• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.32-37
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• 2021

This study proposes a DC series arc fault detector using a frequency analysis method called the discrete wavelet transform (DWT), in which the processing speed of the DWT algorithm is improved effectively. The processing time can be shortened because of the time characteristic of the DWT result. The performance of the developed DC series arc fault detector for a large photovoltaic system is verified with various DC series arc generation conditions. Successful DC series arc detection and improved calculation time were both demonstrated through the measured actual arc experimental result.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.100-105
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• 2022

This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.271-276
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• 2021

Arc fault detector based on multilevel DWT with analysis of high-frequency noise components over 100 kHz is proposed in this study to improve the performance in detecting serial arcs and distinguishing them from inverter noise in PV systems. PV inverters generally operate at a frequency range of 20-50 kHz for switching operation and maximum power tracking control, and the effect of these frequency components on the signal for arc detection leads to negative arc detection. High-speed ADC and multilevel DWT are used in this study to analyze frequency components above 100 kHz. Such high frequency components are less influenced by inverter noise and utilized to detect as well as separate DC series arc from inverter noise. Arc detectors identify the input current of PV inverters using a Rogowski coil. The sensed signal is filtered, amplified, and used in 800kSPS ADC and DWT analysis and arc occurrence determination in DSP. An arc detection simulation facility in UL1699B was constructed and AFD tests the proposed detector were conducted to verify the performance of arc detection and performance of distinction of the negative arc. The satisfactory performance of the arc detector meets the standard of arc detection and extinguishing time of UL1699B with an arc detection time of approximately 0.11 seconds.