A small-scale grid-connected PV system that is easy to install and is inexpensive as a remote monitoring system may cause economic losses if its failure is not found and it is left unattended for a long time.Thus, in this study, we Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data developed a low-cost fault detection remote monitoring system for small-scale grid-connected PV systems.This active monitoring system equipped with a simulation-based fault detection algorithm accurately predicts AC power under normal operating conditions and notifies its failure when the measured power is abnormally low.In order to lower the cost, we used a single board computer (SBC) with edge computing as a data server and designed a monitoring system using openHAB, an open-source software.Additionally, we used the Shewhart control chart as a fault detection criterion and the ratio between the measured and predicted ac power for the normal operation data as an observation.
As a result of the verification test for the actual grid-connected PV system, it was confirmed that the developed Assessment of a metabarcoding approach for the characterisation of vector-borne bacteria in canines from Bangkok, Thailand remote monitoring system was able to accurately identify the system failures in real-time, such as open circuit, short circuit, partial shading, etc.