文献类型：期刊文献

英文题名：Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems

作者：Qing, Xiangyun[1];Karimi, Hamid Reza[2];Niu, Yugang[1];Wang, Xingyu[1]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Univ Agder, Fac Sci & Engn, Dept Engn, N-4898 Grimstad, Norway

年份：2015

卷号：65

起止页码：26

外文期刊名：INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

收录：;EI(收录号：20144500172559);WOS:【SCI-EXPANDED(收录号:WOS:000346541900004)】；

基金：This work was supported by the Fundamental Research Fund for the Central Universities (No. WH1114059) and the National Natural Science Foundation of China (No. 61273073).

语种：英文

外文关键词：Dynamic state estimation; Unscented Kalman filter; Consensus algorithm; Multi-area power system

摘要：A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algorithm on the IEEE 14-bus and 118-bus systems. The low communication requirements and high estimation accuracy of the decentralized UKF make it an alternative solution to the multi-area power system dynamic state estimation. (C) 2014 Elsevier Ltd. All rights reserved.