Traveling Wave Based Fault Location for Complex Network Topologies

ECS-9821090 Abur该项目研究了根据记录的故障暂态确定电力系统故障的准确位置的问题。 利用电力系统故障产生的行波作为确定故障位置的手段的潜力早已被认识到。 然而，缺乏合适的技术工具，高带宽监测的瞬变以及现有的基于傅立叶的信号处理方法在定位信号的突变的局限性，阻碍了全面的行波故障定位方法的努力，到目前为止，本项目的重点是使用离散小波变换在处理行波沿着故障输电线路。 利用小波变换在低尺度下以高时间分辨率捕获故障暂态的能力，开发了故障定位算法。 该算法背后的基本思想是捕获故障期间三相瞬态信号的模态分量的传播时间，因为它们在故障点和进行记录的线路端子之间传播。 然后，基于对被监测线路的各种模式的行进速度的了解，该信息可以被转换为等效距离。 该项目研究的行为行波为基础的方法的性能困难，但常见的网络拓扑结构，如相互耦合的线路，线路与串联补偿电容器，并联线路与环路流量等的小波变换的有效性和计算效率也仔细检查的最佳选择的母小波，尺度的数量，和模态信号进行处理。 开发的方法和相关的算法进行了严格评估的基础上，数字仿真的实际故障瞬变过程中使用的电力系统组件的详细models.The项目的结果预计将启动一个新的方式处理故障瞬变过程，使用在其频谱的较高频率端的信息，而不是目前使用的大多数技术。 这些结果可以潜在地用于相关的应用，如谐波监测，检测和表征的干扰，配电系统故障监测和电力变压器的早期故障检测。

ECS-9821090AburThis project investigates the problem of determining the exact location of power system faults based on the recorded fault transients. The potential of using traveling waves created by power system faults, as a means of determining the location of faults has long been recognized. However, lack of suitable technological tools for high bandwidth monitoring of transients as well as the limitations of existing Fourier based signal processing methods in localizing abrupt changes in signals, have discouraged the efforts of developing comprehensive traveling wave based fault location methods so far.This project focuses on the use of the Discrete Wavelet Transform in processing the traveling waves along the faulted transmission lines. The ability of the Wavelet Transform to capture the fault transients with a high time resolution in lower scales, is exploited in order to develop a fault location algorithm. Essential idea behind the algorithm is to capture the travel time of the modal components of the three phase transient signals during the fault, as they travel between the fault point and the line terminal at which the recording is done. This information can then be translated into an equivalent distance, based on the knowledge of the travel velocities of various modes for the monitored line. The project studies the behavior of the traveling wave based methods' performance under difficult yet common network topologies, such as mutually coupled lines, lines with series compensation capacitors, parallel lines with loop flows, etc. The effectiveness and computational efficiency of the Wavelet Transform is also carefully examined in terms of the optimal choice of the mother wavelet, number of scales, and the modal signals to be processed. Developed methods and the related algorithms are critically evaluated based on digital simulation of actual fault transients using the detailed models of power system components.The project's results are expected to initiate a new way of processing fault transients, using the information at the higher frequency end of their spectrum, as opposed to most of the techniques currently in use today. These results can potentially be used in related applications such as harmonics monitoring, detection and characterization of disturbances, distribution system fault monitoring and incipient failure detection of power transformers.