Method for automatically screening abnormal electricity consumption user

Abstract

The invention belongs to the technical field of intelligent electric energy meters and provides a method for automatically screening an abnormal electricity consumption user. The method comprises the following steps of calculating line loss; acquiring a focus distribution area according to the line loss, wherein the focus distribution area is a distribution area of which the line loss is greater than a set threshold value; processing current electricity consumption data and historic electricity consumption data of users in the focus distribution area to obtain suspected electricity larceny users. User data are classified through normal distribution and are respectively calculated according to the classified users, and the suspected electricity larceny users can be quickly and accurately found according to special event factors, holiday factors, seasonal factors and the like. According to the method, by mining electricity consumption data, the abnormal electricity consumption user can be timely found, electricity consumption disputes are reduced, an electricity larceny behavior is effectively found, and a normal electricity consumption order is maintained. Parameters such as user classification coefficients and the seasonal factors can be finely adjusted according to an actual operating effect after user classification and calculation are completed in a calculation process so as to achieve an accurate analysis effect.

Description

technical field [0001] The invention belongs to the technical field of smart electric energy meters, in particular to an automatic screening method for users with abnormal electricity consumption. Background technique [0002] State Grid and China Southern Power Grid Corporation are doing large-scale replacement of smart meters, and are also vigorously promoting the establishment of power information collection systems. [0003] At present, the reading and collection of a large amount of electric energy information is still in the stage of manual meter reading, so the existing abnormal electricity consumption users are almost found by manual analysis and manual on-site inspection. [0004] The characteristic of manual meter reading is that it is inefficient, and it is impossible to uniformly read all the electric energy meters, and it is impossible to use the read electric energy data to accurately calculate line loss and other analysis, and it is impossible for users to kno...

AI Technical Summary

Problems solved by technology

[0003] At present, the reading and collection of a large amount of electric energy information is still in the stage of manual meter reading, so the existing abnormal electricity consumption users are almost found by manual analysis and manual on-site inspection.

[0004] The characteristic of manual meter reading is that it is inefficient, and it is impossible to read all the electric energy meters uniformly, and it is impossible to use the read electric energy data to accurately calculate line loss and other analysis, and it is impossible for users to know abnormal electricity consumption.

Meter readers who check the meter for abnormality when reading the meter alone have little chance of discovering electricity theft, and cannot meet the requirements of the existing power sector for high-efficiency work.

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