Photovoltaic module-level DC-DC converter with arc fault protection scheme for DC distribution system

Seo, Gab-Su; Cho, Bo-Hyung; Lee, Kyu-Chan

doi:10.1109/ecce-asia.2013.6579215

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Different detection frequencies are also mentioned in other articles. Korean scholars narrow this range down between 50-100 kHz to avoid inverter operating frequency [5]. Engineers from TI draw this range between 40-100 kHz directly from the comparison of arcing signatures with non-arcing signatures [6].…”

Section: Introductionmentioning

confidence: 99%

PV arc-fault feature extraction and detection based on bayesian support vector machines

Gao¹,

Dong²,

Sun³

et al. 2015

ijsgce

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In a PV system, DC arc is regarded as a serious fault, which might cause circuit damage and trigger fires. The arc fault, however, is hard to detect due to the special fields of photovoltaic systems: constant direct current without zerocrossing point, sophisticated components leading to noise interruption, and usually occupying large area. Therefore, detectable characteristics are of great importance to diagnosis and alarm of fault arcs in PV systems. In this paper, we presented a classification method of separating arcing and non-arcing in the feature space. First, data sets of current signal were sampled by designing field experiments with "pull apart" method for arc ignition. Then seven features in both time and frequency domains were defined and two of them in each domain were selected to train BSVM. In order to simplify the computation, the trained BSVM network was replaced by a separating line, which was proved to have a better performance of classification. Testing results showed that this method could diagnose fault arcs with high accuracy. But whether this method is suitable for other PV systems needs to be verified in further work.

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Section: Introductionmentioning

confidence: 99%