SMART SOLAR TRACKER SYSTEM FOR MAXIMIZING SOLAR PANEL EFFICIENCY

Abstract

The increasing demand for renewable energy has positioned solar power as a crucial and sustainable energy source; however, the efficiency of solar photovoltaic (PV) systems is significantly affected by environmental factors, particularly dust accumulation on panel surfaces, which leads to energy losses and increased maintenance costs. Conventional manual cleaning methods are labor-intensive, time-consuming, and inefficient, creating the need for an automated and intelligent solution. This study proposes a Smart Solar Tracker System integrated with an IoT-enabled automated cleaning mechanism to enhance solar panel efficiency and reduce maintenance challenges. The system utilizes components such as PV panels, microcontrollers (Arduino/ESP-based), IoT sensors, water flow control units, and a dual-axis solar tracking mechanism to maximize sunlight capture. Sensors continuously monitor parameters like dust levels, solar irradiance, and panel performance, while IoT connectivity enables real-time data acquisition, remote monitoring, and intelligent control through cloud platforms. The proposed method integrates tracking and automated cleaning using smart algorithms that trigger cleaning operations based on sensor thresholds, thereby reducing unnecessary water usage and operational time. The expected outcomes include improved energy efficiency, reduced cleaning time, optimized water consumption, and minimized human intervention, along with enhanced system reliability through predictive maintenance. In conclusion, the proposed system offers a cost-effective, scalable, and sustainable solution for improving solar energy generation efficiency and advancing intelligent renewable energy technologies.