A Statistical Analysis of Fault Detection in Photovoltaics Using Reflectometry

Ayobami S. Edun, Cody LaFlamme, Evan J. Benoit, Cynthia Furse, Joel B. Harley

Abstract: Spread spectrum time domain reflectometry (SSTDR) has been used to detect different kinds of faults in cables, aircraft wiring, and photovoltaic (PV) setups. One significant problem is that, since most methods that use reflectometry are based on a comparison with a known baseline, variations in the baseline caused by system or environmental variations can overshadow the reflections produced by faults and reduce the probability of detection. The effects of these variations are exacerbated for faults far from the test device. The objective of this work is to statistically estimate the probability that a reflection from a PV array is or is not a fault amid environmental variations, system variations, and at different locations along the line. Our results show the probability of detecting fault presence at different distances from the test device when there are partial and full disconnects over a range of signal-to-noise ratio (SNR). At a distance of 97.54 m (320 ft) from the tester, the probability of detection of a full disconnect is as high as 0.75 with an SNR of about 9 dB, while the probability of detection is nearly zero for partial faults at the same location. We also present scenarios where faults can no longer be detected and how averaging could help improve the probability of detection.

External IDs:doi:10.1109/jphotov.2025.3608439