 and W 主副差 These are the main meter error, secondary meter error, transformer error, daily cumulative energy of the secondary meter, daily cumulative energy of the main meter, main meter error, secondary meter error, and main and secondary meter energy difference for each line metering point. The elements of matrix e(k) are the main meter error, secondary meter error, and transformer error for a single line metering point when matrix e takes the value k.

[0156] Based on the aforementioned energy meter error model, a second L-curve is obtained by curve fitting using the L-curve method. The expression for the second curvature model of the second L-curve is as follows:

[0157]

[0158] ρ2(k)=||e(k)||

[0159] η2(k)=||Ae(k)-B||

[0160] In the formula, ρ2(k) and η2(k) are the L2 norms of e(k) and Ae(k)-B, respectively; ρ′2(k) and η′2(k) are the first derivatives of ρ2(k) and η2(k), respectively; ρ″2(k) and η″2(k) are the second derivatives of ρ2(k) and η2(k), respectively; and ζ2(k) is the second curvature of the second L curve.

[0161] Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k2 when the curvature value is maximized is determined according to the second curvature model.

[0162] Based on the given value k2 and the energy meter error model, matrix C is constructed, where the expression for matrix C is:

[0163] C=η2(k2)(A T A+e(k2)I) -1

[0164] Based on matrix C, a generalized ridge regression equation is introduced to establish an energy meter operation error model for each line metering point. The expression for this energy meter operation error model is as follows:

[0165] e R (k)=(A T A+kR)- 1 A T S

[0166]

[0167] R = diagC- 1

[0168] In the formula, matrix e R element e in 主R e 副R and e 互R These represent the main meter operating error, the secondary meter operating error, and the current transformer operating error corresponding to a single line metering point, respectively, matrix e. R The elements in (k) are matrix e R When taking the value of k, the operating error of the main meter, the operating error of the auxiliary meter, and the operating error of the current transformer are corresponding to a single line metering point; R is a matrix C -1 a diagonal matrix;

[0169] Based on the aforementioned energy meter error operation model, a third L-curve is obtained by curve fitting using the L-curve method. The expression for the third curvature model of the third L-curve is as follows:

[0170]

[0171] ρ3(k)=||e R (k)||

[0172] η3(k)=||Ae R (k)-B||

[0173] In the formula, ρ3(k) and η3(k) are respectively eR (k) and Ae R The second norm of (k)-B, ρ′3(k) and η′3(k) are the first derivatives of ρ3(k) and η3(k) respectively, ρ″3(k) and η″3(k) are the second derivatives of ρ3(k) and η3(k) respectively, and ζ3(k) is the third curvature of the third L curve;

[0174] Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k3 when the curvature value is maximum is determined according to the third curvature model. The value of k3 is then substituted into the energy meter operation error model to calculate the operating error of the primary meter, the operating error of the secondary meter, and the operating error of the transformer for each line metering point. The operating error of the energy meter at each line metering point includes the operating error of the primary meter and the operating error of the secondary meter.

[0175] Preferably, the result output module 206 determines the operating status of the energy meter at each line metering point based on the operating error and accuracy level of the energy meter at each line metering point, including:

[0176] When the absolute value of the operating error of the meter at a line metering point is less than or equal to the error limit corresponding to its accuracy class, the operating status of the meter is determined to be normal.

[0177] When the operating error of a meter at a line metering point is less than x times the error limit corresponding to its accuracy class and greater than the error limit corresponding to its accuracy class, the operating status of the meter is determined to be a warning state, where x is a positive number.

[0178] When the absolute value of the operating error of the meter at a line metering point is greater than or equal to x times the error limit corresponding to its accuracy class, the operating status of the meter is determined to be abnormal.

[0179] The remote monitoring device for the operating error of the energy meter at the junction of the line, as described in this preferred embodiment, acquires the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point equipped with main and auxiliary meters. Then, by calculating the energy difference between the main and auxiliary meters at each line metering point, and based on a pre-established metering point error model, metering point error conversion formula, and energy meter error model, it calculates the operating error of the energy meter at each line metering point. The steps for determining the operating status of the energy meter at each line metering point based on its operating error and accuracy level are the same as those of the remote monitoring method for the operating error of the energy meter at the junction of the line meter described in this invention, and achieve the same technical effect. Therefore, they will not be repeated here.

[0180] Exemplary electronic devices

[0181] Figure 3 This is a schematic diagram of an electronic device according to a preferred embodiment of the present invention. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them. The standalone device may communicate with the first device and the second device to receive the collected input signals from them. Figure 3 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Figure 3 As shown, the electronic device includes one or more processors 301 and memory 302.

[0182] The processor 301 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0183] The memory 302 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 301 may execute the program instructions to implement the energy consumption anomaly diagnosis method based on enterprise energy consumption space of the various embodiments disclosed above, and / or other desired functions. In one example, the electronic device may also include an input device 303 and an output device 304, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0184] In addition, the input device 303 may also include, for example, a keyboard, a mouse, etc.

[0185] The output device 304 can output various information to the outside. The output device 304 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0186] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0187] Exemplary computer program products and computer-readable storage media

[0188] In addition to the methods and devices described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the remote monitoring method for operating errors of a gated energy meter according to various embodiments of this disclosure as described in the "Exemplary Methods" section of this specification.

[0189] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0190] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions that, when executed by a processor, cause the processor to perform the steps in the remote monitoring method for the operating error of a gated energy meter according to various embodiments of this disclosure as described in the "Exemplary Methods" section above.

[0191] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0192] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0193] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0194] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0195] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0196] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps are decomposable and / or recombinable. Such decomposition and / or recombination should be considered equivalent to the present disclosure. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0197] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for remote monitoring of operational errors of a gated energy meter, characterized in that, The method includes: The daily cumulative energy consumption of the main meter and the daily cumulative energy consumption of the auxiliary meter are obtained at the line metering point where the main and auxiliary meters are installed. The energy meter at the gateway includes the main meter and the auxiliary meter at the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point. Calculate the energy difference between the main and auxiliary meters at each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at each line metering point; Based on the pre-established metering point error model, the main metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the main meter of all line metering points, and the secondary metering point error conversion value of all line metering points is calculated according to the daily cumulative electricity of the secondary meter of all line metering points. Based on the pre-established metering point error conversion formula, the main metering point error of all line metering points is calculated according to the main metering point error conversion value of all line metering points, and the secondary metering point error of all line metering points is calculated according to the secondary metering point error conversion value of all line metering points. Based on the pre-established energy meter error model, the operating error of the gate energy meter at each line metering point is calculated according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters. Based on the operating error and accuracy class of the energy meter at each line metering point, determine the operating status of the energy meter at each line metering point.

2. The method according to claim 1, characterized in that, The method for calculating the energy difference between the main and auxiliary meters at each line metering point is as follows: (The formula is not provided in the original text.) IN 主副差 =In 副 -IN 主 +W 副截断 -IN 主截断 In the formula, W 主副差 W 副 W 主 W 副截断 and W 主截断 These represent the energy difference between the main and auxiliary meters at any given line metering point, the daily cumulative energy of the auxiliary meter, the daily cumulative energy of the main meter, the energy cut-off of the auxiliary meter, and the energy cut-off of the main meter. The energy cut-off for each meter at each point is determined based on the decimal point multiple of that meter, and its calculation formula is as follows: W 截断 =10 -(电能表小数位数) *rand(0,1)。 3. The method according to claim 1, characterized in that, The method, based on a pre-established metering point error model, calculates the main metering point error conversion value for all line metering points according to the daily cumulative energy of the main meters for all line metering points, and calculates the secondary metering point error conversion value for all line metering points according to the daily cumulative energy of the secondary meters for all line metering points, including: A ridge regression equation is introduced to establish a measurement point error model, wherein the expression of the measurement point error model is: β(k)=(X T X+kI) -1 X T Y X=[-W 1进 …-W i进 …-W I进 W 1出 …W j出 …W J出 ] In the formula, k>0, k is the ridge parameter, I is the identity matrix, and X T It is the transpose of matrix X, 1≤i≤I, where I is the total number of incoming line metering points, 1≤j≤J, where J is the total number of outgoing line metering points, where W i进 and W j出 β represents the daily cumulative energy consumption of the main meters at the incoming and outgoing metering points, respectively. i进 and β j出 These are the main metering point error conversion values ​​for the i-th incoming metering point and the j-th outgoing metering point, respectively. The elements of matrix β(k) are the main metering point error conversion values ​​for all line metering points when matrix β takes the value k. When W i进 and W j出 β represents the cumulative daily electricity consumption of the secondary meters at the i-th incoming metering point and the j-th outgoing metering point, respectively. i进 and β j出 These are the converted error values ​​of the secondary metering points of the i-th incoming metering point and the j-th outgoing metering point, respectively. Matrix β(β) is the converted error value of the secondary metering points of all line metering points when matrix β takes the value k. Based on the aforementioned measurement point error model, a first L-curve is obtained by curve fitting using the L-curve method. The expression for the first curvature model of the first L-curve is: ρ1(k)=‖β(k)‖ η1(k)=‖Xβ(k)-Y‖ In the formula, k1(k) and η1(k) are the L2 norms of β(k) and Xβ(k)-Y, respectively; ρ′1(k) and η′1(k) are the first derivatives of ρ1(k) and η1(k), respectively; ρ″1(k) and η″1(k) are the second derivatives of ρ1(k) and η1(k), respectively; and ζ1(k) is the first curvature of the first L curve. Based on the daily cumulative electricity of the main meters of all line metering points, the value of the ridge parameter k0 when the curvature value is the maximum is determined according to the first curvature model, and the value of k0 is substituted into the metering point error model to calculate the main metering point error conversion value of all line metering points. Based on the cumulative daily electricity consumption of all line metering points, the value of the ridge parameter k1 when the curvature value is maximum is determined according to the first curvature model, and the value of k1 is substituted into the metering point error model to calculate the converted value of the sub-metering point error of all line metering points.

4. The method according to claim 1, characterized in that, The method, based on a pre-established metering point error conversion formula, calculates the main metering point error of all line metering points according to the main metering point error conversion value of all line metering points, and calculates the secondary metering point error of all line metering points according to the secondary metering point error conversion value of all line metering points. The calculation formula is as follows: In the formula, when β is the converted value of the main metering point error of the line metering point, ε is the corresponding main metering point error of the line metering point; when β is the converted value of the secondary metering point error of the line metering point, ε is the corresponding secondary metering point error of the line metering point.

5. The method according to claim 1, characterized in that, Based on the pre-established energy meter error model, the error of the gate energy meter at each line metering point is calculated according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters. Where: A ridge regression equation is introduced to establish an error model for the electricity meter at each line metering point. The expression for the electricity meter error model is as follows: e(k)=(A T A+kI) -1 A T B In the formula, k>0, k is the ridge parameter, I is the identity matrix, and A T It is the transpose of matrix A, where the elements e in matrix e are... 主 e 副 e 互 The element W in matrix A 副 W 主 and the element ε in matrix B 主 , ε 副 and W 主副差 These are the main meter error, secondary meter error, transformer error, daily cumulative energy of the secondary meter, daily cumulative energy of the main meter, main meter error, secondary meter error, and main and secondary meter energy difference for each line metering point. The elements of matrix e(k) are the main meter error, secondary meter error, and transformer error for a single line metering point when matrix e takes the value k. Based on the aforementioned energy meter error model, a second L-curve is obtained by curve fitting using the L-curve method. The expression for the second curvature model of the second L-curve is as follows: ρ2(k)=‖e(k)‖ η2(k)=‖Ae(k)-B‖ In the formula, ρ2(k) and η2(k) are the L2 norms of e(k) and Ae(k)-B, respectively; ρ′2(k) and η′2(k) are the first derivatives of ρ2(k) and η2(k), respectively; ρ″2(η) and η″2(k) are the second derivatives of ρ2(k) and η2(k), respectively; and ζ2(k) is the second curvature of the second L-curve. Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k2 when the curvature value is maximized is determined according to the second curvature model. Based on the given value k2 and the energy meter error model, matrix C is constructed, where the expression for matrix C is: C=η2(k2)(A T A+e(k2)I) -1 Based on matrix C, a generalized ridge regression equation is introduced to establish an energy meter operation error model for each line metering point. The expression for this energy meter operation error model is as follows: e R (k)=(A T A+kR) -1 AND T B R=diagC -1 In the formula, matrix e R element e in 主R e 副R and e 互R These represent the main meter operating error, the secondary meter operating error, and the current transformer operating error corresponding to a single line metering point, respectively, matrix e. R The elements in (k) are matrix e R When taking the value of k, the operating error of the main meter, the operating error of the auxiliary meter, and the operating error of the current transformer are corresponding to a single line metering point; R is a matrix C -1 a diagonal matrix; Based on the aforementioned energy meter error operation model, a third L-curve is obtained by curve fitting using the L-curve method. The expression for the third curvature model of the third L-curve is as follows: ρ3(k)=‖e R (k)‖ η3(k)=‖Ae R (k)-B‖ In the formula, ρ3(k) and η3(k) are respectively e R (k) and Ae R The second norm of (k)-B, ρ′3(k) and η′3(k) are the first derivatives of ρ3(k) and η3(k) respectively, ρ″3(k) and η″3(k) are the second derivatives of ρ3(k) and η3(k) respectively, and ζ3(k) is the third curvature of the third L curve; Based on the daily cumulative energy of the secondary meter, the daily cumulative energy of the primary meter, the error of the primary meter, the error of the secondary meter, and the energy difference between the primary and secondary meters for each line metering point, the value of the ridge parameter k3 when the curvature value is maximum is determined according to the third curvature model. The value of k3 is then substituted into the energy meter operation error model to calculate the operating error of the primary meter, the operating error of the secondary meter, and the operating error of the transformer for each line metering point. The operating error of the energy meter at each line metering point includes the operating error of the primary meter and the operating error of the secondary meter.

6. The method according to claim 1, characterized in that, Based on the operating error and accuracy class of the energy meters at each line metering point, determine the operating status of the energy meters at each line metering point, including: When the absolute value of the operating error of the meter at a line metering point is less than or equal to the error limit corresponding to its accuracy class, the operating status of the meter is determined to be normal. When the operating error of a meter at a line metering point is less than x times the error limit corresponding to its accuracy class and greater than the error limit corresponding to its accuracy class, the operating status of the meter is determined to be a warning state, where x is a positive number. When the absolute value of the operating error of the meter at a line metering point is greater than or equal to x times the error limit corresponding to its accuracy class, the operating status of the meter is determined to be abnormal.

7. A remote monitoring system for the operating error of a gate electricity meter, characterized in that, The system includes: The data acquisition module is used to acquire the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter at the line metering point where the main and auxiliary meters are installed. The energy meter at the gateway includes the main meter and the auxiliary meter at the line metering point, and the line metering point includes the incoming line metering point and the outgoing line metering point. The first calculation module is used to calculate the difference in energy between the main and auxiliary meters for each line metering point based on the daily cumulative energy of the main meter and the daily cumulative energy of the auxiliary meter for each line metering point. The second calculation module is used to calculate the main metering point error conversion value of all line metering points based on the pre-established metering point error model and the daily cumulative electricity energy of the main meters of all line metering points, and to calculate the secondary metering point error conversion value of all line metering points based on the daily cumulative electricity energy of the secondary meters of all line metering points. The third calculation module is used to calculate the main metering point error of all line metering points based on the pre-established metering point error conversion formula and the main metering point error conversion value of all line metering points, and to calculate the secondary metering point error of all line metering points based on the secondary metering point error conversion value of all line metering points. The fourth calculation module is used to calculate the operating error of the gate energy meter at each line metering point based on the pre-established energy meter error model, according to the main metering point error, the secondary metering point error, the daily cumulative energy of the main meter, the daily cumulative energy of the secondary meter, and the energy difference between the main and secondary meters. The results output module is used to determine the operating status of the energy meter at each line metering point based on the operating error and accuracy level of the energy meter at each line metering point.

8. The system according to claim 7, characterized in that, The result output module determines the operating status of the energy meter at each line metering point based on the operating error and accuracy level of the meter at each line metering point, including: When the absolute value of the operating error of the meter at a line metering point is less than or equal to the error limit corresponding to its accuracy class, the operating status of the meter is determined to be normal. When the operating error of a meter at a line metering point is less than x times the error limit corresponding to its accuracy class and greater than the error limit corresponding to its accuracy class, the operating status of the meter is determined to be a warning state, where x is a positive number. When the absolute value of the operating error of the meter at a line metering point is greater than or equal to x times the error limit corresponding to its accuracy class, the operating status of the meter is determined to be abnormal.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for executing the method described in any one of claims 1 to 6.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 6.

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