An Algorithm for Tracking Synchronous Phasor of Power Signals Based on Improved Strong Tracking Unscented Kalman Filter
Niu Shengsuo1, Wang Chunxin1, Liang Zhirui1, Rao Yi2, Chen Zexiong2
1. College of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 China; 2. Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Guangzhou 510620 China
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.
牛胜锁, 王春鑫, 梁志瑞, 饶毅, 陈泽雄. 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[J]. 电工技术学报, 2021, 36(11): 2255-2264.
Niu Shengsuo, Wang Chunxin, Liang Zhirui, Rao Yi, Chen Zexiong. An Algorithm for Tracking Synchronous Phasor of Power Signals Based on Improved Strong Tracking Unscented Kalman Filter. Transactions of China Electrotechnical Society, 2021, 36(11): 2255-2264.
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