136879 research outputs found
Sort by
Characterizing Photovoltaic System Arc-Faults
Get PDFArc faults are one of the leading causes of photovoltaic (PV) system failure resulting in electrical fires, which can result from equipment failure or improper installation. Thus, arc-faults detector is crucial for safe operation and is a prerequisite for high penetration of PV. Existing arc-faults detectors (AFD) showed a deficiency in detecting arc-faults in PV systems. Developing an effective arc fault detector requires a thorough understanding of the electrical characteristics of PV arcs. Since arcs produce chaotic waveforms, a large sample of arc voltage and current waveforms is needed to understand the PV arcing phenomenon. However, the main barrier to developing and testing new detection methods is the scarcity of PV arc data in the existing literature. This project describes an automated mechatronics testbed developed using the pull-apart method to facilitate scientifically repeatable arc generation studies. Such a setup is needed to create a library of recorded arc voltage and current waveforms to characterize the electrical signature of PV arcs. The hypothesized factors that may affect the PV arc signatures are electrode geometry and material, electrical voltage and current, and electrode gap separation. A different combination of these parameters is used for collecting data. An application with a graphical user interface was designed to allow the user to filter the dataset based on the experimental parameters. The recorded arc voltage and current waveforms were analyzed using the Fast Fourier Transform (FFT) and the Short Time Fourier Transform (STFT). The analyzed data can be used to identify the invariant frequency features that characterize the PV arcs. The initial investigation shows that the frequency spectrums of the arc voltage and current characteristics are affected by the experimental parameters, with a common arcing signature in the arc voltage and current frequency spectrums between 0-20kHz and 0-2kHz, respectively. Also, the STFT showed more potential to be used as a detection process than the FFT. The results can be used in subsequent research to develop a robust PV arc faults detector and provide a public arc data library for further research