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基于正弦信号固有特征的故障选相研究 被引量:2

Study of fault-type identification using inherent characteristics of the sinusoidal signal
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摘要 为快速准确识别高压输电线路短路故障,提出一种故障检测与选相的新方法。基于正弦信号经矩阵变换时移不变的特性,应用4采样点短数据窗的矩阵行列式变换函数,动态滑动窗口进行短路故障检测。对采集的各相电流电压值经短时动态去噪后计算其矩阵变换函数K系数值,通过K值与阈值的比较识别故障类型。在Matlab/Simulink下搭建220 kV双端电源输电系统短路故障模型进行验证,结果表明,该方法能在不同条件下准确识别短路故障,具有较高的灵敏性、可靠性,理论上故障检测与选相不超过5 ms。 In order to identify the short-circuit fault of high-voltage transmission lines fast and accurately, a novel method for fault detection and phase selection is discussed. Based on shift invariant features of sinusoidal signals after matrix transformations, applying matrix transformation function with 4 sampling points ultra-short data window, the short-circuit fault is detected by dynamic sliding window. The sampling values of each phase current and voltage are used to calculate their K values after short-time dynamic denoising, through comparison of the K value and the threshold, the fault type is identified. A short-circuit fault model of 220 kV dual-source power transmission system is established in MATLAB/Simulink environment, simulation results show that the method has high sensitivity and reliability and it can accurately identify the short-circuit fault under different conditions, theoretically, the time of fault detection and phase selection does not exceed 5 ms.
出处 《电力系统保护与控制》 EI CSCD 北大核心 2013年第19期87-94,共8页 Power System Protection and Control
基金 四川省教育厅项目(12ZB131) "流体及动力机械"省部共建教育部重点实验室项目(SBZDPY-11-13 14) 四川省电力电子与电力传动重点学科(SZD0503)
关键词 输电线路 短路故障 故障识别 矩阵变换函数 短时动态去噪 transmission line short-circuit fault fault identification matrix transformation function short-time dynamic denoising
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