A Deep End-to-End Model for Transient Stability Assessment With PMU Data

A Deep End-to-End Model for Transient Stability Assessment With PMU Data

Accurate transient stability assessment (TSA) is a fundamental requirement for ensuring secure and stable operation of power systems. Tremendous efforts have been made to apply artificial intelligence approaches for TSA with phasor measurement unit data. However, many previous approaches may be fail...

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Bibliographic Details
Main Authors: Qiaomu Zhu, Jinfu Chen, Lin Zhu, Dongyuan Shi, Xiang Bai, Xianzhong Duan, Yilu Liu
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Deep learning
feature extraction
PMU data
stacked denoising autoencoder
transient stability assessment
Online Access:https://ieeexplore.ieee.org/document/8492415/

Internet

https://ieeexplore.ieee.org/document/8492415/

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