SVM (Support Vector Machine)-based power consumption abnormality detection method

Abstract

The invention discloses an SVM (Support Vector Machine)-based power consumption abnormality detection method. An overall system comprises a metering database system (1-1), a preprocessing module (1-2), a One-class SVM sorting machine (1-3), a warning message filtering module (1-4) and a warning module (1-5), and the relation of all the modules is shown by using a data flowing direction (1-6); a system flowchart consists of thirteen modules: a data collection module (2-1), a data preprocessing module (2-2), a training sample collection module (2-3), a working day model module (2-4), a holiday model module (2-5), a weekend model module (2-6), a data preprocessing module (2-7), a KKT condition judger module (2-8), a One-class SVM classifier module (2-9), a system decision module (2-10), a warning module (2-11), a program execution direction module (2-12) meeting KKT conditions, and a program execution direction module (2-13) incapable of meeting KKT conditions. The SVM-based power consumption abnormality detection method has the remarkable advantages of being small in training samples, capable of setting detection accuracy, and the like.

Description

technical field [0001] The invention belongs to the technical field of electricity abnormality detection, and is especially suitable for the field of electricity inspection. Background technique [0002] Electricity theft accounts for a large proportion of power grid losses. Traditional anti-theft measures can effectively reduce electricity theft. However, with the promotion of low-voltage centralized copying systems, the degree of automation of power system metering continues to increase, making it difficult for power thieves to steal electricity. increase. Illegal power users can affect the automatic meter reading system through hacking techniques and other means, so as to achieve the purpose of stealing electricity. [0003] Based on the problem of stealing electricity, the idea of ​​using unsupervised machine learning detection is proposed, and it is realized through technical means. The present invention uses the method based on SVM to analyze the sampling data, which...

AI Technical Summary

Problems solved by technology

[0004] Due to the complex and diverse behaviors of stealing electricity, some behaviors have similarities with normal power user load curves, etc., the purpose of the present invention is to solve the problem of abnormal power load

Images