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PCA based electricity theft detection in advanced metering infrastructure

机译:先进计量基础架构中基于PCA的电力盗窃检测

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Advanced metering infrastructure is one of the important components of smart grid and offers an essential link between consumers and their loads, grid, and generation and storage resources. Electricity theft, one of the key concern in AMI, causes million dollar revenue loss every year in developing and developed countries. In this paper, Principal Component Analysis (PCA) based electricity theft detection scheme is proposed. PCA is used to transform a high dimensional dataset into a low dimensional dataset. Using principal components, anomaly score is calculated and compared with a predefined threshold value. The proposed scheme is tested under different attack scenario using real dataset. The results show that the proposed scheme detects electricity theft attacks with high detection rate.
机译:先进的计量基础设施是智能电网的重要组成部分之一,它为用户及其负载,电网以及发电和存储资源之间提供了必不可少的联系。窃电是AMI的关键问题之一,在发展中国家和发达国家每年造成数百万美元的收入损失。本文提出了一种基于主成分分析(PCA)的窃电检测方案。 PCA用于将高维数据集转换为低维数据集。使用主成分,可以计算出异常分数并将其与预定义的阈值进行比较。使用真实数据集在不同的攻击场景下对提出的方案进行了测试。结果表明,该方案能以较高的检测率检测出窃电攻击。

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