基于鲁棒容积卡尔曼滤波器的发电机动态状态估计

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Abstract Phasor measurement unit (PMU) can measure the rotor angle of synchronous machine in power system dynamic process. However, the bad data may decrease the accuracy of state estimations, even lead to the failure of the estimator. Based on the robust cubature Kalman filter (CKF), a novel dynamic state estimator for synchronous machine in the electromechanical transient process is proposed. A time-varying multi-dimensional scale factor is introduced into CKF. The PMU measure- ment covariance can be adjusted according to the innovation. As a result, the PMU measurements will correct the state predictions precisely. The formulation of the scale factor is clarified, and the method for dealing with the problem of the gain matrix singularity is addressed. The detailed process of dynamic state estimation based on robust CKF is given. The simulation results show that the method can prevent the influence of bad data on the precision of the dynamic state estimation.

Key words： Electromechanical transient process dynamic state estimator cubature Kalman filter robustness

Published: 03 March 2016

PACS:

TM711

Fund:国家重点基础研究发展计划（973计划）（2012CB215206）,国家自然科学基金（51222703）,高等学校博士学科点专项科研基金（20120036110009）和“111”计划（B08013）资助项目

Corresponding Authors: 毕天姝女,1973年生,教授,博士生导师,研究方向为电力系统保护与控制、WAMS应用及故障诊断。E-mail: tsbi@ncepu.edu.cn

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	Bi Tianshu
	Chen Liang
	Xue Ancheng
	Yang Qixun

Cite this article:

Bi Tianshu,Chen Liang,Xue Ancheng等. Dynamic State Estimator for Synchronous Machines Based on Robust Cubature Kalman Filter[J]. Transactions of China Electrotechnical Society, 2016, 31(4): 163-169.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I4/163

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