Artificial Intelligence-Controlled Photovoltaic Generator for Optimized Power Point Tracking

Facultad de Ciencias Técnicas, Universidad Internacional Del Ecuador UIDE, Quito 170411, Ecuador

^* Corresponding author: vimoyago@uide.edu.ec

Abstract

This paper addresses the pressing need for sustainable energy solutions by focusing on developing a photovoltaic solar tracker enhanced with artificial intelligence (AI). The current and future global trends challenge energy systems to improve their output while also maintaining an eco-friendly approach, and there is an option to offset carbon emissions through photovoltaic energy. Nevertheless, the solar panel’s efficiency depends upon its ability to follow the sun’s movement to find the optimum energy angle. This project offers a unique solution, adopting a neural network technique that was trained using weather data from the daily weather forecasts to determine the correct angles of the panel at all times. The sampling unit was fabricated using aluminium and PLA materials and monitoring parameters of temperature, humidity, radiation, pressure, and atmospheric variables. A web-based interface lets monitor the system in oh-so-real-time and delivers graphical presentations of crucial metrics, including voltage, current, and power production. The outcomes suggest a significant enhancement in energy output, which ascends from 22.65% to 29.25%, equivalent to a 144.56 kWh-year rise. Although the margins of profitability may differ by region, our study sheds light on the efficiency of this AI-integrated solar tracker, especially in regions like Brazil or Spain, which facilitates alternative energy policies with possible economic benefits.