A hierarchical self-adaptive data-analytics method for real-time power system short-term voltage stability assessment
As one of the most complex and largest dynamic industrial systems, a modern power grid envisages the wide-area measurement protection and control (WAMPAC) system as the grid sensing backbone to enhance security, reliability, and resiliency. However, based on the massive wide-area measurement data, h...
Saved in:
Main Authors: | Zhang, Yuchen, Xu, Yan, Dong, Zhao Yang, Zhang, Rui |
---|---|
其他作者: | School of Electrical and Electronic Engineering |
格式: | Article |
語言: | English |
出版: |
2021
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/151001 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Nanyang Technological University |
語言: | English |
相似書籍
-
Real-time assessment of fault-induced delayed voltage recovery : a probabilistic self-adaptive data-driven method
由: Zhang, Yuchen, et al.
出版: (2020) -
A missing-data tolerant method for data-driven short-term voltage stability assessment of power systems
由: Zhang, Yuchen, et al.
出版: (2021) -
An ensemble approach for short-term load forecasting by extreme learning machine
由: Li, Song, et al.
出版: (2017) -
Robust ensemble data analytics for incomplete PMU measurements-based power system stability assessment
由: Zhang, Yuchen, et al.
出版: (2020) -
Ensemble learning of deep learning-based receiver for 5G communication system implementation
由: Xu, Ziang
出版: (2024)