A method and system for intelligent diagnosis of electric energy metering faults

Abstract

The present invention relates to the technical field of electric energy metering fault diagnosis, and discloses an electric energy metering fault intelligent diagnosis method and system, which include the following steps: Step 1: Obtain the total value of electric energy at the power generation end and the total value of electric energy at the user end, and perform analysis and processing to calculate the electric energy metering characterization value; Step 2: Compare the electric energy metering characterization value with the electric energy metering characterization value threshold, and if the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold, generate an electric energy metering fault signal. The present invention obtains the total value of electric energy at the power generation end and the total value of electric energy at the user end, and performs analysis and processing to calculate the electric energy metering characterization value; compares the electric energy metering characterization value with the electric energy metering characterization value threshold, and generates an electric energy metering normal signal or an electric energy metering fault signal, thereby analyzing the electric energy data at the power generation end and the user end, performing processing and analysis based on the electric energy data, and evaluating the stability of the measured data during the measurement process of the detection cycle.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy metering fault diagnosis, and in particular to an electric energy metering fault intelligent diagnosis method and system. Background Art

[0002] In the current power system, smart meters, as the core equipment for energy measurement, have gradually replaced traditional mechanical meters. Smart meters can not only record users' electricity consumption in real time, but also provide rich energy parameter information, such as voltage, current, power factor, etc.

[0003] However, due to the complexity of the power grid and the influence of the external environment, various abnormal situations may occur during the energy metering process. If these abnormal situations are not discovered and handled in time, they will have a serious impact on the stable operation of the power system and the user's electricity experience. The traditional energy metering troubleshooting method mainly relies on manual inspections and regular testing, which is inefficient and cannot judge and diagnose faults in a timely manner.

[0004] In view of this, we propose an intelligent diagnosis method and system for electric energy metering faults. Summary of the invention

[0005] The object of the present invention is to provide an intelligent diagnosis method and system for electric energy metering faults, so as to solve the problem that manual inspection and regular detection in the above background cannot timely discover electric energy metering faults.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An intelligent diagnosis method and system for electric energy metering faults, comprising the following steps:

[0008] Step 1: Obtain the total value of electric energy at the power generation end and the total value of electric energy at the power consumption end, analyze and process them, and calculate the electric energy metering representation value;

[0009] Among them, the process of obtaining the electric energy metering characterization value is as follows:

[0010] The electric energy data of the power generation end is collected through the electric energy metering equipment and marked as the total value of the electric energy of the power generation end;

[0011] Collect the electric energy data of several user ends on the transmission line, calculate the sum of the electric energy data of multiple user ends, and obtain the total electric energy data of the user end, which is marked as the total electric energy value of the user end;

[0012] Obtain the total electric energy value of the power generation end and the total electric energy value of the power consumption end within the detection period, calculate the difference between the total electric energy value of the power generation end and the total electric energy value of the power consumption end at the same time, and obtain the electric energy difference;

[0013] Obtain the power difference at each moment in the detection cycle;

[0014] The power difference at each moment in the detection period is summed and averaged to obtain the average power difference of the detection period;

[0015] The difference between the electric energy difference at each moment and the electric energy difference mean is calculated to obtain the electric energy difference deviation value at each moment in the detection period;

[0016] Compare the power difference deviation value at each moment in the detection cycle with the power difference threshold;

[0017] If the power difference deviation value is less than or equal to the power difference deviation threshold, it is marked as stable power difference;

[0018] If the power difference deviation value is greater than the power difference deviation threshold, it is marked as fluctuating power difference;

[0019] Obtain all stable power differences and all fluctuating power differences within the detection period;

[0020] All stable electric energy differences are summed up and averaged to obtain the average value of the stable electric energy difference;

[0021] All the fluctuation electric energy differences are summed up and averaged to obtain the average fluctuation electric energy difference;

[0022] The ratio of the average value of the stable electric energy difference to the average value of the fluctuating electric energy difference is calculated to obtain the electric energy metering representation value;

[0023] Step 2: compare the electric energy metering characterization value with the electric energy metering characterization value threshold, and if the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold, generate an electric energy metering fault signal;

[0024] Step 3: Based on the above electric energy metering fault signal, the electric energy data of each user end is obtained, the electric energy metering characterization parameter value of each user end is obtained, and the electric energy metering characterization parameter value of each user end is compared with the user end electric energy metering characterization parameter threshold, the stable state of the electric energy metering of each user end is evaluated, and the user end metering abnormal signal is generated;

[0025] Step 4: When an abnormal metering signal is obtained at the user end, the user end is marked as a user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain a diagnostic route of the user end to be analyzed;

[0026] Obtain the electric energy metering characterization parameter value of each use end to be analyzed, calculate the ratio of the electric energy metering characterization parameter value of each use end to be analyzed to the electric energy metering characterization parameter threshold of the use end, and obtain the metering stability influence ratio of the use end to be analyzed;

[0027] Obtain the average value of the stable end-use power of each end-use terminal to be analyzed, and sum them up to obtain the average value of the stable power consumption of all the ends-use terminals to be analyzed;

[0028] Calculate the ratio of the average stable power consumption of each end to be analyzed to the average stable power consumption of all ends to be analyzed, and obtain the power consumption impact ratio of the end to be analyzed;

[0029] Obtain the transmission line length from each end-to-be-analyzed user to the power generation end, and mark it as the distribution route value of the end-to-be-analyzed user;

[0030] and obtaining the sum of the lengths of all transmission lines from the user end to the generation end, marked as the total value of the distribution route for energy metering;

[0031] Calculate the ratio of the distribution route value of the end to be analyzed to the total value of the distribution route of the electric energy metering to obtain the distribution route ratio of the end to be analyzed;

[0032] When an abnormal metering signal is obtained from a user end, the user end is marked as a user end to be analyzed;

[0033] Obtain the metering stability impact ratio of the end to be analyzed, the electricity consumption impact ratio of the end to be analyzed, and the distribution route ratio of the end to be analyzed, and mark them as BW, BY, and BX respectively. , the diagnostic coefficient XZ of the end to be analyzed is calculated, where a1 and a2 are weight ratio coefficients, a1 is 0.68, and a2 is 0.32.

[0034] As a further solution of the present invention: the process of generating the abnormal signal of the user end metering is:

[0035] Obtain the electric energy metering characterization parameter value of each user end within the detection period;

[0036] Compare the electric energy metering characterization parameter value of each user end within the detection period with the electric energy metering characterization parameter threshold of the user end;

[0037] If the electric energy metering characterization parameter value at the user end is less than the electric energy metering characterization parameter threshold, a user end metering abnormality signal is generated.

[0038] As a further solution of the present invention: the process of obtaining the electric energy metering characteristic parameter value of each user end during the detection period is as follows:

[0039] Obtain all stable end-use power values ​​and all fluctuating end-use power values ​​within the detection period;

[0040] All stable end-use power values ​​are summed and averaged to obtain the stable end-use power average value;

[0041] All the fluctuating end-use electric energy values ​​are summed up and averaged to obtain the average value of the fluctuating end-use electric energy;

[0042] The ratio of the average electric energy of the stable use end to the average electric energy of the fluctuating use end is calculated to obtain the electric energy metering characterization parameter value of each use end.

[0043] As a further solution of the present invention: the process of acquiring the electric energy values ​​of all stable end users and all fluctuating end users within the detection period is as follows:

[0044] The user-end electric energy value at each moment in the detection period is summed and averaged to obtain the user-end electric energy average value of the detection period;

[0045] The difference between the end-use electric energy value at each moment and the end-use electric energy average is calculated to obtain the end-use electric energy deviation value at each moment in the detection period;

[0046] Compare the user-end power energy deviation value at each moment in the detection cycle with the user-end power energy deviation threshold;

[0047] If the user-end power deviation value is less than or equal to the user-end power deviation threshold, it is marked as a stable user-end power value;

[0048] If the user-end power energy deviation value is greater than the user-end power energy deviation threshold, it is marked as a fluctuating user-end power energy value.

[0049] As a further solution of the present invention: specifically comprising:

[0050] Data acquisition and calculation module: obtains the total value of electric energy at the power generation end and the total value of electric energy at the user end, analyzes and processes them, and calculates the electric energy metering representation value;

[0051] Fault judgment module: compares the electric energy metering characterization value with the electric energy metering characterization value threshold, and generates an electric energy metering fault signal if the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold;

[0052] The user-end power analysis module: based on the above power metering fault signal, obtains the power data of each user end, obtains the power metering characterization parameter value of each user end, and compares it with the user-end power metering characterization parameter threshold, evaluates the stable state of power metering of each user end, and generates a user-end metering abnormality signal;

[0053] Diagnostic route acquisition module: When an abnormal metering signal is obtained at the user end, the user end is marked as the user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain the diagnostic route of the user end to be analyzed.

[0054] Beneficial effects of the present invention:

[0055] (1) The present invention obtains the total value of electric energy at the power generation end and the total value of electric energy at the user end, performs analysis and processing, and calculates the electric energy metering characterization value; compares the electric energy metering characterization value with the electric energy metering characterization value threshold, generates an electric energy metering normal signal or an electric energy metering fault signal, thereby analyzing the electric energy data at the power generation end and the user end, performing processing and analysis based on the electric energy data, and evaluating and judging the stability of the measured data during the measurement process of the detection cycle;

[0056] (2) Under the premise that the overall metering line has abnormal fluctuations, the present invention performs distributed fluctuation analysis on each user end to determine the line that may have abnormalities, and then determines the reasonable and optimal diagnostic path based on the impact of the fluctuation degree of each abnormal line on the overall line, the demand degree of the power-consuming equipment (the demand degree is analyzed by the power consumption of the abnormal line) and the time spent on the abnormal line itself during the maintenance process (the time consumption is analyzed by the line length), so that the overall power line can be diagnosed more efficiently and restored to normal use. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention will be further described below in conjunction with the accompanying drawings.

[0058] Figure 1 It is a flow chart of an intelligent diagnosis method for electric energy metering faults of the present invention;

[0059] Figure 2 It is a schematic diagram of a process of obtaining electric energy metering characterization values ​​in an intelligent diagnosis method for electric energy metering faults of the present invention;

[0060] Figure 3 It is a schematic diagram of the process of obtaining the diagnosis coefficient in the intelligent diagnosis method of electric energy metering fault of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1

[0062] See also Figure 1 - Figure 3 As shown, the present invention is an intelligent diagnosis method for electric energy metering faults, comprising the following steps:

[0063] Step 1: Obtain the total value of electric energy at the power generation end and the total value of electric energy at the power consumption end, analyze and process them, and calculate the electric energy metering representation value;

[0064] In some embodiments, the electric energy data of the power generation end is collected through the electric energy metering device and marked as the total value of the electric energy of the power generation end;

[0065] Collect the electric energy data of several user ends on the transmission line, calculate the sum of the electric energy data of multiple user ends, and obtain the total electric energy data of the user end, which is marked as the total electric energy value of the user end;

[0066] Among them, the electric energy metering equipment may be an electric energy meter, a metering box / cabinet;

[0067] The collected electric energy data is analyzed as follows:

[0068] Obtain the total electric energy value of the power generation end and the total electric energy value of the power consumption end within the detection period, calculate the difference between the total electric energy value of the power generation end and the total electric energy value of the power consumption end at the same time, and obtain the electric energy difference;

[0069] The power difference at each moment in the detection period is summed and averaged to obtain the average power difference of the detection period;

[0070] The difference between the electric energy difference at each moment and the electric energy difference mean is calculated to obtain the electric energy difference deviation value at each moment in the detection period;

[0071] Compare the power difference deviation value at each moment in the detection cycle with the power difference threshold (the power difference threshold is set by the staff based on experience);

[0072] If the electric energy difference deviation value is less than or equal to the electric energy difference deviation threshold, it means that the electric energy difference deviation value is slightly different from the electric energy difference deviation mean value, and the electric energy difference at this moment is marked as a stable electric energy difference;

[0073] If the electric energy difference deviation value is greater than the electric energy difference deviation threshold, it means that the electric energy difference deviation value is greatly different from the electric energy difference deviation mean value, and the electric energy difference at this moment is marked as a fluctuating electric energy difference;

[0074] All stable electric energy differences obtained during the detection period are summed and averaged to obtain a stable electric energy difference mean;

[0075] All the fluctuation power difference degrees obtained within the detection period are summed and averaged to obtain the average fluctuation power difference degree;

[0076] The ratio of the average value of the stable electric energy difference to the average value of the fluctuating electric energy difference is calculated to obtain the electric energy metering representation value;

[0077] The meaning of the energy metering characterization value is: by analyzing the energy data of the power generation end and the user end, processing and analyzing the energy data, and evaluating the stability of the measured data during the measurement process of the detection cycle, the larger the energy metering characterization value, the higher the energy measured.

[0078] The more stable and accurate the data is, the smaller the power metering representation value is, which reflects that the measured power data is more unstable and inaccurate;

[0079] Step 2: Compare the electric energy metering characterization value with the electric energy metering characterization value threshold value to generate an electric energy metering normal signal or an electric energy metering fault signal;

[0080] In some embodiments, an electric energy metering characterization value is obtained, and the electric energy metering characterization value is compared with an electric energy metering characterization value threshold (the electric energy metering characterization threshold is set by a person skilled in the art based on historical experimental data summary);

[0081] If the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold, an electric energy metering fault signal is generated;

[0082] If the electric energy metering characterization value is greater than the electric energy metering characterization threshold, a normal electric energy metering signal is generated;

[0083] The core technology of this embodiment is: obtaining the total value of electric energy at the power generation end and the total value of electric energy at the user end, analyzing and processing them, and calculating the electric energy metering characterization value; comparing the electric energy metering characterization value with the electric energy metering characterization value threshold, and generating an electric energy metering normal signal or an electric energy metering fault signal. The present invention analyzes the electric energy data at the power generation end and the user end, performs processing and analysis based on the electric energy data, and evaluates and judges the stability of the measured data during the measurement process of the detection cycle.

[0084] Embodiment 2

[0085] Based on the above embodiments, the present invention is an intelligent diagnosis method for electric energy metering faults, which further includes the following steps:

[0086] Step 3: Based on the above electric energy metering fault signal, the electric energy data of each user end is obtained, the electric energy metering characterization parameter value of each user end is obtained, and the electric energy metering characterization parameter value of each user end is compared with the user end electric energy metering characterization parameter threshold, the stable state of the electric energy metering of each user end is evaluated, and the user end metering normal signal or the user end metering abnormal signal is obtained;

[0087] In some implementation schemes, the collected electric energy value of each user end is analyzed as follows:

[0088] The user-end electric energy value at each moment in the detection period is summed and averaged to obtain the user-end electric energy average value of the detection period;

[0089] The difference between the end-use electric energy value at each moment and the end-use electric energy average is calculated to obtain the end-use electric energy deviation value at each moment in the detection period;

[0090] Compare the user-end power energy deviation value at each moment in the detection cycle with the user-end power energy deviation threshold (the user-end power energy deviation threshold is set by the staff based on experience);

[0091] If the user-end power energy deviation value is less than or equal to the user-end power energy deviation threshold, it means that the user-end power energy deviation value is slightly different from the user-end power energy deviation mean value, and the user-end power energy value at this moment is marked as a stable user-end power energy value;

[0092] If the user-end power energy deviation value is greater than the user-end power energy deviation threshold, it means that the user-end power energy deviation value is significantly different from the user-end power energy deviation mean value, and the user-end power energy value at this moment is marked as a fluctuating user-end power energy value;

[0093] All stable end-use power values ​​obtained during the detection period are summed and averaged to obtain the stable end-use power average value;

[0094] All the fluctuating end-use power energy values ​​obtained during the detection period are summed and averaged to obtain the fluctuating end-use power energy average;

[0095] The average value of the electric energy at the stable user end is calculated by the ratio with the average value of the electric energy at the fluctuating user end, and the electric energy metering characterization parameter value of each user end in history is obtained;

[0096] Compare the electric energy metering characterization parameter value of each user end within the detection period with the user end electric energy metering characterization parameter threshold (the user end electric energy metering characterization parameter threshold is set by a technician in this field based on historical experimental data);

[0097] If the electric energy metering characterization parameter value of the user end is greater than or equal to the electric energy metering characterization parameter threshold, it means that the electric energy metering fluctuation of the user end is small during the detection period, and a user end metering normal signal is generated;

[0098] If the electric energy metering characteristic parameter value of the user end is less than the electric energy metering characteristic parameter threshold value, it means that the electric energy metering fluctuation of the user end is large during the detection period, and a user end metering abnormality signal is generated;

[0099] Step 4: When an abnormal metering signal is obtained at the user end, the user end is marked as a user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain a diagnostic route of the user end to be analyzed;

[0100] In some implementation schemes, when a user end metering abnormality signal is obtained, the user end is marked as a user end to be analyzed;

[0101] Obtain the metering stability impact ratio of the end to be analyzed, the electricity consumption impact ratio of the end to be analyzed, and the distribution route ratio of the end to be analyzed, and mark them as BW, BY, and BX respectively. , the diagnostic coefficient XZ of the end to be analyzed is calculated, where a1 and a2 are weight ratio coefficients, a1 is 0.68, and a2 is 0.32;

[0102] Arrange all the end users to be analyzed from large to small according to the diagnostic coefficients to obtain the diagnostic routes of the end users to be analyzed, and arrange diagnostic personnel to inspect and repair the power transmission lines with metering fluctuations according to their diagnostic routes;

[0103] Among them, the process of obtaining the proportion of the metering stability impact of the user end to be analyzed is:

[0104] Obtain the electric energy metering characterization parameter value of each use end to be analyzed, calculate the ratio of the electric energy metering characterization parameter value of each use end to be analyzed to the electric energy metering characterization parameter threshold of the use end, and obtain the metering stability influence ratio of the use end to be analyzed;

[0105] The process of obtaining the proportion of electricity consumption impact of the end to be analyzed is as follows:

[0106] Obtain the average value of the stable end-use power of each end-use terminal to be analyzed, and sum them up to obtain the average value of the stable power consumption of all the ends-use terminals to be analyzed;

[0107] Compare the average value of the stable end power consumption of each end to be analyzed with the average value of the stable power consumption of all ends to be analyzed to obtain the power consumption impact ratio of the end to be analyzed;

[0108] The process of obtaining the distribution route ratio of the end to be analyzed is as follows:

[0109] Obtain the transmission line length from each end-to-be-analyzed user to the power generation end, and mark it as the distribution route value of the end-to-be-analyzed user;

[0110] and obtaining the sum of the lengths of all transmission lines from the user end to the generation end, marked as the total value of the distribution line for energy metering;

[0111] Calculate the ratio of the distribution route value of the end to be analyzed to the total value of the distribution route of the electric energy metering to obtain the distribution route ratio of the end to be analyzed;

[0112] The technical solution of the embodiment of the present invention is as follows: based on the above-mentioned electric energy metering fault signal, the electric energy data of each user end is obtained, the metering characterization parameter value of each user end is obtained, and the value is compared with the electric energy metering characterization parameter threshold, the stable state of the electric energy metering of each user end is evaluated, and the user end metering normal signal or the user end metering abnormal signal is obtained; the user end metering abnormal signal is marked as the user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain the diagnostic route of the user end to be analyzed;

[0113] In this embodiment, under the premise that the overall metering line has abnormal fluctuations, a distributed fluctuation analysis is performed on each user end to determine the lines that may have abnormalities, and then a reasonable and optimal diagnostic path is determined based on the impact of the fluctuation degree of each abnormal line on the overall line, the demand degree of the power-consuming equipment (the demand degree is analyzed by the power consumption of the abnormal line) and the time spent on the abnormal line itself during the maintenance process (the time consumption is analyzed by the line length), so that the overall power line can be diagnosed more efficiently and restored to normal use.

[0114] Embodiment 3

[0115] Based on the above embodiments, the present invention is an intelligent diagnosis system for electric energy metering faults, which specifically includes:

[0116] Data acquisition and calculation module: obtains the total value of electric energy at the power generation end and the total value of electric energy at the user end, analyzes and processes them, and calculates the electric energy metering representation value;

[0117] Fault judgment module: compares the electric energy metering characterization value with the electric energy metering characterization value threshold, and generates an electric energy metering normal signal or an electric energy metering fault signal;

[0118] The user-end power analysis module: based on the above power metering fault signal, obtains the power data of each user end, obtains the power metering characterization parameter value of each user end, and compares it with the power metering characterization parameter threshold of the user end, evaluates the stable state of the power metering of each user end, and obtains the user end metering normal signal or the user end metering abnormal signal;

[0119] Diagnostic route acquisition module: When an abnormal metering signal is obtained at the user end, the user end is marked as the user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain the diagnostic route of the user end to be analyzed.

[0120] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An intelligent diagnosis method for electric energy metering faults, characterized in that: The following steps are involved: Step 1: Obtain the total value of electric energy at the power generation end and the total value of electric energy at the power consumption end, analyze and process them, and calculate the electric energy metering representation value; Among them, the process of obtaining the electric energy metering characterization value is as follows: The electric energy data of the power generation end is collected through the electric energy metering equipment and marked as the total value of the electric energy of the power generation end; Collect the electric energy data of several user ends on the transmission line, calculate the sum of the electric energy data of multiple user ends, and obtain the total electric energy data of the user end, which is marked as the total electric energy value of the user end; Obtain the total electric energy value of the power generation end and the total electric energy value of the power consumption end within the detection period, calculate the difference between the total electric energy value of the power generation end and the total electric energy value of the power consumption end at the same time, and obtain the electric energy difference; Obtain the power difference at each moment in the detection cycle; The power difference at each moment in the detection period is summed and averaged to obtain the average power difference of the detection period; The difference between the electric energy difference at each moment and the electric energy difference mean is calculated to obtain the electric energy difference deviation value at each moment in the detection period; Compare the power difference deviation value at each moment in the detection cycle with the power difference threshold; If the power difference deviation value is less than or equal to the power difference deviation threshold, it is marked as stable power difference; If the power difference deviation value is greater than the power difference deviation threshold, it is marked as fluctuating power difference; Obtain all stable power differences and all fluctuating power differences within the detection period; All stable electric energy differences are summed up and averaged to obtain the average value of the stable electric energy difference; All the fluctuation electric energy differences are summed up and averaged to obtain the average fluctuation electric energy difference; The ratio of the average value of the stable electric energy difference to the average value of the fluctuating electric energy difference is calculated to obtain the electric energy metering representation value; Step 2: compare the electric energy metering characterization value with the electric energy metering characterization value threshold, and if the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold, generate an electric energy metering fault signal; Step 3: Based on the above electric energy metering fault signal, the electric energy data of each user end is obtained, the electric energy metering characterization parameter value of each user end is obtained, and the electric energy metering characterization parameter value of each user end is compared with the user end electric energy metering characterization parameter threshold, the stable state of the electric energy metering of each user end is evaluated, and the user end metering abnormal signal is generated; Step 4: When an abnormal metering signal is obtained at the user end, the user end is marked as a user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain a diagnostic route of the user end to be analyzed; Obtain the electric energy metering characterization parameter value of each use end to be analyzed, calculate the ratio of the electric energy metering characterization parameter value of each use end to be analyzed to the electric energy metering characterization parameter threshold of the use end, and obtain the metering stability influence ratio of the use end to be analyzed; Obtain the average value of the stable end-use power of each end-use terminal to be analyzed, and sum them up to obtain the average value of the stable power consumption of all the ends-use terminals to be analyzed; Calculate the ratio of the average stable power consumption of each end to be analyzed to the average stable power consumption of all ends to be analyzed, and obtain the power consumption impact ratio of the end to be analyzed; Obtain the transmission line length from each end-to-be-analyzed user to the power generation end, and mark it as the distribution route value of the end-to-be-analyzed user; and obtaining the sum of the lengths of all transmission lines from the user end to the generation end, marked as the total value of the distribution route for energy metering; Calculate the ratio of the distribution route value of the end to be analyzed to the total value of the distribution route of the electric energy metering to obtain the distribution route ratio of the end to be analyzed; When an abnormal metering signal of a user end is obtained, the user end is marked as a user end to be analyzed; Obtain the metering stability impact ratio of the end to be analyzed, the electricity consumption impact ratio of the end to be analyzed, and the distribution route ratio of the end to be analyzed, and mark them as BW, BY, and BX respectively. , the diagnostic coefficient XZ of the end to be analyzed is calculated, where a1 and a2 are weight ratio coefficients, a1 is 0.68, and a2 is 0.

32.

2. The method for intelligent diagnosis of electric energy metering faults according to claim 1 is characterized in that: The process of generating the abnormal signal of the user end metering is as follows: Obtain the electric energy metering characterization parameter value of each user end within the detection period; Compare the electric energy metering characterization parameter value of each user end within the detection period with the electric energy metering characterization parameter threshold of the user end; If the electric energy metering characterization parameter value at the user end is less than the electric energy metering characterization parameter threshold, a user end metering abnormality signal is generated.

3. The method for intelligent diagnosis of electric energy metering faults according to claim 2 is characterized in that: The process of obtaining the electric energy metering characterization parameter value of each user end during the detection cycle is as follows: Obtain all stable end-use power values ​​and all fluctuating end-use power values ​​within the detection period; All stable end-use power values ​​are summed and averaged to obtain the stable end-use power average value; All the fluctuating end-use electric energy values ​​are summed up and averaged to obtain the average value of the fluctuating end-use electric energy; The ratio of the average electric energy of the stable use end to the average electric energy of the fluctuating use end is calculated to obtain the electric energy metering characterization parameter value of each use end.

4. The method for intelligent diagnosis of electric energy metering faults according to claim 3 is characterized in that: The process of obtaining the electric energy values ​​of all stable end users and all fluctuating end users within the detection period is as follows: The user-end electric energy value at each moment in the detection period is summed and averaged to obtain the user-end electric energy average value of the detection period; The difference between the end-use electric energy value at each moment and the end-use electric energy average is calculated to obtain the end-use electric energy deviation value at each moment in the detection period; Compare the user-end power energy deviation value at each moment in the detection cycle with the user-end power energy deviation threshold; If the user-end power deviation value is less than or equal to the user-end power deviation threshold, it is marked as a stable user-end power value; If the user-end power energy deviation value is greater than the user-end power energy deviation threshold, it is marked as a fluctuating user-end power energy value.

5. A system for intelligent diagnosis of electric energy metering faults, the system implementing the method according to any one of claims 1 to 4, characterized in that: Specifically include: Data acquisition and calculation module: obtains the total value of electric energy at the power generation end and the total value of electric energy at the user end, analyzes and processes them, and calculates the electric energy metering representation value; Fault judgment module: compares the electric energy metering characterization value with the electric energy metering characterization value threshold, and generates an electric energy metering fault signal if the electric energy metering characterization value is less than or equal to the electric energy metering characterization threshold; The user-end power analysis module: based on the above power metering fault signal, obtains the power data of each user end, obtains the power metering characterization parameter value of each user end, and compares it with the user-end power metering characterization parameter threshold, evaluates the stable state of power metering of each user end, and generates a user-end metering abnormality signal; Diagnostic route acquisition module: When an abnormal metering signal is obtained at the user end, the user end is marked as the user end to be analyzed, the diagnostic coefficient of the user end to be analyzed is obtained, and the diagnostic coefficients are arranged from large to small to obtain the diagnostic route of the user end to be analyzed.

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