A super-resolution perception-based incremental learning approach for power system voltage stability assessment with incomplete PMU measurements
This paper develops a fully data-driven, missing- data tolerant method for post-fault short-term voltage stability (STVS) assessment of power systems against the incomplete PMU measurements. The super-resolution perception (SRP), based on a deep residual learning convolutional neural network, is emp...
Main Authors: | Ren, Chao, Xu, Yan, Zhao, Junhua, Zhang, Rui, Wan, Tong |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/165110 |
Similar Items
-
A Convolutional Neural Network-Based Broad Incremental Learning Filter for Attenuating Physiological Tremors in Telerobot Systems
by: Guanyu Lai, et al.
Published: (2023-01-01) -
Adaptive Threshold Hierarchical Incremental Learning Method
by: Xingyu Li, et al.
Published: (2023-01-01) -
Incremental approximation computation in incomplete ordered decision systems
by: Guanglei Gou, et al.
Published: (2017-01-01) -
An Incremental Broad-Learning-System-Based Approach for Tremor Attenuation for Robot Tele-Operation
by: Guanyu Lai, et al.
Published: (2023-06-01) -
Robust ensemble data analytics for incomplete PMU measurements-based power system stability assessment
by: Zhang, Yuchen, et al.
Published: (2020)