Distributed Estimation of Oscillations in Power Systems: An Extended Kalman Filtering Approach

被引：9
|
作者：
Yu, Zhe [1 ]
Shi, Di [1 ]
Wang, Zhiwei [1 ]
Zhang, Qibing [2 ]
Huang, Junhui [2 ]
Pan, Sen [3 ]
机构：
[1] GEIRI North Amer, San Jose, CA 95134 USA
[2] State Grid Jiangsu Elect Power Co, Nanjing 210024, Jiangsu, Peoples R China
[3] Global Energy Interconnect Res Inst, Nanjing 210024, Jiangsu, Peoples R China
来源：
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS | 2019年 / 5卷 / 02期
关键词：
Distributed estimation; extended Kalman filter; oscillation detection and estimation; PRONY ANALYSIS; ALGORITHM; COMPUTATION; PARAMETERS;
D O I：
10.17775/CSEEJPES.2017.00730
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
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.
引用
收藏
页码：181 / 189
页数：9
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