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Integrated Fault Location and Power-Quality Analysis in Electric Power Distribution Systems

机译：配电系统中的集成故障定位和电能质量分析

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摘要

This paper presents a methodology for automated disturbance analysis and fault location on electric power distribution systems using a combination of modern techniques for network analysis, signal processing, and intelligent systems. New algorithms to detect, classify, and locate power-quality disturbances are developed. The continuous process of detecting these disturbances is accomplished through statistical analysis and multilevel signal analysis in the wavelet domain. The behavioral indices of the current and voltage signals are extracted by employing the discrete wavelet transform, multiresolution analysis, and the concept of signal energy. These indices are used by a number of independent Fuzzy-ARTMAP neural networks, which aim to classify the fault type and the power-quality events. The fault location is performed after the classification process. A real life three-phase distribution system with 134 nodes—13.8 kV and 7.065 MVA—was used to test the proposed algorithms, providing satisfactory results, attesting that the proposed algorithms are efficient, fast, and, above all, intelligent.
机译：本文介绍了一种结合现代技术进行网络分析，信号处理和智能系统的配电系统自动干扰分析和故障定位的方法。开发了用于检测，分类和定位电能质量干扰的新算法。通过小波域中的统计分析和多级信号分析来完成检测这些干扰的连续过程。通过采用离散小波变换，多分辨率分析和信号能量的概念来提取电流和电压信号的行为指标。这些索引由许多独立的Fuzzy-ARTMAP神经网络使用，目的是对故障类型和电能质量事件进行分类。在分类过程之后执行故障定位。使用具有134个节点（13.8 kV和7.065 MVA）的现实生活中的三相配电系统来测试所提出的算法，提供令人满意的结果，证明所提出的算法高效，快速并且尤其是智能。

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