基于改进强跟踪无迹卡尔曼滤波的电力信号同步相量跟踪算法

doi:10.19595/j.cnki.1000-6753.tces.L90028

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Abstract All kinds of noises in the distribution network have a great impact on phasor measurement, so it is of great significance to study the synchronous phasor measurement algorithm which can reliably detect and quickly track the sudden change of power signal in the high noise environment to ensure the stability and reliability of the power network.An algorithm, adaptive strong tracking unscented Kalman filter based on suboptimal estimate of measurement error covariance (SEMEC-ASTUKF),for synchronous phasor measurement was proposed. An adaptive constant noise statistical estimator was proposed to improve the estimation accuracy of measured noise covariance.Based on the characteristics of power signal after mutation, the mutation detection algorithm and the fading factor sub-optimal estimation algorithm were constructed to improve the strong tracking unscented filter (STUKF) algorithm's weak of mutation detection ability and slow mutation tracking under high noise environment.The results show that the SEMEC-ASTUKF algorithm has higher measurement accuracy, better detection sensitivity and tracking speed for mutation.

Key words： Strongnoise strongtracking unscented Kalman filter adaptive constant noise statistical estimator fading factor

Received: 19 May 2020

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TM712

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	Niu Shengsuo
	Wang Chunxin
	Liang Zhirui
	Rao Yi
	Chen Zexiong

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Niu Shengsuo,Wang Chunxin,Liang Zhirui等. An Algorithm for Tracking Synchronous Phasor of Power Signals Based on Improved Strong Tracking Unscented Kalman Filter[J]. Transactions of China Electrotechnical Society, 2021, 36(11): 2255-2264.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L90028 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I11/2255

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