Event Detection and Classification Using Machine Learning Applied to PMU Data for the Western US Power System-Reference-Cited by-同舟云学术

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Event Detection and Classification Using Machine Learning Applied to PMU Data for the Western US Power System

Published:2024-05-21 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)
language:
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Author:

Yin Tianzhixi¹,Wulff Shaun S.²,Pierre John W.³,Amidan Brett G.⁴

Affiliation:

1. Pacific Northwest National Laboratory,AI & Data Analytics,Richland,WA,USA

2. University of Wyoming,Department of Mathematics and Statistics,Laramie,WY,USA

3. University of Wyoming,Department of Electrical and Computer Engineering,Laramie,WY,USA

4. Brigham Young University-Idaho,Department of Mathematics,Rexburg,ID,USA

Funder

Office of Science

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10571383/10571396/10571471.pdf?arnumber=10571471

Reference33 articles.

1. Synchrophasor-based data mining for power system fault analysis

2. Initial investigation of data mining applications in event classification and location identification using simulated data from MinniWECC

3. A real-time hierarchical framework for fault detection, classification, and location in power systems using PMUs data and deep learning

4. Deep-Learning Based Power System Events Detection Technology Using Spatio-Temporal and Frequency Information

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