arrow
返回

Dynamic Synchrophasor Estimation by Extended Kalman Filter

delete2020-07-01
delete18
PRE
AI
R
Roberto Ferrero *
P
Paolo Attilio Pegoraro
S
Sergio Toscani
DOI:10.1109/TIM.2019.2955797delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Fast synchronized measurements of the phasor, frequency, and rate of change of frequency are expected to be very important for the automated control actions in the smart grid context. In this regard, measurement latency must be kept as short as possible for an effective control implementation when networks characterized by extremely fast dynamics are concerned. Kalman filter (KF)-based estimation algorithms appear to be attractive in this context; however, the conventional implementations suffer from significant limitations in their ability to deal with different types of dynamic conditions due to approximations in the model and in the associated uncertainty. This article proposes an innovative solution, based on an extended KF algorithm using a Taylor model, which is shown to provide improved tracking ability in a vast range of dynamic conditions. A novel element in the proposed technique is the representation of model uncertainty, which takes into account the intrinsic correlation among errors that appear in the state-space description under dynamic conditions. A compatibility check between the forecast and measurement result is also introduced as an effective and metrologically sound approach to detect large unexpected changes in the tracked parameters in order to achieve a fast response of the algorithm also under those conditions. The performance of the algorithm is thoroughly investigated by means of simulation to demonstrate the significant improvement compared to other KF solutions in some conditions of practical relevance.
Keyword:
Phasor measurement units
Frequency measurement
Harmonic analysis
Heuristic algorithms
Kalman filters
Power system dynamics
Mathematical model
Correlation
frequency estimation
Kalman filters (KFs)
measurement uncertainty
phasor measurement units (PMUs)
power system harmonics
power system measurements
voltage measurement
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Instrumentation and Measurement 封面图
IEEE Transactions on Instrumentation and Measurement
IF:
5.9
论文数:
2.0W
被引数:
5.8W

机构

P
Polytechnic University of Milan
学者数:
2.0W
论文数: 1.8W
被引数: 24
U
University of Liverpool
学者数:
2.8W
论文数: 2.5W
被引数: 3.5W
U
university of cagliari
学者数:
1.2W
论文数: 9.7K
被引数: 9
学者 查看更多机构
引用论文

引用论文

err分享
err收藏
err分享
err收藏
Compressive Sensing of a Taylor-Fourier Multifrequency Model for Synchrophasor Estimation
err2015-12-01
err126
errOAAI
errBertocco, Matteo; Frigo, Guglielmo; Narduzzi, Claudio; Muscas, Carlo; Pegoraro, Paolo Attilio
err分享
err收藏
A Dynamic Synchrophasor Estimation Algorithm for Online Application
err2010-04-01
err152
PREAI
errMai, R. K.; He, Z. Y.; Fu, L.; Kirby, B.; Bo, Z. Q.
err分享
err收藏
Dynamic Harmonic Analysis Through Taylor-Fourier Transform
err2011-03-01
err142
PREAI
errAngel Platas-Garza, Miguel; Antonio de la O Serna, Jose
err分享
err收藏
err2000-01-01
err0
PREAI
errVladimir Druskin; Leonid Knizhnerman
err分享
err收藏
学者 查看更多内容