A method and system for calculating phase line loss of a metering box based on smart measurement switches

Abstract

The application discloses a kind of based on intelligent measurement switch calculation metering box phase line loss method and system, and search meter through RS485 bus after the power on of intelligent measurement switch, identify single-phase and three-phase electric energy meter type in metering box;Voltage data is collected to single-phase meter and is determined to access phase by stability verification, and three-phase meter is cached at initial time phase supply and subordinate electric energy meter data;After correcting electric energy abnormal data, phase attribution is classified to electric energy meter data and summed up, according to the fluctuation of phase load;When monitoring time point meets the condition, three-phase line loss rate is independently calculated using slip method;Line loss rate is compared with preset parameter and divided into three levels of abnormality and is differentially reported, while through electric energy proportion analysis and equipment real-time state monitoring, abnormality is traced back to source.The application improves the calculation accuracy of phase line loss, balances the calculation efficiency and resource consumption, optimizes the response efficiency of operation and maintenance, and is suitable for low-voltage distribution network metering box line loss fine management.

Description

Technical Field

[0001] This invention relates to the field of intelligent measurement switch technology, specifically to a method and system for calculating phase line loss of a metering box based on an intelligent measurement switch. Background Technology

[0002] In the operation of low-voltage power distribution networks, metering boxes, as the core unit for energy metering and power distribution, have line losses (i.e., the difference between the energy supplied to the metering box's incoming line and the energy measured by all its subordinate energy meters). These line losses are a key indicator reflecting the operational efficiency of the power distribution network and for detecting metering anomalies and electricity theft. Traditional methods for calculating line losses in metering boxes have the following technical limitations, making it difficult to meet the needs of refined operation and maintenance:

[0003] 1. Insufficient accuracy in phase-by-phase line loss calculation: Traditional methods often calculate overall line loss on a per-transformer-area basis, failing to break down line loss by phase (A, B, C). Because single-phase loads (such as residential electricity) in low-voltage distribution networks often have unbalanced three-phase connections, overall line loss data cannot pinpoint specific phase loss anomalies, making it difficult for maintenance personnel to accurately troubleshoot faults.

[0004] 2. Ambiguous phase assignment of single-phase energy meters: Single-phase and three-phase energy meters are often mixed in the metering box, and there is a lack of effective means to identify the phase connection information of single-phase energy meters (which phase A, B, or C they are connected to). If only manual records or experience are relied upon, it is easy to make mistakes in phase classification and omission of line loss, resulting in deviations in the summation of phase energy, and thus causing distortion of the line loss calculation results.

[0005] 3. Data anomaly interference calculation results: During operation, the electricity meter may experience jumps in electricity data (such as a sudden increase / decrease in data within a short period of time) or stagnation due to factors such as communication interference and hardware failure. Traditional methods do not effectively correct for such abnormal data and directly participate in the phase summation calculation, further amplifying the line loss error.

[0006] 4. Fixed calculation cycle lacks adaptability: Traditional line loss calculation cycles are mostly fixed values ​​(such as 1 hour / 1 day), without considering the impact of load fluctuations. During peak electricity consumption periods (such as residential morning peak and industrial production periods), load fluctuations are drastic, and a fixed long cycle will lead to a lag in the detection of line loss anomalies; while during off-peak electricity consumption periods (such as late at night), the load is stable, and a fixed short cycle will result in data redundancy and wasted computing power.

[0007] 5. Inadequate Anomaly Detection and Response Mechanism: Traditional methods only determine anomalies based on whether the line loss rate exceeds a fixed threshold, without differentiating the severity of the anomaly. Furthermore, the alarm method is uniformly real-time reporting, resulting in a large number of invalid alarm messages for the main station system and reducing maintenance response efficiency. Simultaneously, the lack of anomaly tracing capabilities requires maintenance personnel to check all electricity meters in the metering box one by one, which is time-consuming and labor-intensive.

[0008] To address the aforementioned issues, existing technologies have not yet proposed an integrated phase-by-phase line loss calculation scheme that comprehensively considers accurate phase identification, data anomaly correction, dynamic periodic calculation, hierarchical alarms, and fault tracing. Therefore, there is an urgent need to design a method and system for calculating phase-by-phase line losses in metering boxes based on intelligent measuring switches, in order to solve the problem of insufficient precision in low-voltage distribution network metering box line loss management. Summary of the Invention

[0009] The technical problem to be solved by this invention is to provide a method and system for calculating phase line loss of metering boxes based on intelligent measuring switches, so as to solve the problems of insufficient phase line loss accuracy, ambiguous phase assignment of single-phase energy meters, large data anomaly interference, fixed calculation cycle lack of adaptability and single anomaly judgment response in traditional metering box line loss calculation, and meet the needs of refined operation and maintenance of line loss of metering boxes in low-voltage distribution networks.

[0010] To solve the above-mentioned technical problems, embodiments of the present invention provide the following technical solution: a method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch, comprising the following steps: Step 1: After the measuring switch is powered on, a meter search operation is performed via RS485 bus to obtain the types of all energy meters in the metering box. The energy meter types are divided into single-phase energy meters and three-phase energy meters. Step 2: For single-phase energy meters, the measuring switch collects and buffers the voltage data of the single-phase energy meter. After a preset time of data accumulation and analysis, it identifies and determines the grid phase connected to each single-phase energy meter. For three-phase energy meters, at the first time point T1, the measuring switch buffers the phase power supply energy data provided by its own metering module, denoted as... , , Simultaneously, collect and cache the energy data of all subordinate energy meters; Step 3: Correct any anomalies in the energy data of single-phase and three-phase energy meters, and perform phase-by-phase classification and summation calculations on the energy data of all energy meters to obtain the phase-by-phase summation data of the energy meters at time T1, which are denoted as follows: , , ; Step 4: At the nth time point Tn, cache the phase power supply energy data of the measuring switch itself again. , , And recalculate and cache the total phase-by-phase energy data of the energy meter. , , When n>2, the phase line loss rate calculation is started, the calculation period is set to a dynamic adaptive calculation period, and the slip calculation method is used to calculate the line loss rates of phases A, B, and C respectively. Step 5: Compare the calculated line loss rate of each phase with the preset anomaly judgment parameters, filter out the abnormal line loss data that exceeds the preset range, and report the abnormal line loss status result to the main station system.

[0011] Preferably, the step of identifying and determining the grid phase to which each of the single-phase energy meters is connected specifically involves: Step 2.1: The measuring switch synchronously collects voltage data for each single-phase energy meter for 5 consecutive power grid cycles, and at the same time collects the voltage phase reference signal of its own three phases A, B, and C. The voltage phase reference signal includes the phase start time and the voltage peak time. The voltage data at least covers the voltage effective value, the voltage zero crossing time, and the voltage waveform distortion rate. Step 2.2: Calculate the time difference between the zero-crossing point of the voltage of each single-phase energy meter and the zero-crossing points of the voltages of phases A, B, and C of the measuring switch, and denot them as Δt_A, Δt_B, and Δt_C, respectively. If the absolute value of Δt_A is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase A; similarly, if the absolute value of Δt_B is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase B; if the absolute value of Δt_C is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase C. Step 2.3: For single-phase energy meters with preliminary phase determination, continuously collect voltage waveform distortion rate data within 3 minutes. If all voltage waveform distortion rate data within 3 minutes are ≤3%, the phase determination result of the single-phase energy meter is confirmed. If the voltage waveform distortion rate is >3% at any moment, the voltage data in that time period is discarded, and steps 2.1-2.2 are repeated until a stable phase determination result is obtained.

[0012] Preferably, the step of correcting abnormal energy data for single-phase and three-phase energy meters specifically includes: Step 3.1: Single-phase meter anomaly determination. Calculate the rate of change of the single-phase energy meter's energy data for three consecutive times using the formula ηsingle = (Esingle after - Esingle before) / Esingle before × 100%. If the absolute value of the rate of change is > 20%, mark the current data as trend abnormal data. Step 3.2: Three-phase meter phase determination. For the independent electrical energy data of phases A, B, and C of the three-phase energy meter, calculate the change rate of each phase according to the formula η phase = (after phase E - before phase E) / before phase E × 100%. If the absolute value of the change rate of any phase is > 20%, mark the data of that phase as abnormal. Step 3.3: Data correction and verification. Abnormal data of single-phase meters are corrected by taking the average of valid data in the same period of the past 30 days; abnormal data of each phase of three-phase meters are corrected by taking the average of valid data of the corresponding phase in the past 30 days, and the deviation of the total of the three phases after correction from the original total data is ≤5%.

[0013] Preferably, the step of classifying and summing the energy data of all energy meters by phase to obtain the phase-specific total energy data of the energy meters at time T1 is specifically as follows: A-phase total data:

[0014] B-phase total data:

[0015] C-phase total data:

[0016] in, This represents the corrected energy data of the i-th single-phase energy meter in the A-phase set at time T1, where m is the number of single-phase energy meters in the A-phase set. This represents the corrected phase A energy data of the j-th three-phase energy meter in phase A set at time T1, where k is the total number of three-phase energy meters in the metering box. This represents the corrected energy data of the i-th single-phase energy meter in the B-phase set at time T1, where w is the number of single-phase energy meters in the B-phase set. This represents the corrected B-phase energy data of the j-th three-phase energy meter within the B-phase set at time T1. This represents the corrected energy data of the i-th single-phase energy meter in the C-phase set at time T1, where p is the number of single-phase energy meters in the C-phase set. This represents the corrected C-phase energy data of the j-th three-phase energy meter within the C-phase set at time T1; and all data involved in the summation must undergo the energy data anomaly correction in step 3, and uncorrected data must not be included in the summation calculation.

[0017] Preferably, the method for determining the dynamic adaptive calculation period includes the following steps: Step 4.1: The measuring switch calculates the phase load fluctuation coefficients of phases A, B, and C from time T1 to time Tn-1. The phase load fluctuation coefficient is calculated as follows: (maximum power supply energy of a phase - minimum power supply energy of that phase) / average power supply energy of that phase × 100%. The average power supply energy of a phase is calculated as the sum of the power supply energy of all sampling points of that phase during the statistical period / the number of sampling points. Step 4.2: Determine the current calculation period based on the statistically obtained three-phase load fluctuation coefficients: If the maximum value of the three-phase load fluctuation coefficient is greater than 20%, then the current calculation period will be set to 20 minutes. If the maximum value of the three-phase load fluctuation coefficient is between 10% and 20%, then the current calculation period is set to 25 minutes. If the maximum value of the three-phase load fluctuation coefficient is ≤10%, then the current calculation period is set to 35 minutes. Step 4.3: After every 3 calculation cycles, repeat steps 4.1-4.2 to update the calculation cycle for the next round.

[0018] Preferably, the line loss rates of phases A, B, and C are calculated using the slip calculation method, specifically using the following mathematical formula: Line loss rates of phases A, B, and C at time Tn , , They are respectively:

[0019]

[0020]

[0021] in, , , The measurement switch's phase-by-phase power supply energy data at the time point of the calculation cycle preceding time Tn; , , This is the total energy data of the electricity meter for each phase corresponding to the previous time point; and the calculation process of the line loss rate for each phase is completely independent of the load data and metering data of the other two phases.

[0022] Preferably, the abnormal line loss status result is specifically as follows: Level 1 anomaly: Phase loss rate > 1.2 times the preset upper limit of anomalies, is judged as a serious anomaly; Level 2 anomaly: Phase loss rate > preset anomaly upper limit and ≤ 1.2 times the preset anomaly upper limit, is judged as moderate anomaly; Level 3 anomaly: If the phase loss rate is less than 0.8 times the preset lower limit of anomalies, it is judged as a data anomaly; Perform differentiated reporting operations based on different anomaly levels: If it is determined to be a Level 1 anomaly: the measuring switch sends an emergency alarm message to the main station system through the communication module within ≤10 seconds, and at the same time triggers the local audible and visual alarm device of the measuring switch; If the fault is determined to be a Level 2 anomaly: the measurement switch will recalculate the line loss rate of the phase after a 5-minute delay. If the recalculation result is still a Level 2 anomaly, a normal alarm message will be sent to the main station system. If the abnormality is determined to be Level 3, the measurement switch stores the abnormal line loss data in the local cache module. At a fixed time each day, all Level 3 abnormal data are aggregated and a data verification reminder message is sent to the main station system.

[0023] Preferably, it also includes auxiliary methods for tracing the source of abnormal phase line losses, specifically: Step 6.1: When a phase is determined to have abnormal line loss, the measuring switch extracts the energy data of all single-phase energy meters under that phase and the energy data of the corresponding phase of the three-phase energy meters, and calculates the energy percentage of each energy meter. The energy percentage is calculated as follows: (energy data of a single energy meter / total energy data of all energy meters in that phase) × 100%. Step 6.2: Compare the current energy percentage of each energy meter in this phase with the average energy percentage of the same period in the past 7 days, and calculate the percentage deviation value. The percentage deviation value = |current percentage - average percentage|. If the percentage deviation value of a certain energy meter is >8%, then mark the energy meter as a suspicious energy meter. Step 6.3: The measuring switch collects real-time operating data of the suspected energy meter through the RS485 bus, including real-time current data and real-time voltage data, and determines whether there is a situation where the real-time current is greater than 1.1 times the rated current of the energy meter or the real-time voltage is less than 0.9 times the rated voltage of the energy meter. If either of the above situations exists, an abnormality tracing clue containing the device number of the energy meter and the abnormal operating characteristics is recorded. Step 6.4: The measurement switch packages the abnormality tracing clues, abnormal line loss data of the phase, and abnormality level information together and reports them to the main station system.

[0024] This invention also proposes a system for calculating phase-by-phase line loss of a metering box based on a smart measuring switch, used to implement the above-mentioned method for calculating phase-by-phase line loss of a metering box based on a smart measuring switch. The system includes a smart measuring switch, an energy meter cluster, and a master station system, wherein the smart measuring switch is communicatively connected to the energy meter cluster and the master station system. The intelligent measurement switch includes an RS485 communication module, a 4G / 5G module, a metering acquisition module, a data caching module, a local alarm module, a phase recognition module, a line loss calculation module, an anomaly handling module, and a source tracing auxiliary module. The RS485 communication module is used to establish bidirectional communication with the electricity meter cluster, perform meter search operations to obtain the electricity meter type, and collect the electricity energy data, voltage data, and current data of the electricity meter. The 4G / 5G module establishes a communication connection with the main station system to report abnormal line loss data, alarm information, and tracing clues; The metering and acquisition module is used to collect the A, B, and C phase power supply energy data of the intelligent metering switch itself. , , The data acquisition frequency is synchronized with the data acquisition frequency of the electricity meter; The data caching module is used to store the electricity meter type information, the collected voltage data, energy data, current data, as well as the calculated phase line loss rate data and abnormal data; The local alarm module includes LED indicators and a buzzer, which are used to trigger an audible and visual alarm when the level is determined to be a level one anomaly. The phase identification module is used for phase identification of electricity meters and outputs the phase assignment result for each electricity meter. The line loss calculation module is used to calculate the line loss rate using the slip method. The anomaly handling module is used to classify anomalies into different levels and perform differentiated reporting operations, generating alarm information and handling suggestions; The source tracing auxiliary module is used to assist in tracing the source of abnormal phase line loss and generate clues for tracing the source of the abnormality. The electricity meter cluster includes at least one single-phase electricity meter and / or at least one three-phase electricity meter. Both the single-phase electricity meter and the three-phase electricity meter support the RS485 communication protocol and upload electricity data, voltage data and current data to the smart metering switch. The main station system includes a data receiving module, an archive management module, an alarm handling module, an operation and maintenance suggestion module, and a data storage module; The data receiving module is used to receive various data and information reported by the intelligent measuring switch; The file management module is used to store basic file information for metering boxes, smart metering switches, and electricity meter clusters. The alarm processing module is used to classify, display, and prioritize received alarm information. The operation and maintenance suggestion module is used to generate anomaly handling suggestions by associating historical data; The data storage module is used for long-term storage of phase line loss data, alarm information, and traceability clues.

[0025] The beneficial effects of the above-described technical solution of the present invention are as follows: 1. This invention determines the grid phase affiliation of each single-phase energy meter by comparing voltage characteristics and verifying stability, avoiding interference from phase misjudgment on phase data; at the same time, it performs anomaly detection and correction on energy data, eliminates abnormal data and ensures data consistency, and then completes the summation of phase data and independent line loss rate calculation according to phase affiliation, which can accurately locate the loss anomaly of specific phases and provide a reliable basis for the refined management of line loss in low-voltage distribution networks.

[0026] 2. This invention dynamically adjusts the line loss calculation cycle according to the load fluctuation of each phase, which can capture line loss changes in a timely manner during periods of active load change and reduce invalid data processing during periods of stable load. At the same time, it adopts the slip calculation method to calculate the line loss rate by the difference between adjacent period data, which effectively reduces the random error that may exist in a single data acquisition. Combined with the previous data preprocessing process, it further ensures the reliability of the line loss calculation results and avoids interference from invalid data.

[0027] 3. This invention classifies abnormal line losses into different levels and implements differentiated reporting strategies for different levels, improving the targeting of operation and maintenance response. When an abnormal line loss occurs, suspicious equipment is identified by analyzing the changes in the proportion of electricity energy in the subordinate electricity meters. Further investigation is conducted by combining the real-time operating status of the equipment, providing operation and maintenance personnel with clear clues for tracing the source, avoiding blind investigation, significantly shortening the fault handling time, and reducing the manpower and time costs of distribution network operation and maintenance. Attached Figure Description

[0028] Figure 1 This is a flowchart of the method for calculating phase line loss of a metering box based on an intelligent measuring switch according to the present invention. Figure 2 This is a system architecture block diagram of the present invention for calculating phase line loss of a metering box based on an intelligent measuring switch; Figure 3 This is a block diagram of the intelligent measurement switch components of the system for calculating phase line loss of a metering box based on an intelligent measurement switch, as described in this invention. Figure 4 This is a block diagram of the main station system for calculating phase line loss of a metering box based on an intelligent measuring switch, according to the present invention. Detailed Implementation

[0029] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0030] like Figure 1 As shown, this invention proposes a method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch, comprising the following steps: Step 1: After the measuring switch is powered on, the meter search operation is performed through the RS485 bus to obtain the types of all energy meters in the metering box. The energy meter types are divided into single-phase energy meters and three-phase energy meters. Step 2: For single-phase energy meters, the measuring switch collects and buffers the voltage data of the single-phase energy meter. After a preset time of data accumulation and analysis, it identifies and determines the grid phase connected to each single-phase energy meter. For three-phase energy meters, at the first time point T1, the measuring switch buffers the phase power supply energy data provided by its own metering module, denoted as... , , Simultaneously, collect and cache the energy data of all subordinate energy meters; Step 3: Correct any anomalies in the energy data of single-phase and three-phase energy meters, and perform phase-by-phase classification and summation calculations on the energy data of all energy meters to obtain the phase-by-phase summation data of the energy meters at time T1, which are denoted as follows: , , ; Step 4: At the nth time point Tn, cache the phase power supply energy data of the measuring switch itself again. , , And recalculate and cache the total phase-by-phase energy data of the energy meter. , , When n>2, the phase line loss rate calculation is started, the calculation period is set to a dynamic adaptive calculation period, and the slip calculation method is used to calculate the line loss rates of phases A, B, and C respectively. Step 5: Compare the calculated line loss rate of each phase with the preset anomaly judgment parameters, filter out the abnormal line loss data that exceeds the preset range, and report the abnormal line loss status result to the main station system.

[0031] In this embodiment, the grid phase to which each single-phase energy meter is connected is identified and determined, specifically as follows: Step 2.1: The measuring switch synchronously acquires voltage data for each single-phase energy meter for five consecutive grid cycles, and simultaneously acquires the voltage phase reference signals for its own A, B, and C phases. The voltage phase reference signals include the phase start time and voltage peak time. The voltage data must at least cover the effective voltage value, the voltage zero-crossing point, and the voltage waveform distortion rate. This step is designed based on the periodicity and consistency of the grid voltage characteristics. Acquiring voltage data for five consecutive grid cycles reduces the random error of a single acquisition through the statistical analysis of multi-cycle data; simultaneously acquiring the voltage phase reference signals for the measuring switch's own three phases establishes a reference coordinate system for subsequent single-phase meter phase determination. The effective voltage value reflects the stability of the voltage amplitude, the voltage zero-crossing point is a critical time node for phase synchronization determination, and the voltage waveform distortion rate reflects the purity of the voltage signal.

[0032] Step 2.2: Calculate the time difference between the zero-crossing point of the voltage of each single-phase energy meter and the zero-crossing points of the voltages of phases A, B, and C of the measuring switch, denoted as Δt_A, Δt_B, and Δt_C respectively. If the absolute value of Δt_A is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase A; similarly, if the absolute value of Δt_B is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase B; and if the absolute value of Δt_C is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase C. In a power system, the zero-crossing points of voltage signals of the same phase are highly synchronized in time. Therefore, when the absolute value of the time difference between the zero-crossing point of the voltage of a single-phase energy meter and the zero-crossing point of a certain phase (A / B / C) of the measuring switch is ≤ 0.3ms, they can be considered to belong to the same phase. This time difference threshold-based determination method does not require complex circuit topology testing. It can quickly complete the preliminary phase classification of a single-phase meter through precise measurement in the time dimension, balancing determination efficiency and preliminary accuracy.

[0033] Step 2.3: For single-phase energy meters with preliminary phase determination, continuously collect voltage waveform distortion rate data for 3 minutes. If the voltage waveform distortion rate of all data within 3 minutes is ≤3%, the phase determination result of the single-phase energy meter is confirmed. If the voltage waveform distortion rate is >3% at any moment, the voltage data for that period is discarded, and steps 2.1-2.2 are repeated until a stable phase determination result is obtained. This step ensures the reliability of the phase determination result through the stability verification of the voltage waveform distortion rate. The voltage waveform distortion rate reflects the degree of contamination of the voltage signal by factors such as harmonics and interference. When the distortion rate is ≤3%, it indicates that the voltage signal is in a stable and pure state, and the preliminary phase determination result based on the time difference has high reliability. If the distortion rate is >3%, the voltage signal has serious interference, which will cause deviation in the time difference determination. Therefore, the data for that period needs to be discarded and the determination process needs to be repeated.

[0034] In this embodiment, the steps for correcting abnormal energy data of single-phase and three-phase energy meters specifically include: Step 3.1: Single-phase meter anomaly determination. Calculate the rate of change of energy data for three consecutive times using the formula ηsingle = (Esingle after - Esingle before) / Esingle before × 100%. If the absolute value of the rate of change is > 20%, mark the current data as abnormal trend data. Under normal power consumption scenarios, the rate of change of energy will not show drastic changes. By calculating the rate of change three times consecutively and setting a 20% threshold, data jumps in single-phase meters caused by communication interference or hardware failure can be identified.

[0035] Step 3.2: Phase-by-phase determination of three-phase energy meters. For the independent energy data of phases A, B, and C of the three-phase energy meter, the change rate of each phase is calculated according to the formula η phase = (E phase after - E phase before) / E phase before × 100%. If the absolute value of the change rate of any phase is greater than 20%, the data of that phase is marked as abnormal. The metering of each phase of the three-phase energy meter is independent. The change rate is calculated for each phase and a 20% threshold is set. This can accurately locate the abnormal data of a certain phase (such as a phase module failure) and avoid misjudgment of the whole meter data due to the abnormality of one phase, thus ensuring the accuracy of single-phase data in the phase-by-phase line loss calculation.

[0036] Step 3.3: Data Correction and Verification. For single-phase meters, abnormal data is corrected using the average of valid data from the same period over the past 30 days. For three-phase meters, abnormal data for each phase is corrected using the average of valid data from the corresponding phase over the past 30 days, and the deviation of the corrected total of the three phases from the original total data is ≤5%. Historical data from the same period show similarities in electricity consumption behavior, and correcting abnormal data in this way can restore reasonable values. At the same time, limiting the deviation of the total three-phase data to ≤5% avoids excessive correction of single-phase data from disrupting the overall consistency of the three-phase data.

[0037] In this embodiment, the energy data of all energy meters are classified and summed by phase to obtain the total energy data of the energy meters at time T1, specifically: A-phase total data:

[0038] B-phase total data:

[0039] C-phase total data:

[0040] in, This represents the corrected energy data of the i-th single-phase energy meter in the A-phase set at time T1, where m is the number of single-phase energy meters in the A-phase set. This represents the corrected phase A energy data of the j-th three-phase energy meter in phase A set at time T1, where k is the total number of three-phase energy meters in the metering box. This represents the corrected energy data of the i-th single-phase energy meter in the B-phase set at time T1, where w is the number of single-phase energy meters in the B-phase set. This represents the corrected B-phase energy data of the j-th three-phase energy meter within the B-phase set at time T1. This represents the corrected energy data of the i-th single-phase energy meter in the C-phase set at time T1, where p is the number of single-phase energy meters in the C-phase set. This represents the corrected C-phase energy data of the j-th three-phase energy meter within the C-phase set at time T1; and all data involved in the summation must undergo the energy data anomaly correction in step 3, and uncorrected data must not be included in the summation calculation.

[0041] In this embodiment, the method for determining the dynamic adaptive calculation period includes the following steps: Step 4.1: The measuring switch statistically analyzes the phase load fluctuation coefficients of phases A, B, and C from time T1 to time Tn-1. The phase load fluctuation coefficient is calculated as follows: (Maximum power supply energy of a phase - Minimum power supply energy of that phase) / Average power supply energy of that phase × 100%. Here, the average power supply energy of a phase is the sum of the power supply energy of all sampling points for that phase during the statistical period / the number of sampling points. The degree of load fluctuation in each phase is quantified by calculating the phase load fluctuation coefficient. In the formula, the difference between the maximum and minimum power supply energy reflects the load fluctuation amplitude. Dividing this by the average power supply energy standardizes the fluctuation amplitude, thus determining whether the load is experiencing severe fluctuations, moderate fluctuations, or stability.

[0042] Step 4.2: Determine the current calculation period based on the statistically obtained three-phase load fluctuation coefficients: If the maximum value of the three-phase load fluctuation coefficient is greater than 20%, then the current calculation period will be set to 20 minutes. If the maximum value of the three-phase load fluctuation coefficient is between 10% and 20%, then the current calculation period is set to 25 minutes. If the maximum value of the three-phase load fluctuation coefficient is ≤10%, then the current calculation period is set to 35 minutes.

[0043] This step dynamically adapts the calculation period based on the degree of load fluctuation. When the load fluctuation is large (coefficient > 20%), a short period of 20 minutes is set to quickly capture changes in line loss; when the fluctuation is moderate (10%-20%), a period of 25 minutes is set to balance accuracy and efficiency; when the fluctuation is small (≤10%), a long period of 35 minutes is set to reduce the collection of invalid data. By setting different periods, the optimal balance between accuracy and efficiency in line loss calculation is achieved.

[0044] Step 4.3: After every 3 calculation cycles, repeat steps 4.1-4.2 to update the calculation cycle for the next round.

[0045] In this embodiment, the slip calculation method is used to calculate the line loss rate of phases A, B, and C respectively. The following mathematical formula is used for the calculation: Line loss rates of phases A, B, and C at time Tn , , They are respectively:

[0046]

[0047]

[0048] in, , , The measurement switch's phase-by-phase power supply energy data at the time point of the calculation cycle preceding time Tn; , , This refers to the total electrical energy data of each phase from the electricity meter at the previous time point; and the calculation process for the line loss rate of each phase is completely independent of the load and metering data of the other two phases. Taking phase A as an example, in the numerator, It is the difference in power supply energy of phase A of the measuring switch within adjacent calculation cycles, representing the change in energy at the input terminal of phase A; This is the energy difference between adjacent cycles of the total energy of phase A in the electricity meter, representing the energy change at the output end of phase A. The difference between the two is the energy change of phase A in that cycle. The denominator is the energy change at the input end, and dividing the two gives the line loss rate of phase A at time Tn. This slip (difference between adjacent cycles) calculation method transforms static energy data into dynamic cycle differences, effectively eliminating random errors in single data acquisition and significantly improving the accuracy of line loss rate calculation.

[0049] In this embodiment, the specific result of the abnormal line loss status is as follows: Level 1 anomaly: Phase loss rate > 1.2 times the preset upper limit of anomalies, is judged as a serious anomaly; Level 2 anomaly: Phase loss rate > preset anomaly upper limit and ≤ 1.2 times the preset anomaly upper limit, is judged as moderate anomaly; Level 3 anomaly: If the phase loss rate is less than 0.8 times the preset lower limit of anomalies, it is judged as a data anomaly; Perform differentiated reporting operations based on different anomaly levels: If it is determined to be a Level 1 anomaly: the measuring switch sends an emergency alarm message to the main station system through the communication module within ≤10 seconds, and at the same time triggers the local audible and visual alarm device of the measuring switch; If the fault is determined to be a Level 2 anomaly: the measurement switch will recalculate the line loss rate of the phase after a 5-minute delay. If the recalculation result is still a Level 2 anomaly, a normal alarm message will be sent to the main station system. If the abnormality is determined to be Level 3, the measurement switch stores the abnormal line loss data in the local cache module. At a fixed time each day, all Level 3 abnormal data are aggregated and a data verification reminder message is sent to the main station system.

[0050] This embodiment also includes assistance in tracing the source of abnormal phase line losses, specifically: Step 6.1: When a phase is determined to have abnormal line loss, the measuring switch extracts the energy data of all single-phase energy meters under that phase and the energy data of the corresponding phase of the three-phase energy meters, and calculates the energy percentage of each energy meter. Energy percentage = (energy data of a single energy meter / total energy data of all energy meters in that phase) × 100%; Step 6.2: Compare the current energy percentage of each energy meter in this phase with the average energy percentage of the same period in the past 7 days, and calculate the percentage deviation value. Percentage deviation value = |current percentage - average percentage|. If the percentage deviation value of a certain energy meter is >8%, then mark the energy meter as a suspicious energy meter. Step 6.3: The measuring switch collects real-time operating data of the suspected energy meter through the RS485 bus, including real-time current data and real-time voltage data, and determines whether there is a situation where the real-time current is greater than 1.1 times the rated current of the energy meter or the real-time voltage is less than 0.9 times the rated voltage of the energy meter. If either of the above situations exists, an abnormality tracing clue containing the device number of the energy meter and the abnormal operating characteristics is recorded. Step 6.4: The measurement switch packages the abnormality tracing clues, abnormal line loss data of the phase, and abnormality level information together and reports them to the main station system.

[0051] like Figure 2As shown, the present invention also proposes a system for calculating the phase line loss of a metering box based on a smart metering switch, which is used to implement the above-mentioned method for calculating the phase line loss of a metering box based on a smart metering switch. The system includes a smart metering switch 101, an energy meter cluster 102, and a master station system 103. The smart metering switch 101 is communicatively connected to the energy meter cluster 102 and the master station system 103.

[0052] like Figure 3 As shown, the intelligent measurement switch includes an RS485 communication module 1011, a 4G / 5G module 1012, a metering acquisition module 1013, a data buffer module 1014, a local alarm module 1015, a phase recognition module 1016, a line loss calculation module 1017, an anomaly handling module 1018, and a traceability auxiliary module 1019. Among them, the phase recognition module 1016, the line loss calculation module 1017, the anomaly handling module 1018, and the traceability auxiliary module 1019 are functional modules of the core processor of the intelligent measurement switch. RS485 communication module 1011 is used to establish bidirectional communication with the electricity meter cluster, perform meter search operations to obtain the electricity meter type, and collect the electricity energy data, voltage data, and current data of the electricity meter. 4G / 5G module 1012 establishes a communication connection with the main station system and reports abnormal line loss data, alarm information, and tracing clues; The metering and acquisition module 1013 is used to collect the A, B, and C phase power supply energy data of the intelligent metering switch itself. , , The data collection frequency is synchronized with the electricity meter data. The data cache module 1014 is used to store the electricity meter type information, the collected voltage data, energy data, current data, as well as the calculated phase line loss rate data and abnormal data. The local alarm module 1015 includes LED indicator lights and a buzzer, which are used to trigger an audible and visual alarm when the level is determined to be a level one abnormality; The phase identification module 1016 is used for phase identification of electricity meters and outputs the phase assignment result of each electricity meter. Line loss calculation module 1017 is used to calculate the line loss rate using the slip method; The anomaly handling module 1018 is used to classify anomalies into different levels and perform differentiated reporting operations, generating alarm information and handling suggestions; The tracing assistance module 1019 is used to assist in tracing the source of abnormal phase line loss and generate abnormal tracing clues.

[0053] The electricity meter cluster 102 includes at least one single-phase electricity meter and / or at least one three-phase electricity meter. Both the single-phase and three-phase electricity meters support the RS485 communication protocol and upload energy data, voltage data, and current data to the smart metering switch 101.

[0054] like Figure 4 As shown, the main station system 103 includes a data receiving module 1031, a file management module 1032, an alarm processing module 1033, an operation and maintenance suggestion module 1034, and a data storage module 1035; The data receiving module 1031 is used to receive various data and information reported by the intelligent measuring switch; The file management module 1032 is used to store basic file information of metering boxes, smart metering switches, and electricity meter clusters; The alarm processing module 1033 is used to classify and display the received alarm information and sort it by priority. The operation and maintenance suggestion module 1034 is used to generate anomaly handling suggestions by associating historical data; The data storage module 1035 is used for long-term storage of phase line loss data, alarm information, and traceability clues.

[0055] In summary, the present invention is based on the following specific principles: The first step is initialization and meter identification. After the smart metering switch is powered on, it performs a meter search operation via the RS485 bus to automatically identify the type of electricity meter in the metering box (single-phase / three-phase). Because single-phase meters require clear phase assignment and three-phase meters require splitting the data for each phase, the processing logic for the two is different. This step is a prerequisite for calculating phase-by-phase line loss.

[0056] Secondly, phase identification and data caching are implemented. For single-phase energy meters, the measuring switch synchronously collects voltage data (including RMS value, zero-crossing time, and waveform distortion rate) for five consecutive grid cycles, while simultaneously collecting its own A / B / C three-phase voltage phase reference signals (phase start and peak time). By calculating the zero-crossing time difference between each phase of the single-phase meter and the measuring switch, if the absolute value of the difference is ≤0.3ms, the phase is initially determined. Then, the voltage waveform distortion rate is monitored for another 3 minutes. The phase is confirmed only when all data are ≤3%, avoiding phase misjudgment caused by interference. For three-phase energy meters, the measuring switch's own phase power supply energy data is directly cached at the first time point T1, while simultaneously collecting and caching the energy data of all energy meters.

[0057] Next comes data anomaly correction and phase-by-phase summation. First, anomaly detection is performed on the energy data: for single-phase meters, the rate of change for three consecutive data points is calculated (ηsingle = (Esingle after - Esingle before) / Esingle before × 100%), and an absolute value > 20% is marked as an anomaly; for three-phase meters, the rate of change is calculated phase-by-phase, and any phase exceeding 20% ​​is marked as an anomaly. Then, the average of valid data from the same period over the past 30 days is used to correct the anomaly data (the total corrected data for all three phases deviates from the original total data by ≤ 5%, ensuring data consistency). Finally, according to the confirmed phase assignment, the corrected data is categorized and summed phase-by-phase to obtain the total energy of phases A, B, and C at time T1, ensuring the accuracy of the data used in line loss calculations.

[0058] Next is the dynamic calculation cycle and line loss rate calculation. The load fluctuation coefficient of each phase from time T1 to Tn-1 is statistically analyzed by the measuring switch: (maximum power supply energy of a certain phase - minimum power supply energy) / average power supply energy × 100%. The calculation cycle is dynamically set according to the fluctuation coefficient: 20 minutes for fluctuation > 20% (quickly capture anomalies), 25 minutes for fluctuation 10%-20% (balance accuracy and efficiency), and 35 minutes for fluctuation ≤ 10% (reduce redundancy). The cycle value is updated every 3 cycles. When n>2, the slip calculation method is used to independently calculate the three-phase line loss rate: the difference in power supply energy of each phase at the measuring switch between time Tn and Tn-1 is used as the base, the sum difference of the phases of the energy meters during the same period is subtracted, and then divided by the power supply energy difference to eliminate random errors in single data and achieve independent and accurate calculation for each phase.

[0059] Finally, there is the anomaly detection, reporting, and tracing. The line loss rate is compared with preset parameters to classify anomalies into three levels: Level 1 (>1.2 times the upper limit, severe anomaly) requires an emergency report within 10 seconds plus a local audible and visual alarm; Level 2 (>1.2 times the upper limit, moderate anomaly) requires a normal report if the anomaly persists after a 5-minute recalculation; Level 3 (<0.8 times the lower limit, data anomaly) requires daily summary verification and reminders. When tracing the source of anomalies, the percentage of electricity energy of the meters under the abnormal phase is first calculated and compared with the percentage of the same period in the past 7 days. A deviation >8% marks a suspicious meter. Then, real-time current (>1.1 times the rated value) and voltage (<0.9 times the rated value) data of the suspicious meters are collected to generate tracing clues. These clues, along with the anomaly data and level, are packaged and reported to the main station to assist maintenance personnel in accurately locating the problem.

[0060] At the system level, the RS485 communication module of the smart metering switch is responsible for data transmission, the metering acquisition module synchronously collects power supply data, and the phase recognition, line loss calculation, anomaly handling, and traceability assistance modules support their respective functions; the energy meter cluster uploads data according to the protocol; the main station system receives data, manages files, sorts alarms, and generates operation and maintenance suggestions.

[0061] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch, characterized in that, Includes the following steps: Step 1: After the measuring switch is powered on, a meter search operation is performed via RS485 bus to obtain the types of all energy meters in the metering box. The energy meter types are divided into single-phase energy meters and three-phase energy meters. Step 2: For single-phase energy meters, the measuring switch collects and buffers the voltage data of the single-phase energy meter. After a preset time of data accumulation and analysis, the phase of the power grid connected to each single-phase energy meter is identified and determined. Specifically: Step 2.1: The measuring switch synchronously collects voltage data for each single-phase energy meter for 5 consecutive power grid cycles, and at the same time collects the voltage phase reference signal of its own three phases A, B, and C. The voltage phase reference signal includes the phase start time and the voltage peak time. The voltage data at least covers the voltage effective value, the voltage zero crossing time, and the voltage waveform distortion rate. Step 2.2: Calculate the time difference between the zero-crossing point of the voltage of each single-phase energy meter and the zero-crossing points of the voltages of phases A, B, and C of the measuring switch, and denot them as Δt_A, Δt_B, and Δt_C, respectively. If the absolute value of Δt_A is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase A; similarly, if the absolute value of Δt_B is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase B; if the absolute value of Δt_C is ≤ 0.3ms, it is preliminarily determined that the single-phase energy meter is connected to phase C. Step 2.3: For single-phase energy meters with preliminary phase determination, continuously collect voltage waveform distortion rate data within 3 minutes. If all voltage waveform distortion rate data within 3 minutes are ≤3%, the phase determination result of the single-phase energy meter is confirmed. If the voltage waveform distortion rate is >3% at any moment, the voltage data in that time period is discarded, and steps 2.1-2.2 are repeated until a stable phase determination result is obtained. For a three-phase energy meter, the measuring switch caches the phase power supply energy data provided by its own metering module at the first time point T1, denoted as... , , Simultaneously, collect and cache the energy data of all subordinate energy meters; Step 3: Correct any anomalies in the energy data of single-phase and three-phase energy meters, and perform phase-by-phase classification and summation calculations on the energy data of all energy meters to obtain the phase-by-phase summation data of the energy meters at time T1, which are denoted as follows: , , ; The specific steps for correcting abnormal energy data of single-phase and three-phase energy meters include: Step 3.1: Single-phase meter anomaly determination. Calculate the rate of change of the single-phase energy meter's energy data for three consecutive times using the formula ηsingle = (Esingle after - Esingle before) / Esingle before × 100%. If the absolute value of the rate of change is > 20%, mark the current data as trend abnormal data. Step 3.2: Three-phase meter phase determination. For the independent electrical energy data of phases A, B, and C of the three-phase energy meter, calculate the change rate of each phase according to the formula η phase = (after phase E - before phase E) / before phase E × 100%. If the absolute value of the change rate of any phase is > 20%, mark the data of that phase as abnormal. Step 3.3: Data correction and verification. For single-phase meters, abnormal data is corrected by taking the average of valid data from the same period over the past 30 days. For three-phase meters, abnormal data for each phase is corrected by taking the average of valid data from the corresponding phase over the past 30 days, and the deviation of the corrected total of the three phases from the original total data is ≤5%. Step 4: At the nth time point Tn, cache the phase power supply energy data of the measuring switch itself again. , , And recalculate and cache the total phase-by-phase energy data of the energy meter. , , When n>2, the phase line loss rate calculation is started, the calculation period is set to a dynamic adaptive calculation period, and the slip calculation method is used to calculate the line loss rates of phases A, B, and C respectively. Step 5: Compare the calculated line loss rate of each phase with the preset anomaly judgment parameters, filter out the abnormal line loss data that exceeds the preset range, and report the abnormal line loss status result to the main station system. The method also includes auxiliary methods for tracing the source of abnormal phase line losses, specifically: Step 6.1: When a phase is determined to have abnormal line loss, the measuring switch extracts the energy data of all single-phase energy meters under that phase and the energy data of the corresponding phase of the three-phase energy meters, and calculates the energy percentage of each energy meter. The energy percentage is calculated as follows: (energy data of a single energy meter / total energy data of all energy meters in that phase) × 100%. Step 6.2: Compare the current energy percentage of each energy meter in this phase with the average energy percentage of the same period in the past 7 days, and calculate the percentage deviation value. The percentage deviation value = |current percentage - average percentage|. If the percentage deviation value of a certain energy meter is >8%, then mark the energy meter as a suspicious energy meter. Step 6.3: The measuring switch collects real-time operating data of the suspected energy meter through the RS485 bus, including real-time current data and real-time voltage data, and determines whether there is a situation where the real-time current is greater than 1.1 times the rated current of the energy meter or the real-time voltage is less than 0.9 times the rated voltage of the energy meter. If either of the above situations exists, an abnormality tracing clue containing the device number of the energy meter and the abnormal operating characteristics is recorded. Step 6.4: The measurement switch packages the abnormality tracing clues, abnormal line loss data of the phase, and abnormality level information together and reports them to the main station system.

2. The method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch according to claim 1, characterized in that, The process of classifying and summing the energy data from all energy meters by phase to obtain the total energy data by phase at time T1 is as follows: A-phase total data: B-phase total data: C-phase total data: in, This represents the corrected energy data of the i-th single-phase energy meter in the A-phase set at time T1, where m is the number of single-phase energy meters in the A-phase set. This represents the corrected phase A energy data of the j-th three-phase energy meter in phase A set at time T1, where k is the total number of three-phase energy meters in the metering box. This represents the corrected energy data of the i-th single-phase energy meter in the B-phase set at time T1, where w is the number of single-phase energy meters in the B-phase set. This represents the corrected B-phase energy data of the j-th three-phase energy meter within the B-phase set at time T1. This represents the corrected energy data of the i-th single-phase energy meter in the C-phase set at time T1, where p is the number of single-phase energy meters in the C-phase set. This represents the corrected C-phase energy data of the j-th three-phase energy meter within the C-phase set at time T1; and all data involved in the summation must undergo the energy data anomaly correction in step 3, and uncorrected data must not be included in the summation calculation.

3. The method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch according to claim 1, characterized in that, The method for determining the dynamic adaptive calculation period includes the following steps: Step 4.1: The measuring switch calculates the phase load fluctuation coefficients of phases A, B, and C from time T1 to time Tn-1. The phase load fluctuation coefficient is calculated as follows: (maximum power supply energy of a phase - minimum power supply energy of that phase) / average power supply energy of that phase × 100%. The average power supply energy of a phase is calculated as the sum of the power supply energy of all sampling points of that phase during the statistical period / the number of sampling points. Step 4.2: Determine the current calculation period based on the statistically obtained three-phase load fluctuation coefficients: If the maximum value of the three-phase load fluctuation coefficient is greater than 20%, then the current calculation period will be set to 20 minutes. If the maximum value of the three-phase load fluctuation coefficient is between 10% and 20%, then the current calculation period is set to 25 minutes. If the maximum value of the three-phase load fluctuation coefficient is ≤10%, then the current calculation period is set to 35 minutes. Step 4.3: After every 3 calculation cycles, repeat steps 4.1-4.2 to update the calculation cycle for the next round.

4. The method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch according to claim 1, characterized in that, The slip calculation method is used to calculate the line loss rate of phases A, B, and C respectively, specifically using the following mathematical formula: Line loss rates of phases A, B, and C at time Tn , , They are respectively: in, , , The measurement switch's phase-by-phase power supply energy data at the time point of the calculation cycle preceding time Tn; , , This is the total energy data of the electricity meter for each phase corresponding to the previous time point; and the calculation process of the line loss rate for each phase is completely independent of the load data and metering data of the other two phases.

5. The method for calculating phase-by-phase line loss of a metering box based on an intelligent measuring switch according to claim 1, characterized in that, The specific results of the abnormal line loss status are as follows: Level 1 anomaly: Phase loss rate > 1.2 times the preset upper limit of anomalies, is judged as a serious anomaly; Level 2 anomaly: Phase loss rate > preset anomaly upper limit and ≤ 1.2 times the preset anomaly upper limit, is judged as moderate anomaly; Level 3 anomaly: If the phase loss rate is less than 0.8 times the preset lower limit of anomalies, it is judged as a data anomaly; Perform differentiated reporting operations based on different anomaly levels: If it is determined to be a Level 1 anomaly: the measuring switch sends an emergency alarm message to the main station system through the communication module within ≤10 seconds, and at the same time triggers the local audible and visual alarm device of the measuring switch; If the fault is determined to be a Level 2 anomaly: the measurement switch will recalculate the line loss rate of the phase after a 5-minute delay. If the recalculation result is still a Level 2 anomaly, a normal alarm message will be sent to the main station system. If the abnormality is determined to be Level 3, the measurement switch stores the abnormal line loss data in the local cache module. At a fixed time each day, all Level 3 abnormal data are aggregated and a data verification reminder message is sent to the main station system.

6. A system for calculating phase-separated line losses in a metering box based on an intelligent measuring switch, characterized in that, The system is used to implement the method for calculating the phase line loss of a metering box based on a smart metering switch as described in any one of claims 1-5. The system includes a smart metering switch, an energy meter cluster, and a master station system. The smart metering switch is communicatively connected to the energy meter cluster and the master station system. The intelligent measurement switch includes an RS485 communication module, a 4G / 5G module, a metering acquisition module, a data caching module, a local alarm module, a phase recognition module, a line loss calculation module, an anomaly handling module, and a source tracing auxiliary module. The RS485 communication module is used to establish bidirectional communication with the electricity meter cluster, perform meter search operations to obtain the electricity meter type, and collect the electricity energy data, voltage data, and current data of the electricity meter. The 4G / 5G module establishes a communication connection with the main station system to report abnormal line loss data, alarm information, and tracing clues; The metering and acquisition module is used to collect the A, B, and C phase power supply energy data Ea of the intelligent metering switch itself. n Eb n Ec n The data acquisition frequency is synchronized with the data acquisition frequency of the electricity meter; The data caching module is used to store the electricity meter type information, the collected voltage data, energy data, current data, as well as the calculated phase line loss rate data and abnormal data; The local alarm module includes LED indicators and a buzzer, which are used to trigger an audible and visual alarm when the level is determined to be a level one anomaly. The phase identification module is used for phase identification of electricity meters and outputs the phase assignment result for each electricity meter. The line loss calculation module is used to calculate the line loss rate using the slip method. The anomaly handling module is used to classify anomalies into different levels and perform differentiated reporting operations, generating alarm information and handling suggestions; The source tracing auxiliary module is used to assist in tracing the source of abnormal phase line loss and generate clues for tracing the source of the abnormality. The electricity meter cluster includes at least one single-phase electricity meter and / or at least one three-phase electricity meter. Both the single-phase electricity meter and the three-phase electricity meter support the RS485 communication protocol and upload electricity data, voltage data and current data to the smart metering switch. The main station system includes a data receiving module, an archive management module, an alarm handling module, an operation and maintenance suggestion module, and a data storage module; The data receiving module is used to receive various data and information reported by the intelligent measuring switch; The file management module is used to store basic file information for metering boxes, smart metering switches, and electricity meter clusters. The alarm processing module is used to classify, display, and prioritize received alarm information. The operation and maintenance suggestion module is used to generate anomaly handling suggestions by associating historical data; The data storage module is used for long-term storage of phase line loss data, alarm information, and traceability clues.

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