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Computer Science > Information Theory

arXiv:1405.6426 (cs)
[Submitted on 25 May 2014 (v1), last revised 11 Sep 2014 (this version, v3)]

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

Authors:Junjian Qi, Kai Sun
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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.
Comments: Submitted to IEEE Power Engineering Letters
Subjects: Information Theory (cs.IT); Optimization and Control (math.OC)
Cite as: arXiv:1405.6426 [cs.IT]
  (or arXiv:1405.6426v3 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.1405.6426

Submission history

From: Junjian Qi [view email]
[v1] Sun, 25 May 2014 20:22:25 UTC (13 KB)
[v2] Wed, 10 Sep 2014 03:15:41 UTC (13 KB)
[v3] Thu, 11 Sep 2014 14:37:57 UTC (13 KB)
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