Detection of Power Quality Disturbances Based on Residual Analysis Using Kalman Filter Based on Maximum Likelihood

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Xi, Yanhui*;Tang, Xin*;Li, Zewen;Cui, Yonglin;Zeng, Xiangjun

通讯作者：

Xi, Yanhui;Tang, Xin

作者机构：

[Tang, Xin; Xi, Yanhui; Tang, X; Cui, Yonglin; Li, Zewen; Zeng, Xiangjun] Changsha Univ Sci & Technol, Hunan Prov Higher Educ Key Lab Power Syst Safety, Changsha, Hunan, Peoples R China.

通讯机构：

[Xi, YH; Tang, X] C

Changsha Univ Sci & Technol, Hunan Prov Higher Educ Key Lab Power Syst Safety, Changsha, Hunan, Peoples R China.

语种：

英文

关键词：

power quality disturbances;state estimation;Kalman filter;estimated residuals;detection;the maximum likelihood

期刊：

Electric Power Components and Systems

ISSN：

1532-5008

年：

2019

卷：

期：

9-10

页码：

861-875

DOI：

10.1080/15325008.2019.1627607

基金类别：

National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [51507015, 51577014, 51577013, 51877012]; Natural Science Foundation of Hunan ProvinceNatural Science Foundation of Hunan Province [2018JJ2439]; Education Bureau of Hunan Province, China [18B130]

机构署名：

本校为第一且通讯机构

院系归属：

电气与信息工程学院

摘要：

This paper presents the estimated residuals for the detection of power quality (PQ) disturbances using Kalman filter (KF) based on the maximum likelihood (KF-ML), which uses the ML method to adaptively optimize the error covariance matrices and the initial conditions as the parameters. Aiming at the sensitiveness to noise, residuals between the observed values and the estimated values by the KF-ML are proposed to detect the disturbances, and the estimated residuals exhibit mutation at the starting point and the ending point of disturbances. Thu...

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Detection of Power Quality Disturbances Based on Residual Analysis Using Kalman Filter Based on Maximum Likelihood

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