EKPF-Based Dynamic State Estimation of Electromechanical Transient Process

doi:10.11930/j.issn.10.11930.2015.11.94

Abstract

Abstract: A dynamic state estimation model(DSE) is built according to the dynamic characteristics of generator rotor during electromechanical transient process.Considering the fact that the Extended Kalman Filter (EKF) has poor tracking accuracy and even filter divergence because of the first-order linearization, a transient process dynamic state estimator is proposed in this paper, which combines the Particle Filter (PF) with the choosing rough sampling strategies to prevent sample degradation. Finally, the EKF-based dynamic state estimation, unscented Kalman filter(UKF) and EKPF are achieved respectively on the three-machine nine-bus system of American West Grid (WSCC). Simulation has proved the effectiveness of the EKPF algorithm, and that the filtering performance during electromechanical transient process is obviously superior to the other two methods.

Key words: Extended Kalman Particle Filter (EKPF), sample degradation, electromechanical transient process, resampling strategy

CLC Number:

TM711

YANG Zhenrui, GUI Jianzhong, SHAO Shuai, ZHAO Xiang, ZHENG Cunlong. EKPF-Based Dynamic State Estimation of Electromechanical Transient Process[J]. journal1, 2015, 48(11): 94-98.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.10.11930.2015.11.94

https://www.electricpower.com.cn/EN/Y2015/V48/I11/94

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