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DC Arc-Fault Detection in PV Systems Using Multistage Morphological Fault Detection Algorithm

机译:多级形态故障检测算法的光伏系统直流电弧故障检测

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The series and parallel arc-faults on the DC-side have different characteristics than that of the AC-side of PV systems and hence require advanced detection strategies. This paper proposes a robust, reliable technique for the detection of different types of DC arc-faults. The method uses a fault detector algorithm called the Decomposed Open-Close Alternating Sequence (DOCAS) using morphological filters. The proposed method detects the existence of an arcing fault by generating spikes at its output. The proposed method is tested for different types of series and parallel DC arc-faults under different levels of irradiance. Simulation results demonstrate that the proposed method maintains the selectivity and distinguishes changes in irradiance and load levels from series and parallel faults effectively.
机译:直流侧的串联和并联电弧故障与光伏系统的交流侧具有不同的特性,因此需要先进的检测策略。本文提出了一种鲁棒,可靠的技术来检测不同类型的直流电弧故障。该方法使用故障检测器算法,该算法使用形态过滤器,称为分解开闭交替序列(DOCAS)。所提出的方法通过在其输出处产生尖峰来检测电弧故障的存在。针对不同类型的串联和并联直流电弧故障,在不同的辐照度水平下对所提出的方法进行了测试。仿真结果表明,该方法可以保持选择性,并能有效地将辐照度和负载水平的变化与串联和并联故障区分开。

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