Electric energy meter abnormal behavior analysis and management method, equipment and program product

Abstract

The invention discloses an electric energy meter abnormal behavior analysis and management method, equipment and a program product, relates to the field of power grid safety, and is used for realizing intelligent, efficient and timely operation and maintenance of line loss of a target station area. According to the method, the concentrator is connected with the electric energy meters of the users in the target station area, the event data and the power consumption data recorded by the electric energy meters are obtained from the concentrator at the preset time, and analysis of at least one theme is carried out. According to the invention, intelligent, efficient and timely monitoring of the line loss of the target station area can be realized, the line loss monitoring is comprehensive and high in accuracy, and the operation and maintenance quality and efficiency can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of power grid security, and in particular, to a method for analyzing abnormal behaviors of electric energy meters and a management method therefor. Background Art

[0002] In recent years, the scale of power grid users has been continuously expanding, and the line losses in distribution transformers have become increasingly prominent. Line losses have already become a key task in the metering profession. However, traditional power consumption management technologies and methods are difficult to meet the increasingly prominent problems in the new era. There is a need for an intelligent line loss analysis means to assist management, improve operation and maintenance quality, and optimize line losses in distribution transformers.

[0003] In the initial stage of line loss occurrence, the operation data will have obvious fluctuations, and the positioning difficulty and operation and maintenance cost have the characteristic of increasing with the duration of the abnormality. The current method of manually monitoring the change of line loss indicators cannot find the cause of the abnormality in time and cope with the increasing number of large distribution transformers, and the limited human resources cannot efficiently solve complex line loss problems. Therefore, the traditional line loss operation and maintenance means can no longer meet the needs of the increasingly growing line loss management indicators in distribution transformers. Summary of the Invention

[0004] The object of the present invention is to provide a method for analyzing and managing abnormal behaviors of electric energy meters to achieve intelligent, efficient, and timely operation and maintenance of line losses in target distribution transformers for all or part of the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for analyzing abnormal behaviors of electric energy meters, comprising:

[0007] Connecting the electric energy meters of users in the target distribution transformer by using a concentrator, and respectively obtaining the event data and power consumption data recorded for each electric energy meter from the concentrator at a predetermined time, wherein the concentrator freezes the event data and power consumption data of the connected electric energy meters before the predetermined time;

[0008] Based on edge computing resources, analyzing at least one of the following topics for the corresponding electric energy meter according to the power consumption data: power quantity abnormality diagnosis, voltage and current abnormality diagnosis, abnormal power consumption diagnosis, load abnormality diagnosis, and wiring abnormality diagnosis.

[0009] The present invention also provides an apparatus for analyzing abnormal behaviors of electric energy meters, comprising a processor and a storage medium, wherein a computer program is stored in the storage medium, and when the processor runs the computer program, the above-mentioned method for analyzing abnormal behaviors of electric energy meters is executed.

[0010] The present invention also provides a computer program product, comprising a computer program, and when the computer program is run by a processor, the above-mentioned method for analyzing abnormal behaviors of electric energy meters is executed.

[0011] The present invention also provides a method for managing abnormal behaviors of electric energy meters, which includes:

[0012] Using the above-mentioned method for analyzing abnormal behaviors of electric energy meters to analyze the abnormalities of electric energy meters in the target power supply area; when an abnormal behavior is analyzed, a corresponding work order is generated and dispatched to the operation and maintenance terminal in the target power supply area.

[0013] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0014] This application is connected to the concentrator to obtain the frozen power consumption data and event data of each electric energy meter in the target power supply area in real time, and based on the edge computing resources in the target power supply area, it determines whether the line loss in the target power supply area is abnormal and determines the type of abnormality, so as to realize intelligent, efficient, and timely monitoring of the line loss in the target power supply area. This application can perform abnormal analysis on multiple topics, with comprehensive line loss monitoring and high accuracy. And on this basis, this application also automatically generates a work order corresponding to the type of abnormality and dispatches it to the corresponding operation and maintenance terminal, thereby greatly improving the operation and maintenance quality and efficiency of the target power supply area. Brief Description of the Drawings

[0015] The present invention will be described by way of examples with reference to the accompanying drawings, where:

[0016] Figure 1 is the flowchart of the method for analyzing abnormal behaviors of electric energy meters provided by an embodiment of this application.

[0017] Figure 2 is the structural diagram of the first device provided by an embodiment of this application.

[0018] Figure 3 is the schematic diagram of the topic relevance in an embodiment of this application. Detailed Embodiments

[0019] All the features disclosed in this specification, or all the steps in the disclosed methods or processes, except for mutually exclusive features and / or steps, can be combined in any manner.

[0020] Any feature disclosed in this specification (including any additional claims, abstract) can be replaced by other equivalent or similar-purpose alternative features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only an example of a series of equivalent or similar features.

[0021] Aiming at the problems that the method of manually monitoring the change of line loss indicators to monitor the abnormalities of electric energy meters is inefficient and seriously affected by subjectivity, the embodiments of this application provide a method for analyzing and managing abnormal behaviors of electric energy meters, aiming at the intelligent, efficient, and timely operation and maintenance of the line loss in the target power supply area.

[0022] Such as Figure 1As shown in the figure, the method for analyzing abnormal behavior of an electric energy meter provided by this application includes:

[0023] S1. Use a concentrator to connect to the electric energy meters of users in the target area, and obtain the event data and power consumption data recorded for each electric energy meter from the concentrator at a predetermined time. The concentrator freezes the event data and power consumption data of the connected electric energy meters before the predetermined time.

[0024] In some optional implementation manners, a connection is established between a first device and the concentrator, and the first device obtains the frozen time data and power consumption data of the electric energy meter from the concentrator.

[0025] As Figure 2 shown, the first device uses an MCU as the microcontroller of the device, and an operating system, such as an embedded operating system, is burned into the microcontroller. With the cooperation of the peripheral circuit, data acquisition and analysis are completed. Specifically, the MCU is connected to a power supply circuit, a FLASH memory circuit, a USB port, a Bluetooth circuit, an Ethernet interface, a 4G communication module, and an RS-485 / RS-232 bus interface.

[0026] The first device can establish a connection with the master station through a 4G communication module, an Ethernet interface, or an RS-232 bus interface, establish a connection with a handheld device through a Bluetooth circuit, establish a connection with the concentrator through an RS-485 / RS-232 bus interface, and establish a data connection with an external device through a USB port. The first device is powered by the power supply circuit.

[0027] As a feasible implementation manner, the first device sends read address messages with different baud rates to the concentrator through the RS-485 / RS-232 bus interface, and continuously tries to establish a connection with the concentrator, so as to complete the construction of the communication link with the concentrator without manual debugging.

[0028] In addition, in order to ensure that the concentrator in the target area reads the data of the electric energy meter without being affected by the first device, it is designed that the first device works at a predetermined time, and this predetermined time can be designed and adjusted. The first device obtains the frozen power consumption data and event data acquired by the concentrator at this predetermined time, and performs abnormal behavior analysis locally (i.e., edge computing resources).

[0029] S2. Based on the edge computing resources, at least one of the following analyses is performed on the corresponding electric energy meter according to the power consumption data: power quantity abnormal diagnosis, voltage and current abnormal diagnosis, abnormal power consumption diagnosis, load abnormal diagnosis, clock abnormal diagnosis, wiring abnormal diagnosis, CT secondary circuit abnormal diagnosis.

[0030] As mentioned above, after the first device obtains the event data and power consumption data, it can analyze the abnormal behavior of the electricity meter locally without centralizing these data to the master station for analysis, realizing edge computing of abnormal behavior, reducing the load of the master station and complex data interaction. Especially in the power consumption system with an extremely large number of grid users, it can avoid the overloading operation of the master station and reduce or avoid the problem of abnormal response lag caused by centralized analysis of the master station.

[0031] As an alternative implementation method, the method for analyzing abnormal power consumption includes:

[0032] According to the power consumption data, analyze at least one sub-topic among uneven indication of the electricity meter, flying away of the electricity meter, reverse running of the electricity meter, stopping of the electricity meter, abnormal rate setting of the electricity meter, and abnormal power fluctuation.

[0033] 1.1) Uneven indication of the electricity meter

[0034] The uneven indication of the electricity meter means that the total electricity indication value of the electricity meter is not equal to the sum of the electricity indication values of each rate. Analyze through the positive / negative active electricity indication value data frozen daily by the electricity meter in the power consumption data. The analysis methods include:

[0035] Calculate the difference between the positive / negative active electricity indication value in the frozen data of the electricity meter and the sum of the positive / negative active electricity indication values of each rate, and judge whether the absolute value of the difference exceeds "number of rates × K1 (for example, 0.01)". Among them, exclude the electricity meters with the positive / negative active electricity indication value being 0 or the sum of the positive / negative active electricity indication values of each rate being 0.

[0036] It is expressed by the analysis model as: judge whether |positive / negative active electricity indication value - ∑ positive / negative active electricity indication values of each rate| > number of rates × K1 holds. If the calculated difference exceeds "number of rates × K1", it is determined that there is an uneven indication of the electricity meter.

[0037] Taking the design of four-rate counting as an example, the analysis process of uneven indication of the electricity meter is to calculate whether the absolute value of the difference between the positive active electricity indication value E_MP_DAY_READ.PAP_R and (positive active rate 1 electricity indication value E_MP_DAY_READ.PAP_R1 + positive active rate 2 electricity indication value E_MP_DAY_READ.PAP_R2 + positive active rate 3 electricity indication value E_MP_DAY_READ.PAP_R3 + positive active rate 4 electricity indication value E_MP_DAY_READ.PAP_R4) exceeds "number of rates × K1".

[0038] If there is no situation where the absolute value of the difference between the positive / negative active electricity indication value and the sum of the positive / negative active electricity indication values of each rate is greater than "number of rates × K1" during the observation period (such as 2 periods), and the power consumption data acquisition process is normal, it is regarded as abnormal recovery.

[0039] 1.2) The electricity meter runs away

[0040] The electricity meter running away means that the daily electricity consumption of the electricity meter significantly exceeds the normal value. It is analyzed by using the daily frozen positive / negative active energy indication data in the electricity consumption data. The analysis methods for the electricity meter running away include:

[0041] Judge whether the ratio of the daily electricity consumption of the electricity meter to the possible maximum daily electricity consumption of the user is greater than the threshold K2 (such as 0.6).

[0042] It is expressed by the analysis model as:

[0043] Judge whether the daily electricity consumption / possible maximum daily electricity consumption > K2 holds. If so, it is determined that the electricity meter has run away.

[0044] For single-phase meters, the calculation method of the possible maximum daily electricity consumption is: rated voltage × rated current × 24h;

[0045] For three-phase meters, the calculation method of the possible maximum daily electricity consumption is: rated voltage × rated current × PT × CT × 24h;

[0046] Where PT represents the transformation ratio of the voltage transformer, and CT represents the transformation ratio of the current transformer.

[0047] The above parameters can be obtained from the relevant parameters collected by the electricity meter. For example, the identifier of the rated voltage is D_METER.VOLT_CODE (select the phase voltage for three-phase meters), the identifier of the rated current is D_METER.RATED_CURRENT, the identifier of PT is R_COLL_OBJ.PT_RATIO, and the identifier of CT is R_COLL_OBJ.CT_RATIO.

[0048] For the situation where the abnormal behavior of the electricity meter running away is detected, set an observation period of several days, such as an observation period of 2 days. If there is no situation where the ratio of the daily electricity consumption of the electricity meter to the possible maximum daily electricity consumption of the user is greater than the threshold K2 during the observation period, and the electricity consumption data collection process is normal, it is regarded as the abnormal recovery. Or, if a meter replacement record is generated during the observation period, it is regarded as the abnormal recovery.

[0049] 1.3) The electricity meter runs backward

[0050] The electricity meter running backward means that the data of this meter reading is smaller than that of the previous reading instead.

[0051] The event data reflects the decrease in the electricity meter indication. The electricity consumption data includes the daily frozen positive / negative active total energy indication and the positive (combined) reactive total energy indication. The analysis methods for the electricity meter running backward include:

[0052] For dedicated transformer users and low-voltage three-phase users, judge whether the daily forward / reverse active total energy indication value or the forward (combined) reactive total energy indication value - the indication value one hour ago is less than the threshold K3 (such as 0.01). For low-voltage single-phase users, judge whether the daily forward active total energy indication value and the reverse active total energy indication value - the indication value one day (or one hour) ago is less than the threshold K3.

[0053] It is expressed by the analysis model as:

[0054] Single-phase meter: Judge whether the current forward active total energy indication value - the forward active total energy indication value one day ago < K3 holds;

[0055] Three-phase meter: Judge whether the current forward active total energy indication value - the forward active total energy indication value one hour ago of the previous day < K3 holds; or

[0056] Judge whether the current reverse active total energy indication value - the reverse active total energy indication value one hour ago of the previous day < K3 holds; or

[0057] Judge whether the current forward (combined) reactive total energy indication value - the forward (combined) reactive total energy indication value one hour ago < K3 holds.

[0058] If the judgment condition holds, it is determined that there is an abnormal behavior of the electric energy meter running backwards.

[0059] The above relevant parameters can be obtained by looking up relevant identifiers in the acquired power consumption data. For example, the identifier of the forward active total energy indication value is E_MP_DAY_READ.PAP_R, the identifier of the reverse active total energy indication value is E_MP_DAY_READ.RAP_R, and the identifier of the forward (combined) reactive total energy indication value is E_MP_DAY_READ.PRP_R.

[0060] If there is no situation where the daily forward / reverse active total energy indication value and the forward (combined) reactive total energy indication value - the indication value one hour ago of dedicated transformer users and low-voltage three-phase users are less than the threshold K3 within the observation period (such as 2 days), or the daily forward active total energy indication value and the reverse active total energy indication value - the indication value one day (hour) ago of low-voltage single-phase users are less than the threshold K3, and there is no abnormality in the acquisition of power consumption data, it is regarded as abnormal recovery. If a meter replacement record is generated within the observation period, it is regarded as abnormal recovery.

[0061] 1.4) The electric energy meter stops running

[0062] The electric energy meter stops running means that the electric energy meter stops registering under the actual power consumption situation. The power consumption data includes the daily frozen forward / reverse active total energy indication value and the three-phase total and power curve. The analysis methods for the electric energy meter to stop running include:

[0063] Judge whether the difference in the indicated values of the total active energy in the forward and reverse directions for multiple consecutive (e.g., 3) whole hours or multiple consecutive days (e.g., 3 days) of the electricity meter is equal to 0, and whether there are multiple consecutive (e.g., 3) whole-hour curve values of the total active power greater than 0.01 kW during this period. If so, it is determined that an abnormal behavior of the electricity meter stopping occurs.

[0064] It is expressed by the analysis model as:

[0065] Judge whether the following conditions are satisfied:

[0066] Indicated value of total forward active energy - Indicated value of total forward active energy 2 days (or 2 hours) ago = 0, and Indicated value of total reverse active energy - Indicated value of total forward active energy 2 days (or 2 hours) ago = 0, and there are 3 consecutive whole-hour curve values of the total forward active power > 0.01 kW.

[0067] If the condition is satisfied, it is determined that an abnormal behavior of the electricity meter stopping occurs. The values of 2 days, 2 hours, and 3 in the above model are changeable values.

[0068] The parameters involved in the above analysis process can be obtained through the corresponding identifiers in the electricity consumption data. For example, the identifier for the indicated value of the total forward active energy is E_MP_DAY_READ.PAP_R, the identifier for the indicated value of the total reverse active energy is E_MP_DAY_READ.RAP_R, and the identifier for the total forward active power is E_MP_POWER_CURVE.

[0069] For the situation where the electricity meter stopping is detected, set an observation period of several days, such as 3 days. If the difference in the indicated values of the total active energy in the forward and reverse directions is equal to 0 during the observation period, and there are multiple consecutive whole-hour curve values of the total active power greater than 0.01 kW during this period, and there is no abnormality in the electricity consumption data collection, it is regarded as the recovery of the abnormality. If a meter replacement record is generated during the observation period, it is regarded as the recovery of the abnormality.

[0070] 1.5) Abnormal electricity meter rate setting

[0071] The abnormal electricity meter rate setting means that the indicated value of the electricity meter without rate setting is not 0.

[0072] The electricity consumption data includes the daily frozen indicated values of the forward and reverse active energies. The analysis method for the abnormal electricity meter rate setting includes:

[0073] According to the rate parameters set by the master station, compare the electricity meter indicated values to judge whether the indicated value of the electricity meter without rate setting is not 0. If so, it is determined that there is an abnormal electricity meter rate setting.

[0074] It is expressed by the analysis model as:

[0075] Judge whether the following conditions are satisfied:

[0076] The forward active power rate 5 - 14 electricity energy indication ≠ 0, or

[0077] The reverse active power rate 5 - 14 electricity energy indication ≠ 0.

[0078] If the above conditions are met, it is determined that there is an abnormal setting of the electricity meter rate.

[0079] The forward / reverse active power rate electricity energy indication can be obtained from the electricity consumption data according to the corresponding identification. For example, the identification of the forward active power rate 5 electricity energy indication is E_MP_DAY_READ.PAP_R5... The identification of the forward active power rate 14 electricity energy indication is E_MP_DAY_READ.PAP_R14; the identification of the reverse active power rate 5 electricity energy indication is E_MP_DAY_READ.RAP_R5... The identification of the reverse active power rate 14 electricity energy indication is E_MP_DAY_READ.RAP_R14.

[0080] For the situation of abnormal electricity meter rate setting, an observation period can also be set. For example, an observation period of 2 days. If the electricity energy indications of the electricity meter without rate setting (rates 5 - 14) are all successfully collected and are 0 within the observation period, it is regarded as the recovery of the abnormality. If a meter replacement record is generated within the observation period, it is regarded as the recovery of the abnormality.

[0081] 1.6) Abnormal electricity quantity fluctuation

[0082] Abnormal electricity quantity fluctuation means that the daily electricity quantity after meter replacement significantly exceeds that before meter replacement.

[0083] The event data reflects that the user replaces the electricity meter, and the electricity consumption data includes the daily frozen forward / reverse active power electricity energy indication data. The analysis method for abnormal electricity quantity fluctuation includes:

[0084] Respectively take the daily electricity consumption of multiple days (such as 5 days) before and after meter replacement, remove the highest and lowest two days, calculate the average value of the remaining multiple days (if 5 days remain 3 days), calculate the difference between the two average values. If the absolute value of the difference is greater than the threshold K4, and the ratio of the average daily electricity consumption before and after is outside 0.5 - 2 (the ratio of 0 electricity consumption after meter replacement is regarded as 0), then it is determined that there is an abnormal electricity quantity fluctuation. In addition, exclude the situation where there are abnormal measurement errors in the old electricity meter to be replaced within multiple days before meter replacement.

[0085] The value of K4 determines the accuracy of abnormal electricity quantity fluctuation detection. In some feasible implementation manners, K4 is set to 1.

[0086] For the situation of abnormal electricity quantity fluctuation, no automatic recovery design is carried out, and only manual recovery is performed after manual processing and archiving.

[0087] As an alternative implementation manner, the method for voltage and current abnormal diagnosis and analysis includes:

[0088] Based on event data and power consumption data, analyze at least one of the sub-topics of phase loss of voltage, over-limit of voltage, voltage unbalance, abnormality of phase B in high-voltage supply and high-voltage metering, voltage abnormality, neutral line abnormality, current loss, and current unbalance.

[0089] 2.1) Phase loss of voltage

[0090] Phase loss of voltage indicates that one or more phases of the metering circuit are disconnected.

[0091] Event data reflects phase loss of the watt-hour meter and abnormality of the terminal voltage circuit. Power consumption data includes three-phase voltage curves and three-phase current curves. The analysis methods for phase loss of voltage include:

[0092] Three-phase three-wire phase loss:

[0093] The voltage of any one of the A and C phases is less than K5 × reference voltage, and the voltage of the other phase is not less than K5 × reference voltage.

[0094] Three-phase four-wire phase loss:

[0095] The voltage of any one phase is less than K5 × reference voltage, and the voltage of any one of the other two phases is not less than K5 × reference voltage.

[0096] For direct-through meters, judge whether there is current and the voltage is less than K5 × reference voltage.

[0097] Equipment failure:

[0098] The three-phase voltages are all less than K5 × reference voltage.

[0099] When the above corresponding conditions are satisfied, it is determined that there is a phase loss of voltage phenomenon.

[0100] In addition, in some specific embodiments, multiple points (time points, default 3 points per day) need to be monitored within a day. If a phase loss of voltage event of the watt-hour meter or the terminal is simultaneously monitored, an abnormal report of phase loss of voltage shall be generated immediately. Otherwise, the abnormal report shall be generated only when the data diagnosis requirements are met for 3 consecutive days. Generating a report means that it is determined that an abnormality has occurred and an alarm is given.

[0101] It is represented by the analysis model as:

[0102] Three-phase three-wire:

[0103] U a <K5×U n ,U c ≥K5×U n , or

[0104] U c <K5×U n ,U a ≥K5×U n ;

[0105] Three-phase four-wire:

[0106] U a <K5×U n ,U c |U b ≥K5×U n , or

[0107] U b <K5×U n ,U c |U a ≥K5×U n , or

[0108] U c <K5×U n ,U a |U b ≥K5×U n .

[0109] When the above conditions are met, it is determined that there is a voltage phase break phenomenon.

[0110] In the formula, U a , U b , U c and U n respectively represent the phase A voltage, phase B voltage, phase C voltage and reference voltage. U a |U b represents "U a " or "U b ", and the rest is the same. Among them, the phase voltages can be retrieved from the electricity consumption data through the identifiers E_MP_VOL_CURVE.U1 to U96. Among them, for phase A: E_MP_VOL_CURVE.PHASE_FLAG = 1, for phase B: E_MP_VOL_CURVE.PHASE_FLAG = 2, for phase C: E_MP_VOL_CURVE.PHASE_FLAG = 3, and the reference voltage can be obtained by retrieving the phase voltage from the electricity consumption data through the identifier D_METER.VOLT_CODE.

[0111] For the case where a voltage phase break behavior is detected, an observation period can be designed for self-recovery. The preferred observation period for three-phase three-wire is 2 days, and the preferred observation period for three-phase four-wire is 1 week. If the voltages collected at all time points during the observation period are greater than the recovery threshold except for the failure of electricity consumption data collection, it is regarded as abnormal recovery.

[0112] Three-phase three-wire recovery condition: The AC phase voltages are both greater than K5×reference voltage, and there is no voltage phase break event during the recovery observation window period.

[0113] Three-phase four-wire restoration condition: The voltage of any one phase is greater than K5 × reference voltage, and there is no voltage interruption event within the restoration observation window period.

[0114] During the observation period, the proportion of the number of failed acquisitions of the voltage of any one phase in the total number of acquisitions shall not exceed Q1. The value of Q1 is preferably 1 / 24.

[0115] 2.2) Voltage out-of-limit

[0116] Voltage out-of-limit means that the voltage exceeds the upper limit or the upper-upper limit, or the voltage exceeds the lower limit or the lower-lower limit.

[0117] The event data reflects overvoltage of the electricity meter, undervoltage of the electricity meter, or terminal voltage out-of-limit, which can be determined by the identifier E_ERC24 in the event data. The electricity consumption data includes three-phase voltage curves. The voltage out-of-limit analysis method includes:

[0118] The voltage of any one phase is greater than K 1 × reference voltage; or the voltage of any one phase is lower than K 2 × reference voltage and not lower than K 3 × reference voltage. If the above conditions are met, a voltage out-of-limit event is determined.

[0119] In addition, preferably, multiple points need to be monitored within a day (the default is 3 points per day). If a voltage out-of-limit event of the electricity meter or the acquisition terminal is monitored simultaneously, an abnormal report of voltage out-of-limit shall be generated immediately. Otherwise, the abnormal report shall be generated only when the data diagnosis requirements are met continuously for 3 days.

[0120] It is expressed by the analysis model as:

[0121] Exceeding the upper-upper limit: U a |U b |U c ≥K 4 ×U n ;

[0122] Exceeding the upper limit: K 4 ×U n >U a |U b |U c ≥K 1 ×U n ;

[0123] Exceeding the lower limit: K 2 ×U n ≥U a |U b |U c >K 5 ×U n ;

[0124] Exceeding the lower-lower limit: K 5 ×Un ≥U a |U b |U c >K 3 ×U n 。

[0125] Briefly speaking, it is as follows:

[0126] Upper limit exceeded: Voltage range [K 1 , K 4 ) times the reference voltage

[0127] Lower limit exceeded: Voltage range (K 5 , K 2 ) times the reference voltage;

[0128] Upper upper limit exceeded: Voltage is not less than K 4 times the reference voltage;

[0129] Lower lower limit exceeded: Voltage range (K 3 , K 5 ) times the reference voltage.

[0130] In the above analysis model, K 1 , K 2 , K 3 , K 4 and K 5 are the corresponding thresholds respectively. In some embodiments, K 3 < K 5 < K 2 < K 1 < K 4 , for example, K 1 is 110%, K 2 is 90%, K 3 is 60%, K 4 is 120%, K 5 is 80%.

[0131] The abnormal report of voltage exceeding the limit can be designed with an observation period for self - recovery. The observation period is designed to be 2 days, for example.

[0132] During the observation period, except for the failure of electricity consumption data collection, the voltages collected at all time points are less than the recovery threshold, and all the collected voltage values are lower than K 3 × the reference voltage, and there is no voltage exceeding the limit event during the recovery observation period, which is regarded as abnormal recovery.

[0133] During the observation period, the proportion of the number of failed collection points of any - phase voltage in the total number of collection points shall not exceed Q1.

[0134] 2.3) Voltage unbalance

[0135] The unbalance of electricity consumption indicates that the voltage unbalance exceeds the limit.

[0136] The electricity consumption data uses a three-phase voltage curve. The voltage unbalance analysis method includes:

[0137] When the voltage of each phase is greater than 0, calculate the voltage unbalance rate according to (maximum three-phase voltage - minimum voltage) / maximum voltage, and judge whether it exceeds the limit by comparing whether the voltage unbalance rate is greater than K6. If it exceeds K6, it is out of limit. Among them:

[0138] Three-phase three-wire: (maximum voltage of phases A and C - minimum voltage of phases A and C) / maximum voltage of phases A and C at the same time point,

[0139] Three-phase four-wire: (maximum voltage of phases A, B, and C - minimum voltage of phases A, B, and C) / maximum voltage of phases A, B, and C at the same time point.

[0140] In addition, the situation of abnormal voltage phase break needs to be excluded first.

[0141] In addition, preferably, multiple points need to be monitored within a day, and an abnormal report is generated only when the data diagnosis requirements are met continuously for multiple days (the default is 10 points per day for 3 consecutive days).

[0142] It is expressed by the analysis model as:

[0143] Judge whether the following conditions are established:

[0144] Three-phase three-wire:

[0145]

[0146] Three-phase four-wire:

[0147]

[0148] If the condition is established, a voltage unbalance phenomenon occurs.

[0149] In some embodiments, K6 is designed to be 0.3.

[0150] The abnormal behavior of voltage unbalance can recover by itself after detection. Set an observation period of several days (such as 2 - 3 days). During the observation period, except for the failure of electricity consumption data collection, if the voltage unbalance rate calculated at all time points does not exceed the limit, it is regarded as abnormal recovery. The proportion of the number of failed voltage acquisitions of any one phase during the observation period to the total number of acquired points shall not exceed Q1.

[0151] 2.4) Abnormality of phase B of high supply and high metering

[0152] The voltage of phase B of high supply and high metering three-phase three-wire should be 0. The abnormality of phase B of high supply and high metering means that the voltage of phase B of high supply and high metering three-phase three-wire is not 0.

[0153] The electricity consumption data uses the phase voltage curve. The analysis method for the abnormal situation of the B phase in high supply and high metering includes:

[0154] Judge whether there is a situation where the B-phase voltage is greater than 0 or the B-phase current is not equal to 0. If so, it is determined that there is an abnormal phenomenon in the B phase of high supply and high metering.

[0155] In addition, multiple points need to be monitored within a day (the default is 5 points per day). Only when the abnormal phenomenon of the B phase in high supply and high metering appears at multiple points simultaneously, an abnormal report for the B phase in high supply and high metering will be generated.

[0156] The analysis of this sub-topic is aimed at the metering method of high supply and high metering, that is, the metering method with the metering method identifier C_MP.MEANS_MODE = 1. Its wiring method is three-phase three-wire, and the corresponding wiring method identifier is D_METER.WIRING_MODE = 2.

[0157] After determining the abnormality of the B phase in high supply and high metering, if during the observation period (such as 2 - 3 days), except for the failure of electricity consumption data collection, the collected voltage value of the B phase in high supply and high metering is 0 at all time points, it is regarded as the recovery of the abnormality. The proportion of the number of points with failed B-phase voltage collection during the observation period to the total number of collected points shall not exceed Q1.

[0158] 2.5) Voltage abnormality

[0159] Voltage abnormality indicates that one or more phases of the metering circuit are disconnected or loosely connected.

[0160] The event data reflects that the user uses a new electricity meter (newly installed or replaced), and the electricity consumption data uses the three-phase voltage curve. The voltage abnormality analysis method includes:

[0161] For low-voltage single-phase users:

[0162] Read the single-phase voltage of the single-phase user with an installed electricity meter once, and judge whether the voltage is greater than or equal to K7 and less than K8. If so, it is determined that there is a voltage abnormality.

[0163] For low-voltage three-phase users:

[0164] Read the three-phase voltage of the three-phase user with an installed electricity meter once, and judge whether there is any phase voltage greater than or equal to K7 and less than K8. At the same time, it is necessary to exclude the situation where the voltage and current of this phase are both 0, but including the situation where all three-phase voltages are 0. If it exists, it is determined that there is a voltage abnormality.

[0165] As a feasible implementation method, K7 is designed to be 0V and K8 is designed to be 154V.

[0166] In addition, a threshold K9 can be designed. For the electricity meters determined to have abnormal voltages, when the single-phase (three-phase) voltage is remotely read again later, if the single-phase (three-phase) voltage is not lower than K9, the abnormality is restored. This threshold K9 is greater than K8 and can be designed as 198V, for example.

[0167] 2.6) Neutral wire abnormality

[0168] A neutral wire abnormality indicates poor contact of the neutral wire terminal or misconnection of the neutral wire and the phase wire.

[0169] The event data reflects the user's use of a new electricity meter, and the electricity consumption data uses the three-phase voltage curve. When analyzing the neutral wire abnormality, it is necessary to first exclude the electricity meters with abnormal voltages. The methods for analyzing the neutral wire abnormality include:

[0170] For low-voltage single-phase users:

[0171] Read the single-phase voltage of the single-phase users with installed electricity meters once. If it is determined that the voltage is greater than or equal to K10, then the neutral wire abnormality is determined.

[0172] For low-voltage three-phase users:

[0173] Read the three-phase voltage of the three-phase users with installed electricity meters once, and determine whether there is any phase voltage greater than or equal to K11, and the voltage unbalance rate calculated according to (maximum value of three-phase voltage - minimum value) / maximum value is greater than or equal to K12. If so, then the neutral wire abnormality is determined.

[0174] Among the above thresholds, K10 > K11. In some embodiments, K10 is designed as 300V, K11 is designed as 242V, and K12 is designed as 10%.

[0175] For the behavior of determining the neutral wire abnormality, if later, for low-voltage single-phase users, the daily remotely read voltage is not higher than K13, then the abnormality is restored. This K13 is higher than K11 and is designed as 270V, for example. For low-voltage three-phase users, if the unbalance rate of the daily remotely read three-phase voltage is less than K14, then the abnormality is restored. This K14 is lower than K12 and is 5%, for example.

[0176] 2.7) Current loss

[0177] Current loss means a working condition where any one or two of the three-phase currents are less than the starting current, and the load currents of the other phase wires are greater than 5% of the rated (basic) current.

[0178] The event data reflects the current loss of the electricity meter, and the electricity consumption data includes the three-phase current curve and the three-phase voltage curve. The analysis of current loss needs to meet the voltage range of 0.7 to 0.9 times the rated voltage. The analysis of current loss includes:

[0179] Three-phase three-wire loss of current: The absolute value of the current in any one of the A and C phases is less than 0.5% of the rated (basic) current, and the absolute value of the current in the other phase is not less than 5% of the rated (basic) current;

[0180] Three-phase four-wire loss of current: The absolute value of the current in any one phase is less than 0.5% of the rated (basic) current, and the absolute value of the current in at least one of the other two phases is not less than 10% of the rated (basic) current.

[0181] If the above conditions are met, it is determined that a power loss event has occurred.

[0182] If it is monitored that the event data reflects a power loss event of the electricity meter, and at least one point of power loss event is detected through the electricity consumption data within one day, a current loss anomaly report is generated to determine that a power loss has occurred; otherwise, at least 3 consecutive points need to be monitored through the electricity consumption data within one day to generate a current loss anomaly report.

[0183] It is expressed by the analysis model as:

[0184] When 0.7×U n ≤U≤0.9×U n (U is the detected voltage):

[0185] Three-phase three-wire:

[0186] I a <0.5%I n ,I c ≥5%I n , or

[0187] I c <0.5%I n ,I a ≥5%I n ;

[0188] Three-phase four-wire:

[0189] I a <0.5%I n ,I b |I c ≥10%I n , or

[0190] I b <0.5%I n ,I a |I c ≥10%I n , or

[0191] I c <0.5%I n ,I a |I b ≥10%I n .

[0192] I a ,I b ,I c and I n It represents phase A current, phase B current, phase C current and rated (basic) current in sequence. If the above conditions are met, it is determined that a power loss event occurs.

[0193] Each current is obtained from the power consumption data through the corresponding identification. For example, the phase current identification is E_MP_CUR_CURVE.I1~I96, where the A, B, and C phase current identifications are E_MP_CUR_CURVE.PHASE_FLAG=1,2,3 respectively; the rated current identification is D_METER.RATED_C.

[0194] After the abnormal behavior of current loss is determined, it can recover automatically after a set observation period (such as 2-3 days). During the observation period, except for data collection failure, the current collected at all time points meets the recovery conditions and is considered to be abnormal recovery.

[0195] Three-phase three-wire restoration: When the voltage range is 0.7 to 0.9 times the rated voltage, the AC phase current is greater than 5% of the rated (basic) current.

[0196] Three-phase four-wire recovery: When the voltage range is 0.7 to 0.9 times the rated voltage, if the current of any phase is greater than 5% of the rated (basic) current, it is considered as abnormal recovery.

[0197] During the observation period, the proportion of failed collection points of any phase voltage and current to the total collection points shall not exceed Q1.

[0198] 2.8) Current imbalance

[0199] Current imbalance means that the current imbalance exceeds the limit.

[0200] The power consumption data used is the three-phase current curve. The current imbalance analysis methods include:

[0201] When the absolute value of each phase current is greater than 0 (the default value is 0.3A, and the specific value is set according to the actual situation), the current imbalance rate is calculated according to (maximum value - minimum value of three-phase current) / maximum value to determine whether the current imbalance rate exceeds K15. If it exceeds K15, it is determined that current imbalance occurs. This process needs to exclude the abnormal current loss first. The threshold K15 is preferably designed to be 0.5.

[0202] The three-phase three-wire data range is phases A and C, and the three-phase four-wire judgment range is phases A, B, and C.

[0203] In addition, multiple points need to be monitored within a day, and each point continuously monitored for multiple days must meet the conditions for determining the occurrence of current imbalance phenomenon to generate a current imbalance exception report (default 10 points per day, for 3 consecutive days), and determine the occurrence of current imbalance abnormal behavior.

[0204] Taking three-phase four-wire as an example (similarly modify the data range for three-phase three-wire), it is represented by the analysis model as:

[0205] Judge Whether it holds. If so, it is determined that there is a current imbalance phenomenon.

[0206] After determining the occurrence of current imbalance abnormal behavior, it can recover automatically after the set observation period (such as 2 days). During the observation period, except for data acquisition failures, the current imbalance rates calculated at all time points do not exceed the limit, which is regarded as abnormal recovery. The proportion of the number of data acquisition failures of any phase voltage and current during the observation period to the total number of data acquisition points shall not exceed Q1.

[0207] As an optional implementation method, the method for abnormal electricity consumption diagnosis and analysis includes:

[0208] According to the event data and electricity consumption data, analyze at least one sub-topic among the opening of the meter cover, opening of the terminal button cover of the meter, opening and closing of the metering door, constant magnetic field interference, differential electricity anomaly, differential power anomaly, and power outage event anomaly.

[0209] 3.1) Opening of the meter cover

[0210] The opening of the meter cover indicates the opening of the single-phase and three-phase meter covers, which is reflected through the event data. By reading the meter status word in the event data, if the event data reflects the existence of a meter cover opening event and the opening event is within 1 minute to 3 days, then judge:

[0211] Whether the difference between the meter cover opening time and the meter installation time is greater than the time threshold T1, and this time threshold T1 is, for example, 1 day. If so, it is determined that there is an abnormal behavior of opening the meter cover. Among them, events of normal meter cover opening need to be excluded, such as the case of initial installation and normal work orders, which can be excluded by comparing the work order execution time; cases of incorrect logic of the cover opening time also need to be excluded, such as the cover opening time being before the installation time, then the cover opening time logic is incorrect.

[0212] The relevant parameters can be obtained from the event data through the corresponding identifiers. Among them, the identifier for the meter cover opening event of the meter: E_ERC37, the identifier for the installation time: D_METER.INST_DATE, and the identifier for the cover opening time: E_ERC37.EVENT_TIME.

[0213] If an event of closing the meter cover occurs within the observation period (e.g., 2 days), and no new abnormal event of opening the meter cover occurs after closing the cover, it is regarded as the recovery of the abnormality. If a meter replacement record is generated within the observation period, it is regarded as the recovery of the abnormality.

[0214] 3.2) Opening the start button cover of the electricity meter

[0215] Opening the start button cover of the electricity meter means opening the start button box of the three-phase electricity meter. It is detected through event data. The event data reflects the existence of an event of the start button box of the electricity meter. Read the status word of the electricity meter from the event data. If the time of the start button box is within the range of 1 minute to 3 days, then judge:

[0216] Whether the difference between the time of the start button box of the electricity meter and the installation time of the electricity meter is greater than the time threshold T2. This time threshold T2 is, for example, 1 day. If so, it is determined that there is an abnormal behavior of the start button box of the electricity meter. Among them, normal start button boxes of electricity meters need to be excluded, such as the cases of initial installation and normal work orders; cases with logical errors in the time of the start button box also need to be excluded, such as the time of the start button box being before the installation time.

[0217] Relevant parameters can be obtained from the event data through corresponding identifiers. For example, the event identifier of the start button box of the electricity meter: E_ERC38, and the time identifier of the start button box: E_ERC38.EVENT_TIME.

[0218] If an event of closing the start button box of the electricity meter occurs within the observation period (e.g., 2 days), and no new abnormal event of opening the start button box occurs after closing the start button box, it is regarded as the recovery of the abnormality. If a meter replacement record is generated within the observation period, it is regarded as the recovery of the abnormality.

[0219] 3.3) Opening and closing of the metering door

[0220] Opening and closing of the metering door indicates that the access control of the metering box (cabinet) is opened or closed.

[0221] The event data includes the change record of the terminal status variable, and the electricity consumption data includes the terminal status variable. When analyzing the opening and closing of the metering door, read the change record of the terminal status variable and judge whether the difference between the opening time of the metering door and the installation time is greater than the time threshold T3 (e.g., 1 day). If so, it is determined that there is an abnormal behavior of the opening of the metering door. Among them, normal opening and closing of the metering door need to be excluded, such as the cases of initial installation and normal work orders, and cases with logical errors in the opening and closing time of the metering door also need to be excluded, such as the time of the start button box being earlier than the installation time. In addition, if the same abnormality occurs twice at the same time for the same electricity meter and the abnormality descriptions are the same, it is determined that the abnormal event of the electricity meter is invalid.

[0222] The abnormality of the opening / closing of the metering door can be obtained from the event data through the identifier E_ERC91.

[0223] If abnormal closing of the metering gate occurs within the observation period (e.g., 1 - 2 days), and no new abnormal opening of the metering gate occurs after closing the metering gate, it is regarded as the recovery from the abnormality. If a meter replacement record is generated within the observation period, it is regarded as the recovery from the abnormality.

[0224] 3.4) Constant magnetic field interference

[0225] Constant magnetic field interference means that the electricity meter is interfered by a constant magnetic field.

[0226] When the event data reflects the constant magnetic field interference of the electricity meter, it is judged whether the interference occurrence time is more than 1 day later than the electricity meter installation time, and whether the interference duration exceeds the time threshold T4 (e.g., 1 hour - 8 hours). If so, it is determined that there is an abnormal behavior of constant magnetic field interference.

[0227] Event identification of constant magnetic field interference of electricity meter: E_ERC40, start - stop identification: E_ERC40.START_OR_STOP_SIGN, interference occurrence / end time identification: E_ERC38.EVENT_TIME. The corresponding status and time can be obtained through the corresponding identification, and the interference duration is calculated by subtracting the interference occurrence time from the interference end time.

[0228] If there is no new constant magnetic field interference at all measurement points under the terminal of this measurement point within the observation period (e.g., 2 days), it is regarded as the recovery from the abnormality.

[0229] 3.5) Abnormal power difference

[0230] Abnormal power difference means that there is a large deviation in the electricity quantities of two different circuits. Through the analysis of electricity consumption data, the electricity consumption data includes: the forward active total electricity energy indication value of the metering circuit (referring to the sum of the electricity energies of all measurement points with the nature of settlement points under the terminal, obtained from the electricity consumption data through the identification C_MP.MP_ATTR_CODE = 01), and the forward active total electricity energy indication value of the comparison circuit (referring to the electricity energy of the terminal AC sampling measurement point). The methods for analyzing abnormal power difference include:

[0231] Analyze the electricity quantity difference between the metering circuit and the comparison circuit (such as the AC sampling circuit) in the same period. If the electricity quantity difference exceeds the set threshold K16, it is determined that there is an abnormal behavior of power difference.

[0232] This threshold Among them, Q2: electricity quantity of the metering circuit, Q3: electricity quantity of the comparison circuit.

[0233] In addition, set the threshold K17 = 15% × K16. If the electricity quantity deviation values of two different circuits are both lower than K17 within the observation period (e.g., 1 - 2 days) without acquisition failure, it is regarded as the recovery from the abnormality.

[0234] 3.6) Abnormal power differential

[0235] Power differential anomaly indicates a large deviation in the apparent power of two different circuits. By analyzing power consumption data, which includes the active power curve and reactive power curve at the measurement point. When the current in each phase is greater than 0 and the current in any one phase is greater than 10% of the rated (basic) current, compare the difference in apparent power between different circuits (AC sampling, metering), and determine whether the difference exceeds the defined threshold K18. For example, K18 is 0.15 to 0.3 times the power of the AC sampling circuit. If so, it is determined that there is a power differential anomaly.

[0236] In addition, if it is monitored multiple times within a day and continuously monitored for multiple days (default 5 times a day for 3 consecutive days), and there is a power differential anomaly in all cases, it is determined that there is a power differential anomaly behavior.

[0237] Phase power is obtained from the power consumption data through the identifiers E_MP_POWER_CURVE.P1 to P96. Among them, the active and reactive powers are: E_MP_POWER_CURVE.DATA_TYPE = 1 and 5 respectively.

[0238] If within the observation period (such as 2 days), when the current in each phase is greater than 0 and the current in any one phase is greater than 10% of the rated (basic) current, and the deviation value of the apparent power between two different circuits is lower than 0.15 times the power of the AC sampling circuit, it is regarded as the anomaly recovery.

[0239] 3.7) Power outage event anomaly

[0240] Power outage event anomaly is analyzed through the terminal power on / off event record (identified as E_ERC14), the power failure record of the electric energy meter, and the terminal online / offline record in the event data.

[0241] Analysis of power on / off event anomalies includes:

[0242] A. There is a power on event but no power off event (no power off event in the 4 days before the power on event or multiple consecutive power on events are included in the statistics);

[0243] B. There is a power off event but no power on event;

[0244] C. The power outage duration is too short (less than K19 minutes, such as 5 minutes);

[0245] D. The power outage duration is too long (greater than K20 minutes, such as 3×24×60 minutes).

[0246] When counting, invalid anomaly events need to be excluded. If the same anomaly occurs twice at the same time for the same terminal and the anomaly description is the same, it is determined that the electric energy meter anomaly event is invalid.

[0247] If non-empty data sent later than the power outage event or a power restoration event received later than the power outage event is found within the observation period (such as 3 days), it is regarded as an abnormal restoration.

[0248] As an optional implementation manner, a method for load abnormal diagnosis and analysis includes:

[0249] Based on event data and power consumption data, analyze at least one sub-topic among demand over-capacity, load over-capacity, current over-current, continuous load below the lower limit, and abnormal power factor.

[0250] 4.1) Demand over-capacity

[0251] Demand over-capacity means that the maximum demand exceeds the user's contract capacity. It is analyzed through power consumption data. The power consumption data includes the monthly maximum demand of the measurement point.

[0252] Judge whether the demand of the electricity meter exceeds the user's contract capacity, and calculate whether the ratio of the demand to the capacity exceeds the defined threshold K21. This threshold K21 is, for example, 0.8 - 1.3 times (such as 1.1 - 1.3 times) of the contract capacity.

[0253] For a user with multiple metering points, the maximum demand of the user is obtained by accumulating the demand × CT × PT of each metering point with the nature of the settlement point.

[0254] The parameters involved are identified as: contract capacity: C_CONS.CONTRACT_CAP, total positive active maximum demand: E_MP_DAY_DEMAND.PAP_DEMAND, total negative active maximum demand: E_MP_DAY_DEMAND.RAP_DEMAND, total positive reactive maximum demand: E_MP_DAY_DEMAND.PRP_DEMAND, total negative reactive maximum demand: E_MP_DAY_DEMAND.RRP_DEMAND.

[0255] If, in the case of no acquisition failure, the diagnostic calculation result value in the second month after the event occurs is less than 0.8 times of the contract capacity, it is regarded as an abnormal restoration.

[0256] 4.2) Load over-capacity

[0257] Load over-capacity means that the user's load exceeds the operating capacity, and it is analyzed through power consumption data. The power consumption data includes the active power curve.

[0258] Calculate whether the ratio of the active power to the operating capacity (identified as C_CONS.RUN_CAP) exceeds the defined threshold K22. If so, it is determined that there is a load over-capacity phenomenon. This K22 is, for example, 0.8 - 1.3 times (such as 1.1 - 1.3 times) of the operating capacity.

[0259] In addition, if multiple detections are made within a day and the load overcapacity phenomenon occurs continuously for multiple days (default is 3 times a day for 3 consecutive days, and the parameter configuration can be adjusted), it is determined that there is an abnormal behavior of load overcapacity.

[0260] If within the observation period (such as 2 days), except for acquisition failures, there are time point calculation results greater than 0.8 times the operating capacity at no more than the threshold Q3 (such as 1 / 12), and the data points exceeding 0.8 times the operating capacity are not consecutive time points, it is regarded as abnormal recovery. The proportion of the number of acquisition failure points of active power within the observation period to the total number of acquisition points shall not exceed Q1.

[0261] 4.3) Overcurrent

[0262] Overcurrent means that the load current continuously exceeds the rated current, and it is analyzed through the current overlimit record (identified as E_ERC25) in the event data and the three-phase current curve in the electricity consumption data.

[0263] If any phase current is greater than K22*I n , it is determined that the overcurrent phenomenon occurs. The situation of the load exceeding the transformer capacity needs to be excluded. K22 is 1 - 1.5 times the rated current.

[0264] In addition, if N points are detected within a day, and if there is a current overlimit record in the electric energy meter or acquisition terminal simultaneously, an overcurrent abnormal behavior report is immediately generated to determine the overcurrent abnormal behavior. Otherwise, after the overcurrent phenomenon occurs at N points (such as 10 points) for 3 consecutive days, an overcurrent abnormal behavior report is generated.

[0265] If in the observation period (such as 2 - 3 days), any phase current is less than or equal to K22*I n , and there is no current overlimit event in the electric energy meter or acquisition terminal, and the number of time points of acquisition failure of any phase current within the observation period is not higher than 1 / 24 of the total number of acquisition time points, it is regarded as abnormal recovery. The proportion of the number of acquisition failure points of any phase within the observation period to the total number of acquisition points shall not exceed Q1.

[0266] 4.4) Load continuously below the lower limit

[0267] Load continuously below the lower limit indicates that the electricity load is too small for multiple consecutive days. It is analyzed through the total active power curve in the electricity consumption data.

[0268] In the case where the number of records greater than 0 monitored within 1 day of the total active power exceeds the set threshold (N points, default is 12 points), calculate the ratio of the highest value of the secondary side apparent power to the secondary side rated power on the same day, and determine whether the ratio is not greater than K23 (such as 0.2 - 0.45). If so, it is determined that there is an abnormal behavior of continuous load exceeding the lower limit. Otherwise, after monitoring for M consecutive days (such as 60 days) and the number of records greater than 0 exceeds the set threshold, it is determined that there is an abnormal behavior of continuous load exceeding the lower limit.

[0269] For a user with multiple metering points, the power of each metering point with the nature of the settlement point is accumulated or the total group load is used as the user load.

[0270] The identification of the above-mentioned parameters is as follows: measured point active power: E_MP_POWER_CURVE.P1~P96, enable identification: E_MP_POWER_CURVE.DATA_TYPE = 1; total group active power: E_TOTAL_POWER_CURVE.P1~P96.

[0271] If within the observation period (such as 2 days), in the case where the number of records greater than 0 monitored within 1 day of the total active power exceeds the set threshold, and the ratio of the highest value of the secondary side apparent power to the secondary side rated power on the same day is less than K23, it is regarded as abnormal recovery.

[0272] 4.5) Abnormal power factor

[0273] Abnormal power factor means that the daily average power factor is too low, and it is analyzed through the daily positive active total power and the power factor curve in the electricity consumption data.

[0274] In the case where the daily positive active total power is greater than the set limit, collect the daily power factor curve, and determine whether the daily average power factor is not greater than K24. If so, it is determined that there is an abnormal power factor behavior. This K24 is, for example, 0.3 - 0.5.

[0275] The identification of the parameters involved in the above analysis is as follows: measured point power: E_MP_POWER_CURVE.P1~P96, measured point power factor: E_MP_FACTOR_CURVE.C1~C96.

[0276] If within the observation period (such as 2 days), when the daily positive active total power is greater than the set limit, the power factor curve of any phase is greater than K24, it is regarded as abnormal recovery. The proportion of the number of failed acquisitions of the daily positive active total power and the power factor current of any phase within the observation period to the total number of acquisitions shall not exceed Q1.

[0277] As an optional implementation method, the method for diagnosing and analyzing wiring abnormalities includes:

[0278] Based on event data and power consumption data, analyze at least one of the sub - topics of reverse power anomaly, phase sequence anomaly, power flow reversal, and shunt of single - phase meters.

[0279] 5.1) Reverse power anomaly

[0280] A reverse power anomaly means that a normal power - consuming user has reverse power. Analyze through the data of the daily frozen reverse active energy indication value (identified as E_MP_DAY_ENERGY.RAP_E) in the power consumption data. The analysis methods include:

[0281] If the total reverse active energy indication value of the electricity meter is greater than 0, the reverse power on the current day is greater than the threshold K25, and it satisfies that the total reverse active power > the total forward active power × K26, then it is determined that a reverse power anomaly behavior has occurred. For example, K25 is 1 kWh. For dedicated transformers and low - voltage three - phase users, K26 takes a value of 0.02, and for low - voltage single - phase users, K26 takes a value of 0.1.

[0282] If within the observation period (such as 2 days) under the condition of no acquisition failure, the daily total reverse active power within the observation period is less than K25, or the daily total reverse active power is less than the daily total reverse active power < the total forward active power × K26, then the anomaly is considered to have recovered. The proportion of the number of failed acquisition points of the electrical energy or the electrical energy indication value used to calculate the electrical energy in the total acquisition points during the observation period shall not exceed Q1.

[0283] 5.2) Phase sequence anomaly

[0284] A phase sequence anomaly means that the voltage and current of the electricity meter are in an inverse phase sequence state. Analyze through the records of reverse phase sequence of electricity meter voltage, abnormal terminal phase sequence in the event data and the phase angle of the electricity meter, the total active power of the electricity meter, and the total active power of the terminal in the power consumption data. The analysis methods include:

[0285] If the absolute value of the difference between the total active power of the electricity meter and the total active power of the terminal divided by the total active power of the terminal is greater than the threshold K27 (for example, 0.1), and the terminal has not had a phase sequence anomaly, then it is judged as an electricity meter phase sequence anomaly behavior.

[0286] If within the observation period (such as 2 days) except for acquisition failures, the absolute value of the difference between the total active power of the electricity meter and the total active power of the terminal calculated at all time points is less than or equal to the threshold K27, then the anomaly is considered to have recovered. The proportion of the number of failed acquisition points of the total active power of the electricity meter and the total active power of the terminal in the total acquisition points during the observation period shall not exceed Q1.

[0287] 5.3) Power flow reversal

[0288] Power flow reversal means that the current or power reverses. Analyze through the power flow reversal records in the event data or the current curve and power curve in the power consumption data. The analysis methods include:

[0289] If the number of negative values in the current or power curve data is greater than the set threshold K28 (such as 6 times a day), and the absolute value of the phase - split active power corresponding to the phase when the negative value appears is greater than K29 (such as 0.1 kW), then it is determined that a reverse power flow abnormal behavior occurs.

[0290] If, during the observation period (such as 2 days), except for acquisition failures, the current or power curve data at all time points do not show negative values, or the number of times when the absolute value of the phase - split active power corresponding to the phase when the negative value appears is greater than K29 is less than the set threshold K30 (such as 2 times a day), it is regarded as abnormal recovery. The proportion of the number of acquisition failure points of the current and power curves during the observation period in the total number of acquisition points shall not exceed Q1.

[0291] 5.4) Shunt of single - phase meter

[0292] The shunt of a single - phase meter refers to the phenomenon that due to the change or fault of the metering circuit wiring, no current or only part of the current passes through the current coil. It is analyzed through the current of the current A - phase and the current neutral - line current in the power consumption data. The analysis methods of the shunt of a single - phase meter include:

[0293] Retrieve the A - phase current and the neutral - line current of the intelligent meter of low - voltage single - phase users once. When it is judged that the absolute value of the neutral - line current > 0.1 A, check whether ((the absolute value of the neutral - line current - the absolute value of the A - phase current) / the absolute value of the neutral - line current) > K31 holds. If it holds, then it is determined that the shunt abnormal behavior of the single - phase meter occurs.

[0294] For all users under the I - type collector or II - type concentrator to which the electric energy meter satisfying the above conditions belongs, retrieve their A - phase current and neutral - line current again on the next day. If both the A - phase current and the neutral - line current change compared with the previous day and still satisfy the above shunt judgment conditions, then check again whether there is a situation of sharing the neutral line.

[0295] In addition, if the shunt of single - phase meters occurs for multiple meters under the same terminal, it is suspected that there is a situation of sharing the neutral line, and no abnormality is generated.

[0296] If there are records of retrieving their A - phase current and neutral - line current during the observation period (such as 2 days), and no situation satisfying the shunt judgment conditions is found again, it is regarded as abnormal recovery.

[0297] As an optional implementation method, if two or more topics are analyzed simultaneously, the expected value E of the abnormality of the simultaneously analyzed topics is calculated by the following formula:

[0298]

[0299] In the formula, n is the number of topics analyzed simultaneously; P i is the weight of the i - th topic (see Table 1); R jkis the correlation degree between the j-th theme and the k-th theme (as Figure 3 shown). When the expectation E reaches a predetermined threshold, it is determined that an abnormal behavior has occurred.

[0300] Specifically, when E ≤ 0.8, it is judged as continuous attention. If it does not recover for multiple consecutive days, it is processed as an abnormality (the recommended range of k is 3 to 60); when 0.8 < E ≤ 3, it is judged as an abnormal behavior, and auxiliary determination is made using curve data, etc., and the confirmed abnormality is processed; when E > 3, the abnormal behavior is diagnosed and the abnormality is processed.

[0301] Table 1 Theme Weight Table

[0302]

[0303]

[0304] The embodiment of the present application further provides an abnormal behavior analysis device for an electric energy meter, including a processor and a storage medium. A computer program is stored in the storage medium. When the processor runs the computer program, it executes the abnormal behavior analysis method for the electric energy meter in the above embodiment.

[0305] The embodiment of the present application further provides a computer program product, including a computer program. When the computer program is run by a processor, it executes the abnormal behavior analysis method for the electric energy meter in the above embodiment.

[0306] The embodiment of the present application further provides an abnormal behavior management method for an electric energy meter, which includes: performing abnormal analysis on the electric energy meters in the target distribution area by using the above abnormal behavior analysis method for the electric energy meter; when an abnormal behavior is analyzed, generating a corresponding work order and dispatching it to the operation and maintenance terminal of the target distribution area.

[0307] The so-called "corresponding work order" includes the type of the judged abnormal behavior and the indication of the on-site observation point to guide the inspection content that the operation and maintenance personnel should focus on at the site.

[0308] The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, and any new combination of the steps of any new method or process disclosed.

Claims

1. A method for analyzing abnormal behavior of an electric energy meter, characterized in that: include: Using a concentrator to connect electric energy meters of users in a target area, obtaining event data and power consumption data recorded for each electric energy meter from the concentrator at a predetermined time, wherein the concentrator freezes the event data and power consumption data of the connected electric energy meters before the predetermined time; Based on the edge computing resources, at least one of the following topics is analyzed on the corresponding electric energy meter according to the electricity consumption data: abnormal power consumption diagnosis, abnormal voltage and current diagnosis, abnormal power consumption diagnosis, abnormal load diagnosis, and abnormal wiring diagnosis.

2. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for conducting power anomaly diagnosis and analysis include: Based on the electricity consumption data, analysis is performed on at least one sub-topic of uneven electricity representation, electricity meter flying away, electricity meter running backwards, electricity meter stopping, abnormal electricity meter rate setting, and abnormal electricity fluctuation.

3. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for conducting voltage and current abnormality diagnosis and analysis include: Based on the event data and power consumption data, analysis is performed on at least one sub-topic of voltage phase failure, voltage over-limit, voltage imbalance, high supply and high meter B phase abnormality, voltage abnormality, neutral line abnormality, current loss, and current imbalance.

4. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for conducting abnormal power consumption diagnosis and analysis include: Based on the event data and electricity consumption data, analysis is performed on at least one sub-topic of opening the meter cover, opening the terminal button cover, opening and closing the metering door, constant magnetic field interference, abnormal quantity differential, abnormal power differential, and abnormal power outage event.

5. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for load anomaly diagnosis and analysis include: Based on the event data and power consumption data, an analysis is performed on at least one sub-topic of demand overcapacity, load overcapacity, current overcurrent, load continuously exceeding a lower limit, and power factor abnormality.

6. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for conducting wiring anomaly diagnosis and analysis include: According to the event data and the power consumption data, at least one sub-topic of reverse power anomaly, phase sequence anomaly, power flow reversal, and single-phase meter shunting is analyzed.

7. The method for analyzing abnormal behavior of an electric energy meter according to claim 1, characterized in that: Methods for conducting two or more thematic analyses simultaneously include: The expected E of the subject anomalies analyzed simultaneously is calculated by: Where n is the number of topics analyzed simultaneously; P i is the weight of the ith topic; R jk is the correlation between the jth topic and the kth topic; When the expectation E reaches a predetermined threshold, it is determined that abnormal behavior occurs.

8. An abnormal behavior analysis device for an electric energy meter, comprising a processor and a storage medium, wherein the storage medium stores a computer program, characterized in that: When the processor runs the computer program, it executes the abnormal behavior analysis method of the electric energy meter as described in any one of claims 1-7.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the abnormal behavior analysis method of an electric energy meter as described in any one of claims 1 to 7 is executed.

10. A method for managing abnormal behavior of an electric energy meter, characterized in that: include: Performing abnormal analysis on the electric energy meter in the target area using the electric energy meter abnormal behavior analysis method as described in any one of claims 1 to 7; When abnormal behavior is analyzed, a corresponding work order is generated and dispatched to the operation and maintenance terminal of the target station area.

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