Distributed Estimation of Oscillations in Power Systems: an Extended Kalman Filtering Approach
Optimization and Control
2017-06-19 v1
Abstract
Online estimation of electromechanical oscillation parameters provides essential information to prevent system instability and blackout and helps to identify event categories and locations. We formulate the problem as a state space model and employ the extended Kalman filter to estimate oscillation frequencies and damping factors directly based on data from phasor measurement units. Due to considerations of communication burdens and privacy concerns, a fully distributed algorithm is proposed using diffusion extended Kalman filter. The effectiveness of proposed algorithms is confirmed by both simulated and real data collected during events in State Grid Jiangsu Electric Power Company.
Keywords
Cite
@article{arxiv.1706.05355,
title = {Distributed Estimation of Oscillations in Power Systems: an Extended Kalman Filtering Approach},
author = {Zhe Yu and Di Shi and Zhiwei Wang and Qibing Zhang and Junhui Huang and Sen Pan},
journal= {arXiv preprint arXiv:1706.05355},
year = {2017}
}