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A Super-resolution Perception-based Incremental Learning Approach for Power System Voltage Stability Assessment with Incomplete PMU Measurements

Chao Ren Yan Xu Junhua Zhao Rui Zhang Tong Wan

中国电机工程学会电力与能源系统学报（英文版）2022，Vol.8Issue(1)：76-85,10.

中国电机工程学会电力与能源系统学报（英文版）2022，Vol.8Issue(1)：76-85,10.DOI:10.17775/CSEEJPES.2020.05930

A Super-resolution Perception-based Incremental Learning Approach for Power System Voltage Stability Assessment with Incomplete PMU Measurements

Chao Ren ¹Yan Xu ²Junhua Zhao ³Rui Zhang ⁴Tong Wan⁵

作者信息

1. Interdisciplinary Graduate School,Nanyang Technolog-ical University,Singapore
2. School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore
3. School of Science and Engineering,The Chinese University of Hong Kong (Shenzhen),China
4. Changsha University of Science and Technology,Changsha 410114,China
5. School of Electrical and Information Engineering,University of Sydney,Sydney,Australia
折叠

摘要

关键词

Data-driven/deep residual convolutional neural network/incremental broad learning/short-term voltage stability/super-resolution perception

Key words

Data-driven/deep residual convolutional neural network/incremental broad learning/short-term voltage stability/super-resolution perception

引用本文复制引用

Chao Ren,Yan Xu,Junhua Zhao,Rui Zhang,Tong Wan..A Super-resolution Perception-based Incremental Learning Approach for Power System Voltage Stability Assessment with Incomplete PMU Measurements[J].中国电机工程学会电力与能源系统学报（英文版）,2022,8(1):76-85,10.

基金项目

The work was supported in part by National Natural Science Foundation of China (51807009,71931003,72061147004). （51807009,71931003,72061147004）

中国电机工程学会电力与能源系统学报（英文版）

OACSCDCSTPCDEISCI

ISSN：2096-0042

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