Reducing the Effects of Rain and Moisture on Spread Spectrum Time-Domain Reflectometry Monitoring of Photovoltaics

This article addresses the challenges resulting from the effects of moisture and rain on the velocity of propagation (VOP) in a spread spectrum time-domain reflectometry (SSTDR) monitoring system for detecting and locating faults within a photovoltaic (PV) string. A change in the VOP results in shifts of the SSTDR reflection peaks and prevents accurate localization of faults by the monitoring system. Two algorithms, the scale transform (ST) and dynamic time warping (DTW), are studied as solutions to mitigate these VOP variations. The ST algorithm uniformly stretches signals to align with the baseline, while DTW allows for variable stretching and contracting factors. Both transforms are used to adjust for the changes in VOP to better align data with a known baseline signal, allowing the difference to be used for fault detection and localization. The experimental results demonstrate the influence of rain on VOP within PV systems and compare the performance of the ST and DTW algorithms. Both algorithms significantly reduce variability in the data and improve the ability to detect and locate faults within the PV cabling. The ST is shown to be generally more robust to the variations.