Energy and Power Engineering

Volume 9, Issue 4 (April 2017)

ISSN Print: 1949-243X   ISSN Online: 1947-3818

Google-based Impact Factor: 0.70  Citations  h5-index & Ranking

Fault Identification of Power Grid Based on Wide-Area Differential Current and K-Means Clustering

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DOI: 10.4236/epe.2017.94B003    2,267 Downloads   2,531 Views  
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ABSTRACT

A new method of fault domain identification is proposed based on K-means clustering analysis theories using the wide-area information of power grid. In the method, the node Intelligent Electronic Device (IED) associated domain is defined, and the relationship of positive sequence current fault component for the association domain boundaries is sought, then the conception of positive sequence fault component differential current for node IED association domains is introduced. The information of the positive sequence fault component differential current gathered by node IEDs is selected as the object of K-means clustering. The node IEDs of fault associated domains can be classified into one category, and the node IEDs of non-fault associated domains are classified into another category. With the fault area minimum principle, the group of node IEDs about fault associated domains can be obtained. The overlap of fault associated domains for different nodes is the fault area. A large number of simulations show that the algorithm proposed can identify fault domains with high accuracy and no influence by the operating mode of the system and topological changes.

Cite this paper

Wu, H. and Li, Q. (2017) Fault Identification of Power Grid Based on Wide-Area Differential Current and K-Means Clustering. Energy and Power Engineering, 9, 19-29. doi: 10.4236/epe.2017.94B003.

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