Increasing complexity associated with large-scale renewable resources and novel smart-grid technologies necessitates real-time monitoring and control. Our previous work applied the extended Kalman filter (EKF) with the use of phasor measurement data (PMU) for dynamic state estimation. However, high computation complexity creates significant challenges for real-time applications. In this paper, the problem of distributed dynamic state estimation is investigated. One domain decomposition method is proposed to utilize decentralized computing resources. The performance of distributed dynamic state estimation is tested on a 16-machine, 68-bus test system.
Revised: August 1, 2012 |
Published: August 4, 2011
Citation
Du P., Z. Huang, Y. Sun, R. Diao, K. Kalsi, K.K. Anderson, and Y. Li, et al. 2011.Distributed Dynamic State Estimation with Extended Kalman Filter. In 43rd North American Power Symposium (NAPS 2011), August 4-6, 2011, Boston, Massachusetts. Piscataway, New Jersey:Institute of Electrical and Electronics Engineers, Inc.PNNL-SA-79744.doi:10.1109/NAPS.2011.6024863