A building electricity metering error correction method and system

Abstract

The present application provides a building power metering error correction method and system, which determines the power signal of the building distribution circuit, thereby determining the power error characteristics in the building distribution circuit, extracting the impedance-load rate correlation characteristics in the building distribution circuit from the historical power operation data of the building distribution circuit; determining the optimal distribution ratio of the correction amount when performing error correction on the power of each monitoring node in the building distribution circuit based on the impedance-load rate correlation characteristics and the power error characteristics; determining the fluctuation trend of the impedance in the building distribution circuit with temperature changes based on the temperature of each monitoring node in the monitoring building distribution circuit combined with the voltage signal and the current signal; and determining the corrected power data for each monitoring node in the building distribution circuit based on all the optimal distribution ratios and the fluctuation trends of the impedance with temperature changes. The use of the present application scheme can reduce the impact of real-time interference in response to load fluctuations and temperature changes on the power errors in the building distribution circuit.

Description

Technical Field

[0001] The present application relates to the technical field of error correction, and more specifically, to a method and system for correcting building electricity metering errors. Background Art

[0002] Systematic errors are caused by some fixed reasons, which make the measurement results systematically larger or smaller. For example, the inaccuracy of the instrument itself, the imperfection of the experimental method, and the influence of environmental factors. The error can only be minimized but not completely eliminated. In actual measurement, it is necessary to choose appropriate methods according to the specific situation to reduce the error in order to improve the accuracy and reliability of the measurement results.

[0003] With the increasing complexity of building electrical systems and the integration of distributed energy resources, electricity metering accuracy faces multiple challenges. Traditional energy metering methods for building distribution circuits typically rely on local monitoring nodes and are susceptible to harmonic distortion, dynamic load changes, and ambient temperature fluctuations. For example, nonlinear loads can cause steady-state harmonic pollution, and the nonlinear relationship between load rate changes and line impedance can lead to cumulative metering errors. At the same time, temperature changes cause conductor impedance drift, further amplifying errors. Existing technologies often use single-parameter compensation or static correction models, lacking full-circuit dynamic analysis of the coupling of multiple factors. This leads to insufficient error correction accuracy, affecting energy efficiency management, billing fairness, and grid stability. Furthermore, the grid-connected demand for distributed energy resources places higher demands on the real-time performance and anti-interference capabilities of energy metering. Therefore, how to reduce the impact of real-time interference from load fluctuations and temperature changes on energy errors in building distribution circuits has become a challenge facing the industry. Summary of the Invention

[0004] The present application provides a building electricity metering error correction method and system, which can reduce the impact of real-time interference in response to load fluctuations and temperature changes on electricity errors in the building distribution circuit.

[0005] In a first aspect, the present application provides a method for correcting building electricity metering errors, comprising the following steps:

[0006] The voltage and current signals of each monitoring node in the building power distribution circuit are monitored by the voltage transformer and current transformer pre-installed in the building power distribution circuit monitoring node, thereby determining the power energy signal of the building power distribution circuit;

[0007] performing steady-state harmonic analysis on the electric energy signal to obtain an electric energy error characteristic in the building power distribution circuit, and extracting an impedance-load rate correlation characteristic in the building power distribution circuit from historical power operation data of the building power distribution circuit;

[0008] performing a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation feature and the power energy error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit;

[0009] Monitoring the temperature of each monitoring node in the building power distribution circuit, and determining a fluctuation trend of impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal;

[0010] Based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature, the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit are coupled and corrected to obtain the corrected electric energy data of each monitoring node in the building distribution circuit.

[0011] In some embodiments, performing steady-state harmonic analysis on the electric energy signal to obtain the electric energy error characteristics in the building power distribution circuit specifically includes:

[0012] Converting the electric energy signal into a frequency domain signal;

[0013] extracting the amplitude and phase of the fundamental wave from the frequency domain signal;

[0014] Extracting the amplitude and phase of each harmonic from the frequency domain signal;

[0015] The electric energy error characteristics in the building power distribution circuit are determined based on the amplitude and phase of the fundamental wave combined with the amplitude and phase of each harmonic.

[0016] In some embodiments, extracting the impedance-load rate correlation feature in the building power distribution circuit from the historical power operation data of the building power distribution circuit specifically includes:

[0017] Obtaining historical power operation data of the building's power distribution circuit;

[0018] Determining impedance information and load rate information of each monitoring node in the building power distribution circuit based on the historical power operation data;

[0019] Correlation analysis is performed on the impedance information and load rate information of each monitoring node to obtain impedance-load rate correlation characteristics in the building power distribution circuit.

[0020] In some embodiments, performing a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load ratio correlation feature and the power energy error feature, and then obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit specifically includes:

[0021] Determining a monitoring node group where electric energy in the building power distribution circuit is offset based on the impedance-load rate correlation characteristic and the electric energy error characteristic;

[0022] Correlating the power errors of the monitoring nodes in the building power distribution circuit by using the monitoring node group to obtain correlation correction values ​​of the power errors of the monitoring nodes in the building power distribution circuit;

[0023] Determine the power influence coefficient between each monitoring node in the building power distribution circuit;

[0024] The optimal distribution ratio of the correction amount when performing error correction on the electric energy of each monitoring node in the building distribution circuit is determined according to all associated correction amounts and all electric energy influence coefficients.

[0025] In some embodiments, determining the monitoring node group where the power offset occurs in the building power distribution circuit based on the impedance-load ratio correlation feature and the power error feature specifically includes:

[0026] fusing the impedance-load rate correlation feature and the electric energy error feature to obtain a feature fusion vector;

[0027] Determining a plurality of similar monitoring node groups of electric energy in a building power distribution circuit according to the feature fusion vector;

[0028] The monitoring node group where the electric energy in the building power distribution circuit is offset is determined through all similar monitoring node groups.

[0029] In some embodiments, determining the fluctuation trend of the impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal specifically includes:

[0030] determining an impedance change trend of each monitoring node according to the voltage signal and the current signal;

[0031] Determine the temperature change trend of each monitoring node based on all temperatures obtained by monitoring;

[0032] The fluctuation trend of the impedance in the building power distribution circuit as it changes with temperature is determined through all impedance change trends and all temperature change trends.

[0033] In some embodiments, coupling correction is performed on the electric energy metering errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all optimal distribution ratios and the fluctuation trend of the impedance with temperature, and the corrected electric energy data of each monitoring node in the building power distribution circuit is obtained, specifically including:

[0034] Determining coupling correction amounts for energy metering errors of each group of adjacent monitoring nodes in a building power distribution circuit based on all optimal distribution ratios and fluctuation trends of the impedance as it changes with temperature;

[0035] The electric energy in the building distribution circuit is corrected according to all coupling correction amounts, and the corrected electric energy data of each monitoring node in the building distribution circuit is obtained.

[0036] In some embodiments, each monitoring node includes a power supply monitoring node, a docking point monitoring node, a distribution cabinet monitoring node, an electrical equipment monitoring node, and a switch box monitoring node.

[0037] In some embodiments, the temperature of each sensing monitoring node in the building power distribution circuit is monitored by a temperature sensor.

[0038] In a second aspect, the present application provides a building electricity metering error correction system, comprising:

[0039] A monitoring module is used to monitor the voltage signal and current signal of each monitoring node in the building power distribution circuit through the voltage transformer and current transformer pre-installed in the building power distribution circuit monitoring node, and then determine the power signal of the building power distribution circuit;

[0040] a processing module configured to perform steady-state harmonic analysis on the electric energy signal to obtain an electric energy error characteristic in the building power distribution circuit, and extract an impedance-load rate correlation characteristic in the building power distribution circuit from historical power operation data of the building power distribution circuit;

[0041] The processing module is further configured to perform a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load ratio correlation feature and the power energy error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit;

[0042] The processing module is further configured to monitor the temperature of each monitoring node in the building power distribution circuit, and determine a fluctuation trend of impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal;

[0043] The execution module is used to perform coupling correction on the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature changes, so as to obtain the corrected electric energy data of each monitoring node in the building distribution circuit.

[0044] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0045] The present application provides a building power metering error correction method and system, which first monitors the voltage signal and current signal of each monitoring node in the building power distribution circuit through the voltage transformer and current transformer pre-installed in the building power distribution circuit monitoring node, and then determines the power signal of the building power distribution circuit; performs steady-state harmonic analysis on the power signal, and then obtains the power error characteristics in the building power distribution circuit, extracts the impedance-load rate correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit; and based on the impedance-load rate correlation characteristics and the power error characteristics, the power distribution circuit in the building power distribution circuit is corrected. A global correlation analysis is performed on the electric energy errors of each monitoring node to obtain an optimal distribution ratio of the correction amount when performing error correction on the electric energy of each monitoring node in the building distribution circuit; the temperature of each monitoring node in the building distribution circuit is monitored, and the fluctuation trend of the impedance in the building distribution circuit with temperature changes is determined based on all the monitored temperatures combined with the voltage signal and the current signal; based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature changes, the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit are coupled and corrected to obtain corrected electric energy data for each monitoring node in the building distribution circuit.

[0046] It can be seen that in the process of eliminating errors in building electricity metering, the present application first obtains the electricity error characteristics by performing steady-state harmonic analysis on the electricity signal, effectively separates the fundamental component and the harmonic interference component, reveals the characteristic harmonic distortion law caused by the nonlinear load of the power grid, and improves the error identification accuracy; secondly, extracts the impedance-load rate correlation characteristics from the historical power operation data, establishes a dynamic correlation model between load fluctuations and line impedance changes, and captures the nonlinear change law of impedance parameters under different load conditions; then, based on the impedance-load rate correlation characteristics and the electricity error characteristics, a global correlation analysis is performed to obtain the optimal distribution ratio, and a multi-monitoring node error coupling network model is constructed to achieve the desired effect. The optimal distribution of energy in the spatial dimension is corrected to avoid system oscillations caused by local overcorrection. Next, the node temperature is monitored and combined with electrical signals to determine the impedance fluctuation trend. A three-dimensional dynamic relationship model of temperature-impedance-electrical energy error is established to quantify the influence of the conductor material temperature coefficient on the line parameters. Finally, the electric energy error of the building distribution circuit is coupled and corrected based on the optimal distribution ratio and the impedance temperature fluctuation trend. Corrected electric energy data is obtained for each monitoring node in the building distribution circuit, achieving coordinated compensation under the dual interference of load fluctuation and temperature change. The correction parameters are dynamically adjusted through a time-varying weight allocation algorithm to achieve a balanced optimization of error suppression and system stability. The above scheme can reduce the impact of real-time interference in response to load fluctuation and temperature change on the electric energy error in the building distribution circuit. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1is an exemplary flow chart of a building electricity metering error correction method according to some embodiments of the present application;

[0048] Figure 2 is an exemplary flow chart of determining power error characteristics according to some embodiments of the present application;

[0049] Figure 3 is an exemplary flow chart for determining the fluctuation trend of impedance with temperature according to some embodiments of the present application;

[0050] Figure 4 is a structural diagram of a building power metering error correction system according to some embodiments of the present application;

[0051] Figure 5 It is a structural diagram of a computer device for implementing a building electricity metering error correction method according to some embodiments of the present application. DETAILED DESCRIPTION

[0052] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0053] refer to Figure 1 , which is an exemplary flow chart of a building electric energy metering error correction method according to some embodiments of the present application. The building electric energy metering error correction method 100 mainly includes the following steps:

[0054] In step 101, voltage and current signals of each monitoring node in the building power distribution circuit are monitored by pre-installed voltage transformers and current transformers in the building power distribution circuit monitoring nodes, thereby determining the power signal of the building power distribution circuit.

[0055] In specific implementation, voltage transformers and current transformers are pre-installed at each monitoring node in the building's power distribution circuit. The installed voltage transformers and current transformers are used to monitor the voltage signals and current signals of each monitoring node in the building's power distribution circuit to obtain voltage signals and current signals, wherein the voltage signal represents the signal of the voltage value of each monitoring node during the monitoring time, and the current signal represents the signal of the current value flowing through each monitoring node during the monitoring time. The electric energy signal is calculated by combining the voltage signal and the current signal through the basic formula of electric energy, wherein the electric energy signal represents the signal of the electric energy value of each monitoring node during the monitoring time. In other embodiments, other monitoring methods can also be used, which are not limited here.

[0056] It should be noted that there are multiple monitoring nodes in the building power distribution circuit in this application, including power supply monitoring nodes, junction point monitoring nodes, distribution cabinet monitoring nodes, electrical equipment monitoring nodes, and switch box monitoring nodes. Each monitoring node has multiple types of monitoring nodes. For example, the electrical equipment monitoring nodes include motors, lamps, and communication equipment.

[0057] In step 102, a steady-state harmonic analysis is performed on the electric energy signal to obtain an electric energy error characteristic in the building power distribution circuit, and an impedance-load rate correlation characteristic in the building power distribution circuit is extracted from historical power operation data of the building power distribution circuit.

[0058] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining the electric energy error characteristics in some embodiments of the present application. In this embodiment, steady-state harmonic analysis of the electric energy signal is performed to obtain the electric energy error characteristics in the building power distribution circuit. The following steps can be used to achieve this:

[0059] First, in step 1021, the electric energy signal is converted into a frequency domain signal;

[0060] Next, in step 1022, the amplitude and phase of the fundamental wave are extracted from the frequency domain signal;

[0061] Then, in step 1023, the amplitude and phase of each harmonic are extracted from the frequency domain signal;

[0062] Finally, in step 1024, the power energy error characteristics in the building power distribution circuit are determined based on the amplitude and phase of the fundamental wave combined with the amplitude and phase of each harmonic.

[0063] In specific implementation, the conversion of the electric energy signal into a frequency domain signal can be achieved in the following manner, namely: filtering the electric energy signal through a filter to remove high-frequency noise and interference signals to obtain a processed electric energy signal, and converting the processed electric energy signal into a frequency domain signal through fast Fourier transform to facilitate analysis of the characteristics of the electric energy signal in the frequency domain; extracting the amplitude and phase information of the fundamental wave from the frequency domain signal can be achieved in the following manner, namely: calculating the amplitude of the fundamental wave through the FFT scaling method in the prior art, and calculating the phase of the fundamental wave through the complex phase angle in the prior art; extracting the amplitude and phase of each harmonic from the frequency domain signal can be achieved in the following manner, namely: in this embodiment, the harmonic order can be 3rd, 5th, 7th, 11th, etc. , 13th, the amplitude of each harmonic is calculated by the FFT scaling method in the prior art, and the phase of each harmonic is calculated by the complex phase angle in the prior art; the electric energy error characteristics in the building distribution circuit are determined according to the amplitude and phase of the fundamental wave combined with the amplitude and phase of each harmonic, which can be achieved in the following manner, namely: obtaining the theoretical amplitude and theoretical phase corresponding to the electric energy signal from the database corresponding to the building distribution circuit, calculating the difference between the amplitude and phase of the fundamental wave and the corresponding theoretical amplitude and theoretical phase, calculating the difference between the amplitude and phase of each harmonic and the corresponding theoretical amplitude and theoretical phase, and using all the differences obtained by the above calculations as the electric energy error characteristics in the building distribution circuit; in other embodiments, other methods can also be used for determination, which are not limited here.

[0064] It should be noted that the power error characteristics in this application represent the characteristics of the error degree of power in the building distribution circuit, which can be used to evaluate the quality of power, thereby providing a scientific basis for improving the power quality.

[0065] In some embodiments, extracting the impedance-load rate correlation feature in the building power distribution circuit from the historical power operation data of the building power distribution circuit can be achieved by using the following steps:

[0066] Obtaining historical power operation data of the building's power distribution circuit;

[0067] Determining impedance information and load rate information of each monitoring node in the building power distribution circuit based on the historical power operation data;

[0068] Correlation analysis is performed on the impedance information and load rate information of each monitoring node to obtain impedance-load rate correlation characteristics in the building power distribution circuit.

[0069] In a specific implementation, obtaining the historical power operation data of the building distribution circuit can be achieved in the following manner, namely: obtaining the historical power operation data of the building distribution circuit from the database of the building distribution circuit, wherein the historical power operation data includes historical voltage, current and power data; determining the impedance information and load rate information of each monitoring node in the building distribution circuit according to the historical power operation data can be achieved in the following manner, namely: calculating the average impedance of each monitoring node in the building distribution circuit during each power collection process based on the calculation formula of Ohm's law combined with the historical voltage and current data in the historical power operation data; and calculating the average impedance of each monitoring node in the building distribution circuit during each power collection process. The set of is used as the impedance information of each monitoring node corresponding to the building distribution circuit, wherein the impedance information represents the impedance information of each monitoring node in the building distribution circuit, and the average load rate of each monitoring node in the building distribution circuit during each power collection process is calculated based on the load rate calculation formula in combination with the historical power data in the historical power operation data and the rated power of each monitoring node, and the set of the average load rates of each monitoring node in the building distribution circuit during each power collection process is used as the load rate information corresponding to each monitoring node in the building distribution circuit, wherein the load rate represents the load rate information of each monitoring node in the building distribution circuit; in other embodiments, other methods can also be used for determination, which is not limited here.

[0070] In a specific implementation, the impedance information and load rate information of each monitoring node are correlated and analyzed to obtain the impedance-load rate correlation characteristics in the building distribution circuit. This can be achieved in the following manner: using a statistical method (such as regression analysis) to establish a correlation model between impedance and load rate, and inputting the impedance information and load rate information of each monitoring node into the correlation model. The impedance change trend of each monitoring node under different load rates is analyzed through the correlation model, and a machine learning method (such as a neural network) is combined with the impedance change trend of each monitoring node under different load rates to establish a nonlinear relationship between the impedance and the load rate in the corresponding monitoring node (i.e., the relative change between the impedance and the load rate), and all nonlinear relationships are used as the impedance-load rate correlation characteristics in the building distribution circuit. In other embodiments, other methods can also be used for determination, which are not limited here.

[0071] It should be noted that the impedance-load rate correlation characteristics in this application represent the characteristics of the correlation between the impedance and the load rate in the building distribution circuit, that is, the correlation characteristics of the mutual changes between the impedance and the load rate, which can be used to analyze the correlation between the real-time impedance and the load rate in the building distribution circuit, and then correct the power error in the building distribution circuit.

[0072] In step 103, a global correlation analysis is performed on the power errors of each monitoring node in the building distribution circuit based on the impedance-load rate correlation characteristics and the power error characteristics, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power of each monitoring node in the building distribution circuit.

[0073] In some embodiments, a global correlation analysis of the power errors of each monitoring node in the building power distribution circuit is performed based on the impedance-load ratio correlation feature and the power error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power of each monitoring node in the building power distribution circuit. This can be achieved by using the following steps:

[0074] Determining a monitoring node group where electric energy in the building power distribution circuit is offset based on the impedance-load rate correlation characteristic and the electric energy error characteristic;

[0075] Correlating the power errors of the monitoring nodes in the building power distribution circuit by using the monitoring node group to obtain correlation correction values ​​of the power errors of the monitoring nodes in the building power distribution circuit;

[0076] Determine the power influence coefficient between each monitoring node in the building power distribution circuit;

[0077] The optimal distribution ratio of the correction amount when performing error correction on the electric energy of each monitoring node in the building distribution circuit is determined according to all associated correction amounts and all electric energy influence coefficients.

[0078] In addition, in some embodiments, determining the monitoring node group where the power offset occurs in the building power distribution circuit based on the impedance-load ratio correlation characteristic and the power error characteristic can be achieved by using the following steps:

[0079] fusing the impedance-load rate correlation feature and the electric energy error feature to obtain a feature fusion vector;

[0080] Determining a plurality of similar monitoring node groups of electric energy in a building power distribution circuit according to the feature fusion vector;

[0081] The monitoring node group where the electric energy in the building power distribution circuit is offset is determined through all similar monitoring node groups.

[0082] It should be noted that in the power distribution network, the impedance characteristics of each monitoring node have an inherent relationship with its load rate. Abnormal monitoring nodes will destroy this normal correlation model, and the deviation in electricity metering will manifest as a specific error pattern. Anomalies can be detected through statistical analysis. Therefore, the cluster of monitoring nodes with power deviation in the building distribution circuit can be identified through the impedance-load rate correlation characteristics and the power error characteristics.

[0083] In a specific implementation, the impedance-load rate correlation feature and the electric energy error feature are fused to obtain a feature fusion vector, which can be achieved in the following manner, namely: the impedance-load rate correlation feature and the electric energy error feature are fused by a feature fusion method in the prior art (such as the decision level) to construct a multidimensional feature vector (for example: multidimensional feature vector = [impedance-load rate correlation feature, electric energy error feature]), and the multidimensional feature vector is used as a feature fusion vector, wherein the feature fusion vector represents a feature fusion vector of the impedance-load rate and error of the electric energy in the building distribution circuit; the electric energy in the building distribution circuit is determined according to the feature fusion vector. Multiple similar monitoring node groups can be implemented in the following manner, namely: the monitoring nodes corresponding to the same impedance-load rate correlation feature and electric energy error feature in the feature fusion vector are divided into the same group, that is: the monitoring nodes corresponding to the same nonlinear relationship in the impedance-load rate correlation feature and the same difference in the electric energy error feature are divided into the same group, to obtain multiple groups, and each group is used as a similar monitoring node group for the electric energy in the building distribution circuit, wherein the similar monitoring node group represents a monitoring node group with the same electric energy change in the building distribution circuit; in other embodiments, other methods can also be used for determination, which is not limited here.

[0084] In specific implementation, determining the monitoring node group where electric energy is offset in the building's power distribution circuit through all similar monitoring node groups can be achieved in the following manner, namely: judging the difference in the electric energy error characteristics of different similar monitoring node groups, calculating the average value of all differences in the electric energy error characteristics, comparing the difference corresponding to each similar monitoring node group with the average value, extracting each difference greater than the average value to find the monitoring node group with a larger electric energy error, and using the set of similar monitoring node groups corresponding to each extracted difference as the monitoring node group where electric energy is offset in the building's power distribution circuit; in other embodiments, other methods can also be used for determination, which are not limited here.

[0085] It should be noted that the monitoring node group in this application represents the group of all monitoring nodes where electric energy in the building distribution circuit is offset, which can be used to perform centralized error analysis on the electric energy in the building distribution circuit, thereby reducing the workload of eliminating errors in the building distribution circuit.

[0086] In a specific implementation, the electric energy errors of each monitoring node in the building distribution circuit are correlated through the monitoring node group, and the correlation correction amount of the electric energy errors of each monitoring node in the building distribution circuit can be obtained in the following manner, namely: in the building distribution circuit, the electric energy errors of each monitoring node are not completely independent. The monitoring nodes in the same monitoring node group are affected by similar measurement environments, equipment characteristics and power transmission process factors, and their electric energy errors may have certain statistical correlations. The monitoring nodes in the same group may have common error sources due to the commonalities in measurement equipment, transmission lines and equipment characteristics. As a preferred embodiment, for each monitoring node, the error between its electric energy measurement value and the theoretical value is calculated. The theoretical value can be determined by a calculation model based on circuit principles or a statistical model of historical data. For example, the theoretical electric energy value of each monitoring node is calculated according to Kirchhoff's law and circuit parameters, and then compared with the actual measurement value to obtain the electric energy error of each monitoring node. The correlation coefficient and covariance analysis statistical methods are used to analyze the correlation between the electric energy errors of each monitoring node in the same monitoring node group. The correlation coefficient between each monitoring node is calculated to quantify the strength and direction of the linear relationship between them. For example, the Pearson correlation coefficient can measure the degree of linear correlation between two variables. The value range is between -1 and 1. The closer the absolute value is to 1, the stronger the correlation. By clustering the power errors of each monitoring node and the principal component analysis method, the common error components caused by measurement, transmission or equipment characteristics in the same group are identified. The least squares method and the weighted average method are used to combine the common error components to calculate the associated correction amount of each monitoring node. For example, the least squares method can determine the optimal correction amount by minimizing the sum of squared errors, so that the power error of each monitoring node after correction is as close to the true value as possible. Specifically, if it is found that the error of a certain monitoring node is strongly correlated with other monitoring nodes and the common error component is obvious, then when calculating its associated correction amount, the error conditions of other monitoring nodes in the group and the correlation weights between them will be comprehensively considered to determine the error compensation value that needs to be corrected for the monitoring node; in other embodiments, other methods can also be used for determination, which is not limited here.

[0087] In specific implementation, the following methods can be used to determine the electric energy influence coefficient between each monitoring node in the building distribution circuit, namely: analyze the physical connection relationship, load distribution and electric energy transmission characteristics between each monitoring node in the building distribution circuit, establish a mathematical model, and quantify the impact of the error of one monitoring node on other monitoring nodes through sensitivity analysis or regression model methods, and use the quantified value of the impact of each monitoring node as the electric energy influence coefficient between the corresponding monitoring nodes. The electric energy influence coefficient reflects the weight or proportion of the error propagation in the entire network.

[0088] In specific implementation, the optimal distribution ratio of the correction amount when performing error correction on the electric energy of each monitoring node in the building distribution circuit is determined based on all associated correction amounts and all electric energy influence coefficients. The following method can be used to achieve this: the associated correction amount is calculated based on the statistical correlation and common error component between the errors of each monitoring node in the monitoring node group. It reflects the degree of error correlation between each monitoring node and other monitoring nodes, as well as the error compensation value that needs to be corrected after considering the mutual influence within the group. When allocating the correction amount, the correction amount allocation of each monitoring node should be adjusted in combination with the associated correction amount to fully consider the intrinsic connection between the monitoring nodes and avoid treating the error correction of each monitoring node in isolation; the electric energy influence coefficient reflects the relative importance of each monitoring node in the building distribution circuit or its influence on the overall electric energy metering. For example, some monitoring nodes may correspond to important electrical equipment or areas, and the accuracy of their electric energy metering is more critical to the energy consumption analysis and management of the entire building. Therefore, the electric energy influence coefficients of these monitoring nodes will be relatively high. When determining the correction amount allocation ratio, different weights need to be given to different monitoring nodes according to the electric energy influence coefficient to ensure more accurate error correction of important monitoring nodes; by reasonably allocating Correction amount, so that the total error of electric energy measurement of each monitoring node in the entire building distribution circuit is minimized. This means that the error of each monitoring node and its influence on the overall distribution system should be comprehensively considered to find an optimal distribution scheme so that after correction, the electric energy measurement value of each monitoring node is as close to the true value as possible, thereby improving the accuracy of electric energy measurement of the entire distribution system. As a preferred embodiment, the associated correction amount and electric energy influence coefficient are standardized and converted into values ​​with the same dimension and value range for unified calculation and comparison. For example, the normalization method can be used to convert The associated correction amount and electric energy influence coefficient of each monitoring node are divided by their maximum values ​​so that their value range is between 0 and 1. An optimization model is established with the goal of minimizing the total error (such as the sum of squared errors) remaining after the error correction of the entire distribution circuit, while satisfying the actual constraints of energy conservation, system balance and equipment calibration. All associated correction amounts and electric energy influence coefficients obtained after standardization are used as model parameters, and the optimal distribution ratio of the correction amount of each monitoring node is solved through linear programming, least squares method or other numerical optimization algorithms; in other embodiments, other methods can also be used for determination, which is not limited here.

[0089] It should be noted that the optimal distribution ratio in this application represents the parameter value of the optimal distribution degree of the correction amount when performing error correction on the electric energy of the monitoring node in the building distribution circuit, which can be used to perform error correction on the electric energy in the building distribution circuit, thereby achieving the best correction effect.

[0090] In step 104, the temperature of each monitoring node in the building power distribution circuit is monitored, and the fluctuation trend of the impedance in the building power distribution circuit with temperature change is determined based on all monitored temperatures combined with the voltage signal and the current signal.

[0091] In specific implementation, monitoring the temperature of each monitoring node in the building distribution circuit can be achieved in the following manner, namely: arranging a sensor monitoring node at each monitoring node, monitoring the temperature of each sensor monitoring node in the building distribution circuit through a temperature sensor, and using the temperature of each sensor monitoring node as the temperature of the corresponding monitoring node; in other embodiments, other methods can also be used for determination, which are not limited here.

[0092] In some embodiments, reference Figure 3 As shown in FIG. 1 , this figure is an exemplary flow chart for determining the fluctuation trend of impedance with temperature changes in some embodiments of the present application. In some embodiments of the present invention, the fluctuation trend of impedance with temperature changes in the building power distribution circuit can be determined based on all monitored temperatures combined with the voltage signal and the current signal. The following steps can be used:

[0093] First, in step 1041, the impedance change trend of each monitoring node is determined according to the voltage signal and the current signal;

[0094] Next, in step 1042 , the temperature change trend of each monitoring node is determined based on all temperatures obtained through monitoring;

[0095] Finally, in step 1043, the fluctuation trend of the impedance in the building power distribution circuit as it changes with temperature is determined based on all impedance change trends and all temperature change trends.

[0096] In a specific implementation, the impedance change trend of each monitoring node is determined based on the voltage signal and the current signal, which can be achieved in the following manner, namely: select a monitoring node as the selected monitoring node, calculate the impedance at each monitoring time point based on Ohm's law in combination with the voltage signal and current signal corresponding to the selected monitoring node, and perform trend analysis on all impedances through a trend analysis method (such as polynomial regression analysis), use the result of the trend analysis as the impedance change trend of the selected monitoring node, and continue to determine the impedance change trend of the remaining monitoring nodes, wherein the impedance change trend represents the characteristics of the impedance change trend of the monitoring node over time; determine the temperature change trend of each monitoring node based on all temperatures obtained by monitoring It is implemented in the following manner, namely: select a monitoring node as the selected monitoring node, extract all temperatures of the selected monitoring node from all temperatures obtained by monitoring, arrange all extracted temperatures in chronological order of monitoring time, and use the arranged sequence as the temperature sequence of the selected monitoring node; perform trend analysis on the temperatures in the temperature sequence in the order of arrangement through a trend analysis method (such as polynomial regression analysis), use the result of the trend analysis as the temperature change trend of the selected monitoring node, and continue to determine the temperature change trend of the remaining monitoring nodes. In fact, the temperature change trend represents the temperature change trend of each monitoring node over time; in other embodiments, other methods can also be used for determination, which is not limited here.

[0097] In specific implementation, the following method can be used to determine the fluctuation trend of the impedance in the building distribution circuit as it changes with temperature through all impedance change trends and all temperature change trends, namely: impedance is the resistance to alternating current in the circuit, and its size is related to the resistivity and geometric size factors of the conductor. Temperature will affect the resistivity of the conductor, thereby changing the impedance. Under normal circumstances, an increase in temperature will cause the resistivity to increase, and the impedance will also increase accordingly, and vice versa; select a monitoring node as the selected monitoring node, and perform spatiotemporal alignment processing on the impedance change trend and the temperature change trend of the selected monitoring node to associate the impedance change trend and the temperature change trend, and analyze the change trend between the impedance change trend and the temperature change trend after the association through the trend fluctuation analysis method, and use this change trend as the change trend of the impedance in the selected monitoring node as it changes with temperature, and continue to determine the change trend of the impedance in the remaining monitoring nodes as it changes with temperature, and use all change trends as the fluctuation trend of the impedance in the building distribution circuit as it changes with temperature; in other embodiments, other methods can also be used for determination, which are not limited here.

[0098] It should be noted that the fluctuation trend in this application represents the trend of the degree of fluctuation of the impedance in the building distribution circuit with temperature changes, which can be used to correct the impedance changes in the building distribution circuit, thereby reducing the impact of temperature on the metering of electric energy in the building distribution circuit.

[0099] In step 105, coupling correction is performed on the power metering errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature, so as to obtain the corrected power data of each monitoring node in the building power distribution circuit.

[0100] In some embodiments, coupling correction is performed on the electric energy metering errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all optimal distribution ratios and the fluctuation trend of the impedance with temperature, and the corrected electric energy data of each monitoring node in the building power distribution circuit is obtained by the following steps:

[0101] Determining coupling correction amounts for energy metering errors of each group of adjacent monitoring nodes in a building power distribution circuit based on all optimal distribution ratios and fluctuation trends of the impedance as it changes with temperature;

[0102] The electric energy in the building distribution circuit is corrected according to all coupling correction amounts, and the corrected electric energy data of each monitoring node in the building distribution circuit is obtained.

[0103] In specific implementation, the coupling correction amount of the electric energy metering error of each group of adjacent monitoring nodes in the building distribution circuit is determined according to all the optimal distribution ratios and the fluctuation trend of the impedance with temperature change. It can be achieved in the following way, that is: in the building distribution circuit, according to Kirchhoff's current law (KCL), the sum of the currents flowing into a certain monitoring node is equal to the sum of the currents flowing out of the monitoring node. According to Kirchhoff's voltage law (KVL), the sum of the voltage drops along any closed loop is zero. When the impedance changes with temperature, it will cause the current and voltage distribution in the loop to change, thereby affecting the calculation of electric energy. Since adjacent monitoring nodes are connected by wires The branches are connected, and their power errors will affect each other and there is a coupling relationship. The optimal distribution ratio is determined based on the normal operating state and design parameters of the distribution circuit. It reflects the proportional relationship of power distribution between the branches under ideal conditions. When the impedance changes with temperature in actual operation, the actual power distribution will deviate from the optimal distribution ratio. By comparing the difference between the actual power distribution and the optimal distribution ratio, the power error can be determined, and this difference can be used to calculate the coupling correction amount to adjust the actual power distribution to a state close to the optimal distribution ratio. As a preferred embodiment, the actual power distribution of each monitoring node is compared with the optimal distribution ratio. By comparison, the power error of each monitoring node relative to the optimal distribution state is calculated, and all the power errors are converted into power error vectors. Taking into account that the impedance changes between adjacent monitoring nodes will affect each other, a coupling model of power errors is established based on circuit theory. For example, by analyzing the current and voltage relationship between the monitoring nodes, using Kirchhoff's law and Ohm's law, a set of equations describing the coupling relationship between the power errors of adjacent monitoring nodes can be obtained. This set of equations can be expressed in the matrix form ΔE=C*ΔZ, where ΔE is the power error vector, ΔZ is the impedance change vector, C is the coupling coefficient matrix, and the coupling coefficient matrix The elements of the matrix C reflect the degree of coupling of the electric energy errors between adjacent monitoring nodes, which is related to the topology of the distribution circuit and line parameter factors. Based on the established error coupling model and the actual measured impedance fluctuation ΔZ with temperature, the equation system is solved to obtain the coupling correction value ΔE for the electric energy metering error. The specific solution method can adopt numerical calculation methods, such as matrix inversion and iterative methods. For example, if the coupling coefficient matrix C and the impedance change vector ΔZ are known, the coupling correction value for the electric energy metering error can be calculated as ΔE=C*ΔZ. In other embodiments, other methods can also be used for determination, which are not limited here.

[0104] In specific implementation, the electric energy in the building power distribution circuit is corrected according to all the coupling correction amounts, and the corrected electric energy data of each monitoring node in the building power distribution circuit can be implemented by the following method, that is: according to the topological structure of the power distribution circuit and the connection relationship between the monitoring nodes, a reasonable correction order is determined. Usually, the correction can be carried out in the direction of the current flow or from the power supply end to the load end. For the first monitoring node (usually the power supply monitoring node or the selected starting monitoring node), its original electric energy data is directly adjusted according to the coupling correction amount between it and the adjacent monitoring node. For example, if the coupling correction amount between this monitoring node and the adjacent monitoring node is ΔE1 and the original electric energy data is E1, then the corrected electric energy data E1′ = E1 + ΔE1. For subsequent monitoring nodes, when performing correction, not only the coupling correction amount between it and the previous monitoring node needs to be considered, but also the influence of the corrected adjacent monitoring nodes on it needs to be considered. Taking the monitoring node i as an example, assuming that the coupling correction amount between it and the previous monitoring node i−1 is ΔEi,i−1, and the coupling correction amounts between it and other corrected adjacent monitoring nodes j (j < i) are ΔEi,j, and the original electric energy data is Ei, then the corrected electric energy data Ei′ = Ei + ΔEi,i−1 + ∑j < iΔEi,j. The summation term here represents considering the coupling influence of all corrected adjacent monitoring nodes on the current monitoring node. According to the determined correction order, the above correction operation is sequentially performed on each monitoring node until all monitoring nodes are corrected. The corrected electric energy data of each monitoring node is used as the corrected electric energy data of the corresponding monitoring node in the building power distribution circuit; in other embodiments, other methods can also be used to determine it, which is not limited here.

[0105] In addition, on the other hand of the present application, in some embodiments, the present application provides a building electric energy measurement error correction system. Refer to Figure 4 , which is a schematic structural diagram of the building electric energy measurement error correction system shown according to some embodiments of the present application. The building electric energy measurement error correction system 400 includes: a monitoring module 401, a processing module 402, and an execution module 403, which are described as follows:

[0106] The monitoring module 401. In the present application, the monitoring module 401 is mainly used to monitor the voltage signals and current signals of each monitoring node in the building power distribution circuit through the voltage transformers and current transformers pre-installed at the monitoring nodes of the building power distribution circuit, and then determine the electric energy signal of the building power distribution circuit;

[0107] The processing module 402. In the present application, the processing module 402 is used to perform steady-state harmonic analysis on the electric energy signal, and then obtain the electric energy error characteristics in the building power distribution circuit, and extract the impedance-load ratio correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit;

[0108] It should be noted that the processing module 402 in the present application is further configured to perform a global correlation analysis on the power errors of each monitoring node in the building power distribution circuit based on the impedance-load ratio correlation feature and the power error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power of each monitoring node in the building power distribution circuit;

[0109] In addition, it should be noted that the processing module 402 in the present application is also used to monitor the temperature of each monitoring node in the building power distribution circuit, and determine the fluctuation trend of the impedance in the building power distribution circuit with temperature changes based on all the monitored temperatures combined with the voltage signal and the current signal;

[0110] Execution module 403. In this application, execution module 403 is mainly used to perform coupling correction on the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit based on all optimal distribution ratios and the fluctuation trend of the impedance with temperature changes, and obtain the corrected electric energy data of each monitoring node in the building distribution circuit.

[0111] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned building electricity metering error correction method.

[0112] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a building power metering error correction method according to some embodiments of the present application. A building power metering error correction method in the above embodiment can be achieved by Figure 5 The computer device 500 shown in FIG. 5 is implemented as shown in FIG. 5 . The computer device 500 includes at least one processor 501 , a communication bus 502 , a memory 503 , and at least one communication interface 504 .

[0113] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0114] The communication bus 502 may be used to transmit information between the aforementioned components.

[0115] The memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory 503 may be independent and connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0116] The memory 503 is used to store program code for executing the solution of the present application, and is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0117] The communication interface 504 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0118] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0119] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0120] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned building electricity metering error correction method.

[0121] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0122] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A building electricity metering error correction method, characterized in that: The steps include: The voltage and current signals of each monitoring node in the building power distribution circuit are monitored by the voltage transformer and current transformer pre-installed in the building power distribution circuit monitoring node, thereby determining the power energy signal of the building power distribution circuit; performing steady-state harmonic analysis on the electric energy signal to obtain an electric energy error characteristic in the building power distribution circuit, and extracting an impedance-load rate correlation characteristic in the building power distribution circuit from historical power operation data of the building power distribution circuit; performing a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation feature and the power energy error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit; Monitoring the temperature of each monitoring node in the building power distribution circuit, and determining a fluctuation trend of impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal; Based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature, coupling correction is performed on the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit to obtain corrected electric energy data of each monitoring node in the building distribution circuit; The method of performing a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation feature and the power energy error feature, and then obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit specifically includes: Determining a monitoring node group where electric energy in the building power distribution circuit is offset based on the impedance-load rate correlation characteristic and the electric energy error characteristic; Correlating the power errors of the monitoring nodes in the building power distribution circuit by using the monitoring node group to obtain correlation correction values ​​of the power errors of the monitoring nodes in the building power distribution circuit; Determine the power influence coefficient between each monitoring node in the building power distribution circuit; Determine the optimal distribution ratio of the correction amount when performing error correction on the electric energy of each monitoring node in the building power distribution circuit based on all associated correction amounts and all electric energy influence coefficients; The method of determining the monitoring node group where the electric energy in the building power distribution circuit is offset based on the impedance-load rate correlation characteristic and the electric energy error characteristic specifically includes: fusing the impedance-load rate correlation feature and the electric energy error feature to obtain a feature fusion vector; Determining a plurality of similar monitoring node groups of electric energy in a building power distribution circuit according to the feature fusion vector; The monitoring node group where the electric energy in the building power distribution circuit is offset is determined through all similar monitoring node groups.

2. The method according to claim 1, wherein Performing steady-state harmonic analysis on the electric energy signal to obtain the electric energy error characteristics in the building power distribution circuit specifically includes: Converting the electric energy signal into a frequency domain signal; extracting the amplitude and phase of the fundamental wave from the frequency domain signal; Extracting the amplitude and phase of each harmonic from the frequency domain signal; The electric energy error characteristics in the building power distribution circuit are determined based on the amplitude and phase of the fundamental wave combined with the amplitude and phase of each harmonic.

3. The method according to claim 1, wherein: Extracting the impedance-load rate correlation feature of the building power distribution circuit from the historical power operation data of the building power distribution circuit specifically includes: Obtaining historical power operation data of the building's power distribution circuit; Determining impedance information and load rate information of each monitoring node in the building power distribution circuit based on the historical power operation data; Correlation analysis is performed on the impedance information and load rate information of each monitoring node to obtain impedance-load rate correlation characteristics in the building power distribution circuit.

4. The method according to claim 1, wherein: Determining the fluctuation trend of the impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal specifically includes: determining an impedance change trend of each monitoring node according to the voltage signal and the current signal; Determine the temperature change trend of each monitoring node based on all temperatures obtained by monitoring; The fluctuation trend of the impedance in the building power distribution circuit as it changes with temperature is determined through all impedance change trends and all temperature change trends.

5. The method according to claim 1, wherein: Based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature, the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit are coupled and corrected, and the corrected electric energy data of each monitoring node in the building distribution circuit are obtained, which specifically includes: Determining coupling correction amounts for energy metering errors of each group of adjacent monitoring nodes in a building power distribution circuit based on all optimal distribution ratios and fluctuation trends of the impedance as it changes with temperature; The electric energy in the building distribution circuit is corrected according to all coupling correction amounts, and the corrected electric energy data of each monitoring node in the building distribution circuit is obtained.

6. The method according to claim 1, wherein: The various monitoring nodes include power supply monitoring nodes, docking point monitoring nodes, distribution cabinet monitoring nodes, power equipment monitoring nodes, and switch box monitoring nodes.

7. The method according to claim 1, wherein: The temperature of each sensing monitoring node in the building's power distribution circuit is monitored by temperature sensors.

8. A building electricity metering error correction system, which uses the method according to any one of claims 1 to 7 to perform building electricity metering error correction, characterized in that: The system includes: A monitoring module is used to monitor the voltage signal and current signal of each monitoring node in the building power distribution circuit through the voltage transformer and current transformer pre-installed in the building power distribution circuit monitoring node, and then determine the power signal of the building power distribution circuit; a processing module configured to perform steady-state harmonic analysis on the electric energy signal to obtain an electric energy error characteristic in the building power distribution circuit, and extract an impedance-load rate correlation characteristic in the building power distribution circuit from historical power operation data of the building power distribution circuit; The processing module is further configured to perform a global correlation analysis on the power energy errors of each monitoring node in the building power distribution circuit based on the impedance-load ratio correlation feature and the power energy error feature, thereby obtaining an optimal distribution ratio of the correction amount when performing error correction on the power energy of each monitoring node in the building power distribution circuit; The processing module is further configured to monitor the temperature of each monitoring node in the building power distribution circuit, and determine a fluctuation trend of impedance in the building power distribution circuit as it changes with temperature based on all monitored temperatures combined with the voltage signal and the current signal; The execution module is used to perform coupling correction on the electric energy metering errors of each group of adjacent monitoring nodes in the building distribution circuit based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature changes, so as to obtain the corrected electric energy data of each monitoring node in the building distribution circuit.

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