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Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability

Ying Wang Chao Lu Xinran Zhang

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(3)：P.1064-1074,11.

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(3)：P.1064-1074,11.DOI:10.17775/CSEEJPES.2021.02580

Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability

Ying Wang ¹Chao Lu ²Xinran Zhang³

作者信息

1. School of Technology,Beijing Forestry University,Beijing 100083,China IEEE
2. State Key Laboratory of Control and Simulation of Power System and Generation Equipment,Tsinghua University,Beijing 100084,China IEEE
3. School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,China IEEE
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摘要

关键词

Ambient signal/CNN/field PMU data/load model parameter selection/short-term voltage stability

分类

信息技术与安全科学

引用本文复制引用

Ying Wang,Chao Lu,Xinran Zhang..Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability[J].CSEE Journal of Power and Energy Systems,2024,10(3):P.1064-1074,11.

基金项目

supported by the National Natural Science Foundation of China(U2066601,U1766214). （U2066601,U1766214）

CSEE Journal of Power and Energy Systems

OACSTPCDEI

ISSN：2096-0042

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