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Source Authentication of Distribution Synchrophasors for Cybersecurity of Microgrids

机译:用于微普林网络安全的分布同步素的源认证

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摘要

This letter proposes a hybrid approach combining Self-Adaptive Mathematical Morphology (SAMM) and Time-Frequency (TF) techniques to authenticate the source information of Distribution Synchrophasors (DS) within near-range locations. The SAMM can adaptively regulate the synchrophasors variations which are representatives of local environmental characteristics. Subsequently, TF mapping is employed to extract informative signatures from the regulated synchrophasors variation. Finally, Random Forest Classification (RFC) is used to correlate the extracted signatures with the source information based on the derived TF mapping. Experiment results using DS collected at multiple small geographical scales validated the proposed methodology.
机译:这封信提出了一种混合方法,组合自适应数学形态(SAMM)和时频(TF)技术来验证近范围位置内分布同步素(DS)的源信息。 SAMM可以自适应地调节局部环境特征代表的同步素变异。 随后,采用TF映射来从调节的同步素变异中提取信息性签名。 最后,随机森林分类(RFC)用于基于派生的TF映射将提取的签名与源信息相关联。 使用以多个小地理尺度收集的DS的实验结果验证了所提出的方法。

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