The proposed unsupervised event detection and clustering methods are applied to real-world micro-PMU data. Results show that they can outperform the prevalent ...
Jul 30, 2020 · We develop an unsupervised event detection method based on the concept of Generative Adversarial Networks (GAN). It works by training deep neural networks.
Sep 11, 2024 · It works by training deep neural networks that learn the characteristics of the normal trends in micro-PMU measurements; and accordingly detect ...
Unsupervised Event Detection, Clustering, and Use Case ...
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It works by training deep neural networks that learn the characteristics of the normal trends in micro-PMU measurements; and accordingly detect an event when ...
Jul 30, 2020 · An unsupervised event detection method based on the concept of Generative Adversarial Networks (GAN), which works by training deep neural ...
2016. Unsupervised event detection, clustering, and use case exposition in micro-pmu measurements. A Aligholian, A Shahsavari, EM Stewart, E Cortez, H ...
Dec 11, 2019 · 14 Citations · Unsupervised Event Detection, Clustering, and Use Case Exposition in Micro-PMU Measurements · Armin AligholianA. ShahsavariE.
Feb 15, 2022 · This work proposes a data-driven approach for event detection in microgrids using phasor measurements collected from distribution-level phasor measurement ...
Mohsenian-Rad, “Unsupervised event detection, clustering, and use case exposition in micro-PMU measurements,” IEEE Trans. on Smart. Grid, vol. 12, no. 4, pp ...
May 26, 2022 · The results from various case studies show that GraphPMU leads to significant improvements in the accuracy of event clustering, despite the ...