基于后向预测Prony算法的超高压输电线路故障选相方案

EHV transmission line faulty phase selection scheme based on backward Prony algorithm

基于分布参数的超高压输电线路故障暂态信号成分的分析表明,故障后高频暂态电流信号的幅值和频率特征能够可靠区分各种故障类型。据此提出了一种基于故障后高频暂态电流信号的故障选相方案。方案中后向预测Prony算法和QR分解技术的使用,使电流暂态信号中高频成分特征的提取更加准确、快速。大量ATP仿真分析结果表明,该故障选相方案能够快速、准确地识别各种故障类型,且不受过渡电阻、故障初相角和负荷电流等故障条件的影响。

Component analysis of EHV transmission line fault transient signals based on distributed parameter shows that the amplitude and the frequency of high frequency transient current signals after fault can reliably distinguish various fault types. So a faulty phase selection scheme based on high frequency transient current signals aRer fault is proposed. In this scheme, backward Porny algorithm and QR decomposition are employed, which makes the extraction of HF component more accurate and fast. A large number of ATP simulation results show that the proposed scheme can distinguish different fault types fast and correctly and it is not affected by transition resistances, inception angles, and load current.