微电网窃电检测

A. R. Devidas, M. Ramesh
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引用次数: 10

摘要

在印度等大多数发展中国家,电力盗窃占GDP的1.5%。因此,侦查发展中国家的电力盗窃行为是非常必要的。在本文中,我们提出了一种基于无线网络的窃电检测基础设施,以满足微电网的其他功能需求,如可再生能源集成、自动抄表等。本文提出的窃电检测算法(PTDA)适用于微电网基础设施的分布式智能设备中进行窃电检测。智能设备与PTDA在微电网基础设施中的协同作用,不仅可以实现窃电检测,还可以实现窃电在微电网中的定位。PTDA增加了1)通信成本2)智能设备的能耗3)数据包延迟,如果任何关键数据与微电网中的电力盗窃数据相关联。为了解决这些问题,我们提出了EPTDNA (Efficient Power Theft Data Networking Algorithm)算法,该算法利用窃电检测的频率和窃电的平均功耗来实现窃电的高效路由。本文给出的性能分析和结果显示了EPTDNA如何解决PTDA的主要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power theft detection in microgrids
Theft of electricity amounts to 1.5% GDP, of most of the developing nations like India. Hence there is a great need to detect power thefts in developing nations. In this paper, we have proposed a wireless network based infrastructure for power theft detection which caters to other functional requirements of the microgrid such as renewable energy integration, automatic meter reading etc. Algorithm for power theft detection (PTDA) which is proposed in this paper, works in the distributed intelligent devices of the microgrid infrastructure for power theft detection. The coordinated action of intelligent devices with PTDA in the microgrid infrastructure enables not only the detection of power theft, but the localization of power theft in the micro-grid. PTDA increases the 1) cost of communication 2) energy consumption of intelligent devices 3) packet latency, if any critical data is piggy backed with power theft data in micro-grid. To solve these issues, we have proposed EPTDNA (Efficient Power Theft Data Networking Algorithm) which uses the frequency of power theft detection and average power draw for power theft, for the efficient routing of power theft. The performance analysis and results given in this paper shows how EPTDNA solves the major issues with PTDA.
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