CN113452145B

CN113452145B - Method and system for monitoring power utilization condition of low-voltage transformer area user

Info

Publication number: CN113452145B
Application number: CN202111000360.8A
Authority: CN
Inventors: 何敏生; 余永奎; 邓芳; 刘嘉绮; 吴智海; 谈绮倩; 陈珊珊; 焦海锋; 林永结; 谢玲; 杨腾飞
Original assignee: Zhongshan Power Supply Bureau of Guangdong Power Grid Co Ltd
Current assignee: Zhongshan Power Supply Bureau of Guangdong Power Grid Co Ltd
Priority date: 2021-08-30
Filing date: 2021-08-30
Publication date: 2022-01-25
Anticipated expiration: 2041-08-30
Also published as: CN113452145A

Abstract

The application discloses power consumption condition monitoring method and system for low-voltage transformer area users, all users in a transformer area are divided into high-power consumption users and low-power consumption users according to historical daily average power consumption of the users, power consumption monitoring can be carried out for different power consumption users, then suspicion of electricity stealing is further identified for the high-power consumption users and the low-power consumption users respectively, in the suspicion of electricity stealing of the high-power consumption users, historical normal metering data of an electric energy meter are determined through a dynamic time window, a first threshold value requirement is set accordingly, the real-time metering data of the electric energy meter are compared with the first threshold value requirement, the suspicion of electricity stealing is identified according to a comparison result, in the suspicion of electricity stealing of the low-power consumption users, the real-time metering data of the electric energy meter are compared through a preset second threshold value requirement, and the suspicion of electricity stealing is identified according to the comparison result. Based on the scheme, the load scale and the required power utilization scale of users in the transformer area are fully considered, and the false judgment rate of electricity stealing is reduced.

Description

Method and system for monitoring power utilization condition of low-voltage transformer area user

Technical Field

The application relates to the technical field of power distribution data monitoring, in particular to a method and a system for monitoring power utilization conditions of users in a low-voltage transformer area.

Background

At present, with the deepened application of data acquisition of electric energy meters, the requirement for lean management of power utilization conditions of users in a transformer area is continuously increased. Such as: the records of events such as meter opening of a meter cover of a station area user meter, zero and live line abnormity, voltage loss, current loss, phase failure, latest power failure time, clock out-of-tolerance, voltage loss of a clock battery of an ammeter and the like are not mastered by an effective means, and the abnormity of the station area user electricity utilization can bring great influence on line loss.

At present, the traditional technical means is to carry out on-site user-by-user troubleshooting on a user, or can roughly obtain the line loss condition of the whole distribution area through the distribution area line loss statistical analysis function of a metering automation system, but the power utilization condition of the user in a low-voltage distribution area still lacks accurate data analysis.

The invention discloses an anti-electricity-stealing and line loss analyzing and monitoring system for a low-voltage transformer area, which is disclosed by the invention with the patent application publication number of CN106972628A, wherein the current, voltage, electric quantity, uncapping record and other field real-time parameters related to electricity stealing of low-voltage users in the transformer area are directly and automatically acquired from a background, the analysis and screening accuracy for judging electricity stealing or line loss by combining various parameters is extremely high, suspected electricity stealing users are determined according to data, the inspection is convenient and quick, and the user-by-user inspection of each user on the field is not needed. However, the scheme does not consider the load scale and the required power utilization scale of users under the district, and further leads to high false judgment rate of electricity stealing.

Disclosure of Invention

The application provides a method and a system for monitoring power utilization conditions of users in a low-voltage transformer area, which are used for solving the technical problem that the load scale and the required power utilization scale of the users in the transformer area are not considered in the prior art, so that the misjudgment rate of electricity stealing is high.

In view of the above, a first aspect of the present application provides a method for monitoring power consumption of users in a low-voltage distribution area, including the following steps:

s1, acquiring power utilization attributes of all users in the target distribution area based on the power marketing system, wherein the power utilization attributes comprise user numbers and historical daily average power consumption of the users;

s2, comparing the historical daily average power consumption of the user with a preset power consumption classification threshold, classifying the corresponding user as a high-power-consumption user when the historical daily average power consumption of the user is larger than the preset power consumption classification threshold, classifying the corresponding user as a low-power-consumption user when the historical daily average power consumption of the user is not larger than the preset power consumption classification threshold, and writing the user numbers respectively corresponding to the high-power-consumption user and the low-power-consumption user into two pre-established user files respectively, wherein the pre-established user files comprise a high-power-consumption user file and a low-power-consumption user file;

s3, obtaining an electric energy meter uncapping event of a user in the target platform area, wherein the electric energy meter uncapping event comprises electric energy meter uncapping times and electric energy meter longest uncapping time, judging whether the electric energy meter uncapping times are larger than preset times or not, and whether the electric energy meter longest uncapping time is larger than the preset longest uncapping time or not, if the electric energy meter uncapping times are judged to be larger than the preset times or not, and the electric energy meter longest uncapping time is larger than the preset longest uncapping time or not, generating a timestamp based on a time service system and obtaining corresponding wiring abnormal events of the user, wherein the wiring abnormal events comprise a voltage reverse phase sequence, a current reverse phase sequence and a current reverse state;

s4, judging whether the wiring abnormal event occurs or not, and if the wiring abnormal event occurs, determining that the corresponding user has suspicion of electricity stealing; if the wiring abnormal event is not determined to occur, executing step S5;

s5, acquiring the user number of the user without the wiring abnormal event in the step S4, and performing matching search in the pre-established user file according to the user number so as to judge that the user is a high-power-consumption user or a low-power-consumption user; if the user is determined to be a high power consumption user, executing step S6, and if the user is determined to be a low power consumption user, executing step S8;

s6, obtaining historical normal metering data of the electric energy meter of a user and real-time metering data of a first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, and a time window of the real-time metering data of the first electric energy meter is the current timestamp;

s7, setting a first threshold requirement according to the historical normal metering data of the electric energy meter, comparing the real-time metering data of the first electric energy meter with the first threshold requirement, and determining that the user is suspected of electricity stealing when the real-time metering data of the first electric energy meter is judged not to meet the first threshold requirement;

s8, obtaining second electric energy meter real-time metering data of the electric energy meter of the user, judging whether the second electric energy meter real-time metering data meet a preset second threshold value requirement, and determining that the user is suspected of electricity stealing when the second electric energy meter real-time metering data do not meet the preset second threshold value requirement.

Preferably, step S1 is preceded by:

s101, sending power failure instructions to all transformers in two adjacent transformer areas based on the transformer area control points, wherein the power failure instructions comprise power failure occurrence time and power failure duration time so that the transformers execute power failure actions;

s102, generating power failure event information by accessing an electric energy meter of the transformer, wherein the power failure event information comprises the power failure occurrence time and the power failure duration time;

s103, sending a meter reading signal to the electric energy meters through a meter reading channel so as to read the power failure event information generated by the electric energy meters, and classifying the electric energy meters with the same power failure occurrence time and power failure duration time into the same transformer area by comparing the power failure occurrence time and the power failure duration time of all the electric energy meters.

Preferably, step S3 is preceded by:

s301, a time setting instruction is sent to the electric energy meter through a master station or a local handheld device, and after the electric energy meter receives the time setting instruction, the electric energy meter is broadcasted for time setting.

Preferably, step S6 specifically includes:

s611, obtaining historical normal metering data of an electric energy meter of a user and real-time metering data of a first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, the preset time period is a unit of month, week or year, the historical normal metering data of the electric energy meter comprises historical zero line current time sequence data, historical live line current time sequence data, voltage loss year average times, current loss year average times and phase failure year average times, the historical zero line current time sequence data and the historical live line current time sequence data are identical in time window, and the real-time metering data of the first electric energy meter is the current timestamp and comprises real-time zero line current, real-time live line current, field voltage loss records, field phase failure records and field current loss records;

s612, calculating historical time sequence current ratio data based on the zero line current historical time sequence data and the live line current historical time sequence data, and performing curve fitting on the historical time sequence current ratio data to obtain a current ratio time sequence curve, wherein the historical time sequence current ratio data is the current ratio of corresponding time sequence points in the live line current historical time sequence data and the zero line current historical time sequence data;

s613, discretizing the current ratio time sequence curve to obtain a plurality of discrete values, comparing the discrete values with a preset discrete threshold range, and rejecting the discrete values which are not in the preset discrete threshold range to obtain a rejected current ratio time sequence curve.

Preferably, step S7 specifically includes:

s711, setting the rejected current ratio time sequence curve, the voltage loss average number of times, the current loss average number of times, the phase loss average number of times and the historical electricity utilization average amount as the first threshold requirement;

s712, when the electric energy meter is a single-phase electric meter, calculating a real-time current ratio according to the real-time current of the zero line and the real-time current of the live line, comparing the real-time current ratio with the eliminated current ratio time sequence curve, judging whether the real-time current ratio falls on the eliminated current ratio time sequence curve, and if the real-time current ratio does not fall on the eliminated current ratio time sequence curve, determining that the user has suspicion of electricity stealing;

when the electric energy meter is a three-phase electric energy meter, judging whether the voltage loss times recorded by the field voltage loss are greater than the annual average voltage loss times or not, and if the voltage loss times recorded by the field voltage loss are greater than the annual average voltage loss times, determining that the user is suspected of electricity stealing; judging whether the phase failure times of the field phase failure record are greater than the phase failure annual average times or not, and if the phase failure times of the field phase failure record are greater than the phase failure annual average times, determining that the user has suspicion of electricity stealing; and judging whether the current loss times of the field current loss records are greater than the annual average current loss times or not, and if so, determining that the user has suspicion of electricity stealing.

Preferably, step S8 specifically includes:

s801, acquiring second electric energy meter real-time metering data of an electric energy meter of a user, wherein the second electric energy meter real-time metering data comprises zero line current, live line current, a voltage loss state, a phase failure state and a current loss state;

s802, when the electric energy meter is judged to be a single-phase electric meter, judging whether the ratio of the live wire current to the zero wire current is larger than a preset ratio threshold value, and if the ratio of the live wire current to the zero wire current is judged to be larger than the preset ratio threshold value, determining that the user has suspicion of electricity stealing;

and when the electric energy meter is judged to be a three-phase electric meter, judging whether the electric energy meter is in a voltage loss state, a phase failure state or a current loss state, and if the electric energy meter is judged to be in the voltage loss state, the phase failure state or the current loss state, determining that the user has suspicion of electricity stealing.

Preferably, step S8 is followed by:

s9, when the suspicion of electricity stealing of the user is determined, acquiring a corresponding user address of the user, and loading the user address into a power grid GIS map for marking;

and S10, inputting the historical normal metering data of the electric energy meter, the real-time metering data of the first electric energy meter and the real-time metering data of the second electric energy meter into a browser webpage, and displaying the data in a chart form.

In a second aspect, the present invention further provides a power consumption monitoring system for users in a low-voltage distribution area, including: the system comprises a power utilization attribute acquisition module, a file classification module, a cover opening event judgment module, a wiring abnormity judgment module, a file query module, an electric energy meter data acquisition module, a first electric energy meter data comparison module and a second electric energy meter data comparison module;

the power consumption attribute acquisition module acquires power consumption attributes of all users in a target distribution area based on a power marketing system, wherein the power consumption attributes comprise user numbers and historical daily average power consumption of the users;

the profile classification module is used for comparing the historical daily average power consumption of the user with a preset power consumption classification threshold, classifying the corresponding user as a high-power-consumption user when the historical daily average power consumption of the user is greater than the preset power consumption classification threshold, classifying the corresponding user as a low-power-consumption user when the historical daily average power consumption of the user is not greater than the preset power consumption classification threshold, and respectively writing the user numbers respectively corresponding to the high-power-consumption user and the low-power-consumption user into two pre-established user profiles, wherein the pre-established user profiles comprise a high-power-consumption user profile and a low-power-consumption user profile;

the uncapping event judging module is used for acquiring an electric energy meter uncapping event of a user in the target station area, wherein the electric energy meter uncapping event comprises electric energy meter uncapping times and electric energy meter longest uncapping time, judging whether the electric energy meter uncapping times are greater than preset times or not, and whether the electric energy meter longest uncapping time is greater than the preset longest uncapping time or not, and if the electric energy meter uncapping times are greater than the preset times or not and the electric energy meter longest uncapping time is greater than the preset longest uncapping time, generating a timestamp based on a time service system and acquiring corresponding wiring abnormal events of the user, wherein the wiring abnormal events comprise a voltage reverse phase sequence, a current reverse phase sequence and a current reverse state;

the wiring abnormity judging module is used for judging whether the wiring abnormity event occurs or not and determining that the corresponding user has suspicion of electricity stealing if the wiring abnormity event is judged to occur; the system is also used for sending a working signal to the file inquiry module if the abnormal wiring event is judged not to occur;

the file inquiry module is used for acquiring the user number of the user who does not have the wiring abnormal event, and performing matching search on the pre-established user file according to the user number so as to judge that the user is a high-power-consumption user or a low-power-consumption user;

the electric energy meter data acquisition module is used for acquiring historical normal metering data of an electric energy meter of a user and real-time metering data of the first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, and a time window of the real-time metering data of the first electric energy meter is the current timestamp;

the first electric energy meter data comparison module is used for setting a first threshold requirement according to historical normal metering data of the electric energy meter, comparing the real-time metering data of the first electric energy meter with the first threshold requirement, and determining that the user is suspected of electricity stealing when the real-time metering data of the first electric energy meter is judged not to meet the first threshold requirement;

the second electric energy meter data comparison module is used for acquiring second electric energy meter real-time metering data of an electric energy meter of a user, judging whether the second electric energy meter real-time metering data meets a preset second threshold value requirement, and determining that the user is suspected of electricity stealing when the second electric energy meter real-time metering data is judged not to meet the preset second threshold value requirement.

Preferably, the system further comprises a platform area control module, an information generation module and a user change attribution module;

the transformer area control module is used for sending power failure instructions to all transformers in two adjacent transformer areas, wherein the power failure instructions comprise power failure occurrence time and power failure duration time so as to enable the transformers to execute power failure actions;

the information generation module is used for generating power failure event information by accessing an electric energy meter of the transformer, wherein the power failure event information comprises the power failure occurrence time and the power failure duration;

the household attribution changing module is used for issuing a meter reading signal to the electric energy meter through a meter reading channel so as to read the power failure event information generated by the electric energy meter, and is also used for comparing the power failure occurrence time and the power failure duration time of all the electric energy meters in a difference mode so as to classify the electric energy meters with the same power failure occurrence time and the same power failure duration time into the same transformer area.

Preferably, the system further includes a time synchronization module, where the time synchronization module is configured to send a time synchronization instruction to the electric energy meter through the master station or the local handheld device, and is further configured to broadcast time synchronization to the electric energy meter after the electric energy meter receives the time synchronization instruction.

According to the technical scheme, the invention has the following advantages:

the invention divides all the users in the distribution area into high power consumption users and low power consumption users according to the historical daily average power consumption of the users, can monitor the power consumption of different power consumption users, in the process of monitoring the electricity consumption, after the fact that whether the electricity stealing suspicion exists in a user is determined by combining the cover opening event and the wiring abnormal event of the electric energy meter, further identifying the suspicion of electricity stealing for the high-power-consumption users and the low-power-consumption users respectively, in identifying the suspicion of electricity stealing for the high-power-consumption users, determining historical normal metering data of the electric energy meter through a dynamic time window so as to set a first threshold requirement, and compares the real-time metering data of the electric energy meter with the first threshold requirement so as to identify the suspicion of electricity stealing according to the comparison result, and in the process of identifying the suspicion of electricity stealing of the low-power-consumption user, comparing the suspicion of electricity stealing with the real-time metering data of the electric energy meter through a preset second threshold value requirement, and identifying the suspicion of electricity stealing according to a comparison result. Based on the scheme, the load scale and the required power utilization scale of users in the transformer area are fully considered, and the false judgment rate of electricity stealing is reduced.

Drawings

Fig. 1 is a flowchart of a method for monitoring power consumption of users in a low-voltage distribution area according to an embodiment of the present disclosure;

fig. 2 is a schematic structural diagram of a power consumption monitoring system for users in a low-voltage distribution area according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

For easy understanding, referring to fig. 1, the method for monitoring power consumption of users in a low-voltage distribution area according to the present invention includes the following steps:

s1, acquiring power consumption attributes of all users in the target distribution area based on the power marketing system, wherein the power consumption attributes comprise user numbers and historical daily average power consumption of the users;

s2, comparing the historical daily average power consumption of the users with a preset power consumption classification threshold, classifying the corresponding users into high-power-consumption users when the historical daily average power consumption of the users is larger than the preset power consumption classification threshold, classifying the corresponding users into low-power-consumption users when the historical daily average power consumption of the users is not larger than the preset power consumption classification threshold, and writing user numbers corresponding to the high-power-consumption users and the low-power-consumption users into two pre-established user files respectively, wherein the pre-established user files comprise high-power-consumption user files and low-power-consumption user files;

it should be noted that, because the type of the user may be a common home or a factory enterprise, the power load quantity scale and the power scale of each type of the user are different, in this embodiment, the power consumption classification threshold is 7000 watts, and the users in the target area are classified into low-power-consumption users and high-power-consumption users according to 7000 watts, so that power consumption monitoring can be performed for different power-consumption users.

S3, obtaining electric energy meter uncapping events of users in a target platform area, wherein the electric energy meter uncapping events comprise electric energy meter uncapping times and electric energy meter longest uncapping time, judging whether the electric energy meter uncapping times are larger than preset times or not, and whether the electric energy meter longest uncapping time is larger than the preset longest uncapping time or not, if the electric energy meter uncapping times are judged to be larger than the preset times or not, and the electric energy meter longest uncapping time is larger than the preset longest uncapping time or not, generating timestamps based on a time service system and obtaining corresponding wiring abnormal events of the users, wherein the wiring abnormal events comprise voltage reverse phase sequences, current reverse phase sequences and current reverse states;

s4, judging whether a wiring abnormal event occurs or not, and if the wiring abnormal event occurs, determining that the corresponding user has suspicion of electricity stealing; if the wiring abnormal event is not determined to occur, executing step S5;

it should be noted that the uncovering event of the electric energy meter is an abnormal operation event of the electric energy meter, and after the abnormal operation event of the electric energy meter is confirmed, if a wiring abnormal event occurs, it is indicated that the user operates the wiring of the electric energy meter, so that it is determined that the user has suspicion of electricity stealing.

S5, acquiring the user number of the user without the wiring abnormal event in the step S4, and performing matching search in a pre-established user file according to the user number so as to judge that the user is a high-power-consumption user or a low-power-consumption user; if the user is determined to be a high power consumption user, executing step S6, and if the user is determined to be a low power consumption user, executing step S8;

s6, acquiring historical normal metering data of the electric energy meter of a user and real-time metering data of the first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, and a time window of the real-time metering data of the first electric energy meter is the current timestamp;

in the embodiment, the current timestamp is 2021/1, the time window of the current timestamp can be in units of weeks, months and years when the historical normal metering data of the electric energy meter is acquired, and the time window of the historical normal metering data of the electric energy meter is 2019, 12/31-2021/1. And when the current timestamp is other moments, the current moment is still used for pushing forward for a certain time period, so that the historical normal metering data of the electric energy meter is dynamically determined.

S7, setting a first threshold requirement according to historical normal metering data of the electric energy meter, comparing the real-time metering data of the first electric energy meter with the first threshold requirement, and determining that the user is suspected of electricity stealing when the real-time metering data of the first electric energy meter is judged not to meet the first threshold requirement;

it should be noted that, load power consumption of a high power consumption user is high, generally a factory enterprise, mostly due to a large scale of the number of loads, and meanwhile, there is a change of load increment, and due to a high working power consumption of the loads, it may cause a sudden change of the metering data of the electric energy meter during operation of most loads, and the sudden change may be caused by improper operation of load equipment rather than a power stealing behavior, so that it is necessary to consider the sudden change of the metering data of the electric energy meter caused by the above non-power stealing behavior, and then set a first threshold requirement through the historical normal metering data of the electric energy meter corresponding to a dynamic time window, and since the historical normal metering data of the electric energy meter changes with a timestamp, the historical normal metering data of the electric energy meter may cause a change of the historical normal metering data of the electric energy meter, and the first threshold requirement dynamically changes with the historical normal metering data of the electric energy meter, the influence of sudden changes of the metering data of the electric energy meter caused by non-electricity stealing behaviors can be reduced.

S8, obtaining real-time metering data of a second electric energy meter of the user, judging whether the real-time metering data of the second electric energy meter meets a preset second threshold value requirement, and determining that the user is suspected of electricity stealing when the real-time metering data of the second electric energy meter does not meet the preset second threshold value requirement.

It should be noted that, because the load power consumption of the low-power consumption user is low, and the load scale is relatively stable in a general household, and the change of the metering data of the electric energy meter caused by the load is relatively stable, it can be determined whether the user is suspected of electricity stealing by presetting the second threshold value to the real-time metering data of the second electric energy meter, in a general example, the preset second threshold value is required to be set according to the historical metering data of the user, and is generally a fixed value.

The invention provides a method for monitoring power consumption of users in a low-voltage transformer area, which can be used for monitoring power consumption of different power consumption users by dividing all users in the transformer area into high-power consumption users and low-power consumption users according to historical daily average power consumption of the users, further identifying the suspicion of electricity stealing for the high-power consumption users and the low-power consumption users after determining whether the users have suspicion of electricity stealing by combining an electricity meter uncovering event and a wiring abnormal event in the process of monitoring the power consumption, determining historical normal metering data of the electricity meter through a dynamic time window in the process of identifying the suspicion of electricity stealing of the high-power consumption users, setting a first threshold requirement, comparing the real-time metering data of the electricity meter with the first threshold requirement, thereby identifying the suspicion of electricity stealing according to a comparison result, comparing the real-time metering data of the electricity meter with the predetermined second threshold requirement in the process of identifying the suspicion of electricity stealing of the low-power consumption users, thereby identifying the suspicion of electricity stealing according to the comparison result. Based on the scheme, the load scale and the required power utilization scale of users in the transformer area are fully considered, and the false judgment rate of electricity stealing is reduced.

The following is a detailed description of an embodiment of a method for monitoring power consumption of users in a low-voltage distribution area according to the present invention.

The invention provides a method for monitoring the power utilization condition of users in a low-voltage transformer area, which comprises the following steps:

s102, generating power failure event information through an electric energy meter connected to the transformer, wherein the power failure event information comprises power failure occurrence time and power failure duration;

it will be appreciated that by physically shutting down the transformers in both bays, the outage event information may be stored in the power meter.

In this embodiment, the station control point has a clock compensation mechanism, and performs automatic compensation by calculating the time difference between the clock out-of-tolerance meter and the power failure time, so as to avoid misjudgment caused by the clock out-of-tolerance of the meter and realize accurate station zone allocation.

And S103, sending a meter reading signal to the electric energy meters through the meter reading channel so as to read the power failure event information generated by the electric energy meters, and classifying the electric energy meters with the same power failure occurrence time and power failure duration time into the same distribution area by comparing the power failure occurrence time and the power failure duration time of all the electric energy meters.

In the embodiment, the abnormal power failure time data caused by undervoltage of the clock battery of the electric energy meter is filtered, so that the distribution area is more accurate.

S100, acquiring power consumption attributes of all users in a target distribution area based on a power marketing system, wherein the power consumption attributes comprise user numbers and historical daily average power consumption of the users;

s200, comparing the historical daily average power consumption of the users with a preset power consumption classification threshold, classifying the corresponding users into high-power-consumption users when the historical daily average power consumption of the users is larger than the preset power consumption classification threshold, classifying the corresponding users into low-power-consumption users when the historical daily average power consumption of the users is not larger than the preset power consumption classification threshold, and writing user numbers respectively corresponding to the high-power-consumption users and the low-power-consumption users into two pre-established user files respectively, wherein the pre-established user files comprise high-power-consumption user files and low-power-consumption user files;

S301, a time setting instruction is sent to the electric energy meter through the master station or the local handheld device, and after the electric energy meter receives the time setting instruction, the electric energy meter is broadcasted for time setting.

In this embodiment, the time synchronization error does not exceed 5s, the time synchronization error in 24 h of the system clock in the electric energy meter is less than 0.5 s, and the system clock can keep working normally after the power supply loses power.

S300, obtaining an electric energy meter uncapping event of a user in a target platform area, wherein the electric energy meter uncapping event comprises electric energy meter uncapping times and electric energy meter longest uncapping time, judging whether the electric energy meter uncapping times are larger than preset times or not, and whether the electric energy meter longest uncapping time is larger than the preset longest uncapping time or not, if the electric energy meter uncapping times are judged to be larger than the preset times or not, and the electric energy meter longest uncapping time is larger than the preset longest uncapping time, generating a timestamp based on a time service system and obtaining corresponding wiring abnormal events of the user, wherein the wiring abnormal events comprise a voltage reverse phase sequence, a current reverse phase sequence and a current reverse state;

it should be noted that the electrical energy meter uncapping event is an abnormal operation event of the electrical energy meter, and the electrical energy meter uncapping frequency and the electrical energy meter longest uncapping time are two important features that represent the abnormal operation, in this embodiment, the preset frequency is set to 1, the preset longest uncapping time is set to 20 minutes, if the electrical energy meter uncapping frequency is greater than 1 and the longest uncapping time is greater than 20 minutes, it is indicated that the abnormal operation event of the electrical energy meter occurs, and a timestamp is generated for the abnormal operation event of the time according to the system clock at that time based on the time synchronization system, so as to record the occurrence time of the abnormal operation event. Meanwhile, whether a wiring abnormal event occurs is judged.

S400, judging whether a wiring abnormal event occurs or not, and if the wiring abnormal event occurs, determining that the corresponding user has suspicion of electricity stealing; if the abnormal wiring event is judged not to occur, executing the step S500;

in this embodiment, after it is determined that there is an abnormal operation event of the electric energy meter, if a wiring abnormal event occurs, it is proved that the corresponding electric energy meter is suspected of being stolen by malicious wiring, and in the process of determining the wiring abnormal event, a distinction determination is made according to the type of the electric energy meter, where the type of the electric energy meter includes a single-phase electric energy meter and a three-phase electric energy meter. When the wiring of the three-phase electric energy meter is judged to be abnormal, the real wiring sequence of the current wiring of the three-phase electric energy meter needs to be obtained in advance for comparison.

S500, acquiring the user number of the user without the wiring abnormal event in the step S400, and performing matching search in a pre-established user file according to the user number so as to judge that the user is a high-power-consumption user or a low-power-consumption user; if the user is determined to be a high-power-consumption user, executing step S600, and if the user is determined to be a low-power-consumption user, executing step S800;

s600, acquiring historical normal metering data of an electric energy meter of a user and real-time metering data of a first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, and a time window of the real-time metering data of the first electric energy meter is the current timestamp;

specifically, step S600 specifically includes:

s611, acquiring historical normal metering data of an electric energy meter of a user and real-time metering data of a first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, the preset time period is a unit of month, week or year, the historical normal metering data of the electric energy meter comprises historical zero line current time sequence data, historical live line current time sequence data, voltage loss year average times, current loss year average times and phase loss year average times, the historical zero line current time sequence data and the historical live line current time sequence data have the same time window, and the time window of the real-time metering data of the first electric energy meter is the current timestamp and comprises real-time zero line current, real-time live line current, field voltage loss records, field phase loss records and field current loss records;

the electric energy meter has the advantages that the historical normal metering data of the electric energy meter is historical data, the real-time metering data of the first electric energy meter is real-time data, the electric energy meter has the data management and storage functions, the electric energy meter can record the electric energy meter electricity utilization metering data, meanwhile, a data clearing command can be periodically updated or executed, and dynamic data updating is carried out by storing the current timestamp and the electric energy meter electricity utilization metering data of the adjacent preset time period before the current timestamp in the process of periodically updating or executing the data clearing command.

S612, calculating to obtain historical time sequence current ratio data based on the historical time sequence data of the zero line current and the historical time sequence data of the live line current, and performing curve fitting on the historical time sequence current ratio data to obtain a current ratio time sequence curve, wherein the historical time sequence current ratio data is the current ratio of corresponding time sequence points in the historical time sequence data of the live line current and the historical time sequence data of the zero line current;

It should be noted that, since the time windows of the zero line current historical time sequence data and the live line current historical time sequence data are the same, the comparison between the two can obtain the current ratio of the corresponding time sequence points in the live line current historical time sequence data and the zero line current historical time sequence data under the time window, which is used as historical time sequence current ratio data, and the curve fitting is performed on the historical time sequence current ratio data, so as to draw a current ratio time sequence curve, so as to represent the current ratio of the corresponding time sequence points in the live line current historical time sequence data and the zero line current historical time sequence data, meanwhile, the abscissa of the current ratio time sequence curve represents time, and the ordinate represents the historical time sequence current ratio, so as to represent the variation trend of the historical time sequence current ratio data, discretize the value on the current ratio time sequence curve, and set a discrete threshold range according to the normal historical data (data caused by non-electricity-stealing behavior), values which are not within the range of the discrete threshold are eliminated, so that abnormal mutation values are eliminated, a current ratio time sequence curve after elimination is obtained, influence on subsequent comparison results due to mutation data caused by abnormal behaviors (including electricity stealing behaviors) is avoided, and the subsequent comparison results are more accurate when the subsequent comparison results are taken as reference curves.

S700, setting a first threshold requirement according to historical normal metering data of the electric energy meter, comparing the real-time metering data of the first electric energy meter with the first threshold requirement, and determining that the user is suspected of electricity stealing when the real-time metering data of the first electric energy meter is judged not to meet the first threshold requirement;

Specifically, step S700 specifically includes:

s711, setting the rejected current ratio time sequence curve, the voltage loss average number of times, the current loss average number of times, the phase loss average number of times and the historical electricity utilization average number of times as first threshold requirements;

it should be noted that, in order to avoid the comparative influence of the sudden change caused by the non-electricity-stealing behavior on the real-time metering data, the ratio of the current of the zero line to the current of the live line, the voltage loss frequency, the current loss frequency, the phase failure frequency and the electricity consumption are subjected to curve trending or averaging, so as to reduce the influence of the sudden change caused by the non-electricity-stealing behavior.

S712, when the electric energy meter is a single-phase electric energy meter, calculating a real-time current ratio according to real-time current of a zero line and real-time current of a live line, comparing the real-time current ratio with the current ratio time sequence curve after elimination, judging whether the real-time current ratio falls on the current ratio time sequence curve after elimination, and if the real-time current ratio does not fall on the current ratio time sequence curve after elimination, determining that the electricity stealing suspicion exists for the user;

it should be noted that the type of the electric energy meter may be obtained before step S712, if the electric energy meter is a single-phase electric energy meter, the power utilization condition is determined only according to the ratio of the current of the zero line to the current of the live line, because the values corresponding to the respective timing points on the current ratio timing curve after the rejection are all historical occurrences and do not show the behavior of electricity stealing, and meanwhile, because the current ratio timing curve after the rejection rejects abnormal data through the discrete threshold range, if the real-time current ratio falls on the current ratio timing curve after the rejection, it is indicated that the user does not have the suspicion electricity stealing, and otherwise, it is indicated that the user has the suspicion on electricity stealing.

When the electric energy meter is a three-phase electric energy meter, judging whether the voltage loss times recorded by the field voltage loss are greater than the voltage loss annual average times or not, and if the voltage loss times recorded by the field voltage loss are greater than the voltage loss annual average times, determining that the electricity stealing suspicion exists in the user; judging whether the phase failure times recorded in the field phase failure are more than the phase failure year average times or not, and if the phase failure times recorded in the field phase failure are more than the phase failure year average times, determining that the user has suspicion of electricity stealing; and judging whether the current loss times of the field current loss records are greater than the annual average current loss times or not, and if so, determining that the electricity stealing suspicion exists for the user.

S800, obtaining real-time metering data of a second electric energy meter of the user, judging whether the real-time metering data of the second electric energy meter meets a preset second threshold value requirement or not, and determining that the user has suspicion of electricity stealing when judging that the real-time metering data of the second electric energy meter does not meet the preset second threshold value requirement

Specifically, step S800 specifically includes:

s802, when the electric energy meter is judged to be a single-phase electric meter, judging whether the ratio of the live wire current to the zero wire current is larger than a preset ratio threshold value, and if the ratio of the live wire current to the zero wire current is larger than the preset ratio threshold value, determining that the electricity stealing suspicion exists in the user;

it should be noted that the type of the electric energy meter may be obtained before step S802, if the electric energy meter is a single-phase electric energy meter, whether suspicion of electricity stealing exists may be determined according to a ratio of the line current to the zero line current, and the preset ratio threshold may be a fixed value and does not need to be dynamically changed.

And when the electric energy meter is judged to be a three-phase electric meter, judging whether the electric energy meter is in a voltage loss state, a phase loss state or a current loss state, and if the electric energy meter is judged to be in the voltage loss state, the phase loss state or the current loss state, determining that the electricity stealing suspicion exists for the user.

It should be noted that, because the probability of sudden change of the electric energy meter metering data of the user with low power consumption is small, or the probability of sudden change caused by non-electricity-stealing behavior is small, the second threshold requirement may be set to 0, that is, if a voltage loss state, a phase loss state, or a current loss state occurs, it may be determined that the user is suspected of electricity stealing.

S9, when the suspicion of electricity stealing of the user is determined, acquiring a user address of the corresponding user, and loading the user address into a power grid GIS map for marking;

it should be noted that the user address can be found in the platform account of the platform area user, and the user address is loaded into the power grid GIS map for marking, so that the operation and maintenance personnel can quickly find the address and maintain the address.

And S10, inputting the historical normal metering data of the electric energy meter, the real-time metering data of the first electric energy meter and the real-time metering data of the second electric energy meter into a browser webpage, and displaying in a chart form.

It should be noted that, the historical normal metering data of the electric energy meter, the real-time metering data of the first electric energy meter and the real-time metering data of the second electric energy meter are displayed in a chart form, so that the data occupation ratio can be visually embodied.

In another embodiment, historical normal metering data of the electric energy meter, real-time metering data of the first electric energy meter and real-time metering data of the second electric energy meter can be input to the APP end of the mobile phone.

The above is a detailed description of an embodiment of a method for monitoring power consumption of a low-voltage transformer area user according to the present invention, and the following is a detailed description of an embodiment of a system for monitoring power consumption of a low-voltage transformer area user according to the present invention.

For easy understanding, referring to fig. 2, the present invention provides a system for monitoring power consumption of users in a low-voltage distribution area, including: the system comprises an electricity utilization attribute acquisition module 100, a file classification module 200, a cover opening event judgment module 300, a wiring abnormity judgment module 400, a file query module 500, an electric energy meter data acquisition module 600, a first electric energy meter data comparison module 700 and a second electric energy meter data comparison module 800;

the power consumption attribute acquisition module 100 is used for acquiring power consumption attributes of all users in the target distribution area based on the power marketing system, wherein the power consumption attributes comprise user numbers and historical daily average power consumption of the users;

the profile classification module 200 is used for comparing the historical daily average power consumption of the user with a preset power consumption classification threshold, classifying the corresponding user as a high-power-consumption user when the historical daily average power consumption of the user is greater than the preset power consumption classification threshold, classifying the corresponding user as a low-power-consumption user when the historical daily average power consumption of the user is not greater than the preset power consumption classification threshold, and respectively writing user numbers respectively corresponding to the high-power-consumption user and the low-power-consumption user into two pre-established user profiles, wherein the pre-established user profiles comprise the high-power-consumption user profile and the low-power-consumption user profile;

the system comprises a cover opening event judging module 300, a time stamp generation module and a wiring abnormal event acquisition module, wherein the cover opening event acquisition module is used for acquiring an electric energy meter cover opening event of a user in a target platform area, the electric energy meter cover opening event comprises electric energy meter cover opening times and electric energy meter longest cover opening time, judging whether the electric energy meter cover opening times are greater than preset times or not and whether the electric energy meter longest cover opening time is greater than the preset longest cover opening time or not, and if the electric energy meter cover opening times are greater than the preset times and the electric energy meter longest cover opening time is greater than the preset longest cover opening time, generating a time stamp based on a time service system and acquiring the corresponding wiring abnormal event of the user, and the wiring abnormal event comprises a voltage reverse phase sequence, a current reverse phase sequence and a current reverse state;

the abnormal wiring judgment module 400 is configured to judge whether an abnormal wiring event occurs, and if the abnormal wiring event occurs, determine that a corresponding user is suspected of electricity stealing; the system is further configured to send a working signal to the archive inquiry module 500 if it is determined that the abnormal wiring event does not occur;

the profile query module 500 is configured to obtain a user number of a user who has not generated a wiring abnormal event, and perform matching search on a pre-established user profile according to the user number, so as to determine that the user is a high-power consumption user or a low-power consumption user;

the electric energy meter data acquisition module 600 is configured to acquire historical normal metering data of an electric energy meter of a user and real-time metering data of a first electric energy meter, where a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, and a time window of the real-time metering data of the first electric energy meter is the current timestamp;

the first electric energy meter data comparison module 700 is used for setting a first threshold requirement according to historical normal metering data of the electric energy meter, comparing real-time metering data of the first electric energy meter with the first threshold requirement, and determining that the user has suspicion of electricity stealing when the real-time metering data of the first electric energy meter is judged not to meet the first threshold requirement;

the second electric energy meter data comparison module 800 is configured to obtain second electric energy meter real-time metering data of the electric energy meter of the user, determine whether the second electric energy meter real-time metering data meets a preset second threshold requirement, and determine that the user is suspected of electricity stealing when it is determined that the second electric energy meter real-time metering data does not meet the preset second threshold requirement.

It should be noted that the working process of the power consumption monitoring system for the low-voltage distribution room users is consistent with the flow of the power consumption monitoring method for the low-voltage distribution room users, and is not described herein again.

The invention provides a power consumption condition monitoring system for low-voltage station users, which can be used for carrying out power consumption monitoring aiming at different power consumption users by dividing all users in a station area into high-power consumption users and low-power consumption users according to the historical daily average power consumption of the users, and in the power consumption monitoring process, after determining whether the users have suspicion of electricity stealing by combining an electricity meter uncovering event and a wiring abnormal event, the suspicion of electricity stealing is further identified for the high-power consumption users and the low-power consumption users respectively, in the process of identifying the suspicion of electricity stealing of the high-power consumption users, the historical normal metering data of the electricity meter is determined through a dynamic time window, so as to set a first threshold value requirement, and the real-time metering data of the electricity meter is compared with the first threshold value requirement, so as to identify the suspicion of electricity stealing according to a comparison result, in the process of identifying the suspicion of electricity stealing of the low-power consumption users, the real-time metering data of the electricity meter is compared with the predetermined second threshold value requirement, thereby identifying the suspicion of electricity stealing according to the comparison result. Based on the scheme, the load scale and the required power utilization scale of users in the transformer area are fully considered, and the false judgment rate of electricity stealing is reduced.

Furthermore, the system also comprises a platform area control module, an information generation module and a user change attribution module;

the transformer area control module is used for sending power failure instructions to all transformers in two adjacent transformer areas, and the power failure instructions comprise power failure occurrence time and power failure duration time so that the transformers execute power failure actions;

the information generation module is used for generating power failure event information through an electric energy meter connected to the transformer, and the power failure event information comprises power failure occurrence time and power failure duration;

the household attribution module is used for issuing a meter reading signal to the electric energy meters through the meter reading channel so as to read the power failure event information generated by the electric energy meters, and is also used for carrying out difference comparison on the power failure occurrence time and the power failure duration time of all the electric energy meters so as to classify the electric energy meters with the same power failure occurrence time and power failure duration time into the same transformer area.

Furthermore, the system also comprises a time synchronization module, wherein the time synchronization module is used for sending a time synchronization instruction to the electric energy meter through the master station or the local handheld device, and is also used for broadcasting time synchronization to the electric energy meter after the electric energy meter receives the time synchronization instruction.

Further, the electric energy meter data acquisition module comprises a first electric energy meter data acquisition sub-module, a curve fitting sub-module and a discrete sub-module;

the first electric energy meter data acquisition submodule is used for acquiring historical normal metering data of an electric energy meter of a user and real-time metering data of the first electric energy meter, a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, the preset time period is a unit of month, week or year, the historical normal metering data of the electric energy meter comprises historical zero line current time sequence data, historical live line current time sequence data, voltage loss year average times, current loss year average times and phase failure year average times, the time windows of the historical zero line current time sequence data and the historical live line current time sequence data are the same, the time window of the real-time metering data of the first electric energy meter is the current timestamp and comprises real-time zero line current, real-time live line current, field voltage loss records, field phase failure records and field current loss records;

the curve fitting submodule is used for calculating to obtain historical time sequence current ratio data based on the historical time sequence data of the zero line current and the historical time sequence data of the live line current, and is also used for performing curve fitting on the historical time sequence current ratio data to obtain a current ratio time sequence curve, and the historical time sequence current ratio data is the current ratio of corresponding time sequence points in the historical time sequence data of the live line current and the historical time sequence data of the zero line current;

the discrete sub-module is used for discretizing the current ratio time sequence curve to obtain a plurality of discrete values, comparing the discrete values with a preset discrete threshold range, and removing the discrete values which are not in the preset discrete threshold range.

Further, the first electric energy meter data comparison module comprises a threshold setting submodule and a first data comparison submodule;

the threshold setting submodule is used for setting a ratio time sequence curve of zero line current and live wire current, voltage loss average times, current loss average times, phase failure average times and historical electricity consumption average time as a first threshold requirement;

the data comparison sub-module is used for calculating a real-time current ratio according to real-time current of a zero line and real-time current of a live line when the electric energy meter is a single-phase electric meter, comparing the real-time current ratio with a current ratio time sequence curve, judging whether the real-time current ratio falls on the current ratio time sequence curve or not, and determining that a user has suspicion of electricity stealing if the real-time current ratio is judged not to fall on the current ratio time sequence curve;

the system is also used for judging whether the voltage loss times recorded by the field voltage loss are greater than the annual average voltage loss times or not when the electric energy meter is a three-phase electric energy meter, and determining that the electricity stealing suspicion exists in the user if the voltage loss times recorded by the field voltage loss is greater than the annual average voltage loss times; the system is also used for judging whether the phase failure times of the field phase failure record are greater than the phase failure year average times or not, and determining that the user has suspicion of electricity stealing if the phase failure times of the field phase failure record are greater than the phase failure year average times; the method is also used for judging whether the current loss times of the field current loss records are greater than the annual average current loss times or not, and determining that the user has suspicion of electricity stealing if the current loss times of the field current loss records are greater than the annual average current loss times.

Further, the second electric energy meter data comparison module comprises a second electric energy meter data acquisition submodule and a second data comparison submodule;

the second electric energy meter data acquisition submodule is used for acquiring second electric energy meter real-time metering data of an electric energy meter of a user, and the second electric energy meter real-time metering data comprises zero line current, live line current, a voltage loss state, a phase failure state and a current loss state;

the second data comparison submodule is used for judging whether the ratio of the live wire current to the zero wire current is greater than a preset ratio threshold value or not when the electric energy meter is judged to be a single-phase electric meter, and is also used for determining that the electricity stealing suspicion exists in the user when the ratio of the live wire current to the zero wire current is judged to be greater than the preset ratio threshold value;

the method and the device are further used for judging whether the electric energy meter is in a voltage loss state, a phase loss state or a current loss state when the electric energy meter is judged to be a three-phase electric meter, and determining that the user is suspected of electricity stealing if the electric energy meter is judged to be in the voltage loss state, the phase loss state or the current loss state.

Furthermore, the system also comprises a loading module and a display module;

the loading module is used for acquiring a user address of a corresponding user and loading the user address into a power grid GIS map for marking after the suspicion of electricity stealing of the user is determined;

the display module is used for inputting the historical normal metering data of the electric energy meter, the real-time metering data of the first electric energy meter and the real-time metering data of the second electric energy meter into a browser webpage and displaying the data in a chart form.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims

1. A power utilization condition monitoring method for users in a low-voltage distribution area is characterized by comprising the following steps:

step S6 specifically includes:

s613, discretizing the current ratio time sequence curve to obtain a plurality of discrete values, comparing the discrete values with a preset discrete threshold range, and eliminating discrete values which are not in the preset discrete threshold range to obtain an eliminated current ratio time sequence curve;

step S7 specifically includes:

when the electric energy meter is a three-phase electric energy meter, judging whether the voltage loss times recorded by the field voltage loss are greater than the annual average voltage loss times or not, and if the voltage loss times recorded by the field voltage loss are greater than the annual average voltage loss times, determining that the user is suspected of electricity stealing; judging whether the phase failure times of the field phase failure record are greater than the phase failure annual average times or not, and if the phase failure times of the field phase failure record are greater than the phase failure annual average times, determining that the user has suspicion of electricity stealing; judging whether the current loss times of the field current loss records are greater than the annual average current loss times or not, and if the current loss times of the field current loss records are greater than the annual average current loss times, determining that the user has suspicion of electricity stealing;

s8, obtaining second electric energy meter real-time metering data of an electric energy meter of a user, judging whether the second electric energy meter real-time metering data meets a preset second threshold value requirement, and determining that the user has suspicion of electricity stealing when the second electric energy meter real-time metering data does not meet the preset second threshold value requirement;

step S8 specifically includes:

2. The method for monitoring the power utilization of the users in the low-voltage transformer area according to claim 1, wherein step S1 is preceded by the steps of:

3. The method for monitoring the power utilization of the users in the low-voltage transformer area according to claim 1, wherein step S3 is preceded by the steps of:

4. The method for monitoring the power utilization of the users in the low-voltage transformer area according to claim 1, wherein step S8 is followed by the steps of:

5. A system for monitoring power usage by a low voltage distribution area user, comprising: the system comprises a power utilization attribute acquisition module, a file classification module, a cover opening event judgment module, a wiring abnormity judgment module, a file query module, an electric energy meter data acquisition module, a first electric energy meter data comparison module and a second electric energy meter data comparison module;

the electric energy meter data acquisition module is specifically used for:

acquiring historical normal metering data of an electric energy meter of a user and real-time metering data of a first electric energy meter, wherein a time window of the historical normal metering data of the electric energy meter is a preset time period adjacent to a current timestamp, the preset time period is a unit of month, week or year, the historical normal metering data of the electric energy meter comprises historical zero line current time sequence data, historical live line current time sequence data, voltage loss year average times, current loss year average times and phase loss year average times, the historical zero line current time sequence data and the historical live line current time sequence data have the same time window, and the time window of the real-time metering data of the first electric energy meter is the current timestamp and comprises real-time zero line current, real-time live line current, field voltage loss records, field phase loss records and field current loss records;

the zero line current historical time sequence data and the live line current historical time sequence data are used for calculating to obtain historical time sequence current ratio data, curve fitting is carried out on the historical time sequence current ratio data to obtain a current ratio time sequence curve, and the historical time sequence current ratio data are the current ratio of corresponding time sequence points in the live line current historical time sequence data and the zero line current historical time sequence data;

the current ratio time sequence curve is discretized to obtain a plurality of discrete values, the discrete values are compared with a preset discrete threshold range, and the discrete values which are not in the preset discrete threshold range are removed to obtain the removed current ratio time sequence curve;

the first electric energy meter data comparison module is specifically configured to:

setting the rejected current ratio time sequence curve, the voltage loss annual average frequency, the current loss annual average frequency, the phase loss annual average frequency and the historical electricity utilization annual average quantity as the first threshold requirement;

the electric energy meter is also used for calculating a real-time current ratio according to the real-time current of the zero line and the real-time current of the live line when the electric energy meter is a single-phase electric meter, comparing the real-time current ratio with the eliminated current ratio time sequence curve, judging whether the real-time current ratio falls on the eliminated current ratio time sequence curve, and if the real-time current ratio does not fall on the eliminated current ratio time sequence curve, determining that the user has suspicion of electricity stealing;

the system is also used for judging whether the voltage loss times of the field voltage loss records are greater than the annual average voltage loss times or not when the electric energy meter is a three-phase electric energy meter, and determining that the user is suspected of electricity stealing if the voltage loss times of the field voltage loss records are greater than the annual average voltage loss times; judging whether the phase failure times of the field phase failure record are greater than the phase failure annual average times or not, and if the phase failure times of the field phase failure record are greater than the phase failure annual average times, determining that the user has suspicion of electricity stealing; judging whether the current loss times of the field current loss records are greater than the annual average current loss times or not, and if the current loss times of the field current loss records are greater than the annual average current loss times, determining that the user has suspicion of electricity stealing;

the second electric energy meter data comparison module is used for acquiring second electric energy meter real-time metering data of an electric energy meter of a user, judging whether the second electric energy meter real-time metering data meets a preset second threshold requirement or not, and determining that the user has suspicion of electricity stealing when the second electric energy meter real-time metering data is judged not to meet the preset second threshold requirement;

the second electric energy meter data comparison module is specifically configured to:

acquiring second electric energy meter real-time metering data of an electric energy meter of a user, wherein the second electric energy meter real-time metering data comprises zero line current, live line current, a voltage loss state, a phase failure state and a current loss state;

the electric energy meter is also used for judging whether the ratio of the live wire current to the zero wire current is greater than a preset ratio threshold value or not when the electric energy meter is judged to be a single-phase electric meter, and determining that the user has suspicion of electricity stealing if the ratio of the live wire current to the zero wire current is judged to be greater than the preset ratio threshold value;

and the method is also used for judging whether the electric energy meter is in a voltage loss state, a phase loss state or a current loss state when the electric energy meter is judged to be a three-phase electric meter, and determining that the user is suspected of electricity stealing if the electric energy meter is judged to be in the voltage loss state, the phase loss state or the current loss state.

6. The system for monitoring the power utilization condition of the low-voltage transformer area users as claimed in claim 5, further comprising a transformer area control module, an information generation module and a user change attribution module;

7. The system for monitoring the power consumption of the users in the low-voltage transformer area according to claim 5, further comprising a time synchronization module, wherein the time synchronization module is configured to send a time synchronization instruction to the electric energy meter through a master station or a local handheld device, and further configured to broadcast the time synchronization to the electric energy meter after the electric energy meter receives the time synchronization instruction.