融合小波面积矩阵和GRA的矿井电网故障选线方法

A fault line selection method for mine power network incorporating wavelet decomposition waveform area matrix and GRA

  • 摘要: 针对现有矿井高压电网故障选线方法存在的故障特征利用不充分、判据单一易误判等问题,提出融合小波分解波形面积矩阵和灰色关联度分析的矿井电网故障选线方法。首先,对各线路暂态零序电流进行coif5小波分解,构建其重构系数的面积矩阵,剔除面积矩阵中低频带与高频带分量,并通过设定的选线裕度公式得到选线特征尺度和初次选线结果;其次,利用该选线特征尺度下的各线路零序电流分量构建灰色关联度矩阵,通过设定的选线裕度公式得到再次选线结果;最后,根据等权重投票方法得出最终选线结果。通过大量仿真试验验证所提方法的有效性。该选线方法准确率高、可靠性好,并对故障初相角、过渡电阻、故障发生距离以及噪声干扰等因素均具有较强适应性。

     

    Abstract: This study proposes a fault line selection method for mine power network based on wavelet decomposition waveform area matrix and grey-relational analysis (GRA) to address the insufficient utilization of fault characteristics misjudgment based on single criterion in the existing fault line selection methods for mine high-voltage power network. Specifically, the transient zero-sequence current of each line was decomposed by coif5 wavelet and the reconstruction coefficient area matrix was constructed. The low-frequency band and high-frequency band components in the area matrix were eliminated, and the characteristic scale and the preliminary result of line selection were obtained by the set line selection margin formula; the grey correlation matrix was constructed by using the zero-sequence current component of each line under the characteristic scale of line selection, and the result of line selection was again obtained by setting the line selection margin formula; the final line selection result was obtained according to equal weight voting. The proposed algorithm was verified by various simulation experiments. Results show that the line selection algorithm exhibits high accuracy and high reliability, and shows strong adaptability to different fault initial phase angles, different transition resistances, different fault occurrence distances and noise interference.

     

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