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Detection of Electricity Theft based on Compressed Sensing

机译:基于压缩感知的窃电检测

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Electricity Theft, a major non-technical loss during transmission and distribution systems, is a cause of serious concern in developing countries. Detecting and dealing with energy thefts have become a challenging task for the utility companies. Electricity thefts impair the power supply quality, increase the load on generating stations and impact the tariff. This paper proposes methods for detection of electricity thefts based on compressed sensing and sparse representation techniques. Compressed sensing is a promising signal processing technique which is used to accurately reconstruct signals and information that are sparse, from small number of random measurements. Since electricity thefts are infrequent, the difference between power consumed actually and the power measured in the meters results in a set of equations which has sparse solutions. This sparse structure enables to detect electricity thefts with minimal number of sensors.
机译:电力盗窃是输配电系统中的主要非技术损失,在发展中国家引起了人们的严重关注。对于公用事业公司而言,检测和处理能源盗窃已成为一项具有挑战性的任务。窃电会损害电源质量,增加发电站的负荷并影响电价。本文提出了一种基于压缩感知和稀疏表示技术的窃电检测方法。压缩感测是一种有前途的信号处理技术,可用于从少量随机测量中准确地重建稀疏的信号和信息。由于不经常发生窃电事件,因此实际消耗的功率与电表中测得的功率之间的差会导致一组方程式稀疏。这种稀疏的结构可以用最少的传感器检测电盗窃事件。

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