Power System Dynamic State Estimation by Unscented Kalman Filter with Guaranteed Positive Semidefinite State Covariance
Information Theory
2014-09-12 v3 math.IT
Optimization and Control
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.
Keywords
Cite
@article{arxiv.1405.6426,
title = {Power System Dynamic State Estimation by Unscented Kalman Filter with Guaranteed Positive Semidefinite State Covariance},
author = {Junjian Qi and Kai Sun},
journal= {arXiv preprint arXiv:1405.6426},
year = {2014}
}
Comments
Submitted to IEEE Power Engineering Letters