Abstract This paper proposes a novel methodology to define fault current direction along the Distribution Feeder (DF) considering Distributed Generation (DG) integration. The proposed methodology is based on Empirical Decomposition (ED), Decision Trees (DT) and Support Vector Machine (SVM). Using ED, it is possible to determine different Principal Components (PCs) that are used are inputs in these DT and SVP classifiers. Assessment of methodology considering different faults, inception angles, fault distances, and others are carried out. Besides, the proposed methodology is tested successfully considering different distribution system topologies and by analyzing special features required by relay manufacturers. Test results highlight the efficiency of the methodology, which presents a concise design and a simple mathematical formulation in the time domain.

中文翻译：

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基于信号相关性和机器学习的分布式发电集成配电馈线无电压传感器的高速方向保护

摘要 本文提出了一种考虑分布式发电 (DG) 集成的新方法来定义沿配电馈线 (DF) 的故障电流方向。所提出的方法基于经验分解 (ED)、决策树 (DT) 和支持向量机 (SVM)。使用 ED，可以确定在这些 DT 和 SVP 分类器中用作输入的不同主成分 (PC)。进行了考虑不同断层、起始角、断层距离等的方法论评估。此外，考虑到不同的配电系统拓扑结构并通过分析继电器制造商所需的特殊功能，对所提出的方法进行了成功测试。测试结果突出了该方法的效率，