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Arc fault detection and localization in photovoltaic systems using feature distribution maps of parallel capacitor currents

  • Qing Xiong
  • , Xiaojun Liu
  • , Xianyong Feng
  • , Angelo L. Gattozzi
  • , Yuhang Shi
  • , Lingyu Zhu
  • , Shengchang Ji
  • , Robert E. Hebner
  • University of Texas at Austin
  • Xi'an Jiaotong University

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

Abstract

Arc faults threaten the safe operation of photovoltaic (PV) systems. An arc fault detection and localization approach using parallel capacitors is proposed. A PV system has been analyzed and tested with five capacitors paralleled with the branches in the system. Series and parallel arc faults at nine locations have been tested in the system. When an arc occurred, current pulses were generated in the capacitors and their amplitudes and polarities were obtained through Hall current sensors. Discrete wavelet transformation was performed on the capacitor currents and the distributions of their amplitudes, frequency spectrums, and polarities are here reported. The results indicate that the distributions are unique under different fault types and locations, which could be used to detect and localize arc faults in PV systems. Moreover, the amplitudes of the capacitor currents can also help to localize a series arc fault within a PV string. Finally, the proposed approach is validated by a double-fault test.

Original languageEnglish
Pages (from-to)1090-1097
Number of pages8
JournalIEEE Journal of Photovoltaics
Volume8
Issue number4
DOIs
StatePublished - Jul 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Arc detection
  • discrete wavelet transform
  • fault localization
  • photovoltaic (PV) system
  • spectrum distribution

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