CN-121978611-A - Dynamic metering calibration method and system for electric energy meter

CN121978611ACN 121978611 ACN121978611 ACN 121978611ACN-121978611-A

Abstract

The invention provides a dynamic metering calibration method and a system of an electric energy meter, and relates to the technical field of electric energy meter calibration, wherein the method comprises the steps of collecting multi-source metering data of the electric energy meter, constructing an error propagation topology network according to error influence relation of the multi-source metering data of the electric energy meter, quantifying errors of all nodes in a node set and obtaining an error propagation energy field; an error propagation energy field model is built, an error propagation energy evolution sequence based on time evolution is generated, an energy evolution feature vector is extracted, a current evolution state is identified, a calibration trigger time window is generated if the current evolution state is detected to be in a critical evolution state, and metering calibration is performed on the electric energy meter. The technical problem that in the prior art, the electric energy meter is calibrated by adopting a fixed period or a fixed time node, so that the dynamic change of errors is difficult to reflect in real time is solved. The technical effects of dynamically determining the calibration time node and improving the metering precision and the resource utilization efficiency are achieved.

Inventors

ZHANG YAN
WANG HANGWEI
HOU GUANG
DU YONGBO
YANG XIAOQIN
LAN BAOXIA

Assignees

航天亮丽电气有限责任公司

Dates

Publication Date: 20260505
Application Date: 20260320

Claims (10)

1. The dynamic metering calibration method for the electric energy meter is characterized by comprising the following steps of: Collecting multisource metering data of the electric energy meter through an internal sampling module of the electric energy meter; constructing an error propagation topology network according to the error influence relation of the multi-source metering data of the electric energy meter, and quantizing the error of each node in the node set based on the error propagation topology network to obtain an error propagation energy field; Constructing an error propagation energy field model based on the error propagation energy field, generating an error propagation energy evolution sequence based on time evolution by using the error propagation energy field model, and extracting an energy evolution feature vector of the error propagation energy evolution sequence; And identifying the current evolution state according to the energy evolution feature vector, generating a calibration trigger time window if the current evolution state is detected to be in the critical evolution state, and executing metering calibration on the electric energy meter in the calibration trigger time window.
2. The method of dynamic metering calibration of an electric energy meter of claim 1, wherein the current evolution state is identified from the energy evolution feature vector, the method further comprising: the energy evolution feature vector comprises an energy growth rate, an energy growth acceleration and an energy fluctuation amplitude; Constructing an evolution state judging function by taking the energy growth rate, the energy growth acceleration and the energy fluctuation amplitude as input variables, wherein the evolution state judging function comprises a plurality of defined evolution states and a plurality of energy evolution characteristic vector sample groups corresponding to the evolution states; Wherein the plurality of evolution states includes an energy evolution steady state, an energy slow growth state, an energy fast growth state, and an energy abrupt change state; And inputting the energy evolution feature vector into the evolution state judgment function to perform feature vector similarity calculation, and outputting the current evolution state based on a feature vector similarity calculation result.
3. The method of dynamic metering calibration of an electric energy meter of claim 2, wherein the calibration trigger time window is generated if the current evolution state is detected to be in a critical evolution state, the critical evolution state including an energy fast-growth state and an energy abrupt change state of the plurality of evolution states.
4. The method for dynamically metering and calibrating an electric energy meter according to claim 1, wherein the error of each node in the node set is quantized based on the error propagation topology network, and an error propagation energy field is obtained, the method comprising: reading data sources of all nodes and real-time metering data from the error propagation topology network; calculating an error data set of each node based on the real-time metering data and the theoretical metering data; Analyzing the propagation weight of the error propagation topology network to obtain an error propagation weight matrix; Calculating a set of node error propagation energies based on the error propagation weight matrix and the set of error data; And mapping the node error propagation energy set into the error propagation topological network to acquire an error propagation energy field.
5. The method of dynamic meter calibration of claim 1, wherein constructing an error propagation energy field model based on the error propagation energy field comprises: Defining a time evolution parameter, and introducing an initial decay function to perform space diffusion evolution based on the time evolution parameter on the error propagation energy field to obtain an error propagation diffusion evolution energy field; Comparing the error propagation diffusion evolution energy field with the error propagation diffusion theory energy field, and performing iterative optimization on the attenuation coefficient of the attenuation function according to the evolution accuracy obtained by the comparison until an optimized attenuation function with the evolution accuracy reaching a preset threshold value is obtained; And an error propagation energy field model constructed based on the optimized attenuation function is based on an error propagation energy evolution sequence of time evolution.
6. The method of dynamic metering calibration of an electric energy meter of claim 1, wherein the calibration trigger time window is generated if the current evolution state is detected to be in a critical evolution state, the method further comprising: setting a calibration time tolerance window; and expanding the time nodes in the critical evolution state based on the calibration time tolerance window to obtain a calibration trigger time window.
7. The method for dynamically metering calibration of an electrical energy meter of claim 6, wherein a calibration time tolerance window is set, the method comprising: Calculating the error evolution change rate of each data type according to the error evolution feature vector; based on the error evolution change rate, acquiring calibration sensitivity indexes of each data type; and acquiring the current data source type corresponding to the calibration request, and setting the size of the calibration time tolerance window according to the calibration sensitivity index inverse proportion corresponding to the current data source type.
8. The method for dynamically metering and calibrating an electric energy meter according to claim 1, wherein an error propagation energy evolution sequence based on time evolution is generated by using the error propagation energy field model, and an evolution time window of the time evolution is larger than an initial calibration time window; The initial calibration time window is an initial calibration time window which can be used for executing metering calibration by the electric energy meter.
9. The method of dynamic meter calibration of claim 8, wherein the calibration trigger time window is a sub-window of the initial calibration time window.
10. An electric energy meter dynamic measurement calibration system, characterized by the steps for implementing the electric energy meter dynamic measurement calibration method according to any one of claims 1 to 9, comprising: the data acquisition component is used for acquiring multisource metering data of the electric energy meter through the internal sampling module of the electric energy meter; The error quantization component is used for constructing an error propagation topology network according to the error influence relation of the multi-source metering data of the electric energy meter, and quantizing the error of each node in the node set based on the error propagation topology network to obtain an error propagation energy field; The evolution sequence generation component is used for constructing an error propagation energy field model based on the error propagation energy field, generating an error propagation energy evolution sequence based on time evolution by using the error propagation energy field model, and extracting an energy evolution feature vector of the error propagation energy evolution sequence; And the metering calibration component is used for identifying the current evolution state according to the energy evolution characteristic vector, generating a calibration trigger time window if the current evolution state is detected to be in the critical evolution state, and executing metering calibration on the electric energy meter in the calibration trigger time window.

Description

Dynamic metering calibration method and system for electric energy meter Technical Field The invention relates to the technical field of electric energy meter calibration, in particular to a dynamic metering calibration method and a dynamic metering calibration system for an electric energy meter. Background The electric energy meter is used as key metering equipment in an electric power system, the metering accuracy of the electric energy meter directly influences the accuracy of electric energy metering, and in the prior art, the metering calibration of the electric energy meter usually adopts a periodic calibration or fixed time node calibration mode, namely, the electric energy meter is calibrated according to a preset time interval or fixed time point. However, in the actual operation process, the metering error of the electric energy meter is affected by various factors including voltage sampling deviation, current sampling drift, load fluctuation, electromagnetic interference and the like, the influence of different factors on the error is obviously different, and the change rate and the evolution rule of the error are obviously different in different operation stages. Because the unified time node is adopted for calibration in the prior art, the dynamic change process of the error of the electric energy meter is difficult to accurately reflect. When the error is still in a stable stage, calibration is performed, which may result in waste of calibration resources, and when the error enters a rapid evolution stage and is not calibrated in time, larger metering deviation may be caused, and the metering precision of the electric energy meter and the operation safety of the electric power system are affected. Based on the above, an electric energy meter dynamic metering calibration method capable of comprehensively analyzing the error propagation relation and the error evolution state of multi-source data and dynamically determining the calibration time node is needed, so that the real-time monitoring and intelligent calibration of errors are realized, and the metering precision and reliability of the electric energy meter are improved. In summary, the prior art has the technical problems that the electric energy meter is calibrated by adopting a fixed period or a fixed time node, so that the dynamic change of errors is difficult to reflect in real time, and the calibration resource waste or the measurement deviation is increased. Disclosure of Invention The application aims to provide a dynamic metering calibration method and a dynamic metering calibration system for an electric energy meter, which are used for solving the technical problems that in the prior art, the electric energy meter is calibrated by adopting a fixed period or a fixed time node, so that the dynamic change of errors is difficult to reflect in real time, and the calibration resource waste or the metering deviation is increased. In view of the above problems, the application provides a method and a system for calibrating dynamic metering of an electric energy meter. The application provides a dynamic metering calibration method of an electric energy meter, which comprises the steps of collecting multi-source metering data of the electric energy meter through an internal sampling module of the electric energy meter, constructing an error propagation topological network according to an error influence relation of the multi-source metering data of the electric energy meter, quantifying errors of all nodes in a node set based on the error propagation topological network to obtain an error propagation energy field, constructing an error propagation energy field model based on the error propagation energy field, generating an error propagation energy evolution sequence based on time evolution through the error propagation energy field model, extracting an energy evolution feature vector of the error propagation energy sequence, identifying a current evolution state according to the energy evolution feature vector, generating a calibration trigger time window if the current evolution state is detected to be in a critical evolution state, and executing metering calibration on the electric energy meter within the calibration trigger time window. The method comprises the steps of selecting an energy evolution feature vector, constructing an evolution state judging function by taking the energy growth rate, the energy growth acceleration and the energy fluctuation amplitude as input variables, wherein the evolution state judging function comprises a plurality of evolution feature vector sample sets based on a plurality of defined evolution states and corresponding to the evolution states, the evolution states comprise an energy evolution stable state, an energy slow growth state, an energy fast growth state and an energy mutation state, inputting the energy evolution feature vector into the evolution state judging function to perform feature ve