Method for locating out-of-tolerance electric-energy meters in operation

Abstract

The invention provides a method for locating out-of-tolerance electric-energy meters in operation. The method includes: 1. acquiring line loss electric quantity of a specific stage area at each day for a period of time and power consumption of each user at each day under the stage area; 2. according to a Pearson correlation coefficient calculation formula (as is described in the specification), using the acquired line loss electric quantity of the state area at each day as X and the power consumption of each user at each day or power consumption after combination of users as Y, the number of acquired samples as n, calculating the Pearson correlation coefficient of the power consumption of each user at each day and the line loss electric quantity of the stage area at each day, or calculating the Pearson correlation coefficient of the power consumption after combination of the different users and the line loss electric quantity of the state area; 3. comparing the correlation coefficient of the power consumption of each user and the line loss electric quantity of the stage area or the coefficient of the power consumption after the combination of the users and the line loss electric quantity of the stage area so that user electric-energy meters with correlation coefficient >=0.8 is suspicious electric-energy meters; 4. locating rapidly the suspicious out-of-tolerance electric-energy meters according to the above-mentioned steps.

Description

technical field [0001] The invention relates to a method for locating an ultra-tolerance electric energy meter in operation. Background technique [0002] At present, the running meters are generally managed and controlled by random inspection, periodic verification, and periodic rotation. [0003] Periodic verification is only carried out on-site for large-scale user electric energy meters, and it is only carried out once a year, and out-of-tolerance meters cannot be found in time. Due to the large number of low-voltage users, periodic verification cannot be performed, and only random inspections can be used. The electric energy meters of low-voltage users are randomly inspected once a month, dozens of them each time, it is difficult to find out-of-tolerance electric energy meters in a targeted manner, which is blind. The cycle is rotated once every ten years, and the out-of-tolerance meters cannot be found in time. At present, there is no special method for finding out-o...

AI Technical Summary

Problems solved by technology

[0003] Periodic verification is only carried out on-site for large-scale user electric energy meters, and it is only carried out once a year. It is impossible to detect out-of-tolerance meters in time. Due to the large number of low-voltage users, periodic verification cannot be carried out, and only random inspections can be used.

Sampling inspections are arranged once a month for low-voltage user electric energy meters, dozens of each time, it is difficult to find out-of-tolerance electric energy meters in a targeted manner, which is blind

The cycle is rotated once every ten years, and the out-of-tolerance meters cannot be found in time

At present, there is no special method for finding out-of-tolerance operating electric energy meters in the prior art. Only when the abnormal line loss of the electric energy meter is analyzed can it be found that there are abnormal electric energy meters under the electric energy meter in the electric energy meter. Compare the power consumption line chart of each user with the power loss line chart of the station area, and find out a group that is more similar for analysis and investigation. However, the disadvantages of this method are: 1. The workload is heavy, and it needs to be calculated according to each household’s power consumption. Generate a line graph of power consumption and line loss in the station area. If there are many users in the station area, the workload can be imagined; 2. The search result is not accurate, because this method is performed by manually viewing the line graph, it is qualitative Analysis, there is no quantitative analysis of the correlation between user power and line loss power in the station area

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