Smart Solar Plant Optimization Using MPPT Controller and IoT Alert System

Abstract: This paper presents a smart solar monitoring and predictive maintenance system that improves the efficiency and reliability of photovoltaic systems using IoT and sensor integration with an MPPT charge controller. The system is based on an Atmega328 microcontroller and uses sensors to measure voltage, current, sunlight intensity, dust levels, and vibrations. Real-time data is transmitted through an ESP8266 Wi-Fi module to the ThingSpeak cloud for remote analysis. By comparing actual power output with expected values, the system detects performance issues such as shading, dust accumulation, or faults. It also predicts cleaning needs and identifies potential physical damage or disturbances. The system is powered by a solar PV panel integrated with and Maximum Power Point Tracking (MPPT)-based charge controller and battery backup to ensure reliable and uninterrupted operation. The implemented MPPT controller continuously tracks the maximum power point of the solar panel to maximize energy extraction and improve charging efficiency. The proposed solution minimizes manual maintenance requirements while providing an efficient, economical, and scalable approach for intelligent solar energy management.

Keywords: Solar Panel Monitoring, IoT-based System, Predictive Maintenance, ThingSpeak Cloud, MPPT Charge Controller, Renewable Energy, Real-time Data, and Remote Monitoring.