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Use of data-mining for non-invasive signature recognition in micro-grids: A preliminary approach applied to residential areas with PV converters

机译:数据挖掘在微电网中的非侵入式签名识别中的应用:一种适用于带有光伏转换器的住宅区的初步方法

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The future of distribution networks tends more and more to include computational power, embedded intelligence and smart metering on the high voltage level as well as the low voltage micro-grids. Several hardware solutions were developed to implement the so-called smart grids with measurement devices delivering data about the state of networks on various levels. This work introduces the use of a specific electric signature based on harmonic response of power converters in order to be able to get information in a non-invasive manner. A simulated residential grid with several loads and PV converters has been run real-time with 1 μs sampled data, for being able to retrieve information through data mining methods.
机译:配电网络的未来越来越趋向于包括计算能力,嵌入式智能和高电压水平以及低压微电网上的智能计量。开发了几种硬件解决方案来实现所谓的智能电网,其中的测量设备可提供有关各个级别网络状态的数据。这项工作介绍了基于功率转换器的谐波响应的特定电子签名的使用,以便能够以非侵入性的方式获取信息。已使用1μs采样数据实时运行了具有多个负载和PV转换器的模拟住宅网格,以便能够通过数据挖掘方法检索信息。

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