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基于小波神经网络的小电流接地系统单相接地故障定位研究

Study of Single Phase-to-earth Fault Location Based on Wavelet and ANN for the Small Current Neutral Grounding System

【作者】 惠学军

【导师】 李训铭;

【作者基本信息】 河海大学 , 控制理论与控制工程, 2002, 硕士

【摘要】 小电流接地系统是指中性点不直接接地系统,其中大多数采用中性点经消弧线圈接地方式。这类系统发生单相接地故障时,故障电流较小,三相线电压仍保持对称,对负荷供电没影响。多年以来,许多科研人员在小电流接地系统单相接地故障定位方面作了大量工作,但由于该系统单相接地故障特征不明显,虽然取得一定的进展,但尚未取得实质性的突破,在实际中也无较好应用。提高供电可靠性的要求和配电网自动化水平的迅猛发展使得对故障定位的研究日益紧迫。 本文在中性点不同接地方式下,研究和分析了线路零序故障特征量的稳态和暂态特点,主要从信号处理的角度,提出将小波分析理论和人工神经网络原理运用到故障定位,将基于稳态信号的定位原理转移到基于故障特征量暂态信号的定位原理。论文提出利用各个出线零序电流在频带上小波包系数模极大值的方向和大小的不同来实现故障选线,讨论了利用小波分析的奇异性来判断故障启动时刻,提出将小波分析和人工神经网络结合,利用人工神经网络的非线性逼近能力,实现故障暂态量到故障距离的非线性映射,完成测距。并通过典型的10KV仿真算例验证了该方法的可行性。 尽管本论文中选择的仿真算例针对的情况有限,但是仿真结果表明:利用小波分析理论对电力系统故障暂态信号进行特征提取处理是行之有效的方法。

【Abstract】 The small current neutral grounding system is a kind of system without neutral grounding, in most of which the neutral point connects to ground through a reactor. When single-phase ground fault occurs in this system, the fault current is much low and the phase-phase voltage is still symmetrical. So the system still can supply power to load. Although many researchers have done much concerning on fault location for years, the key problem remain unsolved because of the undistinguished fault feature. With the requirement of improving the reliability of power supply and the fast development of the distributed power system automation, the study of fault location becomes more and more important.This paper analyses the steady and transient character of line fault when the neutral point connects to ground in different ways. From the angle of signal processing, the wavelet analysis theory and the artificial neural networks are introduced to fault location, in which the fault character is not the steady signal but the transient signal. Judging by the different magnitude and direction of the wavelet packet coefficient modular maximum, we can select the single phase-to-earth line. The method using wavelet singularity detection theory to extract the fault time is discussed. A fault distance measurement algorithm combining wavelet analysis used for separating the character from the transient fault signal with artificial neural networks used for the nonlinear approximation from the transient character to fault distance is presented. The data from a typical small current grounding neutral system example validate the feasibility of the algorithms.In spite of the limited samples, the simulation result shows that using Wavelet analysis to separate the character from the transient fault signals is an efficient way.

  • 【网络出版投稿人】 河海大学
  • 【网络出版年期】2002年 02期
  • 【分类号】TM862
  • 【被引频次】12
  • 【下载频次】495
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