The PMU-Based Power System Dynamic State Estimation Using Extended Kalman Filter

DOI

10.2991/icmmct-16.2016.233How to use a DOI?

Keywords

PMU; Dynamic State Estimation; Extended Kalman Filter

Abstract

Dynamic state estimation of power system is a sophisticated problem since voltage and current phasors under dynamic conditions are nonlinear and hard to be obtained. This paper presents a new power system dynamic state estimation method using Extended Kalman Filter (EKF) based on Phasor Measurement Unit (PMU). EKF can be used to deal with nonlinear system. With the help of PMU which is the key unit of Wide Area Measurement Systems (WAMS), continuous time waveforms with high accuracy and synchronized time stamps can be estimated. In case study, the effectiveness of the proposed method has been evaluated by dynamic state estimation of 3-bus powers system in Matlab, and scenarios with different PMU placement are compared. The proposed method achieves high accuracy in all these scenarios.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xianing Jin
AU  - Guanqun Wang
AU  - Zhenyu Xue
AU  - Chongbo Sun
AU  - Yi Song
PY  - 2016/03
DA  - 2016/03
TI  - The PMU-Based Power System Dynamic State Estimation Using Extended Kalman Filter
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1184
EP  - 1189
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.233
DO  - 10.2991/icmmct-16.2016.233
ID  - Jin2016/03
ER  -