Generative Adversarial Networks-Based Synthetic PMU Data Creation for Improved Event Classification

Generative Adversarial Networks-Based Synthetic PMU Data Creation for Improved Event Classification

A two-stage machine learning-based approach for creating synthetic phasor measurement unit (PMU) data is proposed in this article. This approach leverages generative adversarial networks (GAN) in data generation and incorporates neural ordinary differential equation (Neural ODE) to guarantee underly...

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Bibliographic Details
Main Authors: Xiangtian Zheng, Bin Wang, Dileep Kalathil, Le Xie
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Event classification
phasor measurement unit
generative adversarial network
neural ODE
Online Access:https://ieeexplore.ieee.org/document/9361704/

Internet

https://ieeexplore.ieee.org/document/9361704/

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