CN117763419A - On-site electric energy meter monitoring method - Google Patents

Abstract

The application relates to a field electric energy meter monitoring method, which is realized based on system side equipment and field side equipment, and comprises the following steps: the system side equipment acquires the acquired electric energy meter data, analyzes the electric energy meter data, and classifies the state of each electric energy meter according to an analysis result; the classification of the electric energy meter comprises normal, abnormal acquisition, abnormal electric energy meter and suspected electricity larceny; the system side equipment generates a corresponding work order according to the electric energy meter with abnormal collection, abnormal electric energy meter and suspected electricity larceny, and dispatches the work order to operation and maintenance personnel; the operation and maintenance personnel installs field side equipment on the electric energy meter field for collecting abnormal electric energy meter, abnormal electric energy meter and suspected electricity larceny according to the work order, and the field side equipment is installed in a meter box of the electric energy meter; the field side equipment responds to the scheduling control of the system side equipment, communicates with the electric energy meter, monitors the electric energy meter, and sends a monitoring result to the system side equipment, so that the problem of the electric energy meter can be found in time.

Description

On-site electric energy meter monitoring method

Technical Field

The application relates to the technical field of power protection, in particular to a field electric energy meter monitoring method.

Background

The electric energy meter can be used for monitoring the running condition of the power system, so that an operator of the power system is helped to better grasp the running condition of the power system. Through the electric energy meter, the electric power company can monitor the use condition of electric energy and the running condition of each device in the electric power system in real time. These data can help the utility to better identify potential problems and take timely action to address them.

The utility company establishes an electricity consumption information acquisition system and a metering automation system to remotely read and control the data of the electric energy meter, and based on the reason of a transmission network, resident users generally read the data (generally zero point) at one time point in one day, and can not read the data in an environment with large partial carrier interference. In addition, for users who find data abnormal and suspected electricity larceny on the system, the electric power company can arrange personnel to go to the site for checking, but many current electricity larceny methods are more concealed, and particularly for the intermittent electricity larceny method, the possibility of going to the site for checking is lower.

Disclosure of Invention

The purpose of the application is to provide a field electric energy meter monitoring method, which can find out the problem of the electric energy meter in time in a mode of combining a system side with field side equipment.

To achieve the above object, an embodiment of the present application provides a method for monitoring a field electric energy meter, the method being implemented based on a system-side device and a field-side device, the method including:

the system side equipment acquires the acquired electric energy meter data, analyzes the electric energy meter data and classifies the state of each electric energy meter according to an analysis result; the classification of the electric energy meter comprises normal, abnormal acquisition, abnormal electric energy meter and suspected electricity larceny;

the system side equipment generates a corresponding work order according to the electric energy meter with abnormal collection, abnormal electric energy meter and suspected electricity larceny, and dispatches the work order to operation and maintenance personnel;

the operation and maintenance personnel installs the field side equipment on the electric energy meter field for collecting abnormal electric energy meter, abnormal electric energy meter and suspected electricity larceny according to the work order, and the field side equipment is installed in a meter box of the electric energy meter;

the field side device receives the scheduling instruction of the system side device, communicates with the electric energy meter, monitors the electric energy meter and sends a monitoring result to the system side device.

Further, the system side device acquires the acquired electric energy meter data, analyzes the electric energy meter data, classifies the state of each electric energy meter according to the analysis result, and specifically includes:

traversing all the collected data of the electric energy meters under the transformer area by taking the transformer area as a unit to calculate the daily electric quantity of the electric energy meters;

and marking the electric energy meter with the data of the non-current day as acquisition abnormality according to the traversal calculation result.

Further, the system side device acquires the acquired electric energy meter data, analyzes the electric energy meter data, classifies the state of each electric energy meter according to the analysis result, and specifically includes:

removing and collecting abnormal electric energy meters from the electric energy meter data to obtain removed electric energy meter data;

analyzing the voltage and the current of the electric energy meter according to the removed electric energy meter data, checking whether the electric energy meter is under-voltage or out-of-phase, and if so, temporarily marking the electric energy meter as abnormal;

according to the removed electric energy meter data, analyzing the daily electricity quantity data of the electric energy meter in the last 30 days, setting the data of one electric energy meter in the last 30 days as X1-X30, carrying out difference calculation on the data of each day and the data of the previous day to obtain difference values Y1-Y29, carrying out mean value calculation on the difference values Y1-Y29 to obtain a mean value S, respectively carrying out percentage deviation on the mean value S and the difference values Y1-Y29, and temporarily marking the electric energy meter as the electric energy meter is abnormal if a certain percentage deviation is larger than 80%;

introducing a station area line loss value, performing correlation coefficient calculation on the station area line loss value and daily electricity quantity data of the electric energy meter based on a Pearson correlation coefficient algorithm, extracting the electric energy meter with the correlation coefficient between 0.7 and 1, and temporarily marking the electric energy meter as abnormal;

analyzing the uncapping event and the magnetic field event of all the electric energy meters temporarily marked as the electric energy meter abnormality, determining whether the electric energy meters suspected to steal electricity exist in all the electric energy meters according to the analysis result, if yes, modifying the mark as suspected to steal electricity, and if not, reserving the mark of the electric energy meter abnormality;

and marking the rest electric energy meters which are not marked as abnormal, abnormal in acquisition and suspected electricity larceny as normal.

Further, the field side device includes:

a remote port, including a 4G and/or network port communication interface, for communicating with the system side device;

the local port comprises an RS485 local interface, a carrier wave local interface and/or a Bluetooth local interface and is used for communicating with the electric energy meter;

the camera is used for sensing the action of opening the meter box, shooting the picture of an operator of opening the meter box and uploading the picture to the system side equipment;

the Beidou positioning module is used for acquiring the position information of the meter box and synchronously storing the position information with the system side equipment;

the magnetic field detection module is used for detecting the magnetic field intensity in the current environment;

the data storage module is used for caching the acquired data of the electric energy meter in the meter box and uploading the acquired data to the system side equipment;

the display unit is used for displaying and performing touch operation;

further, the field side device includes:

the safety unit is used for encrypting and decrypting the communication data, and the field side equipment, the system side equipment and the electric energy meter are required to meet the safety requirement in communication;

the system side equipment is used for acquiring the electric energy meter file information in the meter box, and the electric energy meter file information is used for networking and communication;

and the control driving module is used for driving and controlling the local communication.

Further, the field side device includes:

3 paths of field voltage and current monitoring are used for monitoring voltage and current values at the inlet wire end of the electric energy meter and comparing the voltage and current values with the actual read electric energy meter to confirm whether the electric energy meter is abnormal or has electricity stealing behavior;

further, the field side device includes:

the reading strategy module is used for responding to the scheduling control of the system side equipment, identifying the current missing data of the electric energy meter and controlling reading content, reading time point and reading priority;

the abnormal strategy module is used for responding to the scheduling control of the system side equipment, automatically entering a site abnormality handling link for the electric energy meter with failed site reading, and checking whether the electric energy meter is abnormal, the communication address and the system are not corresponding to abnormality or the protocol is not corresponding to abnormality;

further, the field side device includes:

the multi-protocol support module comprises support 645, 698.45 and 376.2 communication protocols, and is used for responding to the scheduling control of the system side equipment, identifying the type of the electric energy meter and the communication protocols, automatically selecting the corresponding communication protocols for reading, and entering an abnormal strategy if the reading is unsuccessful.

Embodiments of the present application have the following beneficial effects:

(1) And (3) automatic treatment: the system side equipment can analyze the collected electric energy meter data, and automatically classify the states of the electric energy meter according to analysis results, so that the workload of manual processing is reduced.

(2) Fault diagnosis: the system side equipment can generate corresponding work orders for the electric energy meters with abnormal collection, abnormal electric energy meters and suspected electricity larceny, and the work orders are given to operation and maintenance personnel, so that quick diagnosis and treatment of faults are realized.

(3) Efficiency is improved: through automated processing and rapid diagnosis, the working efficiency of operation and maintenance personnel can be improved, and the time of fault processing is reduced.

(4) Preventing electricity theft: by monitoring the state of the electric energy meter, the suspected electricity larceny condition can be found in time, and corresponding measures are taken to prevent the occurrence of electricity larceny events.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a method for monitoring an on-site electric energy meter according to an embodiment of the present application.

Fig. 2 is a schematic diagram of a system-side device and a field-side device in an embodiment of the present application.

Fig. 3 is a schematic diagram of a temporary data collection flow in an embodiment of the present application.

Fig. 4 is a flowchart illustrating a long-term data acquisition procedure in an embodiment of the present application.

Fig. 5 is an exemplary diagram of a monitoring flow of an on-site electric energy meter according to an embodiment of the present application.

Detailed Description

The detailed description of the drawings is intended as a description of the present embodiments of the application and is not intended to represent the only forms in which the present application may be practiced. It is to be understood that the same or equivalent functions may be accomplished by different embodiments that are intended to be encompassed within the scope of the application.

Referring to fig. 1, an embodiment of the present application provides a method for monitoring an on-site electric energy meter, where the method is implemented based on the system-side device and the on-site device shown in fig. 2, and the method includes the following steps:

step S1, acquiring acquired electric energy meter data by the system side equipment, analyzing the electric energy meter data, and classifying the state of each electric energy meter according to an analysis result; the classification of the electric energy meter comprises normal, abnormal acquisition, abnormal electric energy meter and suspected electricity larceny;

step S2, the system side equipment generates a corresponding work order according to the electric energy meter with abnormal collection, abnormal electric energy meter and suspected electricity larceny, and dispatches the work order to operation and maintenance personnel;

step S3, the operation and maintenance personnel installs the field side equipment on the electric energy meter field for collecting the abnormality, the electric energy meter abnormality and suspected electricity larceny according to the work order, and the field side equipment is installed in a meter box of the electric energy meter;

and S4, the field side equipment receives the scheduling instruction of the system side equipment, communicates with the electric energy meter, monitors the electric energy meter and sends a monitoring result to the system side equipment.

Further, the step S1 specifically includes:

step S11, traversing all the collected data of the electric energy meters in the transformer area by taking the transformer area as a unit to calculate the daily electric quantity of the electric energy meters;

and step S12, marking the electric energy meter without the day data as abnormal acquisition according to the traversal calculation result.

Further, the system side device acquires the acquired electric energy meter data, analyzes the electric energy meter data, classifies the state of each electric energy meter according to the analysis result, and specifically includes:

step S13, eliminating and collecting abnormal electric energy meters from the electric energy meter data to obtain electric energy meter data after elimination;

step S14, analyzing the voltage and the current of the electric energy meter according to the removed electric energy meter data, checking whether the electric energy meter has under-voltage or phase failure, and if so, temporarily marking the electric energy meter as abnormal;

specifically, under-voltage refers to that the voltage value measured by the electric energy meter is lower than the normal range, and may indicate that a circuit connected with the electric energy meter has a power supply problem; the phase failure refers to that the current of a certain phase in the current value measured by the electric energy meter is 0, which may indicate that a problem exists in a certain phase line in a circuit connected with the electric energy meter; temporary marking means that this meter is temporarily marked as abnormal, requiring further confirmation and handling;

step S15, according to the removed electric energy meter data, analyzing the daily electric energy data of the electric energy meter for 30 days recently, setting the data of one electric energy meter for 30 days recently as X1-X30 (X1, X2, X3, … …, X30), carrying out difference calculation on the daily data and the data of the previous day to obtain difference values Y1-Y29 (Y1, Y2, Y3, … …, Y29), carrying out average calculation on the difference values Y1-Y29 to obtain an average value S, respectively carrying out percentage deviation on the average value S and the difference values Y1-Y29, and temporarily marking the electric energy meter as abnormal if a certain percentage deviation is larger than 80%;

specifically, first, daily electricity quantity data of a certain electric energy meter for the last 30 days is expressed as X1 to X30, wherein X1 represents the electricity quantity of the last day and X30 represents the electricity quantity of the day before 30 days; then, carrying out difference calculation on the electric quantity data of each day and the electric quantity data of the previous day to obtain difference values Y1-Y29, wherein Y1 represents the electric quantity difference value of the last day and the previous day, and Y29 represents the electric quantity difference value of the second day and the third day; then, carrying out average value calculation on the difference values Y1 to Y29 to obtain an average value S; then, respectively calculating the percentage deviation of the average value S and the difference values Y1-Y29, wherein the percentage deviation refers to the relative difference degree between the difference value and the average value; finally, if the percentage deviation of a certain difference value is larger than 80%, the electric energy meter is temporarily marked as abnormal; for example, assume that the average value S is 100, the difference Y1 is 120, and the difference Y2 is 90. Calculating the percentage deviation of Y1 and S to be (120-100)/100=20%, and calculating the percentage deviation of Y2 and S to be (90-100)/100= -10%; if the percentage deviation of a certain difference value is more than 80%, for example, more than 100%, then the electric energy meter is considered to have an abnormal condition; temporary marking means that this meter is temporarily marked as abnormal, requiring further confirmation and handling; the purpose of the step is to judge whether the electric energy meter has abnormal conditions or not by analyzing the change condition of the electric quantity difference value;

step S16, introducing a district line loss value, carrying out correlation coefficient calculation on the district line loss value and daily electricity quantity data of the electric energy meter based on a Pearson correlation coefficient algorithm, extracting the electric energy meter with the correlation coefficient between 0.7 and 1, and temporarily marking the electric energy meter as abnormal;

specifically, the pearson correlation coefficient is a statistic used to measure the degree of linear correlation between two variables, and the pearson correlation coefficient algorithm can be expressed as: xs=corr (X, Y), where Xs is a correlation coefficient, X is line loss data, Y is daily electricity data of a single metering point, xs is between-1 and-1, positive number of Xs indicates positive correlation, and the larger the value is, the higher the correlation is;

let us assume that we have the following cell line loss values and daily electricity data of the electric energy meter:

station area line loss value: 10,15,20,25,30 daily electrical data for electric energy meter 1: 100,150,200,250,300 daily electrical data for electric energy meter 2: 80,120,160,200,240 daily electrical data for electric energy meter 3:

[120,180,240,300,360]；

firstly, calculating a pearson correlation coefficient between a line loss value of a platform area and daily electric quantity data of each electric energy meter;

for electric energy meter 1: calculating a correlation coefficient between the line loss value of the station area and daily electricity quantity data of the electric energy meter 1: correlation coefficient= cov (district line loss value, daily electrical quantity data of electric energy meter 1)/(std (district line loss value) ×std (daily electrical quantity data of electric energy meter 1)), where cov denotes covariance and std denotes standard deviation;

the calculation process is as follows: cov (district line loss value, daily data of electric energy meter 1) = ((10-22.5) (100-210) + (15-22.5) (150-210) + (20-22.5) (200-210) + (25-22.5) (250-210) + (30-22.5))/5= -375std (district line loss value) = sqrt (((10-22.5)/(2+ (15-22.5)/(2+ (20-22.5)/(2+ (25-22.5)/(2+ (30-22.5)/(2)/5))= 7.9057std (daily data of electric energy meter 1) =)

sqrt(((100-210)^2+(150-210)^2+(200-210)^2+(250-210)^2+(300-210)^2)/5)＝47.4342；

Correlation coefficient = -375/(7.9057 x 47.4342) = -0.9999;

for electric energy meter 2 and electric energy meter 3, the same calculation process, the obtained correlation coefficients are respectively: correlation coefficient of electric energy meter 2=0.9999 correlation coefficient of electric energy meter 3=0.9999;

according to the calculation result, the correlation coefficients of the electric energy meter 1, the electric energy meter 2 and the electric energy meter 3 are all between 0.7 and 1, which means that a strong positive correlation exists between the electric energy meter 1, the electric energy meter 2 and the station area line loss value;

therefore, according to the pearson correlation coefficient algorithm, the electric energy meter 1, the electric energy meter 2 and the electric energy meter 3 can be temporarily marked as the electric energy meter abnormality, and further confirmation and processing are needed;

step S17, analyzing a cover opening event and a magnetic field event of all electric energy meters temporarily marked as abnormal electric energy meters, determining whether the electric energy meters suspected to be stolen exist in all the electric energy meters according to analysis results, if yes, modifying the mark as suspected power theft, and if not, reserving the mark of the abnormal electric energy meters;

specifically, firstly, analyzing the uncovering event of the electric energy meters, namely checking whether the electric energy meters are illegally opened; if the electric energy meter is found to be illegally opened, modifying the mark of the electric energy meter into suspected electricity larceny; then, analyzing magnetic field events of the electric energy meters, namely checking whether the electric energy meters are interfered by external magnetic fields; if the electric energy meter is found to be interfered by an external magnetic field, modifying the mark of the electric energy meter into suspected electricity larceny; if any suspected electricity theft is found during the analysis, the corresponding meter label is modified to be suspected electricity theft; if no suspected electricity larceny is found, the electric energy meters can keep the abnormal marks of the electric energy meters; the method comprises the steps of determining whether a suspected electricity larceny condition exists or not by analyzing an uncovering event and a magnetic field event of the electric energy meter; if a suspected theft is found, further investigation and processing is required. If no suspected theft is found, these meters are still considered abnormal;

and S18, marking the rest electric energy meters which are not marked as abnormal, are collected abnormally and are suspected to be stolen as normal.

Further, the field side device includes:

the remote port comprises interfaces such as 4G, network port communication and the like and is used for communicating with the system side equipment;

the local port comprises a local interface such as RS485, a carrier wave and Bluetooth and is used for communicating with the electric energy meter in the meter box;

the camera is used for sensing the action of opening the meter box, triggering shooting the picture of an operator of opening the meter box and uploading the picture to the system side equipment;

the Beidou positioning module is used for acquiring the position information of the meter box and synchronously storing the position information with the system side equipment;

the magnetic field detection module is used for detecting the magnetic field intensity in the current environment; specifically, the magnetic field can cause the transformer of the electric energy meter to be abnormal without metering or with less metering;

the data storage module is used for caching the acquired data of the electric energy meter in the meter box and uploading the acquired data to the system side equipment; specifically, after the data of the electric energy meter in the meter box is collected, the data is firstly stored locally and then uploaded to the system side equipment, and the historical data of one year can be stored for the equipment which is installed in the meter box for a long time;

the display unit is used for displaying and performing touch operation;

the safety unit is used for encrypting and decrypting the communication data, and the field side equipment, the system side equipment and the electric energy meter are required to meet the safety requirements of an electric company;

the system side equipment is used for acquiring the electric energy meter file information in the meter box, and the electric energy meter file information is used for networking and communication;

the control driving module is used for driving and controlling local communication and can drive the support RS485 and the carrier wave simultaneously;

3 paths of field voltage and current monitoring are used for monitoring voltage and current values at the inlet wire end of the electric energy meter and comparing the voltage and current values with the actual read electric energy meter to confirm whether the electric energy meter is abnormal or has electricity stealing behavior; specifically, the monitored voltage and current values are compared with the actual read voltage and current values, and if the monitored voltage and current values have larger differences from the actual read voltage and current values, the electric energy meter may mean that the electric energy meter is abnormal or has electricity stealing behavior;

the reading strategy module is used for responding to the scheduling control of the system side equipment, identifying the current missing data of the electric energy meter and controlling reading content, reading time point and reading priority; specifically, the reading policy module receives a scheduling control instruction of the system side device; according to the instructions, the data condition of the current electric energy meter is analyzed, and whether the electric energy meter with missing data exists or not is judged; for the electric energy meter with missing data, a reading strategy module can determine reading content, reading time point and reading priority according to a set reading strategy; the reading content can comprise information such as voltage, current, power and the like of the electric energy meter; the reading time point can be determined according to the requirement of the system, such as reading in a low-load period; the reading priority can be determined according to the importance of the electric energy meter or other factors so as to ensure that important electric energy meter data can be read in time; through the control of the reading strategy module, the electric energy meter with missing data can be read in a targeted manner, so that the integrity and the accuracy of the data are ensured; meanwhile, the reading strategy module can schedule reading according to the requirements and the priority of the system so as to improve the reading efficiency and the resource utilization rate;

the abnormal strategy module is used for responding to the scheduling control of the system side equipment, automatically entering a site abnormality handling link for the electric energy meter with failed site reading, and checking whether the electric energy meter is abnormal, the communication address and the system are not corresponding to abnormality or the protocol is not corresponding to abnormality; specifically, when the field reading fails, the abnormal policy module receives a scheduling control instruction of the system side device; according to the instructions, the electric energy meter which fails to read is subjected to abnormal processing; firstly, an abnormality policy module checks whether an electric energy meter is abnormal or not; this may include a hardware failure of the electric energy meter, a failure of the electric energy meter data acquisition module, etc.; by diagnosing and detecting the electric energy meter, whether the electric energy meter is abnormal or not can be determined; secondly, the abnormal strategy module checks whether the communication address corresponds to the system or not; if the communication address does not correspond to the system, the communication address may be caused by a change in the installation position of the device or a communication configuration error; the abnormal strategy module can try to reconfigure the communication address so as to ensure that the communication is normal; finally, the abnormal strategy module checks whether the protocol corresponds or not; if the protocols do not correspond, the protocol may be caused by equipment upgrade or system protocol change; the abnormal strategy module can try to update the protocol or perform protocol conversion so as to ensure that the communication is normal; the abnormal situation of the electric energy meter which fails to read on site can be automatically identified and solved through the processing of the abnormal strategy module; the stability and the reliability of the system are improved, and the accuracy and the integrity of the data of the electric energy meter are ensured;

the multi-protocol support module comprises support 645, 698.45 and 376.2 communication protocols, is used for responding to the scheduling control of the system side equipment, identifying the type of the electric energy meter and the communication protocols, automatically selecting the corresponding communication protocols for reading, and entering an abnormal strategy if the reading is unsuccessful; specifically, the multi-protocol support module supports multiple communication protocols, including 645, 698.45, 376.2, and the like; when the system side equipment sends scheduling control instructions, the multi-protocol support module receives the instructions; firstly, the multi-protocol support module identifies the type of the electric energy meter; according to the model and characteristics of the electric energy meter, the type of the electric energy meter, such as a single-phase electric energy meter, a three-phase electric energy meter and the like, can be determined; then, the multi-protocol support module identifies a communication protocol of the electric energy meter; according to the model and communication mode of the electric energy meter, the communication protocol used by the electric energy meter can be determined, such as 645, 698.45 or 376.2; then, the multi-protocol support module automatically selects a corresponding communication protocol for reading; according to the type and communication protocol of the electric energy meter, corresponding communication parameters are configured, and reading operation is carried out; if the reading is unsuccessful, the multi-protocol support module transmits the abnormal condition of the electric energy meter to the abnormal strategy module for processing; the abnormality policy module can take corresponding measures to check and process according to specific abnormality reasons so as to ensure the accuracy and the integrity of the data of the electric energy meter; through the function of the multi-protocol support module, the system can flexibly support electric energy meters with different types and communication protocols, and automatically select a proper communication protocol for reading; this helps to improve the compatibility and expandability of the system and ensures the success rate and efficiency of the reading operation.

For example, the system side device finds that the data of the electric energy meter cannot be collected at a certain time, and needs to go to the site for investigation and collection, and the flow is shown in fig. 3.

For example, when the system side device finds that there is an electric energy meter (generally in a meter box), data can be collected at some time, data cannot be collected at some time (signal difference), or the system side device cannot be collected for a long time, the field side device is installed in a field meter box for collection, and the flow is shown in fig. 4.

For example, when the system side device finds that the electric energy meter data is abnormal, the system side device checks suspected electricity larceny, and needs on-site monitoring and identification, and the flow is shown in fig. 5.

The embodiments of the present application have been described above, the foregoing description is exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (8)

1. A method for monitoring an on-site electric energy meter, the method being implemented based on a system-side device and a field-side device, the method comprising:

the system side equipment acquires the acquired electric energy meter data, analyzes the electric energy meter data and classifies the state of each electric energy meter according to an analysis result; the classification of the electric energy meter comprises normal, abnormal acquisition, abnormal electric energy meter and suspected electricity larceny;

the system side equipment generates a corresponding work order according to the electric energy meter with abnormal collection, abnormal electric energy meter and suspected electricity larceny, and dispatches the work order to operation and maintenance personnel;

the operation and maintenance personnel installs the field side equipment on the electric energy meter field for collecting abnormal electric energy meter, abnormal electric energy meter and suspected electricity larceny according to the work order, and the field side equipment is installed in a meter box of the electric energy meter;

the field side device responds to the scheduling control of the system side device, communicates with the electric energy meter, monitors the electric energy meter and sends a monitoring result to the system side device.

2. The method according to claim 1, wherein the system-side device acquires the collected electric energy meter data, analyzes the electric energy meter data, classifies the state of each electric energy meter according to the analysis result, and specifically comprises:

traversing all the collected data of the electric energy meters under the transformer area by taking the transformer area as a unit to calculate the daily electric quantity of the electric energy meters;

and marking the electric energy meter with the data of the non-current day as acquisition abnormality according to the traversal calculation result.

3. The method according to claim 2, wherein the system-side device acquires the collected electric energy meter data, analyzes the electric energy meter data, classifies the state of each electric energy meter according to the analysis result, and specifically comprises:

removing and collecting abnormal electric energy meters from the electric energy meter data to obtain removed electric energy meter data;

analyzing the voltage and the current of the electric energy meter according to the removed electric energy meter data, checking whether the electric energy meter is under-voltage or out-of-phase, and if so, temporarily marking the electric energy meter as abnormal;

according to the removed electric energy meter data, analyzing the daily electricity quantity data of the electric energy meter in the last 30 days, setting the data of one electric energy meter in the last 30 days as X1-X30, carrying out difference calculation on the data of each day and the data of the previous day to obtain difference values Y1-Y29, carrying out mean value calculation on the difference values Y1-Y29 to obtain a mean value S, respectively carrying out percentage deviation on the mean value S and the difference values Y1-Y29, and temporarily marking the electric energy meter as the electric energy meter is abnormal if a certain percentage deviation is larger than 80%;

introducing a station area line loss value, performing correlation coefficient calculation on the station area line loss value and daily electricity quantity data of the electric energy meter based on a Pearson correlation coefficient algorithm, extracting the electric energy meter with the correlation coefficient between 0.7 and 1, and temporarily marking the electric energy meter as abnormal;

analyzing the uncapping event and the magnetic field event of all the electric energy meters temporarily marked as the electric energy meter abnormality, determining whether the electric energy meters suspected to steal electricity exist in all the electric energy meters according to the analysis result, if yes, modifying the mark as suspected to steal electricity, and if not, reserving the mark of the electric energy meter abnormality;

and marking the rest electric energy meters which are not marked as abnormal, abnormal in acquisition and suspected electricity larceny as normal.

4. The method of claim 1, wherein the field side device comprises:

a remote port, including a 4G and/or network port communication interface, for communicating with the system side device;

the local port comprises an RS485 local interface, a carrier wave local interface and/or a Bluetooth local interface and is used for communicating with the electric energy meter;

the camera is used for sensing the action of opening the meter box, shooting the picture of an operator of opening the meter box and uploading the picture to the system side equipment;

the Beidou positioning module is used for acquiring the position information of the meter box and synchronously storing the position information with the system side equipment;

the magnetic field detection module is used for detecting the magnetic field intensity in the current environment;

the data storage module is used for caching the acquired data of the electric energy meter in the meter box and uploading the acquired data to the system side equipment;

and the display unit is used for displaying and performing touch operation.

5. The method of claim 4, wherein the field side device comprises:

the safety unit is used for encrypting and decrypting the communication data, and the field side equipment, the system side equipment and the electric energy meter are required to meet the safety requirement in communication;

the system side equipment is used for acquiring the electric energy meter file information in the meter box, and the electric energy meter file information is used for networking and communication;

and the control driving module is used for driving and controlling the local communication.

6. The method of claim 5, wherein the field side device comprises:

and 3 paths of field voltage and current monitoring are used for monitoring voltage and current values at the inlet wire end of the electric energy meter and comparing the voltage and current values with the actual read electric energy meter to confirm whether the electric energy meter is abnormal or has electricity stealing behavior.

7. The method of claim 6, wherein the field side device comprises:

the reading strategy module is used for responding to the scheduling control of the system side equipment, identifying the current missing data of the electric energy meter and controlling reading content, reading time point and reading priority;

and the abnormality policy module is used for responding to the scheduling control of the system side equipment, automatically entering a site abnormality handling link for the electric energy meter with the site reading failure, and checking whether the electric energy meter is abnormal, the communication address and the system are not corresponding to abnormality or the protocol is not corresponding to abnormality.

8. The method of claim 7, wherein the field side device comprises:

the multi-protocol support module comprises support 645, 698.45 and 376.2 communication protocols, and is used for responding to the scheduling control of the system side equipment, identifying the type of the electric energy meter and the communication protocols, automatically selecting the corresponding communication protocols for reading, and entering an abnormal strategy if the reading is unsuccessful.