AI-Driven Real-Time Solar Tracking System Using Perovskite PV Technology for Enhanced Energy Harvesting.

The increasing need for clean and sustainable energy sources has led to the development of high-efficiency solar energy technologies. Perovskite solar cells have been identified as a potential substitute for traditional silicon solar cells due to their high-power conversion efficiency, low production cost, and lightweight design. However, the total energy production of solar cells is greatly affected by their orientation with respect to the sun. Traditional fixed and sensor- controlled solar tracking systems often fail to perform well under dynamic environmental conditions, such as cloud cover, environmental disturbances, and varying light intensity. This paper presents an AI-assisted real-time solar tracking system combined with perovskite solar technology to improve the efficiency of energy production. The proposed system employs AI algorithms to continuously monitor environmental factors and adjust the solar panel’s tilt angle and orientation in real- time. Unlike traditional solar tracking systems that use light- dependent resistors or fixed time schedules, the AI-assisted system intelligently responds to dynamic weather conditions to ensure continuous and optimal energy production. They system design includes a perovskite solar cell, a microcontroller-based control system, motorized actuators, and an AI-controlled decision-support system. The experimental outcome shows improved energy efficiency, minimized human intervention, and improved system reliability compared to fixed and traditional solar tracking systems. Additionally, the proposed system is cost- effective, adaptable, and applicable to advanced solar energy systems, such as solar roofs, smart solar farms, and electric vehicle charging stations.