Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flyin...Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flying plot) caused by sampling device itself has brought tremendous pressure to the power system. The traditional flying plot detection algorithm has plenty of defects, such as low pertinence, low sensitivity and long sampling period. This paper proposes a new algorithm to identify flying plot by analyzing the wave form characteristics of sampling data. The traditional waveform recognition methods are combined in this algorithm. It has the concept of standard wave window and can distinguish flying plot in a short time. In addition, sine recovery algorithm is used to recover the flying plot. This paper uses PSCAD software to verify the validity of this algorithm. Simulation results show that the proposed method has high reliability.展开更多
针对风电场送出线路纵联保护在数据延时传输及异常采样数据下保护性能不佳的问题,提出了基于正序阻抗幅值比的纵联保护。通过分析风电系统送出线路发生区内外故障时正序阻抗幅值特征,得出区内外故障下双端正序阻抗幅值差异比特征不同。...针对风电场送出线路纵联保护在数据延时传输及异常采样数据下保护性能不佳的问题,提出了基于正序阻抗幅值比的纵联保护。通过分析风电系统送出线路发生区内外故障时正序阻抗幅值特征,得出区内外故障下双端正序阻抗幅值差异比特征不同。引入综合层次聚类(balanced iterative reducing and clustering using hierarchies,BIRCH)方法剔除正序阻抗幅值序列中异常采样数据,形成不含异常采样数据的故障时间序列聚类特征,并结合双端正序阻抗幅值差异比特征,构造不受数据延时传输影响的纵联保护判据。仿真结果表明,所提出的纵联保护不受系统运行工况、故障类型、数据延时传输及异常采样数据的影响。在过渡电阻达到150Ω时,所提出的纵联保护仍能正确判别故障方向,具有较强的抗噪性能,适用于含风电接入的弱馈型电力系统。展开更多
文摘Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flying plot) caused by sampling device itself has brought tremendous pressure to the power system. The traditional flying plot detection algorithm has plenty of defects, such as low pertinence, low sensitivity and long sampling period. This paper proposes a new algorithm to identify flying plot by analyzing the wave form characteristics of sampling data. The traditional waveform recognition methods are combined in this algorithm. It has the concept of standard wave window and can distinguish flying plot in a short time. In addition, sine recovery algorithm is used to recover the flying plot. This paper uses PSCAD software to verify the validity of this algorithm. Simulation results show that the proposed method has high reliability.
文摘针对风电场送出线路纵联保护在数据延时传输及异常采样数据下保护性能不佳的问题,提出了基于正序阻抗幅值比的纵联保护。通过分析风电系统送出线路发生区内外故障时正序阻抗幅值特征,得出区内外故障下双端正序阻抗幅值差异比特征不同。引入综合层次聚类(balanced iterative reducing and clustering using hierarchies,BIRCH)方法剔除正序阻抗幅值序列中异常采样数据,形成不含异常采样数据的故障时间序列聚类特征,并结合双端正序阻抗幅值差异比特征,构造不受数据延时传输影响的纵联保护判据。仿真结果表明,所提出的纵联保护不受系统运行工况、故障类型、数据延时传输及异常采样数据的影响。在过渡电阻达到150Ω时,所提出的纵联保护仍能正确判别故障方向,具有较强的抗噪性能,适用于含风电接入的弱馈型电力系统。
