期刊
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
卷 65, 期 -, 页码 26-33出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2014.09.024
关键词
Dynamic state estimation; Unscented Kalman filter; Consensus algorithm; Multi-area power system
资金
- Fundamental Research Fund for the Central Universities [WH1114059]
- National Natural Science Foundation of China [61273073]
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.
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