Transient Stability Prediction of Power Systems Based on Deep Residual Network and Data Augmentation

Transient Stability Prediction of Power Systems Based on Deep Residual Network and Data Augmentation

In traditional data-driven power system transient stability assessment methods, the impact of noise in the collected data and the information missing problems are rarely considered for the transient stability prediction. To deal with these problems, this paper presents a method for transient stabili...

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Bibliographic Details
Main Authors: Yanzhen ZHOU, Xianyu ZHA, Jian LAN, Qinglai GUO, Hongbin SUN, Feng XUE, Shengming WANG
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2020-01-01
Series:Zhongguo dianli
Subjects:
transient stability
deep learning
deep residual network
data augmentation
power system
noise
information missing
Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201912113
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https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201912113

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