文献类型：期刊文献

英文题名：Extended set-membership filter for power system dynamic state estimation

作者：Qing, Xiangyun[1];Yang, Fuwen[1];Wang, Xingyu[1]

机构：[1]E China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China

年份：2013

卷号：99

起止页码：56

外文期刊名：ELECTRIC POWER SYSTEMS RESEARCH

收录：;EI(收录号：20131116123664);WOS:【SCI-EXPANDED(收录号:WOS:000317707300009)】；

基金：The authors would like to thank the editor and anonymous referees for their valuable comments. This work was supported by the Fundamental Research Funds for the Central Universities (Nos. WH1114059 and WJ0913001), the National Natural Science Foundation of China (Nos. 61074113 and 61174064), and the National Program on Key Basic Research Project (No. 2012CB720502).

语种：英文

外文关键词：Nonlinear filter; Dynamic state estimation; Unscented Kalman filter; Single machine infinite bus; Set-membership filter

摘要：A new method for power system dynamic state estimation is presented. It is based on the application of the extended set-membership filter (ESMF). The ESMF provides an on-line nonlinear guaranteed estimation that assumes that noise sources are unknown but bounded, rather than stochastic as in probabilistic estimation algorithms such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). Thus, the ESMF provides 100% confidence to the estimated states for the safety and reliability of power systems. In this paper, the ESMF is derived and demonstrated by using two different single machine infinite bus (SMIB) systems. The performance of the ESMF is compared with the classical UKF by using one SMIB system modeled as a second-order nonlinear dynamic equation. The feasibility of the ESMF method with unknown inputs is also presented on the other SMIB system, in which the exciter output voltage may be unavailable but bounded. The ESMF method is also tested on a multi-machine system model to demonstrate its effectiveness. (C) 2013 Elsevier B.V. All rights reserved.