E3S Web of Conferences (Jan 2021)

Study on the Feature Space Detection Method of DC Arc Fault for Photovoltaic system

  • Sun Liling,
  • Wu Han,
  • Lu Xiangdong

DOI
https://doi.org/10.1051/e3sconf/202125601015
Journal volume & issue
Vol. 256
p. 01015

Abstract

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An arc fault on the DC side of the photovoltaic system is a potential safety hazard and is difficult to detect due to the complexity of photovoltaic systems. The detection method of series arc fault in photovoltaic systems is investigated here. The DC arc fault test platform for a photovoltaic system is established to collect the current signal under normal and fault conditions. In this study, the time domain characteristics, frequency domain characteristics, and time-frequency domain characteristics are compared by analysing the current data from the photovoltaic system in before and after fault states: corresponding feature vectors are used to construct the arc fault feature space of the system, and according to the position of the current signal in the feature space the fault is detected, so as to realise effective arc fault feature information. Then the method of establishing the arc fault feature space is introduced and key parameters of the feature space are determined. Finally, the anti-interference ability of arc fault feature space detection is verified. The results showed that the detection method is both feasible and accurate.