Enhanced Denoising Autoencoder-aided Bad Data Filtering for Synchrophasor-based State Estimation  

作　　者：Guanyu Tian Yingzhong Gu Zhe Yu Qibing Zhang Di Shi Qun Zhou Zhiwei Wang 

机构地区：[1]GEIRI North America,San Jose,CA 95134 USA [2]GEIRI North America,San Jose,CA 95134 USA on leave from Department of Electrical and Computer Engineering,University of Central Florida,Orlando,FL 32816 USA [3]Grid Dispatch Center,State Grid Jiangsu Electric Power Company Ltd.,Nanjing 210024,China [4]Department of Electrical and Computer Engineering,University of Central Florida,Orlando,FL 32816 USA

出　　处：《CSEE Journal of Power and Energy Systems》2022年第2期640-651,共12页中国电机工程学会电力与能源系统学报（英文）

基　　金：This work was supported by SGCC Science and Technology Program under project“AI-based oscillation detection and control”(SGJS0000DKJS1801231)。

摘　　要：Due to its high accuracy and ease of calculation,synchrophasor-based linear state estimation(LSE)has attracted a lot of attention in the last decade and has formed the cornerstone of many wide area monitor system(WAMS)applications.However,an increasing number of data quality concerns have been reported,among which bad data can significantly undermine the performance of LSE and many other WAMS applications it supports.Bad data filtering can be difficult in practice due to a variety of issues such as limited processing time,non-uniform and changing patterns,and etc.To pre-process phasor measurement unit(PMU)measurements for LSE,we propose an improved denoising autoencoder(DA)-aided bad data filtering strategy in this paper.Bad data is first identified by the classifier module of the proposed DA and then recovered by the autoencoder module.Two characteristics distinguish the proposed methodology:1)The approach is lightweight and can be implemented at individual PMU level to achieve maximum parallelism and high efficiency,making it suited for real-time processing;2)the system not only identifies bad data but also recovers it,especially for critical measurements.We use numerical experiments employing both simulated and real-world phasor data to validate and illustrate the effectiveness of the proposed method.

关 键 词：Autoencoder bad data processing linear state estimation PMU 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]