Power utilization abnormal behavior recognition method based on fuzzy neural network

Abstract

The invention provides a power utilization abnormal behavior recognition method based on a fuzzy neural network, and the method comprises the steps: extracting original data of a part of users as sample data from a power utilization database; carrying out the data preprocessing; designing a power utilization abnormal behavior evaluation index system on the basis of the analysis of power utilization abnormal behavior cases; constructing an expert sample based on the preprocessed data; taking an power utilization abnormal behavior mark as an input item, taking a power utilization abnormal behavior suspicion coefficient as an output item, and constructing a fuzzy neural network model; inputting test data into a built fuzzy neural network model, and carrying out the diagnosis of the power utilization abnormal behavior; evaluating a power utilization abnormal behavior diagnosis result, and a setting a target evaluation and optimization model. The method provided by the invention achieves the automatic recognition and diagnosis of the power utilization abnormal behavior, achieves the automatic training learning and modeling of a system, achieves the quick and precise positioning of a suspected user, and facilitates the obtaining of various illegal behaviors of power utilization.

Description

technical field [0001] The invention belongs to the technical field of electricity consumption data analysis and processing and data mining, and in particular relates to a method for identifying abnormal electricity consumption behaviors by using a fuzzy neural network algorithm. Background technique [0002] Abnormal electricity consumption behaviors such as electricity theft and leakage are problems that the power industry often needs to face. These abnormal electricity consumption behaviors will lead to missed or undercharged electricity bills, which will bring considerable economic losses to power companies. [0003] In response to this kind of problem, the traditional solutions to prevent abnormal electricity consumption behaviors such as electricity theft and leakage include regular inspections, user reports, and regular meter calibration. The goals are not clear enough. [0004] At present, many power supply bureaus in my country mainly use the abnormal alarm functio...

AI Technical Summary

Problems solved by technology

This method requires online supervision by staff, and there are problems of terminal false alarms and information redundancy in the process of collecting information such as power abnormalities, load abnormalities, terminal alarms, and master station alarms.

At the same time, this method also has problems such as high cost, complex model, and insufficient accuracy of monitoring results, especially in cases involving various complex phenomena and abnormal electricity consumption behaviors such as electricity theft and leakage, and cannot achieve effective monitoring. monitor

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