Abnormal power consumption detection method based on neural network

Abstract

The invention relates to an abnormal power consumption detection method based on a neural network. The method diagnoses and analyzes an operation condition of equipment based on an established abnormal power consumption detection model, judges whether metering equipment is in a normal operation condition and realizes an aid decision-making function. The method concretely comprises the following steps of (1) data acquisition: data are mainly from electric energy metering data, operation condition data and event recording data in an electric energy meter and an acquisition terminal; (2) data cleaning: the used data can enter the model after being subjected to data cleaning and screening; (3) data classification: after data cleaning completes, the data are calibrated, one column of numbers for representing data classification is added at the end of the data for classification, and the data subjected to data calibration are integrated into training data; (4) a modeling process: an algorithm model is constructed in a manner of supervised learning; (5) model implementation; and (6) result analysis: the final accuracy rate of abnormal power consumption found by the model maintains at a high level.

Description

technical field [0001] The invention relates to a method for detecting abnormal power consumption based on a neural network, and belongs to the technical field of detecting abnormal power consumption of power grids. Background technique [0002] With the continuous improvement of informatization, the era of big data has arrived, and mining valuable information from a large amount of data with low value density has become a hot issue that all walks of life pay close attention to. For the power industry, with the continuous improvement of the informatization level of the power system and the rapid growth of the data volume of distribution and consumption, various devices and systems have a large amount of data to be processed, the data scale is huge, and the event information contained is various. But so far, it still faces the important problem of "massive data and lack of information". [0003] At the same time, due to a variety of communication failures, equipment failures...

AI Technical Summary

Problems solved by technology

This processing method consumes a lot of manpower and material resources, and has low efficiency and poor effect. At the same time, this method has great human factors, which is not conducive to the management of the electric power industry.

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