Spatio-Temporal Frequency Domain Analysis of PMU Data for Unsupervised Event Detection

被引:0
|
作者
Senaratne, Dilan [1 ]
Kim, Jinsub [1 ]
Cotilla-Sanchez, Eduardo [1 ]
机构
[1] Oregon State Univ, Sch Elect Engn & Comp Sci, Corvallis, OR 97331 USA
来源
2021 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT) | 2021年
关键词
Phasor measurement unit; short time Fourier transform; convolutive dictionary model;
D O I
10.1109/ISGT49243.2021.9372192
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We consider the unsupervised detection of potter system events based on PMU measurements. We first present a convolutive dictionary model as a generative model for the short time Fourier transform (STFTs) of PMU data streams from multiple PMUs in the pmsence of a p system everit. In the presence of an event, the STFTs from different PMUs display a common two-dimensional event signature at the event time with its magnitude le aryiag across PMUs, thus lye develop a coin Intim dictionary model to capture this unique spatio-temporal correlation. We leverage this convolutive dictionary model to formulate a bitiaq hypothesis testing for event detection and implement a generalized likelihood ratio test to perform unsupervised event detection. The efficacy, of the proposed detector is demonstrated using the experiments based on real life Phil" data collected from a US Interconnection.
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页数:5
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