Distributed estimation of oscillations in power systems: An extended Kalman filtering approach

Zhe Yu; Di Shi; Zhiwei Wang; Qibing Zhang; Junhui Huang; Sen Pan

doi:10.17775/CSEEJPES.2017.00730

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Distributed estimation of oscillations in power systems: An extended Kalman filtering approach

更新时间：2025-12-18

- Distributed estimation of oscillations in power systems: An extended Kalman filtering approach
- CSEE Journal of Power and Energy Systems Vol. 5, Issue 2, Pages: 181-189(2019)
- 作者机构：
  
  1. GEIRI North America,CA,San Jose,USA,95134
  2. State Grid Jiangsu Electric Power Company,Nanjing,China,210024
  3. Global Energy Interconnection Research Institute,Nanjing,China,210024
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2017.00730
  CLC：
- Published：2019
- 稿件说明：
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Zhe Yu, Di Shi, Zhiwei Wang, et al. Distributed estimation of oscillations in power systems: An extended Kalman filtering approach[J]. CSEE Journal of Power and Energy Systems, 2019, 5(2): 181-189.
DOI：

Zhe Yu, Di Shi, Zhiwei Wang, et al. Distributed estimation of oscillations in power systems: An extended Kalman filtering approach[J]. CSEE Journal of Power and Energy Systems, 2019, 5(2): 181-189. DOI： 10.17775/CSEEJPES.2017.00730.

摘要

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.

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