The PMU-Based Power System Dynamic State Estimation Using Extended Kalman Filter
- 10.2991/icmmct-16.2016.233How to use a DOI?
- PMU; Dynamic State Estimation; Extended Kalman Filter
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.
- © 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/).
Cite this article
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 -