Multi-timescale Electricity Theft Detection and Localization in Distribution Systems Based on State Estimation and PMU Measurements

Côme Carquex, C. Rosenberg
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引用次数: 6

Abstract

Electricity theft is a serious issue for distribution companies around the world. Often linked to criminal activities, it is dangerous for the grid and the neighborhoods. While placing measurement points at each bus would allow an easy detection, it is not a practical approach. In this paper, a multi-timescale theft estimation (MISTE) method that takes advantage of smart-meters as well as the sparse grid sensing infrastructure that is being envisaged for state estimation is proposed. It combines power and voltage measurement across time to detect any inconsistency caused by electricity theft. Contrary to existing approaches which are snapshot-based and assume smart-meters to be able to measure instantaneous power consumption, the proposed method models smart-meters as energy measurement devices and combines the measurement timescales of the smart-meters and the PMUs in the computations. The detection performance of the proposed approach is compared to the state of the art theft detection methods. Both the true positive rate as well as the false negative rate are considered, which few papers have discussed previously. Insights on the impact of theft location on theft detection are also given.
基于状态估计和PMU测量的配电系统多时间尺度窃电检测与定位
窃电是世界各地配电公司面临的一个严重问题。它经常与犯罪活动联系在一起,对电网和社区都是危险的。虽然在每个总线上放置测量点可以很容易地进行检测,但这不是一种实用的方法。本文提出了一种多时间尺度盗窃估计(MISTE)方法,该方法利用了智能电表以及正在设想用于状态估计的稀疏网格传感基础设施。它结合了跨时间的功率和电压测量,以检测由电力盗窃引起的任何不一致。与现有的基于快照并假设智能电表能够测量瞬时功耗的方法相反,该方法将智能电表建模为能量测量设备,并在计算中结合智能电表和pmu的测量时间尺度。将该方法的检测性能与现有的艺术品盗窃检测方法进行了比较。同时考虑了真阳性率和假阴性率,这在以前的文献中很少讨论。此外,本文还分析了盗窃地点对盗窃侦查的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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