High-Quality Sample Generation for Power System Transient Stability Assessment Based on Data-Driven Methods
Deep learning technology is identified as a valid tool for transient stability assessment (TSA). Moreover, the superior performance of the TSA model depends on generously labeled samples. However, the power grid is dynamic, and some topologies or operation conditions change substantially. The tradit...
Saved in:
| Main Authors: | Baoqin Li, Pengfei Fan, Qixin Chen, Rong Li, Kaijun Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
China electric power research institute
2025-01-01
|
| Series: | CSEE Journal of Power and Energy Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10838237/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Assessment of Power System Transient Stability Based on Active Transfer Learning
by: Chenhao ZHAO, et al.
Published: (2025-01-01) -
Power System Transient Stability Assessment Based on Intelligent Enhanced Transient Energy Function Method
by: Tianxiao Mo, et al.
Published: (2024-11-01) -
Transient Stability Prediction of Power Systems Based on Deep Residual Network and Data Augmentation
by: Yanzhen ZHOU, et al.
Published: (2020-01-01) -
Stability Improvement of Grid-Connected DFIG Wind Farm With STATCOM Compensated Power Network Using RL-Based Coordinated Transient Controller
by: Muhammad Rasheed, et al.
Published: (2025-01-01) -
Analysis of power system transient stability with PSO-optimized distributed generation and HVDC transmission systems
by: Jiyeon Jang, et al.
Published: (2025-03-01)