Frequency adaptive linear Kalman filter for fast and accurate estimation of grid voltage parameters

M. Reza, M. Ciobotaru, V. Agelidis
{"title":"Frequency adaptive linear Kalman filter for fast and accurate estimation of grid voltage parameters","authors":"M. Reza, M. Ciobotaru, V. Agelidis","doi":"10.1109/POWERCON.2012.6401446","DOIUrl":null,"url":null,"abstract":"This paper presents a comparative analysis of three different quadrature signal generators such as the frequency locked loop (FLL) based linear Kalman filter (LKF) (LKF-FLL), the second order generalized integrator (SOGI) and FLL based quadrature signal generator (QSG) (SOGI-FLL) and the extended Kalman filter (EKF). In the LKF-FLL technique, the FLL is integrated with the LKF, where the LKF tracks the orthogonal waveforms of the gird voltage fundamental component based on the fundamental frequency estimated by the FLL. The LKF-FLL technique provides better steady state results and also takes smaller convergence time during the transients as compared to the SOGI-FLL and the EKF techniques. Moreover, the LKF-FLL technique is less complex than the EKF. Synthetically generated grid voltage waveforms are used in MATLAB/Simulink to depict the superior performance of the LKF-FLL technique.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"26 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON.2012.6401446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

This paper presents a comparative analysis of three different quadrature signal generators such as the frequency locked loop (FLL) based linear Kalman filter (LKF) (LKF-FLL), the second order generalized integrator (SOGI) and FLL based quadrature signal generator (QSG) (SOGI-FLL) and the extended Kalman filter (EKF). In the LKF-FLL technique, the FLL is integrated with the LKF, where the LKF tracks the orthogonal waveforms of the gird voltage fundamental component based on the fundamental frequency estimated by the FLL. The LKF-FLL technique provides better steady state results and also takes smaller convergence time during the transients as compared to the SOGI-FLL and the EKF techniques. Moreover, the LKF-FLL technique is less complex than the EKF. Synthetically generated grid voltage waveforms are used in MATLAB/Simulink to depict the superior performance of the LKF-FLL technique.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
频率自适应线性卡尔曼滤波用于快速准确地估计电网电压参数
本文对基于锁频环(FLL)的线性卡尔曼滤波器(LKF) (LKF-FLL)、二阶广义积分器(SOGI)和基于锁频环(FLL)的正交信号发生器(QSG) (SOGI-FLL)和扩展卡尔曼滤波器(EKF)三种不同的正交信号发生器进行了比较分析。在LKF-FLL技术中,FLL与LKF相结合,其中LKF根据FLL估计的基频跟踪电网电压基频分量的正交波形。与SOGI-FLL和EKF技术相比,LKF-FLL技术提供了更好的稳态结果,并且在瞬态期间的收敛时间也更短。此外,LKF-FLL技术比EKF技术更简单。在MATLAB/Simulink中使用综合生成的电网电压波形来描述LKF-FLL技术的优越性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A study on global solar radiation forecasting models using meteorological data and their application to wide area forecast Adaptive Frequency Control for Hybrid Wind-Diesel power system using system estimator Smart grid standards for home and building automation Demand response plan considering available spinning reserve for system frequency restoration Economic evaluation of grid-connected solar PV production cost in New Zealand
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1