Abstract
For solar power plants to provide the most electricity, they must be monitored. This aids in recovering efficient power production from power plants while keeping an eye out for problems that might impair solar performance, such as damaged solar panels, connections, dust buildup on panels that reduces output, and other similar problems. In order to identify
problem locations, this project proposes a hardware design for a smart grid home gateway that combines a smart home network with solar system integration for PV. Thus, we
suggest an Internet of Things (IoT)-based automated solar power monitoring system that enables automatic solar power monitoring from any location over the internet. This project uses an Arduino-based system that incorporates PT, CT, and
LDR sensors to measure parameters and keep an eye on the
solar panel. By comparing the voltage recorded by the panel with the intensity of the LDR sensor, the fault has been
identified. Our technology continuously checks the solar panel and sends the power output to the Internet of Things system. Keywords: Light Dependent Resistance (LDR), Internet of
Things (IOT), and fault system. I.INTRODUCTION
The amount of electricity generated by solar sources has
steadily increased over the last several decades. Research
on solar panels with higher efficiency has kept pace with
this development. The current record efficiency is 44.7%, which is defined as the ratio of incoming solar energy to
the highest possible output power. There is a well- established interest in the surrounding equipment in
addition to research on solar panels. Power inverters, which transform dc energy from solar panels to ac grid
output, are a component of these systems. Since any
losses would impact the whole system's efficiency, the
efficiency issues with solar panels inevitably influence the
entire system. The field of photovoltaic (PV) inverters has
advanced recently to distributed inverter systems, in
which each panel is linked to a tiny inverter module. This
is advantageous since the energy harvest may be
increased by locally optimizing each panel. This not only increases
efficiency but also makes it possible to test each solar panel separately. These new capabilities open up new avenues for solar panel health
monitoring. Fault detection is a method that is now the subject of
ongoing study. The goal of fault detection is to quickly identify
damaged and defective solar panels. Solar panels inherently deteriorate, and measuring the rate of deterioration over time is interesting