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Classification of high impedance fault using MWT and enhanced fuzzy logic controller in power system

机译:MWT和增强模糊控制器在电力系统高阻抗故障分类中的应用。

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This paper contains a new algorithm for High Impedance Fault (HIF) protection. The HIF is happen when a conductor touch a high impedance surface such as asphalt road, sand, cemented or tree. The main goal of this projected system is to recognize and categorize the HIF based improved system which is used to examine the amplitudes of voltage and current in the system is relatively insufficient and also progress the presentation of the power system. So, the area of defect classification and position regarded as removing characteristics that may aid from the temporary presentation of the voltage and current waveforms. In this document, multi wavelets transform (MWT) and enhanced fuzzy logic controller (FLC) are exploited to identify and categorize the HIF in the power system. Genetic algorithm (GA) is engaged for producing the regulations for fuzzy logic controller. Primarily, the characteristics of the power signal are removed by using the wavelet algorithm and the arithmetical metrics are intended. The calculated qualities are useful to the controlled learning technique and the worth of the signal is categorized. The learning technique, which is associated to the learning algorithm, inspects the data and differentiates the samples applied for the principle of categorization and weakening examination. FLC is employed to categorize the HIF in the power system and its fundamental structure is really not suitable for the rule of an extremely composite system since typically there are not adequate facts about the system obtainable. Consequently, a competent method is necessary to develop the presentation of FLC. Depend on these, the projected technique is executed in MATLAB/Simulink platform and its presentation is estimated and contrasted with other conventional techniques.
机译:本文包含一种用于高阻抗故障(HIF)保护的新算法。当导体接触高阻抗表面(如柏油路,沙子,水泥或树木)时,会发生HIF。该投影系统的主要目标是对基于HIF的改进系统进行识别和分类,该系统用于检查系统中电压和电流的幅度是否相对不足,并且可以促进电力系统的发展。因此,缺陷分类和位置区域被认为是去除特性,可以从电压和电流波形的临时表示中获得帮助。在本文中,多小波变换(MWT)和增强型模糊逻辑控制器(FLC)被用于识别和分类电力系统中的HIF。遗传算法(GA)用于产生模糊逻辑控制器的规则。首先,通过使用小波算法去除功率信号的特性,并达到算术指标。计算出的质量对于受控学习技术很有用,并且对信号的价值进行了分类。与学习算法相关的学习技术检查数据并区分用于分类和弱化检查原理的样本。 FLC用于对电力系统中的HIF进行分类,并且其基本结构实际上不适合极度复杂的系统的规则,因为通常没有足够的事实可获取该系统。因此,必须有一种有效的方法来发展FLC的表现形式。依赖于此,在MATLAB / Simulink平台中执行所投影的技术,并估计其表示形式并与其他常规技术进行对比。

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