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Risk Prediction Method of Low Frequency Oscillation in Maintenance Power Network Based on Long Short Term Memory Neural Network
Power Generation Technology Vol. 45, Issue 2, Pages: 353-362(2024)
Smart Grid|Updated：2025-06-15
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Risk Prediction Method of Low Frequency Oscillation in Maintenance Power Network Based on Long Short Term Memory Neural Network
- “In the field of power systems, experts have proposed a low-frequency oscillation risk prediction method for maintenance state power grids based on LSTM neural networks, providing a solution for evaluating the low-frequency oscillation risk of power grids.”
DOI：10.12096/j.2096-4528.pgt.22152
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Related Author
ZHOU Acheng
LIU Hanchen
LI Jianlin
CUI Sen
CHEN Laijun
XUE Sheng
DAI Linhao
LI Jinjian
Related Institution
College of Energy and Electrical Engineering, Qinghai University
Department of Electrical Engineering, Tsinghua University, Haidian District
School of Mechanical Engineering, Qinghai University
College of Electrical and Information Engineering, Lanzhou University of Technology
State Grid Jiangsu Electric Power Co., Ltd.
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