LSTM-CNN-Based Transient Stability Assessment-Reference-Cited by-同舟云学术

LSTM-CNN-Based Transient Stability Assessment

Published:2021-12-08 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Power System Technology (POWERCON)
language:
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Author:

Han Xiaoyan¹,Chen Zhen²,Wang Yucui³,Lai Xinyi³,Ding Lijie²,Wen Fushuan³

Affiliation:

1. State Grid Sichuan Electric Power Company,Chengdu,China

2. State Grid Sichuan Electric Power Company,Electric Power Research Institute,Chengdu,China

3. Zhejiang University,School of Electrical Engineering,Hangzhou,China

Funder

National Natural Science Foundation of China

Science and Technology Project of State Grid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9697403/9697404/09697781.pdf?arnumber=9697781

Reference24 articles.

1. Learning Deep Architectures for AI

2. A Method for Power System Transient Stability Assessment Based on Deep Belief Networks;zhu;Proceedings of the CSEE,2018

3. Transient Stability Assessment of Power System Based on Two-stage Ensemble Deep Belief Network;shao;Power System Technology,2020

4. Transient Stability Assessment for Power System Based on One-dimensional Convolutional Neural Network;gao;Automation of Electric Power Systems,2019

5. Power System Transient Stability Assessment Based on Comprehensiive Convolutional Neural Network Model and Steady-state Features;tian;Proceedings of the CSEE,2019

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1. Transfer Learning for Transient Stability Predictions in Modern Power Systems Under Enduring Topological Changes;IEEE Transactions on Automation Science and Engineering;2023