Series DC Arc Fault Detection for a Grid-Tie Solar PV Power Generation System

A real-time algorithm is developed for the detection of series dc arc faults in a grid-tie solar photovoltaic (PV) installation. The sensed dc bus current, which is sampled using an analog-to-digital converter with Galvanic isolation, is filtered using a wavelet-based, two-level filter bank. The filter bank, referred to as the post-processing filter, improves the robustness of the algorithm to any false tripping by rejecting power converter harmonics that are added to the dc bus current. To determine if a fault has occurred, the algorithm calculates the variance of the filter bank output and sees if the calculated variance exceeds an upper threshold value. If the upper threshold is exceeded, and the dc bus voltage falls below a predefined lower limit for a set number of instances, the algorithm trips. The algorithm can detect a series arc fault in under two seconds and does not rely on machine learning techniques to process the sensed signal. The detection algorithm is implemented on a commercial microcontroller using C code, and the filter bank convolutions are implemented using 32-bit floating point variables.