Electric energy metering misalignment monitoring method, device, system and electronic equipment

Abstract

This application discloses a method, device, system, and electronic equipment for monitoring meter metering inaccuracies, belonging to the field of power technology. The method includes: determining whether there are metering inaccuracies in the target metering box based on metering data from a first target monitoring period; obtaining the error coefficient corresponding to the meter based on the actual value of the second active power of each meter in the first target monitoring period and the power deviation rate of the target metering box; obtaining a predicted value of the power deviation rate for the second target monitoring period if the correlation between the metering data of the first target monitoring period and the metering data of the second target monitoring period is less than or equal to a first threshold; and determining whether the metering is inaccurate based on the actual value and the predicted value of the power deviation rate for the second target monitoring period. The metering inaccuracies monitoring method, device, system, and electronic equipment disclosed in this application can achieve more real-time and accurate monitoring of metering inaccuracies.

Description

Technical Field

[0001] This application belongs to the field of power technology, and in particular relates to a method, device, system and electronic equipment for monitoring meter metering inaccuracies. Background Technology

[0002] In related technologies, electricity meters are key devices used in power systems to measure electrical energy. The accuracy of electricity meter measurement directly affects the electricity billing of power companies and the electricity costs for users. However, in actual operation, due to various factors, electricity meters may experience measurement inaccuracies.

[0003] Traditional methods for testing the accuracy of electricity meters mainly rely on periodic laboratory verification or on-site calibration. However, this method is not only labor-intensive but also unable to monitor the operating status and metering accuracy of electricity meters in real time. Existing online monitoring methods that can monitor the metering accuracy of electricity meters in real time mainly include the transformer area energy balance method, the electricity consumption state clustering method, and the evaluation system construction method. The transformer area energy balance method for locating low-voltage side metering inaccuracies is easily affected by factors such as line losses and transformer area changes, resulting in poor stability of monitoring results and a tendency for errors. Furthermore, it relies on long-term data series, making online monitoring insufficiently timely. The electricity consumption state clustering method can only identify and correct sudden abnormal data in the short term, but it is difficult to accurately locate meters that gradually become inaccurate during normal operation, resulting in poor monitoring accuracy. The evaluation system construction method involves a strong degree of subjectivity, resulting in insufficient objectivity and poor accuracy of the monitoring results. In summary, how to achieve real-time and accurate monitoring of metering inaccuracies in electricity meters has become a pressing technical challenge in this field. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a method, device, system, and electronic equipment for monitoring meter metering inaccuracies, which can achieve more real-time and accurate monitoring of metering inaccuracies.

[0005] In a first aspect, this application provides a method for monitoring metering inaccuracies in electricity meters, the method comprising: Based on the metering data of the first target monitoring cycle, it is determined whether there are any inaccurate electricity meters in the target electricity meter metering box; the metering data includes the first active power of the target electricity meter metering box and the second active power measured by each electricity meter; In the event that an inaccurate energy meter exists within the target energy meter metering box, the error coefficient corresponding to the energy meter is obtained based on the actual value of the second active power of each energy meter in the first target monitoring cycle and the power deviation rate of the target energy meter metering box, respectively. The correlation between the metering data of the first target monitoring cycle and the metering data of the second target monitoring cycle is also determined. The power deviation rate of the target energy meter metering box is used to indicate the degree of deviation between the first active power and the sum of each second active power in one monitoring cycle. The second target monitoring cycle is the first monitoring cycle following the first target monitoring cycle. When the correlation is less than or equal to the first threshold, the predicted value of the power deviation rate of the second target monitoring period corresponding to the power meter is obtained based on the error coefficient corresponding to each of the power meters and the second active power of the second target monitoring period. Based on the actual value of the power deviation rate during the second target monitoring period and the predicted value of the power deviation rate during the second target monitoring period for each of the energy meters, it is determined whether the energy meter is inaccurate.

[0006] According to the electricity meter metering inaccuracy monitoring method of this application, electricity meter metering inaccuracy monitoring is carried out by whole-box metering based on electricity meter metering boxes. By using the active power data of each monitoring cycle of the electricity meter metering box and each electricity meter, a mathematical model is constructed to determine whether the electricity meter is inaccurate. This method can achieve more real-time and more accurate monitoring of electricity meter metering inaccuracy. Furthermore, it can be implemented using the edge computing capabilities of the power collection terminal, and has the advantages of strong real-time performance and high accuracy. It can provide strong support for the intelligent and refined construction of electricity meter metering boxes, as well as line loss analysis and electricity theft investigation.

[0007] According to one embodiment of this application, determining whether there is a metering inaccuracy in the electricity meter based on the metering data of the first target monitoring period includes: Based on the metering data of the first target monitoring period, obtain the actual value of the power deviation rate of the target energy meter box in the first target monitoring period; If the actual value of the power deviation rate of the target electricity meter box is greater than the second threshold during the first target monitoring period, it is determined that the electricity meter has a metering inaccuracy.

[0008] According to one embodiment of this application, obtaining the actual value of the power deviation rate of the target energy meter box during the first target monitoring period based on the metering data of the first target monitoring period includes: The first difference between the first active power and the sum of each of the second active powers during the first target monitoring period; The ratio of the first difference to the first active power in the first target monitoring period is obtained as the actual value of the power deviation rate of the target energy meter box in the first target monitoring period.

[0009] According to one embodiment of this application, determining the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period includes: Obtain the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the correlation coefficient is used to indicate the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0010] According to one embodiment of this application, the correlation coefficient is the Pearson correlation coefficient.

[0011] According to one embodiment of this application, the error coefficient corresponding to the energy meter is obtained based on the actual value of the second active power of the energy meter in each of the first target monitoring cycles and the power deviation rate of the target energy meter metering box, including: For each of the aforementioned energy meters, the actual value of the power deviation rate of the target energy meter metering box during the first target monitoring period is obtained as the ratio of the second active power of the energy meter, which is used as the error coefficient corresponding to the energy meter.

[0012] According to one embodiment of this application, obtaining the predicted value of the power deviation rate for the second target monitoring period corresponding to each of the energy meters, based on the error coefficient corresponding to each energy meter and the second active power for the second target monitoring period, includes: For each of the aforementioned energy meters, the product of the error coefficient corresponding to the energy meter and the second active power of the energy meter in the second target monitoring period is obtained, and used as the predicted value of the power deviation rate of the energy meter in the second target monitoring period.

[0013] According to one embodiment of this application, determining whether the energy meter is inaccurate based on the actual value of the power deviation rate during the second target monitoring period and the predicted value of the power deviation rate during the second target monitoring period for each energy meter includes: Based on the metering data of the second target monitoring period, obtain the actual value of the power deviation rate of the target energy meter box of the second target monitoring period; For each of the aforementioned energy meters, the ratio of the second difference to the actual value of the power deviation rate of the target energy meter metering box during the second target monitoring period is obtained as the prediction error rate corresponding to the energy meter; the second difference is the difference between the predicted value and the actual value of the power deviation rate corresponding to the energy meter during the second target monitoring period. If the prediction error rate corresponding to the electricity meter is less than the third threshold, the electricity meter is determined to be inaccurate.

[0014] According to one embodiment of this application, before determining whether there is a malfunctioning energy meter in the target energy meter box based on the metering data of the first target monitoring cycle, the method includes: The first target monitoring cycle is used to obtain the frozen active power data of the smart measuring terminal set in the target energy meter meter box as the first active power, and the first target monitoring cycle is used to obtain the frozen active power data of each energy meter as the second active power.

[0015] According to one embodiment of this application, after determining whether the electricity meter is inaccurate, the method further includes: In the event of at least one of the aforementioned electricity meters being inaccurate, a warning message is reported to the main station; the warning message is used to indicate the information of the electricity meter in the target electricity meter box that is inaccurate.

[0016] Secondly, this application provides a device for monitoring meter metering inaccuracies, the device comprising: The first determining module is used to determine whether there is an inaccurate energy meter in the target energy meter box based on the metering data of the first target monitoring cycle; the metering data includes the first active power of the target energy meter box and the second active power measured by each of the energy meters; The first acquisition module is used to acquire the error coefficient corresponding to the energy meter based on the actual value of the second active power of the energy meter in each of the first target monitoring cycles and the power deviation rate of the target energy meter meter box when there is an energy meter with inaccurate metering in the target energy meter meter box; the power deviation rate of the target energy meter meter box is used to indicate the degree of deviation between the first active power and the sum of each second active power in one monitoring cycle; The second determining module is used to determine the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the second target monitoring period is the first monitoring period after the first target monitoring period; The second acquisition module is used to acquire the predicted value of the power deviation rate of the second target monitoring period corresponding to the energy meter based on the error coefficient corresponding to each energy meter and the second active power of the second target monitoring period when the correlation is less than or equal to the first threshold. The third determining module is used to determine whether the electricity meter is inaccurate based on the actual value of the power deviation rate in the second target monitoring period and the predicted value of the power deviation rate in the second target monitoring period for each electricity meter.

[0017] According to the electricity meter metering inaccuracy monitoring device of this application, electricity meter metering inaccuracy monitoring is carried out by whole-box metering based on electricity metering boxes. By using the active power data of each monitoring cycle of the electricity metering box and each electricity meter, a mathematical model is constructed to determine whether the electricity meter is inaccurate. It can achieve more real-time and more accurate monitoring of electricity meter metering inaccuracy. Furthermore, it can be realized by utilizing the edge computing capabilities of the power collection terminal. It has the advantages of strong real-time performance and high accuracy, and can provide strong support for the intelligent and refined construction of electricity metering boxes, as well as line loss analysis and electricity theft investigation.

[0018] Thirdly, this application provides an energy meter metering inaccuracy monitoring system, which includes: an energy meter metering inaccuracy monitoring device as described in the second aspect above and at least one intelligent measurement terminal; the intelligent measurement terminal is used to acquire the active power of the energy meter metering box.

[0019] Fourthly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the electricity meter metering inaccuracy monitoring method described in the first aspect above.

[0020] Fifthly, this application provides a non-volatile computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the electricity meter metering inaccuracy monitoring method as described in the first aspect above.

[0021] In a sixth aspect, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the electricity meter metering inaccuracy monitoring method as described in the first aspect.

[0022] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the electricity meter metering inaccuracy monitoring method as described in the first aspect above.

[0023] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0024] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is one of the flowcharts illustrating the method for monitoring meter metering inaccuracies provided in this application. Figure 2 This is a schematic diagram illustrating an application scenario of the electricity meter metering inaccuracy monitoring method provided in this application embodiment; Figure 3 This is the second flowchart illustrating the method for monitoring meter metering inaccuracies provided in this application. Figure 4 This is a schematic diagram of the structure of the electricity meter metering inaccuracy monitoring device provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of the electricity meter metering inaccuracy monitoring system provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0026] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0027] The following description, in conjunction with the accompanying drawings, details the method for monitoring meter metering inaccuracies, the device for monitoring meter metering inaccuracies, the electronic device, and the readable storage medium provided in this application, through specific embodiments and application scenarios.

[0028] Among them, the method for monitoring metering inaccuracies can be applied to the terminal, and can be executed by the hardware or software in the terminal.

[0029] The method for monitoring meter metering inaccuracies provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the method. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The following description uses an electronic device as the execution subject to illustrate the method for monitoring meter metering inaccuracies provided in this application embodiment.

[0030] like Figure 1 As shown, the method for monitoring metering inaccuracies includes steps 110, 120, 130, 140, and 150.

[0031] In practical application, this method for monitoring meter metering inaccuracies can be used in situations such as... Figure 2 The scene shown. (As shown) Figure 2 As shown, the electricity meter box contains electricity meters and other equipment, and serves as the property boundary between the power supply company and the user's equipment. A smart metering switch can be installed at the inlet of the electricity meter box. Figure 2 The meter misalignment monitoring device, consisting of an intelligent measurement terminal (not shown in the diagram) and an energy meter misalignment monitoring unit, serves as the main implementer of this energy meter misalignment monitoring method. It periodically collects electrical quantity data from the intelligent measurement terminal and the energy meter in the metering box for analysis and monitoring of energy meter misalignment. The intelligent measurement terminal and the energy meter can remotely interact with the energy meter misalignment monitoring device via HPLC (High-speed Power Line Carrier) dual-mode communication (including high-speed power line carrier communication and high-speed low-power communication). The energy meter misalignment monitoring device can interact with the main station via wireless networks such as 4G / 5G (4th Generation Mobile Communication Technology / 5th Generation Mobile Communication Technology).

[0032] In some embodiments, the power acquisition terminal may include the electricity meter misalignment monitoring device, or the power acquisition terminal may function as the electricity meter misalignment monitoring device. Typically, multiple power acquisition terminals can communicate with the master station through a concentrator. Accordingly, the concentrator may be a Type I concentrator supporting HPLC.

[0033] Figure 2An exemplary case is shown with three electricity meter boxes and six electricity meters installed in each electricity meter box, but the electricity meter inaccuracy monitoring method can be applied to a case with at least one electricity meter box and at least one electricity meter installed in each electricity meter box.

[0034] It should be noted that the electricity meter metering inaccuracy monitoring method provided in this application is a method for detecting and monitoring electricity meter metering inaccuracy based on big data analysis. With the construction of smart grids and the widespread application of electricity consumption information collection systems, a large amount of electricity meter data can be collected in real time, which is the technical basis for real-time detection and monitoring of electricity meter metering inaccuracy.

[0035] Step 110: Based on the metering data of the first target monitoring cycle, determine whether there are any inaccurate electricity meters in the target electricity meter metering box; the metering data includes the first active power of the target electricity meter metering box and the second active power measured by each electricity meter.

[0036] In actual implementation, data collection can begin by acquiring metering data for each monitoring cycle. The metering data for each monitoring cycle can include the active power of the target energy meter box and the active power measured by each energy meter within that box. The active power of the target energy meter box is recorded as the first active power, and the active power measured by each energy meter is recorded as the second active power. It is understandable that... Figure 2 Any of the electricity meter boxes in the list can be used as the target electricity meter box.

[0037] In some embodiments, the first active power of the target electricity meter box in a monitoring cycle can be obtained through a smart measurement terminal in the electricity meter box or by other means.

[0038] It should be noted that the second active power measured by the energy meter in a monitoring cycle is the amount of electricity the energy meter has consumed in that monitoring cycle.

[0039] The method for collecting the active power of the target electricity meter box and the electricity consumption of the electricity meter in a monitoring cycle can be any conventional method, and the embodiments of this application do not limit this method.

[0040] The duration of the monitoring cycle can be set according to actual conditions, such as 15 minutes or 30 minutes. This application does not limit the specific value of the monitoring cycle duration.

[0041] In some embodiments, according to relevant standards and specifications in the field of power data acquisition, the master station can issue a 15-minute active power freeze curve acquisition task to the power data acquisition terminal. The power data acquisition terminal can then acquire and store the 15-minute active power curves of the smart metering terminals and electricity meters in each metering box within the distribution area, based on this acquisition task. In this embodiment, the monitoring period is 15 minutes, which is compatible with existing power data acquisition terminals without requiring any changes to the terminal's hardware or software.

[0042] In some embodiments, the first target monitoring period can be any monitoring period. In some embodiments, the first target monitoring period can be a monitoring period that has just ended, at which point the next monitoring period for the first target monitoring period has not yet ended.

[0043] In some embodiments, after acquiring the first active power of the target energy meter box and the second active power measured by each energy meter in the target energy meter box during the first target monitoring period, the power deviation of the target energy meter box can be calculated. By calculating the power deviation of the target energy meter box, it can be preliminarily determined whether there are any inaccurate energy meters in the target energy meter box. If an inaccurate energy meter is preliminarily located in the target energy meter box, subsequent judgment steps 120 to 140 can be performed.

[0044] It should be noted that, in the implementation of this application, the power deviation of the target energy meter box is the deviation between the first active power of the target energy meter box and the sum of the second active power measured by each energy meter in the target energy meter box within the same monitoring period. If the deviation between the first active power of the target energy meter box and the sum of the second active power measured by each energy meter in the target energy meter box within a monitoring period is large, it can be preliminarily determined that there are energy meters with metering inaccuracies in the target energy meter box; if the deviation between the first active power of the target energy meter box and the sum of the second active power measured by each energy meter in the target energy meter box within a monitoring period is small, it can be temporarily assumed that there are no metering inaccuracies in the energy meters in the target energy meter box.

[0045] In some embodiments, the degree of deviation between the first active power of the target energy meter box during the first target monitoring period and the sum of the second active power measured by each energy meter in the target energy meter box during the first target monitoring period can be calculated and denoted as the actual value of the power deviation rate of the target energy meter box during the first target monitoring period. It is understood that the power deviation rate of the target energy meter box can reflect the degree of power deviation of the target energy meter box, and therefore the power deviation rate of the target energy meter box can be used to indicate the degree of deviation between the first active power and the sum of each second active power in the same monitoring period.

[0046] Step 120: In the case of a metered energy meter with inaccurate metering in the target energy meter metering box, based on the actual value of the second active power of each energy meter in the first target monitoring cycle and the power deviation rate of the target energy meter metering box, obtain the error coefficient corresponding to the energy meter, and determine the correlation between the metering data of the first target monitoring cycle and the metering data of the second target monitoring cycle; the power deviation rate of the target energy meter metering box is used to indicate the degree of deviation between the first active power and the sum of each second active power in a monitoring cycle; the second target monitoring cycle is the first monitoring cycle after the first target monitoring cycle.

[0047] In actual implementation, if it is initially determined that there are inaccurate electricity meters in the target electricity meter box, the error coefficient corresponding to each electricity meter in the target electricity meter box can be calculated separately.

[0048] It should be noted that, for each energy meter in the target energy meter metering box, the corresponding error coefficient can be used to indicate the relationship between the second active power measured by the energy meter and the power deviation of the target energy meter metering box.

[0049] In some embodiments, after step 110, the aforementioned metering data for the next monitoring cycle of the first target monitoring cycle can also be obtained, as well as the first active power of the target energy meter box and the second active power measured by each energy meter for the next monitoring cycle of the first target monitoring cycle. The next monitoring cycle of the first target monitoring cycle is the second target monitoring cycle. It is understood that the method and steps for obtaining the metering data of the second target monitoring cycle are similar to or the same as the method and steps for obtaining the metering data of the first target monitoring cycle, and will not be described again here.

[0050] In some embodiments, after obtaining the measurement data for the second target monitoring period, any feasible method for representing correlation can be used to calculate the correlation between the measurement data for the first target monitoring period and the measurement data for the second target monitoring period.

[0051] It should be noted that if the correlation between the metering data of the first and second target monitoring periods is strong (i.e., a strong correlation exists between the two periods), then the metering data of the second target monitoring period cannot be used to subsequently locate which meter(s) in a specific target meter box are malfunctioning; in other words, the metering data of the second target monitoring period is invalid for locating malfunctioning meters. Conversely, if the correlation between the metering data of the first and second target monitoring periods is weak (i.e., a weak correlation exists between the two periods), then the metering data of the second target monitoring period can be used to subsequently locate which meter(s) in a specific target meter box are malfunctioning; in other words, the metering data of the second target monitoring period is valid for locating malfunctioning meters.

[0052] In some embodiments, whether the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is strong or weak can be determined by comparing whether the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is greater than a first threshold. If the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is greater than the first threshold, it can be determined that the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is strong; if the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is less than or equal to the first threshold, it can be determined that the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is weak.

[0053] It should be noted that the first threshold is a correlation threshold, which can be called the correlation threshold. The first threshold can be determined based on the method used to calculate the correlation between the metering data of the first target monitoring period and the metering data of the second target monitoring period, as well as the actual situation of the electricity meter box and the electricity meter. The specific value of the first threshold is not limited in the embodiments of this application.

[0054] It should be noted that by utilizing the correlation between the metering data of the first target monitoring period and the metering data of the second target monitoring period, it is possible to determine whether the metering data of the second target monitoring period is valid for locating inaccurate electricity meters, thereby removing invalid data and improving the detection rate of inaccurate electricity meters.

[0055] Step 130: When the correlation is less than or equal to the first threshold, obtain the predicted value of the power deviation rate of the second target monitoring period corresponding to each electricity meter based on the error coefficient corresponding to each electricity meter and the second active power of the second target monitoring period.

[0056] In actual implementation, if the correlation between the metering data of the first target monitoring period and the metering data of the second target monitoring period is less than or equal to the first threshold, the power deviation verification of the metering box can be performed for each electricity meter to locate which one or more electricity meters in the target electricity metering box are inaccurate.

[0057] In some embodiments, power deviation verification for each electricity meter may include, based on the error coefficient corresponding to the electricity meter and the second active power measured by the electricity meter in the second target monitoring period, predicting the power deviation rate of the target electricity meter meter box in the second target monitoring period, and calculating the predicted value of the power deviation rate of the target electricity meter meter box corresponding to the electricity meter in the second target monitoring period.

[0058] It should be noted that for each energy meter in the target energy meter metering box, the error coefficient corresponding to that energy meter can be used to indicate the relationship between the second active power measured by that energy meter and the power deviation of the target energy meter metering box. Therefore, by applying this relationship to the second active power measured by that energy meter in the second target monitoring period, the power deviation rate of the target energy meter metering box in the second target monitoring period can be predicted.

[0059] Step 140: Determine whether the electricity meter is inaccurate based on the actual value of the power deviation rate of the second target monitoring cycle and the predicted value of the power deviation rate of the second target monitoring cycle for each electricity meter.

[0060] In actual implementation, power deviation verification is performed on each electricity meter. Based on the error coefficient corresponding to the electricity meter and the second active power measured by the electricity meter in the second target monitoring period, the power deviation rate of the target electricity meter meter box in the second target monitoring period is predicted. Then, based on the deviation between the predicted value of the power deviation rate of the target electricity meter meter box in the second target monitoring period and the actual value of the power deviation rate of the target electricity meter meter box in the second target monitoring period, it can be determined whether the electricity meter is inaccurate. If the deviation between the predicted value and the actual value of the power deviation rate of the target energy meter meter box for the second target monitoring period corresponding to the energy meter is small, it can be determined that the energy meter is inaccurate, i.e., the energy meter is inaccurate. If the deviation between the predicted value and the actual value of the power deviation rate of the target energy meter meter box for the second target monitoring period corresponding to the energy meter is large, it cannot be determined whether the energy meter is inaccurate at this time, and further judgment can be made by waiting for the metering data of the subsequent monitoring period.

[0061] It is understandable that the method and steps for obtaining the actual value of the power deviation rate of the target energy meter box in the second target monitoring cycle are similar to or the same as the method and steps for obtaining the actual value of the power deviation rate of the target energy meter box in the first target monitoring cycle, and will not be repeated here.

[0062] It should be noted that the electricity meter misalignment monitoring method provided in this application embodiment can be an electricity meter misalignment monitoring method that includes "data acquisition - electricity meter misalignment analysis - misalignment early warning". In the electricity meter misalignment analysis, an electricity meter misalignment algorithm based on whole-box metering provided in this application embodiment is used, which includes "power deviation rate calculation of electricity meter box - error coefficient calculation corresponding to electricity meter - determination of whether metering data is valid - power deviation verification of electricity meter box".

[0063] The method for monitoring meter metering inaccuracies provided in this application monitors metering inaccuracies by using whole-box metering based on the metering box. It utilizes active power data from the metering box and each meter in each monitoring cycle to construct a mathematical model to determine whether the metering is inaccurate. This method achieves more real-time and accurate monitoring of metering inaccuracies and can leverage the edge computing capabilities of the power collection terminal. It boasts advantages such as high real-time performance and accuracy, providing strong support for the intelligent and refined construction of metering boxes, as well as line loss analysis and electricity theft investigation.

[0064] It should be noted that the electricity meter misalignment monitoring method provided in this application embodiment monitors electricity meter misalignment based on the whole-box metering of the electricity metering box, which can solve the core pain points of traditional monitoring modes such as poor real-time performance, insufficient accuracy, and reliance on manual labor. The electricity meter misalignment monitoring method provided in this application embodiment uses the centralized electricity metering box as the basic monitoring unit. By synchronously collecting active power data of the electricity metering box and each electricity meter in each monitoring cycle, a multi-dimensional data comparison and error analysis mathematical model is constructed, which can more accurately determine the metering misalignment status of the electricity meter.

[0065] It should be noted that, in terms of technical implementation, the electricity meter inaccuracy monitoring method provided in this application fully utilizes edge computing capabilities, decentralizing core processes such as data acquisition, cleaning, and model calculation to the local end of the electricity meter box. This eliminates the need for large-scale data transmission and centralized computation at a main station, significantly shortening the data processing cycle and ensuring that metering inaccuracies can be identified and triggered within minutes. Compared to traditional methods relying on periodically freezing electricity consumption or manual verification, the active power data from each monitoring cycle is high-frequency and continuous, effectively capturing metering deviations under different load conditions and avoiding misjudgments or omissions caused by load fluctuations or data lag. Furthermore, model algorithms can quantify and correct interference factors such as distribution line losses and / or inherent equipment errors, further improving the accuracy of metering inaccuracy judgment and ensuring that error identification accuracy meets electricity metering management standards.

[0066] It should be noted that, from an application value perspective, the electricity meter miscalculation monitoring method provided in this application not only provides key technical support for the intelligent and refined construction of electricity meter boxes, promoting the transformation of power metering equipment from "passive operation and maintenance" to "active monitoring," but also provides accurate data for distribution area line loss analysis. Furthermore, by locating miscalculated electricity meters, it can distinguish whether abnormal line losses originate from equipment failure or line problems, thus facilitating lean line loss management. In addition, for metering anomalies caused by electricity theft (such as meter stopping and / or slow reading), the electricity meter miscalculation monitoring method provided in this application can also quickly identify abnormal fluctuations in active power, providing technical support for power sector electricity theft investigations, effectively recovering lost electricity, and ensuring fair and economically secure power grid metering.

[0067] In some embodiments of this application, determining whether there is an inaccurate electricity meter based on the metering data of the first target monitoring period includes: obtaining the actual value of the power deviation rate of the target electricity meter metering box of the first target monitoring period based on the metering data of the first target monitoring period.

[0068] In actual implementation, the actual value of the power deviation rate of the target energy meter box in the first target monitoring period can be calculated based on the metering data of the first target monitoring period. The power deviation rate of the target energy meter box in the first target monitoring period can be the ratio of the power deviation of the target energy meter box in the first target monitoring period to the first active power of the target energy meter box in the first target monitoring period.

[0069] If the actual value of the power deviation rate of the target electricity meter box in the first target monitoring cycle is greater than the second threshold, an electricity meter with metering inaccuracy is identified.

[0070] In actual implementation, after obtaining the actual value of the power deviation rate of the target energy meter box in the first target monitoring period, it is possible to determine whether there are any inaccurate energy meters in the target energy meter box by comparing the actual value of the power deviation rate of the target energy meter box in the first target monitoring period with the second threshold.

[0071] In some embodiments, if the actual value of the power deviation rate of the target energy meter box during the first target monitoring period is greater than the second threshold, it can be determined that there is an energy meter with inaccurate metering in the target energy meter box; if the actual value of the power deviation rate of the target energy meter box during the first target monitoring period is less than or equal to the second threshold, it can be considered that no energy meter with inaccurate metering has been found in the target energy meter box.

[0072] It should be noted that the second threshold is the threshold for the power deviation rate of the electricity meter box, which can be called the electricity meter box threshold. The second threshold can be determined according to the actual situation of the electricity meter box and electricity meter and other equipment in the distribution area. The specific value of the second threshold is not limited in the embodiments of this application. For example, the second threshold can be 3% or 5%, etc.

[0073] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, when the actual value of the power deviation rate of the target electricity meter metering box in the first target monitoring period is greater than the second threshold, it is preliminarily determined that there are electricity meters with metering inaccuracy in the electricity metering box. Based on the whole box metering of the electricity metering box, it can more timely and accurately determine the electricity meters with metering inaccuracy in the electricity metering box, thereby achieving more real-time and more accurate monitoring of electricity meter metering inaccuracy.

[0074] In some embodiments of this application, based on the metering data of the first target monitoring period, the actual value of the power deviation rate of the target energy meter box of the first target monitoring period is obtained, including: the first difference between the first active power and the sum of each second active power in the first target monitoring period.

[0075] In actual implementation, the power deviation of the target energy meter box during the first target monitoring period can be calculated. The power deviation of the target energy meter box during the first target monitoring period is equal to the first active power of the target energy meter box during the first target monitoring period minus the sum of the second active power measured by all energy meters in the target energy meter box during the first target monitoring period. In other words, it is the difference between the active power data of the target energy meter box during the first target monitoring period and the sum of the second active power measured by all energy meters in the target energy meter box during the first target monitoring period. It can be understood that the difference between the first active power of the target energy meter box during the first target monitoring period and the sum of the second active power measured by all energy meters in the target energy meter box during the first target monitoring period is the first difference.

[0076] The power deviation (i.e., the first difference) of the target energy meter box for each monitoring cycle can be expressed by the following formula (taking the j-th monitoring cycle as the first target monitoring cycle as an example): (1).

[0077] Where m represents the number of energy meters in the target energy meter box, and n represents the number of monitoring cycles (each monitoring cycle can be used as a data collection point). This represents the second active power measured by the i-th energy meter in the target energy meter box during the j-th monitoring cycle. This represents the first active power of the target energy meter box during the j-th monitoring cycle; This represents the power deviation of the target energy meter box during the j-th monitoring cycle.

[0078] The ratio of the first difference to the first active power of the first target monitoring period is obtained as the actual value of the power deviation rate of the target energy meter box in the first target monitoring period.

[0079] In actual implementation, the actual value of the power deviation rate of the target energy meter box in the first target monitoring period can be calculated based on the power deviation of the target energy meter box in the first target monitoring period.

[0080] The power deviation (i.e., the first difference) of the target energy meter box for each monitoring cycle can be expressed by the following formula (taking the j-th monitoring cycle as the first target monitoring cycle as an example): (2).

[0081] in, This represents the power deviation rate of the target energy meter box during the j-th monitoring cycle; This represents the first active power of the target energy meter box during the j-th monitoring cycle; This represents the power deviation of the target energy meter box during the j-th monitoring cycle.

[0082] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, when the actual value of the power deviation rate of the target electricity meter metering box in the first target monitoring period is greater than the second threshold, it is preliminarily determined that there are electricity meters with metering inaccuracy in the electricity metering box. Based on the whole box metering of the electricity metering box, it can more timely and accurately determine the electricity meters with metering inaccuracy in the electricity metering box, thereby achieving more real-time and more accurate monitoring of electricity meter metering inaccuracy.

[0083] In some embodiments of this application, determining the correlation between measurement data of a first target monitoring period and measurement data of a second target monitoring period includes: obtaining the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the correlation coefficient is used to indicate the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0084] In practice, the correlation coefficient can be used to indicate the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0085] In some embodiments, the metering data from the (j+1)th monitoring period (or the (j+1)th monitoring period if the jth monitoring period is the first target monitoring period, or the j+1th monitoring period is the second target monitoring period) can be used for verification. The validity of the metering data from the (j+1)th monitoring period in determining which meter(s) in the target metering box are inaccurate can be determined based on the correlation coefficient. The metering data from the jth monitoring period can be represented as a vector. The measurement data for the j-th monitoring period can be represented as a vector. It can calculate vectors and The correlation coefficient is used as the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0086] In some embodiments, the correlation coefficient may be at least one of the Pearson correlation coefficient and the Spearman correlation coefficient.

[0087] According to the electricity meter measurement inaccuracy monitoring method provided in the embodiments of this application, the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period is used to determine whether the measurement data of the second target monitoring period is valid for locating the electricity meter with measurement inaccuracy. Invalid data can be removed, thereby improving the detection rate of electricity meters with measurement inaccuracy.

[0088] In some embodiments of this application, the correlation coefficient is the Pearson correlation coefficient.

[0089] In practice, the Pearson correlation coefficient can be used as the correlation coefficient.

[0090] In some embodiments, the measurement data for the j-th monitoring period can be represented as a vector. The measurement data for the j-th monitoring period can be represented as a vector. It can calculate vectors and Pearson correlation coefficient The correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0091] vector and Pearson correlation coefficient The calculation formula is as follows: (3).

[0092] in, Representing vectors The i-th element; .

[0093] It should be noted that when using the Pearson correlation coefficient, the first threshold can be set to 95% or 90%, depending on the specific circumstances of the transformer area. (In vector...) and Pearson correlation coefficient If it is greater than the first threshold, and Strong correlation. The metering data of the (j+1)th monitoring period is invalid for determining which one or more meters in the target metering box are inaccurate. If so, we can return to step 110 and start the calculation again.

[0094] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, the Pearson correlation coefficient between the metering data of the first target monitoring period and the metering data of the second target monitoring period is used to determine whether the metering data of the second target monitoring period is valid for locating the metering inaccurate electricity meter, which can remove invalid data and improve the detection rate of metering inaccurate electricity meters.

[0095] In some embodiments of this application, the error coefficient corresponding to the energy meter is obtained based on the actual value of the second active power of each energy meter and the power deviation rate of the target energy meter metering box during the first target monitoring period, including: for each energy meter, obtaining the ratio of the actual value of the power deviation rate of the target energy meter metering box to the second active power of the energy meter during the first target monitoring period as the error coefficient corresponding to the energy meter.

[0096] In actual implementation, the metering data from the j-th monitoring period can be used to calculate the error coefficient for each energy meter in the target energy meter box. The error coefficient for each energy meter in the target energy meter box can be expressed as the following formula (taking the j-th monitoring period as the first target monitoring period as an example): (4).

[0097] in, This represents the error coefficient corresponding to the i-th energy meter in the target energy meter box during the j-th monitoring cycle; This represents the power deviation of the target energy meter box during the j-th monitoring cycle; This represents the second active power measured by the i-th energy meter in the target energy meter box during the j-th monitoring cycle.

[0098] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, by using a whole-box metering method that includes "power deviation rate calculation of electricity meter metering box - error coefficient calculation of electricity meter - determination of whether metering data is valid - power deviation verification of electricity meter metering box", it is possible to achieve more real-time and more accurate monitoring of electricity meter metering inaccuracy.

[0099] In some embodiments of this application, the predicted value of the power deviation rate of the second target monitoring period corresponding to the energy meter is obtained based on the error coefficient corresponding to each energy meter and the second active power of the energy meter in the second target monitoring period. This includes: for each energy meter, obtaining the product of the error coefficient corresponding to the energy meter and the second active power of the energy meter in the second target monitoring period as the predicted value of the power deviation rate of the energy meter in the second target monitoring period.

[0100] In actual implementation, the error coefficient corresponding to the i-th energy meter in the target energy meter box can be used for the j-th monitoring cycle (taking the j-th monitoring cycle as the first target monitoring cycle as an example). and the second active power measured by the i-th energy meter in the target energy meter box during the (j+1)-th monitoring cycle. Calculate the power deviation rate of the target energy meter box during the (j+1)th monitoring cycle. The predicted value is used as the predicted value of the power deviation rate of the target energy meter box for the (j+1)th monitoring cycle corresponding to the i-th energy meter.

[0101] In some embodiments, the power deviation rate of the target energy meter box in the (j+1)th monitoring cycle is... The formula for calculating the predicted value is as follows: (5).

[0102] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, the product of the error coefficient corresponding to each electricity meter in the target electricity meter metering box and the second active power of the electricity meter in the second target monitoring period is obtained as the predicted value of the power deviation rate of the electricity meter in the second target monitoring period. Based on the predicted value of the power deviation rate of the electricity meter in the second target monitoring period, it is possible to determine whether the electricity meter is metering inaccurate, which can more accurately determine whether the electricity meter is metering inaccurate.

[0103] In some embodiments of this application, determining whether an energy meter is inaccurate is based on the actual value of the power deviation rate of the second target monitoring period and the predicted value of the power deviation rate of the second target monitoring period corresponding to each energy meter, including: obtaining the actual value of the power deviation rate of the target energy meter meter box of the second target monitoring period based on the metering data of the second target monitoring period.

[0104] In actual implementation, the actual value of the power deviation rate of the target energy meter box during the second target monitoring period can be obtained based on the metering data of the second target monitoring period. The method and steps for obtaining the actual value of the power deviation rate of the target energy meter box in the second target monitoring cycle are similar to or the same as those for obtaining the actual value of the power deviation rate of the target energy meter box in the first target monitoring cycle, and will not be repeated here.

[0105] For each electricity meter, the ratio of the second difference to the actual value of the power deviation rate of the target electricity meter metering box in the second target monitoring period is obtained as the prediction error rate corresponding to the electricity meter; the second difference is the difference between the predicted value and the actual value of the power deviation rate of the electricity meter in the second target monitoring period.

[0106] In actual implementation, the power deviation rate of the target energy meter box can be based on j+1 monitoring cycles (where the j-th monitoring cycle is the first target monitoring cycle and the j+1 monitoring cycle is the second target monitoring cycle). Predicted and actual values Obtain the prediction error rate for each electricity meter in the target electricity meter box. .

[0107] In some embodiments, the prediction error rate corresponding to each energy meter in the target energy meter box is... The calculation formula is as follows: (6).

[0108] If the prediction error rate corresponding to the electricity meter is less than the third threshold, the electricity meter is determined to be inaccurate.

[0109] In actual implementation, for the i-th energy meter in the target energy meter box, the prediction error rate corresponding to that energy meter can be compared. The third threshold is used to determine whether the electricity meter is inaccurate. If the prediction error rate corresponding to the electricity meter is less than the third threshold, the electricity meter can be determined to be inaccurate, i.e., the electricity meter is inaccurate. If the prediction error rate corresponding to the electricity meter is greater than or equal to the third threshold, it cannot be determined whether the electricity meter is inaccurate at this time, and further judgment can be made by waiting for the metering data of the subsequent monitoring cycle.

[0110] It should be noted that the third threshold is the threshold for the prediction error rate of the power deviation rate of the electricity meter box, and can be called the prediction error rate threshold of the power deviation rate of the electricity meter box. The third threshold can be determined according to the actual situation of the electricity meter box and electricity meter and other equipment in the distribution area. The specific value of the third threshold is not limited in the embodiments of this application. For example, the second threshold can be 3% or 2%, etc.

[0111] It should be noted that the aforementioned first threshold, second threshold, and third threshold are all dynamic parameters that can be adjusted according to the actual situation of the transformer area to improve the adaptability of the algorithm and the method for monitoring inaccurate electricity meter readings.

[0112] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, the electricity meter is determined to be inaccurate when the prediction error rate corresponding to the electricity meter is less than a third threshold, which can more accurately determine whether the electricity meter is inaccurate.

[0113] In some embodiments of this application, before determining whether there is an inaccurate electricity meter in the target electricity meter box based on the metering data of the first target monitoring period, the method includes: obtaining frozen data of the active power of the smart measurement terminal set in the target electricity meter box during the first target monitoring period as the first active power, and obtaining frozen data of the active power of each electricity meter during the first target monitoring period as the second active power.

[0114] In actual operation, the main station issues a 15-minute (min) active power freeze curve acquisition task to the electricity meter misalignment monitoring device. The device then collects and stores the 15-minute active power curves of the smart measurement terminals and individual electricity meters in the target electricity meter box within the distribution area, thereby obtaining the metering data for the first target monitoring cycle (i.e., taking traditional power data acquisition as an example, the monitoring cycle duration is 15 minutes).

[0115] In some embodiments, the intelligent measurement terminal can be installed at the inlet of the target energy meter box to collect the active power at the inlet of the target energy meter box in each monitoring cycle, which is used as the first active power of the target energy meter box.

[0116] In some embodiments, the energy meter misalignment monitoring device can acquire 15 minutes of frozen active power data from the smart metering terminal and each energy meter in the target energy meter metering box, respectively, as the first active power and the second active power of each monitoring cycle. The active power of the smart metering terminal is the total active power of the target energy meter metering box.

[0117] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, a centralized electricity meter metering box is used as the basic monitoring unit. A high-precision intelligent measurement terminal deployed at the inlet of the electricity meter metering box is used to simultaneously collect the total metering data of active power on the inlet side and the active power curve data of each branch electricity meter in the electricity meter metering box for the same time period. A multi-dimensional data comparison and error analysis mathematical model is constructed to more accurately determine the metering inaccuracy status of the electricity meter.

[0118] In some embodiments, in terms of technical implementation, the electricity meter metering inaccuracy monitoring method provided in this application fully utilizes the edge computing capabilities of smart measurement terminals and power acquisition terminals, and pushes the core processes such as data acquisition, cleaning, and model calculation down to the local end of the meter box. It does not rely on large-scale data transmission and centralized computing at the main station, which greatly shortens the data processing cycle and ensures that inaccuracy anomalies can be identified and trigger early warnings within minutes.

[0119] In some embodiments of this application, after determining whether the electricity meter is inaccurate, the method further includes: reporting a warning message to the main station in the case of at least one electricity meter being inaccurate; the warning message is used to indicate the information of the inaccurate electricity meter in the target electricity meter box.

[0120] In actual operation, once it is determined that at least one electricity meter in the target electricity meter box is malfunctioning, an early warning message can be generated and reported to the main station. The early warning message can carry information about the malfunctioning electricity meter in the target electricity meter box, such as its serial number and identification number (ID). The main station can then push the information about the malfunctioning meter to maintenance personnel so that they can conduct on-site investigations.

[0121] According to the electricity meter metering inaccuracy monitoring method provided in the embodiments of this application, by reporting early warning information to the main station when at least one electricity meter in the target electricity meter metering box is inaccurate, maintenance personnel can be notified to investigate the problem more promptly.

[0122] To facilitate understanding of the above embodiments of this application, the following description is provided in conjunction with... Figure 3 This paper describes the implementation process of a method for monitoring metering inaccuracies in electricity meters. (Reference) Figure 3 A method for monitoring metering inaccuracies may include the following steps.

[0123] Step 310, Data Acquisition.

[0124] The power acquisition terminal can collect frozen active power data of the smart measuring terminal and each energy meter in the target energy meter box every 15 minutes (taking a monitoring cycle of 15 minutes as an example) according to the acquisition task issued by the main station, and obtain the metering data for each monitoring cycle.

[0125] Step 320: Determine whether the power deviation of the electricity meter box exceeds the threshold.

[0126] The actual value of the power deviation rate of the target energy meter box in the j-th monitoring cycle (taking the j-th monitoring cycle as the first target monitoring cycle as an example) can be calculated, and it can be determined whether the actual value of the power deviation rate of the target energy meter box in the j-th monitoring cycle exceeds the second threshold. If it exceeds the threshold, step 330 can be executed; if it does not exceed the threshold, step 310 can be returned to be executed.

[0127] Step 330: Calculate the error coefficient for each electricity meter.

[0128] The error coefficient for each energy meter in the target energy meter box can be calculated using the metering data from the j-th monitoring period.

[0129] Step 340: Determine whether the measurement data of the first target monitoring period is strongly correlated with the measurement data of the second target monitoring period.

[0130] The Pearson correlation coefficient between the metering data of the j-th monitoring period and the metering data of the (j+1)-th monitoring period can be calculated. Based on this Pearson correlation coefficient, it can be determined whether the metering data of the j-th monitoring period and the (j+1)-th monitoring period are strongly correlated. If there is a strong correlation, step 330 can be returned to increment j, i.e., the error coefficients corresponding to each energy meter in the (j+2)-th monitoring period can be calculated; if there is no strong correlation, step 350 can be executed.

[0131] Step 350: Perform deviation verification of the electricity meter box to determine whether there are any electricity meters with a corresponding prediction error rate exceeding the threshold.

[0132] The deviation of the electricity meter box can be verified based on the metering data of j+1 monitoring cycles to determine whether there are any electricity meters with a prediction error rate exceeding the third threshold. If such a meter exists, step 360 can be executed; otherwise, the process can return to step 320.

[0133] Step 360, Inaccuracy Warning.

[0134] It can generate early warning information and report it to the main station. The early warning information can carry information about the inaccurate meters in the target meter box, such as their serial numbers and identification numbers (IDs). The main station can then push the information about the inaccurate meters to maintenance personnel so that they can investigate on-site.

[0135] The electricity meter misalignment monitoring method provided in this application can be executed by an electricity meter misalignment monitoring device. This application uses an electricity meter misalignment monitoring device executing the method as an example to illustrate the electricity meter misalignment monitoring device provided in this application.

[0136] This application also provides a device for monitoring meter metering inaccuracies. For example... Figure 4 As shown, the electricity meter metering inaccuracy monitoring device includes: a first determination module 410, a first acquisition module 420, a second determination module 430, a second acquisition module 440, and a third determination module 450.

[0137] The first determining module 410 is used to determine whether there are any inaccurate energy meters in the target energy meter metering box based on the metering data of the first target monitoring cycle; the metering data includes the first active power of the target energy meter metering box and the second active power measured by each energy meter; The first acquisition module 420 is used to acquire the error coefficient corresponding to the energy meter based on the actual value of the second active power of each energy meter in the first target monitoring cycle and the power deviation rate of the target energy meter meter box when there is an energy meter with inaccurate metering in the target energy meter meter box; the power deviation rate of the target energy meter meter box is used to indicate the degree of deviation between the first active power and the sum of each second active power in a monitoring cycle. The second determining module 430 is used to determine the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the second target monitoring period is the first monitoring period after the first target monitoring period. The second acquisition module 440 is used to acquire the predicted value of the power deviation rate of the second target monitoring period corresponding to the energy meter based on the error coefficient corresponding to each energy meter and the second active power of the second target monitoring period when the correlation is less than or equal to the first threshold. The third determining module 450 is used to determine whether the electricity meter is inaccurate based on the actual value of the power deviation rate of the second target monitoring cycle and the predicted value of the power deviation rate of the second target monitoring cycle corresponding to each electricity meter.

[0138] The electricity meter miscalculation monitoring device provided in the embodiments of this application monitors electricity meter miscalculation by using whole-box metering based on the electricity meter box. It uses active power data from the electricity meter box and each electricity meter in each monitoring cycle to construct a mathematical model to determine whether the electricity meter is miscalculated. This device can achieve more real-time and accurate monitoring of electricity meter miscalculation. Furthermore, it can be implemented using the edge computing capabilities of the power collection terminal. It has the advantages of strong real-time performance and high accuracy, and can provide strong support for the intelligent and refined construction of electricity meter boxes, as well as line loss analysis and electricity theft investigation.

[0139] In some embodiments, the first determining module 410 may include: The first acquisition unit is used to acquire the actual value of the power deviation rate of the target energy meter box in the first target monitoring period based on the metering data of the first target monitoring period. The first determining unit is used to determine that there is a metering inaccuracy when the actual value of the power deviation rate of the target electricity meter meter box in the first target monitoring period is greater than the second threshold.

[0140] In some embodiments, the first acquisition unit may be specifically used for: The first difference between the first active power and the sum of each second active power in the first target monitoring cycle; The ratio of the first difference to the first active power of the first target monitoring period is obtained as the actual value of the power deviation rate of the target energy meter box in the first target monitoring period.

[0141] In some embodiments, the second determining module 430 may be specifically used to obtain the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the correlation coefficient is used to indicate the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

[0142] In some embodiments, the correlation coefficient is the Pearson correlation coefficient.

[0143] In some embodiments, the first acquisition module 420 may be specifically used to acquire, for each energy meter, the ratio of the actual value of the power deviation rate of the target energy meter metering box in the first target monitoring period to the second active power of the energy meter, as the error coefficient corresponding to the energy meter.

[0144] In some embodiments, the second acquisition module 440 may be specifically used to acquire, for each energy meter, the product of the error coefficient corresponding to the energy meter and the second active power of the energy meter in the second target monitoring period, as the predicted value of the power deviation rate of the energy meter in the second target monitoring period.

[0145] In some embodiments, the third determining module 450 may include: The second acquisition unit is used to acquire the actual value of the power deviation rate of the target energy meter box in the second target monitoring period based on the metering data of the second target monitoring period. The third acquisition unit is used to acquire, for each energy meter, the ratio of the second difference to the actual value of the power deviation rate of the target energy meter metering box in the second target monitoring period, as the prediction error rate corresponding to the energy meter; the second difference is the difference between the predicted value and the actual value of the power deviation rate of the energy meter in the second target monitoring period. The second determining unit is used to determine that the electricity meter is inaccurate when the prediction error rate corresponding to the electricity meter is less than the third threshold.

[0146] In some embodiments, the electricity meter misalignment monitoring device may further include: The third acquisition module is used to acquire frozen data of active power of the smart measurement terminal set in the target energy meter box during the first target monitoring period, as the first active power, and to acquire frozen data of active power of each energy meter during the first target monitoring period, as the second active power.

[0147] In some embodiments, the electricity meter misalignment monitoring device may further include: The early warning module is used to report early warning information to the main station when at least one electricity meter is inaccurate; the early warning information is used to indicate the information of the inaccurate electricity meter in the target electricity meter box.

[0148] The electricity meter miscalculation monitoring device in this application embodiment can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the specific type of device.

[0149] The electricity meter miscalculation monitoring device in this application embodiment can be a device with an operating system. This operating system can be a Microsoft (Windows) operating system, an Android operating system, an iOS operating system, or other possible operating systems; this application embodiment does not specifically limit it.

[0150] The electricity meter metering inaccuracy monitoring device provided in this application embodiment can achieve... Figures 1 to 3The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0151] This application also provides a system for monitoring meter metering inaccuracies. For example... Figure 5 As shown, the electricity meter misalignment monitoring system 500 includes: an electricity meter misalignment monitoring device 510 and at least one intelligent measurement terminal 520; the intelligent measurement terminal 520 is used to acquire the active power of the electricity meter box.

[0152] In actual implementation, the electricity meter metering inaccuracy monitoring device 510 can be any of the electricity meter metering inaccuracy monitoring devices provided in the aforementioned embodiments.

[0153] In some embodiments, the power acquisition terminal may include the meter misalignment monitoring device 510, or the power acquisition terminal may serve as the meter misalignment monitoring device 510.

[0154] In some embodiments, the smart measurement terminal 520 may be installed inside the electricity meter box. In some embodiments, the smart measurement terminal 520 may be installed at the inlet of the electricity meter box.

[0155] The electricity meter misalignment monitoring system provided in this application monitors electricity meter misalignment by using whole-box metering based on the electricity meter box. It utilizes active power data from the electricity meter box and each meter in each monitoring cycle to construct a mathematical model to determine whether the electricity meter is misaligned. This system achieves more real-time and accurate monitoring of electricity meter misalignment and can be implemented using the edge computing capabilities of the power collection terminal. It boasts advantages such as high real-time performance and accuracy, providing strong support for the intelligent and refined construction of electricity meter boxes, as well as line loss analysis and electricity theft investigation.

[0156] In some embodiments, such as Figure 6 As shown, this application embodiment also provides an electronic device 600, including a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the computer program is executed by the processor 601, it implements the various processes of the above-described embodiment of the method for monitoring the metering inaccuracy of electricity meters and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0157] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0158] This application also provides a non-volatile computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described embodiment of the method for monitoring meter metering inaccuracies and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0159] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0160] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for monitoring meter metering inaccuracies.

[0161] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0162] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described embodiments of the electricity meter metering inaccuracy monitoring method, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0163] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0164] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0165] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0166] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0167] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0168] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for monitoring metering inaccuracies in electricity meters, characterized in that, include: Based on the metering data of the first target monitoring cycle, determine whether there are any inaccurate electricity meters in the target electricity meter box; The metering data includes the first active power of the target energy meter metering box and the second active power measured by each of the energy meters; In the case where there is an inaccurate meter in the target meter box, based on the actual value of the second active power of the meter in each of the first target monitoring cycles and the power deviation rate of the target meter box, the error coefficient corresponding to the meter is obtained, and the correlation between the metering data of the first target monitoring cycle and the metering data of the second target monitoring cycle is determined. The power deviation rate of the target energy meter box is used to indicate the degree of deviation between the first active power and the sum of each of the second active power in one monitoring cycle; the second target monitoring cycle is the first monitoring cycle after the first target monitoring cycle; When the correlation is less than or equal to the first threshold, the predicted value of the power deviation rate of the second target monitoring period corresponding to the power meter is obtained based on the error coefficient corresponding to each of the power meters and the second active power of the second target monitoring period. Based on the actual value of the power deviation rate during the second target monitoring period and the predicted value of the power deviation rate during the second target monitoring period for each of the energy meters, it is determined whether the energy meter is inaccurate.

2. The method for monitoring metering inaccuracies according to claim 1, characterized in that, Determining whether an energy meter has metering inaccuracies based on the metering data from the first target monitoring period includes: Based on the metering data of the first target monitoring period, obtain the actual value of the power deviation rate of the target energy meter box in the first target monitoring period; If the actual value of the power deviation rate of the target electricity meter box is greater than the second threshold during the first target monitoring period, it is determined that the electricity meter has a metering inaccuracy.

3. The method for monitoring metering inaccuracies according to claim 2, characterized in that, The step of obtaining the actual value of the power deviation rate of the target energy meter box during the first target monitoring period based on the metering data of the first target monitoring period includes: The first difference between the first active power and the sum of each of the second active powers during the first target monitoring period; The ratio of the first difference to the first active power in the first target monitoring period is obtained as the actual value of the power deviation rate of the target energy meter box in the first target monitoring period.

4. The method for monitoring metering inaccuracies according to any one of claims 1 to 3, characterized in that, Determining the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period includes: Obtain the correlation coefficient between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; the correlation coefficient is used to indicate the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period.

5. The method for monitoring metering inaccuracies according to claim 4, characterized in that, The correlation coefficient mentioned is the Pearson correlation coefficient.

6. The method for monitoring metering inaccuracies according to any one of claims 1 to 3, characterized in that, Based on the actual values ​​of the second active power of the energy meter and the power deviation rate of the target energy meter metering box for each of the first target monitoring cycles, the error coefficient corresponding to the energy meter is obtained, including: For each of the aforementioned energy meters, the actual value of the power deviation rate of the target energy meter metering box during the first target monitoring period is obtained as the ratio of the second active power of the energy meter, which is used as the error coefficient corresponding to the energy meter.

7. The method for monitoring metering inaccuracies according to claim 6, characterized in that, The step of obtaining the predicted value of the power deviation rate for the second target monitoring period corresponding to each of the energy meters, based on the error coefficient corresponding to each of the energy meters and the second active power for the second target monitoring period, includes: For each of the aforementioned energy meters, the product of the error coefficient corresponding to the energy meter and the second active power of the energy meter in the second target monitoring period is obtained, and used as the predicted value of the power deviation rate of the energy meter in the second target monitoring period.

8. The method for monitoring metering inaccuracies according to claim 7, characterized in that, The step of determining whether the electricity meter is inaccurate based on the actual value of the power deviation rate during the second target monitoring period and the predicted value of the power deviation rate during the second target monitoring period for each electricity meter includes: Based on the metering data of the second target monitoring period, obtain the actual value of the power deviation rate of the target energy meter box of the second target monitoring period; For each of the aforementioned energy meters, the ratio of the second difference to the actual value of the power deviation rate of the target energy meter metering box during the second target monitoring period is obtained as the prediction error rate corresponding to the energy meter; the second difference is the difference between the predicted value and the actual value of the power deviation rate corresponding to the energy meter during the second target monitoring period. If the prediction error rate corresponding to the electricity meter is less than the third threshold, the electricity meter is determined to be inaccurate.

9. The method for monitoring metering inaccuracies according to claim 1, characterized in that, Before determining whether there is a malfunctioning energy meter in the target energy meter box based on the metering data from the first target monitoring cycle, the method includes: The first target monitoring cycle is used to obtain the frozen active power data of the smart measuring terminal set in the target energy meter meter box as the first active power, and the first target monitoring cycle is used to obtain the frozen active power data of each energy meter as the second active power.

10. The method for monitoring metering inaccuracies according to claim 1, characterized in that, After determining whether the electricity meter is inaccurate, the method further includes: In the event of at least one of the aforementioned electricity meters being inaccurate, a warning message is reported to the main station; the warning message is used to indicate the information of the electricity meter in the target electricity meter box that is inaccurate.

11. A device for monitoring metering inaccuracy in electricity meters, characterized in that, include: The first determining module is used to determine whether there is an inaccurate electricity meter in the target electricity meter box based on the metering data of the first target monitoring cycle. The metering data includes the first active power of the target energy meter metering box and the second active power measured by each of the energy meters; The first acquisition module is used to acquire the error coefficient corresponding to the energy meter based on the actual value of the second active power of the energy meter in each of the first target monitoring cycles and the power deviation rate of the target energy meter meter box when there is an energy meter with inaccurate metering in the target energy meter meter box; the power deviation rate of the target energy meter meter box is used to indicate the degree of deviation between the first active power and the sum of each second active power in one monitoring cycle; The second determining module is used to determine the correlation between the measurement data of the first target monitoring period and the measurement data of the second target monitoring period; The second target monitoring period is the first monitoring period following the first target monitoring period; The second acquisition module is used to acquire the predicted value of the power deviation rate of the second target monitoring period corresponding to the energy meter based on the error coefficient corresponding to each energy meter and the second active power of the second target monitoring period when the correlation is less than or equal to the first threshold. The third determining module is used to determine whether the electricity meter is inaccurate based on the actual value of the power deviation rate in the second target monitoring period and the predicted value of the power deviation rate in the second target monitoring period for each electricity meter.

12. A metering inaccuracy monitoring system for electricity meters, characterized in that, include: The energy meter metering inaccuracy monitoring device and at least one intelligent measuring terminal as described in claim 11; the intelligent measuring terminal is used to acquire the active power of the energy meter metering box.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for monitoring meter metering inaccuracies as described in any one of claims 1 to 10.

14. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for monitoring meter metering inaccuracies as described in any one of claims 1 to 10.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for monitoring meter metering inaccuracies as described in any one of claims 1 to 10.

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