Real time arc fault detection in PV systems using wavelet decomposition

Hezi Zhu, Zhan Wang, Robert Balog

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Reliable arc fault detection is crucial for the safe operation of photovoltaic (PV) system. Fourier transform methods have been previously used to detect arcing by examining the frequency characteristics of the PV voltage or current but are not well suited because arcs are chaotic, not periodic and not stationary. In contract, wavelet-based transforms are well suited because the technique does not assume periodicity and is adept at detecting discontinuities in the signal. This paper reports on results from the development of a real time arc fault detection technique that was built as a wavelet decomposition based arc detector using a TI C2000 platform DSP. The arc fault detector was tested on a composite arc signal constructed from recordings of real-world inverter noise and real-world arc events replayed through a high-fidelity test bed to compare the ability to differentiate inverter only and inverter plus arcing signals. The results demonstrate that the wavelet decomposition and arc discrimination algorithms can be implemented in real-time on a low-cost DSP.

Original languageEnglish
Title of host publication2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1761-1766
Number of pages6
Volume2016-November
ISBN (Electronic)9781509027248
DOIs
Publication statusPublished - 18 Nov 2016
Externally publishedYes
Event43rd IEEE Photovoltaic Specialists Conference, PVSC 2016 - Portland, United States
Duration: 5 Jun 201610 Jun 2016

Other

Other43rd IEEE Photovoltaic Specialists Conference, PVSC 2016
CountryUnited States
CityPortland
Period5/6/1610/6/16

Fingerprint

Wavelet decomposition
Fault detection
Detectors
Fourier transforms
Composite materials
Electric potential
Costs

Keywords

  • arc fault detection
  • real time
  • wavelet decomposition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

Zhu, H., Wang, Z., & Balog, R. (2016). Real time arc fault detection in PV systems using wavelet decomposition. In 2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016 (Vol. 2016-November, pp. 1761-1766). [7749926] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PVSC.2016.7749926

Real time arc fault detection in PV systems using wavelet decomposition. / Zhu, Hezi; Wang, Zhan; Balog, Robert.

2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. Vol. 2016-November Institute of Electrical and Electronics Engineers Inc., 2016. p. 1761-1766 7749926.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhu, H, Wang, Z & Balog, R 2016, Real time arc fault detection in PV systems using wavelet decomposition. in 2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. vol. 2016-November, 7749926, Institute of Electrical and Electronics Engineers Inc., pp. 1761-1766, 43rd IEEE Photovoltaic Specialists Conference, PVSC 2016, Portland, United States, 5/6/16. https://doi.org/10.1109/PVSC.2016.7749926
Zhu H, Wang Z, Balog R. Real time arc fault detection in PV systems using wavelet decomposition. In 2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. Vol. 2016-November. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1761-1766. 7749926 https://doi.org/10.1109/PVSC.2016.7749926
Zhu, Hezi ; Wang, Zhan ; Balog, Robert. / Real time arc fault detection in PV systems using wavelet decomposition. 2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. Vol. 2016-November Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1761-1766
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