Robust Event Classification Using Imperfect Real-World PMU Data-Reference-Cited by-同舟云学术

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Robust Event Classification Using Imperfect Real-World PMU Data

Published:2023-05-01 Issue:9 Volume:10 Page:7429-7438
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Liu Yunchuan¹^ORCID,Yang Lei¹^ORCID,Ghasemkhani Amir²^ORCID,Livani Hanif³,Centeno Virgilio A.⁴,Chen Pin-Yu⁵^ORCID,Zhang Junshan⁶^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Nevada Reno, Reno, NV, USA

2. Department of Computer Science and Engineering, California State University San Bernardino, San Bernardino, CA, USA

3. Department of Electrical and Biomedical Engineering, University of Nevada Reno, Reno, NV, USA

4. Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

5. Trusted AI Group, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA

6. College of Engineering, University of California at Davis, Davis, CA, USA

Funder

Department of Energy National Energy Technology Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

https://ieeexplore.ieee.org/ielam/6488907/10106528/9780546-aam.pdf

Reference30 articles.

1. Preliminary work to classify the disturbance events recorded by phasor measurement units

2. Real-Time Event Identification Through Low-Dimensional Subspace Characterization of High-Dimensional Synchrophasor Data

3. Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning

4. Smart grid line event classification using supervised learning over PMU data streams

5. Application of Multisynchrosqueezing Transform for Subsynchronous Oscillation Detection Using PMU Data

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1. Grid-aware learning of characterized waveform measurements for power quality and transient events situational awareness;Electric Power Systems Research;2024-11

2. Robust Distributed Load Frequency Control for Multiarea Wind Energy-Dominated Microgrids Considering Phasor Measurement Unit Failures;IEEE Internet of Things Journal;2024-07-01

3. Event Detection and Classification Using Machine Learning Applied to PMU Data for the Western US Power System;2024 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA);2024-05-21

4. High impedance fault classification in microgrids using a transformer-based model with time series harmonic synchrophasors under data quality issues;Neural Computing and Applications;2024-05-02

5. Synchrophasor Technology Applications and Optimal Placement of Micro-Phasor Measurement Unit (μPMU): Part II;2024 28th International Electrical Power Distribution Conference (EPDC);2024-04-23

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