Zhejiang University

Yuankui Wang

Xin Zhang

Hao Ma

Xueqi Liu

Fanfan Lin

Disclosed in the present invention is a graph theory-based method for locating an instability fault source in a direct-current microgrid. The method includes: collecting key electrical feature quantities through an instability fault feature collection and extraction link to accurately capture an instability oscillation phenomenon, and utilizing wavelet packet decomposition to construct fault feature vectors; then, according to the structure of the direct-current microgrid, constructing an undirected graph model G=(V, E, X), which lays a foundation for analysis; applying a graph convolutional neural network for deep learning and training to further improve the accuracy and efficiency of diagnosis; deploying the trained model in an actual system to effectively achieve accurate fault diagnosis and location of an instability source. Also provided in the present invention is a device for locating an instability fault source in a direct-current microgrid. The method provided by the present invention can significantly improve a maintenance level of the direct-current distribution network, and greatly improve a detection and adjustment ability of system operation stability through advanced automatic diagnosis technology.

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Hangzhou, China

Yuankui Wang