Detection of Parallel Arc Fault on Photovoltaic System Based on Fast Fourier Transform

Mufid Murtadho, Eka Prasetyono, D. O. Anggriawan
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引用次数: 3

Abstract

Photovoltaic is one of the alternative electric producers that is widely used considering the availability of the main source of photovoltaic. The photovoltaic as an electrical energy source, it also to pay more attention to the risks that can cause the failure with the worst is an event of a fire. The fault causes the failure is parallel DC arc fault. However, Parallel DC Arc Fault cannot be detected by the conventional safety device such as Circuit Breaker. Therefore, the proposed algorithm fast Fourier transform is designed to detect and identify the event of the parallel arc fault. To identify the parallel arc fault and its characteristic, simulation using PSIM is used to get the current waveform of the parallel arc fault. To see the characteristic of the arc fault current, the initial current flow through the arc generator is needed. The order condition in the simulation is Short Circuit, Arc Fault, and then the Normal condition. The sum of the frequency spectrum is used as the method of comparing normal condition and fault condition with the result is the sum of the frequency spectrum during arc fault condition has a bigger value than normal condition. Moreover, the simulation result shows that the proposed algorithm has the accurate result for parallel arc fault detection.
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基于快速傅里叶变换的光伏系统并联电弧故障检测
考虑到光伏发电的主要来源的可获得性,光伏发电是一种被广泛使用的替代发电方式。而光伏作为一种电能来源,它也要更加注意其可能造成的风险,最坏的情况是发生火灾。引起故障的故障为直流并联电弧故障。而传统的断路器等安全装置无法检测到并联直流电弧故障。为此,设计了快速傅立叶变换算法来检测和识别并联电弧故障事件。为了识别并联电弧故障及其特征,采用PSIM仿真得到并联电弧故障的电流波形。为了了解电弧故障电流的特性,需要通过电弧发生器的初始电流。仿真中的顺序条件为短路、电弧故障、正常。采用频谱之和作为正常工况和故障工况的比较方法,结果表明电弧故障工况下的频谱之和比正常工况下的频谱之和大。仿真结果表明,该算法对并联电弧故障检测具有准确的结果。
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