基于层次分析法的加权LOF窃电检测方法研究

为解决传统窃电检测方法的局限性，本文提出一种基于层次分析法的加权LOF窃电检测方法。该方法首先通过对窃电现象的系统分析，提出新的用电特征指标，构建合理的窃电嫌疑评价体系；其次针对各电气指标数据异常所能代表窃电的不同概率，采用层次分析法合理量化各电气指标的权重，并结合加权LOF算法对海量用户数据进行加权离群分析，使用综合离群因子表征用户窃电嫌疑程度。最后通过实测数据验证，结果表明所提检测方法相较传统LOF算法在较低检测率时能够挖掘出更多的窃电用户，进而提升采集系统的窃电检测效率。

Research on Weighted LOF Stealing Detection Method Based on Analytic Hierarchy Process

In order to solve the limitation of the traditional methods of detecting stealing electricity, this paper presents a weighted LOF method based on analytic hierarchy process. the technique firstly analyzes the phenomenon of stealing electricity and puts forward a new characteristic index of electricity consumption and constructs a reasonable evaluation system of stealing. Secondly, according to different probability of the abnormal electrical indicators of data can represent the electric larceny, the weight of each electrical index is quantified by analytic hierarchy process (AHP) quantitatively. The massive data can be analyzed by weighted outlier analysis with the weighted LOF algorithm, and using a comprehensive outlier factor to characterize the theft of users. Finally the experiments through the measured data demonstrate that the proposed method can dig out more stealing users compared with the traditional LOF algorithm when the detection rate is low, and improving the efficiency of the detection of electricity larceny.