Detection and location of fault in a micro grid using wavelet transform

B. Panigrahi, P. Ray, P. Rout, S. Sahu
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引用次数: 15

Abstract

The main objective of utility companies is continuous power supply which motivates them for the quick detection and location of faults occurring in a power system. Fault analysis of different fault condition is a difficult task in a Hybrid power system. The wavelet transform is used for the detection and location of fault taking place in a hybrid power system. For proper fault analysis, exact location of the fault distance from the source and type of fault information is very much essential. The proposed model used in this paper is a hybrid combination of wind energy and photovoltaic generation system. For detecting the fault voltage signals are extracted and passed through wavelet transform. Detailed information about the faulted signal is received. The wavelet transform has the special property of time-frequency resolution, from which we can detect the fault. In this paper wavelet transform (WT) is used for determining the location and detection of fault. For clearing the fault in less time detection and location of fault are two important tasks for a power engineer. All the signals are analyzed using the wavelet transform toolbox after selecting the suitable wavelet level. From the analyzed signal the pre fault and post fault coefficients are derived. The fault detection and location study are simulated in MATLAB/Simulink for a typical power system.
基于小波变换的微电网故障检测与定位
电力公司的主要目标是持续供电,这促使他们快速检测和定位电力系统中发生的故障。不同故障状态的故障分析是混合动力系统的难点问题。将小波变换用于混合电力系统故障的检测和定位。准确定位故障源与故障信息的距离和类型是进行故障分析的关键。本文所提出的模型是一个风能和光伏发电系统的混合组合。为了检测故障电压信号,提取故障电压信号并进行小波变换。接收到故障信号的详细信息。小波变换具有时频分辨率高的特点,可以用来检测故障。本文将小波变换用于故障的定位和检测。为了在较短的时间内清除故障,故障检测和定位是电力工程师的两项重要任务。在选择合适的小波电平后,使用小波变换工具箱对所有信号进行分析。从分析的信号中推导出故障前系数和故障后系数。在MATLAB/Simulink中对典型电力系统的故障检测与定位研究进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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