Building electric energy metering error correction method and system

Abstract

The invention provides a building electric energy metering error correction method and system, and the method comprises the steps: determining an electric energy signal of a building power distribution loop, thereby determining an electric energy error feature in the building power distribution loop, and extracting an impedance-load rate correlation feature in the building power distribution loop from the historical power operation data of the building power distribution loop; based on the impedance-load rate correlation characteristics and the electric energy error characteristics, determining an optimal distribution ratio of correction values when error correction is carried out on the electric energy of each monitoring node in the building power distribution loop; determining the fluctuation trend of the impedance in the building power distribution loop along with the temperature change according to the temperature of each monitoring node in the monitored building power distribution loop in combination with the voltage signal and the current signal; and determining the corrected electric energy data of each monitoring node in the building power distribution loop based on all the optimal distribution ratios and the fluctuation trend of the impedance along with the temperature change. By adopting the scheme of the invention, the influence of real-time interference responding to load fluctuation and temperature change on electric energy errors in a building power distribution loop can be reduced.

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 the error of building power metering. Background Art

[0002] System error is caused by a certain fixed reason, making the measurement result 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 cannot be completely eliminated. In actual measurement, it is necessary to select a suitable method according to the specific situation to reduce the error, so as to improve the accuracy and reliability of the measurement result.

[0003] With the improvement of the complexity of building electrical systems and the access of distributed energy, the accuracy of power metering faces multiple challenges. The traditional power metering method for building distribution circuits usually relies on local monitoring nodes for monitoring, and is easily affected by factors such as harmonic distortion, dynamic load changes, and environmental temperature fluctuations. For example, nonlinear loads will cause steady-state harmonic pollution, and the nonlinear relationship between load rate changes and line impedance will cause the accumulation of metering errors; at the same time, temperature changes cause conductor impedance drift, further amplifying the errors. Existing technologies mostly use single-parameter compensation or static correction models, lacking a full-loop dynamic analysis of the coupling effect of multiple factors, resulting in insufficient error correction accuracy, affecting energy efficiency management, billing fairness, and grid stability. In addition, the grid connection requirements of distributed energy put forward higher requirements for the real-time performance and anti-interference ability of power metering. Therefore, how to reduce the impact of real-time interference in response to load fluctuations and temperature changes on the power error in building distribution circuits has become a problem faced by the industry. Summary of the Invention

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

[0005] In the first aspect, the present application provides a method for correcting the error of building power metering, including the following steps: Monitoring the voltage signals and current signals of each monitoring node in the building distribution circuit through the voltage transformer and current transformer pre-installed in the monitoring nodes of the building distribution circuit, and then determining the power signal of the building distribution circuit; Performing steady-state harmonic analysis on the power signal, and then obtaining the power error characteristics in the building distribution circuit, and extracting the impedance-load rate correlation characteristics in the building distribution circuit from the historical power operation data of the building distribution circuit; Based on the impedance-load rate correlation feature and the power error feature, globally analyze the power errors of each monitoring node in the building power distribution circuit, and then obtain the optimal distribution ratio of the correction amount when correcting the power errors of each monitoring node in the building power distribution circuit; Monitor the temperatures 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 change according to all the monitored temperatures in combination with the voltage signal and the current signal; Based on all the optimal distribution ratios and the fluctuation trend of the impedance with temperature change, perform coupled correction on the power metering errors of each group of adjacent monitoring nodes in the building power distribution circuit to obtain the corrected power data of each monitoring node in the building power distribution circuit.

[0006] In some embodiments, performing steady-state harmonic analysis on the power signal, and then obtaining the power error feature in the building power distribution circuit specifically includes: Convert the power signal into a frequency-domain signal; Extract the amplitude and phase of the fundamental wave from the frequency-domain signal; Extract the amplitudes and phases of each harmonic from the frequency-domain signal; Determine the power error feature in the building power distribution circuit according to the amplitude and phase of the fundamental wave in combination with the amplitudes and phases of each harmonic.

[0007] 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: Obtain the historical power operation data of the building power distribution circuit; Determine the impedance information and load rate information of each monitoring node in the building power distribution circuit according to the historical power operation data; Perform correlation analysis on the impedance information and load rate information of each monitoring node to obtain the impedance-load rate correlation feature in the building power distribution circuit.

[0008] In some embodiments, globally analyzing the power errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation feature and the power error feature, and then obtaining the optimal distribution ratio of the correction amount when correcting the power of each monitoring node in the building power distribution circuit specifically includes: Based on the impedance-load rate correlation feature and the power error feature, determine the group of monitoring nodes where the power in the building power distribution circuit has shifted; Correlate the power errors of each monitoring node in the building power distribution circuit through the group of monitoring nodes to obtain the correlated correction amount of the power errors of each monitoring node in the building power distribution circuit; Determine the power influence coefficients between each monitoring node in the building power distribution circuit; Determine the optimal allocation ratio of the correction amount when correcting the power of each monitoring node in the building power distribution circuit according to all the associated correction amounts and all the power influence coefficients.

[0009] In some embodiments, determining the group of monitoring nodes with power deviation in the building power distribution circuit based on the impedance-load rate association feature and the power error feature specifically includes: Fuse the impedance-load rate association feature and the power error feature to obtain a feature fusion vector; Determine multiple similar monitoring node groups of power in the building power distribution circuit according to the feature fusion vector; Determine the group of monitoring nodes with power deviation in the building power distribution circuit through all the similar monitoring node groups.

[0010] In some embodiments, determining the fluctuation trend of the impedance varying with temperature in the building power distribution circuit according to all the monitored temperatures in combination with the voltage signal and the current signal specifically includes: Determine the 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 according to all the monitored temperatures; Determine the fluctuation trend of the impedance varying with temperature in the building power distribution circuit through all the impedance change trends and all the temperature change trends.

[0011] In some embodiments, perform coupled correction on the power measurement errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature, and obtain the corrected power data of each monitoring node in the building power distribution circuit, specifically including: Determine the coupled correction amount of the power measurement errors of each group of adjacent monitoring nodes in the building power distribution circuit according to all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature; Correct the power in the building power distribution circuit according to all the coupled correction amounts to obtain the corrected power data of each monitoring node in the building power distribution circuit.

[0012] In some embodiments, each monitoring node includes a power supply monitoring node, a mating point monitoring node, a power distribution cabinet monitoring node, an electrical equipment monitoring node, and a switch box monitoring node.

[0013] In some embodiments, monitor the temperature of each sensing monitoring node in the building power distribution circuit through a temperature sensor.

[0014] In a second aspect, the present application provides a building electrical energy metering error correction system, including: A monitoring module, configured to monitor voltage signals and current signals of each monitoring node in a building power distribution circuit through a voltage transformer and a current transformer pre-installed at the monitoring nodes of the building power distribution circuit, and further determine the electrical energy signal of the building power distribution circuit; A processing module, configured to perform steady-state harmonic analysis on the electrical energy signal, and further obtain the electrical energy error characteristics in the building power distribution circuit, and extract the impedance-load rate correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit; The processing module is further configured to perform global correlation analysis on the electrical energy errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation characteristics and the electrical energy error characteristics, and further obtain the optimal allocation ratio of the correction amount when correcting the electrical 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 the fluctuation trend of the impedance change with temperature in the building power distribution circuit according to all the monitored temperatures in combination with the voltage signal and the current signal; An execution module, configured to perform coupled correction on the electrical energy metering errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all the optimal allocation ratios and the fluctuation trend of the impedance change with temperature, and obtain the corrected electrical energy data of each monitoring node in the building power distribution circuit.

[0015] The technical solution provided by the embodiments disclosed in the present application has the following beneficial effects: In a method and system for correcting building power metering errors provided by this application, first, voltage transformers and current transformers pre-installed at monitoring nodes of building distribution circuits are used to monitor voltage signals and current signals of each monitoring node in the building distribution circuit, and then the power signal of the building distribution circuit is determined; steady-state harmonic analysis is performed on the power signal to obtain the power error characteristics in the building distribution circuit, and the impedance-load rate correlation characteristics in the building distribution circuit are extracted from the historical power operation data of the building distribution circuit; based on the impedance-load rate correlation characteristics and the power error characteristics, global correlation analysis is performed on the power errors of each monitoring node in the building distribution circuit to obtain the optimal distribution ratio of correction amounts when correcting the power of each monitoring node in the building distribution circuit; the temperature of each monitoring node in the building distribution circuit is monitored, and based on all the monitored temperatures, in combination with the voltage signal and the current signal, the fluctuation trend of the impedance changing with temperature in the building distribution circuit is determined; based on all the optimal distribution ratios and the fluctuation trend of the impedance changing with temperature, coupled correction is performed on the power metering errors of each group of adjacent monitoring nodes in the building distribution circuit to obtain the corrected power data of each monitoring node in the building distribution circuit.

[0016] It can be seen that in the process of eliminating errors in building power metering in this application, first, power error characteristics are obtained through steady-state harmonic analysis of power signals, effectively separating the fundamental wave component and the harmonic interference component, revealing the characteristic harmonic distortion law caused by non-linear loads in the power grid, and improving the error identification accuracy; second, impedance-load rate correlation characteristics are extracted from historical power operation data, establishing a dynamic correlation model between load fluctuations and line impedance changes, and capturing the non-linear change law of impedance parameters under different load conditions; then, based on the impedance-load rate correlation characteristics and the power error characteristics, global correlation analysis is performed to obtain the optimal distribution ratio, constructing a multi-monitoring node error coupling network model to achieve the optimal distribution of correction energy in the spatial dimension and avoid system oscillation caused by local overcorrection; then, the temperature of the monitoring node is monitored and combined with the electrical signal to determine the impedance fluctuation trend, establishing a three-dimensional dynamic relationship model of temperature-impedance-power error, and quantifying the influence mechanism of the conductor material temperature coefficient on the line parameters; finally, based on the optimal distribution ratio and the impedance temperature fluctuation trend, coupled correction is performed on the power error of the building distribution circuit to obtain the corrected power data of each monitoring node in the building distribution circuit, realizing collaborative compensation under the dual interference of load fluctuation and temperature change, and dynamically adjusting the correction parameters through the time-varying weight distribution algorithm to achieve the balance optimization of error suppression and system stability. By adopting the above solution, the influence of real-time interference in response to load fluctuation and temperature change on the power error in the building distribution circuit can be reduced. Description of the Drawings

[0017] Figure 1It is an exemplary flowchart of a method for correcting building power metering errors shown in some embodiments of the present application; Figure 2 It is an exemplary flowchart of determining the characteristics of power error shown in some embodiments of the present application; Figure 3 It is an exemplary flowchart of determining the fluctuation trend of impedance varying with temperature shown in some embodiments of the present application; Figure 4 It is a schematic structural diagram of a building power metering error correction system shown in some embodiments of the present application; Figure 5 It is a schematic structural diagram of a computer device for implementing a method for correcting building power metering errors shown in some embodiments of the present application. Detailed implementation manners

[0018] To better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0019] Refer to Figure 1 , which is an exemplary flowchart of a method for correcting building power metering errors shown in some embodiments of the present application. The method for correcting building power metering errors 100 mainly includes the following steps: In step 101, the voltage signals and current signals of each monitoring node in the building power distribution circuit are monitored through the voltage transformer and current transformer pre-installed at the monitoring nodes of the building power distribution circuit, and then the power signal of the building power distribution circuit is determined.

[0020] Specifically, when implemented, voltage transformers and current transformers are pre-installed at each monitoring node of the building power distribution circuit. The voltage signals and current signals of each monitoring node in the building power distribution circuit are monitored through the installed voltage transformers and current transformers to obtain the voltage signals and current signals. Among them, 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 power signal is calculated by combining the voltage signal and the current signal according to the basic formula of power. Among them, the power signal represents the signal of the power value of each monitoring node during the monitoring time; in other embodiments, other monitoring methods may also be used, which are not limited here.

[0021] It should be noted that there are multiple monitoring nodes in the building power distribution circuit of the present application. The monitoring nodes include power supply monitoring nodes, mating point monitoring nodes, power distribution cabinet monitoring nodes, electrical equipment monitoring nodes, and switch box monitoring nodes. Each type of monitoring node has multiple types of monitoring nodes. For example, among the electrical equipment monitoring nodes, there are motors, lamps, and communication equipment.

[0022] In step 102, a steady-state harmonic analysis is performed on the electric energy signal, so as to obtain the electric energy error characteristics in the building power distribution circuit, and the impedance-load rate correlation characteristics in the building power distribution circuit are extracted from the historical power operation data of the building power distribution circuit.

[0023] In some embodiments, referring to Figure 2 As shown, this figure is an exemplary flowchart for determining the electric energy error characteristics in some embodiments of the present application. In this embodiment, the steady-state harmonic analysis of the electric energy signal to obtain the electric energy error characteristics in the building power distribution circuit can be implemented by the following steps: First, in step 1021, the electric energy signal is converted into a frequency-domain signal; Secondly, in step 1022, the amplitude and phase of the fundamental wave are extracted from the frequency-domain signal; Furthermore, in step 1023, the amplitude and phase of each harmonic are extracted from the frequency-domain signal; Finally, in step 1024, the electric energy error characteristics in the building power distribution circuit are determined according to the amplitude and phase of the fundamental wave in combination with the amplitude and phase of each harmonic.

[0024] When specifically implemented, the conversion of the electric energy signal into a frequency-domain signal can be implemented in the following manner, that is: the electric energy signal is filtered by a filter to remove high-frequency noise and interference signals, and the processed electric energy signal is obtained, and the processed electric energy signal is converted into a frequency-domain signal through a fast Fourier transform to facilitate the analysis of the characteristics of the electric energy signal in the frequency domain; the extraction of the amplitude and phase information of the fundamental wave from the frequency-domain signal can be implemented in the following manner, that is: the amplitude of the fundamental wave is calculated by the FFT scaling method in the prior art, and the phase of the fundamental wave is calculated by the complex phase angle in the prior art; the extraction of the amplitude and phase of each harmonic from the frequency-domain signal can be implemented in the following manner, that is: in this embodiment, the harmonic orders can be 3, 5, 7, 11, 13, 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 determination of the electric energy error characteristics in the building power distribution circuit according to the amplitude and phase of the fundamental wave in combination with the amplitude and phase of each harmonic can be implemented in the following manner, that is: the theoretical amplitude and theoretical phase corresponding to the electric energy signal are obtained from the database corresponding to the building power distribution circuit, the differences between the amplitude and phase of the fundamental wave and the corresponding theoretical amplitude and theoretical phase are calculated, the differences between the amplitude and phase of each harmonic and the corresponding theoretical amplitude and theoretical phase are calculated, and all the differences calculated above are used as the electric energy error characteristics in the building power distribution circuit; in other embodiments, other methods can also be used for determination, which are not limited here.

[0025] It should be noted that the power error feature in this application represents the feature of the power error degree in the building power distribution circuit, which can be used to evaluate the power quality and thus provide a scientific basis for the improvement of power quality.

[0026] In some embodiments, the impedance-load rate correlation feature in the building power distribution circuit can be extracted from the historical power operation data of the building power distribution circuit by the following steps: Obtain the historical power operation data of the building power distribution circuit; Determine the impedance information and load rate information of each monitoring node in the building power distribution circuit according to the historical power operation data; Perform correlation analysis on the impedance information and load rate information of each monitoring node to obtain the impedance-load rate correlation feature in the building power distribution circuit.

[0027] Specifically, the historical power operation data of the building power distribution circuit can be obtained in the following way, that is: obtain the historical power operation data of the building power distribution circuit from the database of the building power distribution circuit, where the historical power operation data includes historical voltage, current, and power data; the impedance information and load rate information of each monitoring node in the building power distribution circuit can be determined according to the historical power operation data in the following way, that is: calculate the average impedance of each monitoring node in the building power distribution circuit during each power acquisition process based on Ohm's law calculation formula combined with the historical voltage and current data in the historical power operation data, and use the set of the average impedance of each monitoring node in the building power distribution circuit during each power acquisition process as the impedance information of the corresponding monitoring nodes in the building power distribution circuit, where the impedance information represents the information of the impedance of each monitoring node in the building power distribution circuit, calculate the average load rate of each monitoring node in the building power distribution circuit during each power acquisition process based on the load rate calculation formula combined with the historical power data and the rated power of each monitoring node in the historical power operation data, and use the set of the average load rate of each monitoring node in the building power distribution circuit during each power acquisition process as the load rate information of the corresponding monitoring nodes in the building power distribution circuit, where the load rate represents the information of the load rate of each monitoring node in the building power distribution circuit; in other embodiments, other methods can also be used to determine, which are not limited here.

[0028] In specific implementation, the impedance - load rate correlation characteristics in the building power distribution loop can be obtained by performing correlation analysis on the impedance information and load rate information of each monitoring node in the following way: using statistical methods (such as regression analysis) to establish a correlation model between impedance and load rate, inputting the impedance information and load rate information of each monitoring node into this correlation model, analyzing the change trend of impedance of each monitoring node at different load rates through this correlation model, and using machine learning methods (such as neural networks) to combine the change trend of impedance of each monitoring node at different load rates to establish a non - linear relationship between impedance and load rate in the corresponding monitoring node (i.e., the relative change situation between impedance and load rate), and taking all the non - linear relationships as the impedance - load rate correlation characteristics in the building power distribution loop; in other embodiments, other methods can also be used to determine it, which is not limited here.

[0029] It should be noted that the impedance - load rate correlation characteristics in this application represent the characteristics of the correlation between impedance and load rate in the building power distribution loop, that is: the correlation characteristics of the mutual change situation between impedance and load rate, which can be used to analyze the correlation situation of the real - time impedance and load rate in the building power distribution loop, and further correct the power error in the building power distribution loop.

[0030] In step 103, based on the impedance - load rate correlation characteristics and the power error characteristics, a global correlation analysis is performed on the power errors of each monitoring node in the building power distribution loop, and then the optimal distribution ratio of the correction amount is obtained when correcting the power errors of each monitoring node in the building power distribution loop.

[0031] In some embodiments, the optimal distribution ratio of the correction amount can be obtained by performing the following steps when performing a global correlation analysis on the power errors of each monitoring node in the building power distribution loop based on the impedance - load rate correlation characteristics and the power error characteristics: Determine the group of monitoring nodes where power deviation occurs in the building power distribution loop based on the impedance - load rate correlation characteristics and the power error characteristics; Correlate the power errors of each monitoring node in the building power distribution loop through the group of monitoring nodes to obtain the correlated correction amount of the power errors of each monitoring node in the building power distribution loop; Determine the power influence coefficients between each monitoring node in the building power distribution loop; Determine the optimal distribution ratio of the correction amount when correcting the power errors of each monitoring node in the building power distribution loop according to all the correlated correction amounts and all the power influence coefficients.

[0032] In addition, in some embodiments, determining the monitoring node group where power offset occurs in the building power distribution loop based on the impedance-load rate correlation feature and the power error feature can be achieved by the following steps: Fuse the impedance-load rate correlation feature and the power error feature to obtain a feature fusion vector; Determine multiple similar monitoring node groups of power in the building power distribution loop according to the feature fusion vector; Determine the monitoring node group where power offset occurs in the building power distribution loop through all the similar monitoring node groups.

[0033] It should be noted that in the power distribution network, there is an inherent relationship between the impedance characteristics of each monitoring node and its load rate. Abnormal monitoring nodes will disrupt this normal association model, and power metering deviation will be manifested as a specific error pattern. Abnormalities can be detected through statistical analysis. Therefore, the monitoring node cluster where power offset occurs in the building power distribution loop can be identified through the impedance-load rate correlation feature and the power error feature.

[0034] In specific implementation, fusing the impedance-load rate correlation feature and the power error feature to obtain a feature fusion vector can be achieved in the following way, that is: fuse the impedance-load rate correlation feature and the power error feature through a feature fusion method in the prior art (such as the decision level) to construct a multi-dimensional feature vector (for example: multi-dimensional feature vector = [impedance-load rate correlation feature, power error feature]), and use this multi-dimensional feature vector as the feature fusion vector, where the feature fusion vector represents the vector of the feature fusion of the impedance-load rate and error of power in the building power distribution loop; determining multiple similar monitoring node groups of power in the building power distribution loop according to the feature fusion vector can be achieved in the following way, that is: divide the monitoring nodes corresponding to the same impedance-load rate correlation feature and power error feature in the feature fusion vector into the same group, that is: divide the monitoring nodes corresponding to the same non-linear relationship in the impedance-load rate correlation feature and the same difference in the power error feature into the same group to obtain multiple groups, and regard each group as a similar monitoring node group of power in the building power distribution loop, where the similar monitoring node group represents the monitoring node group with the same power change situation in the building power distribution loop; in other embodiments, other methods can also be used for determination, which is not limited here.

[0035] When specifically implemented, the monitoring node group with power offset in the building power distribution circuit can be determined by all similar monitoring node groups in the following way: judge the differences in the power error characteristics of different similar monitoring node groups, calculate the average value of all the differences in the power error characteristics, compare the differences corresponding to each similar monitoring node group with this average value, extract the differences greater than this average value to find the monitoring node groups with larger power errors, and use the set of similar monitoring node groups corresponding to the extracted differences as the monitoring node group with power offset in the building power distribution circuit; in other embodiments, other methods can also be used to determine, which is not limited here.

[0036] It should be noted that the monitoring node group in this application represents the group of all monitoring nodes with power offset in the building power distribution circuit, which can be used for centralized error analysis of the power in the building power distribution circuit, thereby reducing the workload of eliminating errors in the building power distribution circuit.

[0037] When specifically implemented, the correlation of the power errors of each monitoring node in the building power distribution circuit is performed through the monitoring node group, and the correlation correction amount of the power errors of each monitoring node in the building power distribution circuit can be implemented by the following method, that is: in the building power distribution circuit, the power errors of each monitoring node are not completely independent. The monitoring nodes within the same monitoring node group may have certain statistical correlations in their power errors due to being affected by similar measurement environments, equipment characteristics, and power transmission process factors. The monitoring nodes within 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, calculate the error between its power measurement value and the theoretical value. The theoretical value can be determined through a calculation model based on circuit principles or a statistical model of historical data. For example, calculate the theoretical power values of each monitoring node according to Kirchhoff's laws and circuit parameters, and then compare them with the actual measurement values to obtain the power error of each monitoring node. Use statistical methods such as correlation coefficient and covariance analysis to analyze the correlation between the power errors of each monitoring node within the same monitoring node group, and calculate the correlation coefficient between every two monitoring nodes to quantify the strength and direction of the linear relationship between them. For example, the Pearson correlation coefficient can measure the linear correlation degree between two variables, and its value range is between -1 and 1. The closer the absolute value is to 1, the stronger the correlation. Through clustering analysis and principal component analysis methods of the power errors of each monitoring node, identify the common error components caused by measurement, transmission, or equipment characteristic factors within the same group, and use mathematical methods such as the least squares method and weighted average method to calculate the correlation correction amount of each monitoring node in combination with the common error components. For example, the least squares method can determine the optimal correction amount by minimizing the sum of the squares of the errors, so that the power errors of each monitoring node after correction are as close as possible to the true value. Specifically, if it is found that the error of a certain monitoring node has a strong correlation with other monitoring nodes and the common error components are obvious, then when calculating its correlation correction amount, the error conditions of other monitoring nodes within the group and the correlation weights between them will be comprehensively considered to determine the error compensation value that the monitoring node needs to correct; in other embodiments, other methods can also be used to determine, which are not limited here.

[0038] When specifically implemented, the power influence coefficient between each monitoring node in the building power distribution circuit can be determined by the following method, that is: analyze the physical connection relationship, load distribution, and power transmission characteristics between each monitoring node in the building power distribution circuit, establish a mathematical model, and through sensitivity analysis or regression model methods, quantify the influence degree of the error of one monitoring node on other monitoring nodes, and use the quantified values of the influence degrees of each monitoring node as the power influence coefficients between the corresponding monitoring nodes. The power influence coefficient reflects the weight or proportion of the error propagation in the entire network.

[0039] In specific implementation, to determine the optimal allocation ratio of the correction quantity for error correction of the electric energy of each monitoring node in the building distribution circuit based on all the correlation correction quantities and all the electric energy influence coefficients, the following method can be adopted, that is: The correlation correction quantity is calculated based on the statistical correlation and common error components among the errors of each monitoring node within 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 quantity, it is necessary to adjust the correction quantity allocation of each monitoring node in combination with the correlation correction quantity to fully consider the internal 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 for 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 quantity 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 for important monitoring nodes; By reasonably allocating the correction quantity, the total error of the electric energy measurement of each monitoring node in the entire building distribution circuit is minimized. This means that it is necessary to comprehensively consider the error situation of each monitoring node and its influence on the overall distribution system, and find an optimal allocation scheme so that after correction, the electric energy measurement values of each monitoring node are as close as possible to the true values, thereby improving the accuracy of the electric energy metering of the entire distribution system. As a preferred embodiment, the correlation correction quantity and the electric energy influence coefficient are standardized, and they are converted into numerical values with the same dimension and value range for unified calculation and comparison. For example, the normalization method can be used to divide the correlation correction quantity and the electric energy influence coefficient of each monitoring node by their maximum values respectively, so that their value ranges are both between 0 and 1. Build an optimization model with the goal of minimizing the total error (such as the sum of squared errors) remaining after error correction of the entire distribution circuit, while satisfying the actual constraints of energy conservation, system balance, and equipment calibration. Use all the correlation correction quantities and electric energy influence coefficients obtained after standardization as model parameters, and through linear programming, the least squares method, or other numerical optimization algorithms, solve the optimal allocation ratio of the correction quantity for each monitoring node; In other embodiments, other methods can also be used to determine, which are not limited here.

[0040] It should be noted that the optimal allocation ratio in this application represents the parameter value of the optimal allocation degree of the correction quantity for error correction of the electric energy of the monitoring nodes in the building distribution circuit, and can be used for error correction of the electric energy in the building distribution circuit to achieve the best correction effect.

[0041] In step 104, monitor the temperatures of all monitoring nodes in the building power distribution circuit, and determine the fluctuation trend of the impedance varying with temperature in the building power distribution circuit based on all the monitored temperatures in combination with the voltage signal and the current signal.

[0042] When specifically implemented, the monitoring of the temperatures of all monitoring nodes in the building power distribution circuit can be achieved by the following method, that is: arrange a sensing monitoring node at each monitoring node, monitor the temperatures of all sensing monitoring nodes in the building power distribution circuit through temperature sensors, and use the temperatures of all sensing monitoring nodes as the temperatures of the corresponding monitoring nodes; in other embodiments, it can also be determined by other methods, which are not limited here.

[0043] In some embodiments, refer to Figure 3 As shown, this figure is an exemplary flowchart for determining the fluctuation trend of impedance varying with temperature in some embodiments of the present application. In this embodiment, in some embodiments, the determination of the fluctuation trend of the impedance varying with temperature in the building power distribution circuit based on all the monitored temperatures in combination with the voltage signal and the current signal can be achieved by the following steps: First, in step 1041, determine the impedance change trend of each monitoring node according to the voltage signal and the current signal; Secondly, in step 1042, determine the temperature change trend of each monitoring node according to all the monitored temperatures; Finally, in step 1043, determine the fluctuation trend of the impedance varying with temperature in the building power distribution circuit through all the impedance change trends and all the temperature change trends.

[0044] In specific implementation, the impedance change trend of each monitoring node can be determined according to the voltage signal and the current signal in the following way: 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 the impedances through a trend analysis method (such as polynomial regression analysis). Take the result obtained from the trend analysis as the impedance change trend of the selected monitoring node, and continue to determine the impedance change trends of the remaining monitoring nodes. Herein, the impedance change trend represents the characteristics of the change trend of the impedance of the monitoring node over time. The temperature change trend of each monitoring node can be determined according to all the monitored temperatures in the following way: select a monitoring node as the selected monitoring node, extract all the temperatures of the selected monitoring node from all the monitored temperatures, arrange all the extracted temperatures in the order of the monitoring time, take the arranged sequence as the temperature sequence of the selected monitoring node, perform trend analysis on the temperatures in the temperature sequence in the arranged order through a trend analysis method (such as polynomial regression analysis), and take the result obtained from the trend analysis as the temperature change trend of the selected monitoring node, and continue to determine the temperature change trends of the remaining monitoring nodes. In fact, the temperature change trend represents the change trend of the temperature of each monitoring node over time. In other embodiments, it can also be determined in other ways, which are not limited herein.

[0045] In specific implementation, the fluctuation trend of the impedance with respect to temperature in the building power distribution circuit can be determined according to all the impedance change trends and all the temperature change trends in the following way: Impedance is the hindrance to alternating current in a circuit, and its magnitude is related to factors such as the resistivity and geometric dimensions of the conductor. Temperature affects the resistivity of the conductor, thereby changing the impedance. Generally, an increase in temperature will lead to an increase in resistivity and also an increase in impedance, and vice versa. Select a monitoring node as the selected monitoring node, perform spatio-temporal alignment processing on the impedance change trend and temperature change trend of the selected monitoring node to associate the impedance change trend and temperature change trend, and analyze the change trend between the impedance change trend and temperature change trend after association through a trend fluctuation analysis method. Take this change trend as the change trend of the impedance with respect to temperature in the selected monitoring node, and continue to determine the change trend of the impedance with respect to temperature in the remaining monitoring nodes. Take all the change trends as the fluctuation trend of the impedance with respect to temperature in the building power distribution circuit. In other embodiments, it can also be determined in other ways, which are not limited herein.

[0046] It should be noted that the fluctuation trend in this application represents the trend of the fluctuation degree of the impedance with respect to temperature in the building power distribution circuit, and can be used to correct the impedance change in the building power distribution circuit, thereby reducing the influence of temperature on the measurement of electric energy in the building power distribution circuit.

[0047] In step 105, based on all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature, the power metering errors of each group of adjacent monitoring nodes in the building power distribution loop are coupled and corrected to obtain the corrected power data of each monitoring node in the building power distribution loop.

[0048] In some embodiments, based on all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature, the coupling and correction of the power metering errors of each group of adjacent monitoring nodes in the building power distribution loop to obtain the corrected power data of each monitoring node in the building power distribution loop can be implemented by the following steps: Determine the coupling correction amount of the power metering errors of each group of adjacent monitoring nodes in the building power distribution loop according to all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature; Correct the power in the building power distribution loop according to all the coupling correction amounts to obtain the corrected power data of each monitoring node in the building power distribution loop.

[0049] In specific implementation, the coupling correction amount of the power metering error of each group of adjacent monitoring nodes in the building power distribution loop can be determined according to all the optimal distribution ratios and the fluctuation trend of the impedance varying with temperature, which can be implemented in the following manner: In the building power distribution loop, 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 this monitoring node. According to Kirchhoff's voltage law (KVL), the sum of the voltage drops along any closed loop is zero. When the impedance varies with temperature, it will cause changes in the current and voltage distributions in the loop, thereby affecting the calculation of electric energy. Since the adjacent monitoring nodes are connected by lines, 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 power distribution loop, which reflects the proportional relationship of power distribution between each branch under ideal conditions. When the impedance varies 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, compare the actual power distribution of each monitoring node with the optimal distribution ratio, calculate the power error of each monitoring node relative to the optimal distribution state, and generate a power error vector for all the power errors. Considering that the impedance changes between adjacent monitoring nodes will affect each other, establish a coupling model of power errors according to circuit theory. For example, by analyzing the current and voltage relationships between monitoring nodes and using Kirchhoff's laws and Ohm's law, a system of equations describing the coupling relationship between the power errors of adjacent monitoring nodes can be obtained. This system of equations can be expressed in matrix form as ΔE = C * ΔZ, where ΔE is the power error vector, ΔZ is the impedance change vector, and C is the coupling coefficient matrix. The elements of the coupling coefficient matrix C reflect the coupling degree of the power errors between adjacent monitoring nodes, which is related to the topological structure of the power distribution loop and line parameter factors. According to the established error coupling model, combined with the fluctuation amount ΔZ of the impedance varying with temperature obtained by actual measurement, solve the system of equations to obtain the coupling correction amount ΔE of the power metering error. The specific solution method can adopt numerical calculation methods such as matrix inversion and iterative method. For example, if the coupling coefficient matrix C and the impedance change vector ΔZ are known, the coupling correction amount of the power metering error can be calculated by ΔE = C * ΔZ; In other embodiments, other methods can also be used to determine, which are not limited here.

[0050] In specific implementation, the electric energy in the building power distribution circuit is corrected according to all the coupling correction amounts. The corrected electric energy data of each monitoring node in the building power distribution circuit can be implemented in the following manner, 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 already 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 already 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 already corrected adjacent monitoring nodes on the current monitoring node. According to the determined correction order, the above correction operations are 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, it can also be determined in other ways, which are not limited here.

[0051] 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: 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; 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 rate correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit; It should be noted that in the present application, the processing module 402 is further configured to perform a global correlation analysis on the power errors of each monitoring node in the building power distribution loop based on the impedance-load ratio correlation feature and the power error feature, so as to obtain the optimal allocation ratio of the correction amount when correcting the power errors of each monitoring node in the building power distribution loop; In addition, it should be noted that in the present application, the processing module 402 is further configured to monitor the temperature of each monitoring node in the building power distribution loop, and determine the fluctuation trend of the impedance in the building power distribution loop with temperature change according to all the monitored temperatures in combination with the voltage signal and the current signal; Execution module 403. In the present application, the execution module 403 is mainly configured to perform coupled correction on the power metering errors of each group of adjacent monitoring nodes in the building power distribution loop based on all the optimal allocation ratios and the fluctuation trend of the impedance with temperature change, so as to obtain the corrected power data of each monitoring node in the building power distribution loop.

[0052] In addition, the present application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned method for correcting building power metering errors.

[0053] In some embodiments, refer to Figure 5 , this figure is a schematic structural diagram of a computer device for implementing a method for correcting building power metering errors according to some embodiments of the present application. The method for correcting building power metering errors in the above embodiments can be implemented by Figure 5 The computer device shown. The computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0054] The processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0055] The communication bus 502 can be used to transmit information between the above components.

[0056] The memory 503 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 503 can exist independently and be connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0057] Among them, the memory 503 is used to store the program code for executing the solution of this application and is controlled by the processor 501 for execution. The processor 501 is used to execute the program code stored in the memory 503. The program code can include one or more software modules. The methods used in the above embodiments can be implemented by one or more software modules in the program code in the processor 501 and the memory 503.

[0058] 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 networks (WLAN), etc.

[0059] In a specific implementation, as an embodiment, the computer device can include multiple processors, and each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0060] The computer device described above can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a desktop computer, a laptop 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 the present application do not limit the type of the computer device.

[0061] In addition, the present application also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for correcting the building electrical energy metering error.

[0062] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0063] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A method for correcting the metering error of building electric energy, characterized in that, It includes the following steps: Monitor the voltage signals and current signals 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 electric energy signal of the building power distribution circuit; Conduct 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 rate correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit; Based on the impedance-load rate correlation characteristics and the electric energy error characteristics, conduct global correlation analysis on the electric energy errors of each monitoring node in the building power distribution circuit, and then obtain the optimal distribution ratio of the correction amount when correcting the electric energy of each monitoring node in the building power distribution circuit; Monitor the temperature of each monitoring node in the building power distribution circuit, and determine the fluctuation trend of the impedance changing with temperature in the building power distribution circuit according to 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 changing with temperature, conduct coupled correction on the electric energy measurement errors of each group of adjacent monitoring nodes in the building power distribution circuit to obtain the corrected electric energy data of each monitoring node in the building power distribution circuit.

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

3. The method according to claim 1, characterized in that, Extracting the impedance-load rate correlation characteristics in the building power distribution circuit from the historical power operation data of the building power distribution circuit specifically includes: Obtain the historical power operation data of the building power distribution circuit; Determine the impedance information and load rate information of each monitoring node in the building power distribution circuit according to the historical power operation data; Conduct correlation analysis on the impedance information and load rate information of each monitoring node to obtain the impedance-load rate correlation characteristics in the building power distribution circuit.

4. The method according to claim 1, wherein Based on the impedance-load rate correlation characteristics and the electric energy error characteristics, conducting global correlation analysis on the electric energy errors of each monitoring node in the building power distribution circuit to obtain the optimal distribution ratio of the correction amount when correcting the electric energy of each monitoring node in the building power distribution circuit specifically includes: Based on the impedance-load rate correlation characteristics and the electric energy error characteristics, determine the monitoring node group where the electric energy in the building power distribution circuit deviates; Correlate the electric energy errors of each monitoring node in the building power distribution circuit through the monitoring node group to obtain the correlation correction amount of the electric energy errors of each monitoring node in the building power distribution circuit; Determine the electric energy influence coefficient between each monitoring node in the building power distribution circuit; Determine the optimal distribution ratio of the correction amount when correcting the electric energy of each monitoring node in the building power distribution circuit according to all the correlation correction amounts and all the electric energy influence coefficients.

5. The method according to claim 4, wherein Determining the monitoring node group where power deviation occurs in the building power distribution circuit based on the impedance-load rate correlation feature and the power error feature specifically includes: Fusing the impedance-load rate correlation feature and the power error feature to obtain a feature fusion vector; Determining multiple similar monitoring node groups of power in the building power distribution circuit according to the feature fusion vector; Determining the monitoring node group where power deviation occurs in the building power distribution circuit through all the similar monitoring node groups.

6. The method according to claim 1, wherein Determining the fluctuation trend of the impedance changing with temperature in the building power distribution circuit according to all the monitored temperatures in combination with the voltage signal and the current signal specifically includes: Determining the impedance change trend of each monitoring node according to the voltage signal and the current signal; Determining the temperature change trend of each monitoring node according to all the monitored temperatures; Determining the fluctuation trend of the impedance changing with temperature in the building power distribution circuit through all the impedance change trends and all the temperature change trends.

7. The method according to claim 1, wherein Performing coupling correction on the power metering errors of each group of adjacent monitoring nodes in the building power distribution circuit based on all the optimal allocation ratios and the fluctuation trend of the impedance changing with temperature to obtain the corrected power data of each monitoring node in the building power distribution circuit specifically includes: Determining the coupling correction amount of the power metering errors of each group of adjacent monitoring nodes in the building power distribution circuit according to all the optimal allocation ratios and the fluctuation trend of the impedance changing with temperature; Correcting the power in the building power distribution circuit according to all the coupling correction amounts to obtain the corrected power data of each monitoring node in the building power distribution circuit.

8. The method according to claim 1, wherein Each monitoring node includes a power supply monitoring node, a mating point monitoring node, a power distribution cabinet monitoring node, an electrical equipment monitoring node, and a switch box monitoring node.

9. The method according to claim 1, wherein Monitoring the temperature of each sensing monitoring node in the building power distribution circuit through a temperature sensor.

10. An architectural electric energy metering error correction system, characterized in that, Including: A monitoring module, configured to monitor the voltage signal and the current signal of each monitoring node in the building power distribution circuit through the voltage transformer and the current transformer pre-installed in the monitoring nodes of the building power distribution circuit, and further determine the power signal of the building power distribution circuit; A processing module, configured to perform steady-state harmonic analysis on the power signal, and further obtain the power error feature in the building power distribution circuit, and extract the impedance-load rate correlation feature in the building power distribution circuit from the historical power operation data of the building power distribution circuit; The processing module is further configured to perform global correlation analysis on the power errors of each monitoring node in the building power distribution circuit based on the impedance-load rate correlation feature and the power error feature, and further obtain the optimal allocation ratio of the correction amount when correcting the power errors 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 the fluctuation trend of the impedance changing with temperature in the building power distribution circuit according to all the monitored temperatures in combination with the voltage signal and the current signal; An execution module, configured to perform coupled correction on the power metering errors of each group of adjacent monitoring nodes in a building power distribution loop based on all the optimal allocation ratios and the fluctuation trend of the impedance varying with temperature, so as to obtain the corrected power data of each monitoring node in the building power distribution loop.

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