Power distribution network user electricity stealing behavior diagnosis method based on three-layer progressive analysis model

Abstract

The invention discloses a power distribution network user electricity larceny behavior diagnosis method based on a three-layer progressive analysis model, and the method comprises the steps: taking three parts, to be specific: judgment of the existence of an electricity larceny behavior of a transformer area of a master station layer, collection of an electricity larceny user suspicion degree evaluation system of four-dimensional indexes of a terminal layer, and evidence collection and confirmation of high-frequency collection and event reporting of an electric energy surface layer as a main body, establishing a three-layer progressive analysis model; judging whether the electricity stealing behavior of the transformer area exists or not based on user-transformer relation identification and theoretical line loss comparison; calculating and dividing the electricity stealing suspicion degree of the users in the transformer area through the four-dimensional index system; and further confirming and obtaining evidence according to event report and high-frequency acquisition data, and forming an inspection work order. The method gives full play to the advantage of deepening the application function of the HPLC, matches the actual calculation capability of the main station and the edge side of the current power utilization information acquisition system, and achieves the quick response, accurate positioning and effective evidence collection of the electricity stealing behavior of the power distribution network user.

Description

technical field [0001] The invention relates to the field of power system distribution network line loss management and control, in particular to a method for diagnosing electricity stealing behavior of distribution network users based on a three-layer progressive analysis model. Background technique [0002] In recent years, electricity has provided more and more support for China's economic and social development. At the same time, electricity theft has become more serious, which not only affects the quality of electricity used by users, but may also endanger the safe operation of the power grid. In addition, the annual loss caused by electricity theft in my country is more than 10 billion. The reform and innovation of power supply units, the development direction of improving quality and efficiency require them to further strengthen line loss management and inspection of electricity theft. Line loss power is the difference between power supply and power consumption. Elect...

AI Technical Summary

Problems solved by technology

However, the traditional electricity stealing inspection methods generally rely on anti-electricity stealing physical devices, on-site manual investigation in high-loss station areas, and user reports. With the upgrading of electricity stealing methods, this method has problems of low efficiency and difficult evidence collection.

[0004] The academic community has proposed some intelligent algorithms based on artificial intelligence, but the computing and processing capabilities of the actual on-site acquisition equipment are difficult to achieve

In addition, many algorithms are intelligent analysis models established for the lack of collected data and low frequency. There is no power-stealing analysis scheme configured for the deepened application function of HPLC newly promoted and applied by the State Grid

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