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Preprint . 2014
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arXiv.org e-Print Archive
Preprint . 2014
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https://dx.doi.org/10.48550/ar...
Article . 2014
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Power System Dynamic State Estimation by Unscented Kalman Filter with Guaranteed Positive Semidefinite State Covariance

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Jan 2014Embargo end date: 01 Jan 2014Publisher:arXiv
Authors: Qi, Junjian; Sun, Kai;

doi: 10.48550/arxiv.1405.6426

arXiv: http://arxiv.org/abs/1405.6426 , 1405.6426

Power System Dynamic State Estimation by Unscented Kalman Filter with Guaranteed Positive Semidefinite State Covariance

Abstract

In this paper an unscented Kalman filter with guaranteed positive semidefinite state covariance is proposed by calculating the nearest symmetric positive definite matrix in Frobenius norm and is applied to power system dynamic state estimation. The proposed method is tested on NPCC 48-machine 140-bus system and the results validate its effectiveness.

Submitted to IEEE Power Engineering Letters

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Keywords

FOS: Computer and information sciences, Optimization and Control (math.OC), Computer Science - Information Theory, Information Theory (cs.IT), FOS: Mathematics, Mathematics - Optimization and Control

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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