Power consumption data anomaly detection method and system based on big data analysis

Abstract

The invention discloses an electricity consumption data anomaly detection method and system based on big data analysis, and belongs to the field of electric power safety detection. The method comprises the following steps: integrating historical electricity stealing behaviors, obtaining historical electricity stealing data, and constructing an electricity stealing accurate identification and electricity stealing feedback data analysis model; measuring the accuracy of the electric power stealing accurate identification and electric power stealing feedback data analysis model through the standardized covariance, and correcting the electric power stealing accurate identification and electric power stealing feedback data analysis model by using a loss function; and collecting real-time power utilization data, and inputting the real-time power utilization data into the accurate identification and electricity stealing feedback data analysis model to obtain whether an electricity stealing phenomenon exists or not and line loss data. The user electricity larceny analysis method based on the big data is beneficial to efficient investigation of electricity larceny behaviors, can analyze the electricity larceny behaviors, and is beneficial to line loss treatment of a power supply company.

Description

technical field [0001] The invention relates to the field of power safety detection, and more particularly to a method and system for abnormality detection of power consumption data based on big data analysis. Background technique [0002] In recent years, with the continuous development of my country's economy, the scale of the power grid, the scope of power supply, and the number of users have continued to expand, and the power consumption of users has also increased. It is inevitable that illegal electricity theft will occur. Electricity theft breaks the normal order of electricity consumption, seriously affects the safety of power grid operation, and threatens the safety of personal and property. The damage to power equipment such as transformers and personal electric shock accidents caused by electricity theft often occur, bringing greater economic benefits to power supply enterprises and society. loss. [0003] The traditional power-stealing user investigation is main...

AI Technical Summary

Problems solved by technology

Stealing electricity breaks the normal order of electricity consumption, seriously affects the safety of power grid operation, threatens the safety of personal property, and damages transformers and other electrical equipment and personal electric shock accidents caused by stealing electricity occur from time to time, bringing great economic benefits to power supply companies and society. loss

[0003] Traditional electricity stealing user investigation is mainly through manual door-to-door inspection of station areas with high line loss, which is time-consuming and laborious, with a huge workload, more personnel required for on-site inspection, and higher labor costs

Moreover, the investigation work lacks pertinence, and the single-household inspection takes a long time, which is prone to false reports. It often requires staff to go to the site for investigation many times, and the efficiency is low.

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