International Journal of Electrical and Computer Engineering (IJECE) Vol. 15, No. 2, April 2025, pp. 1251~1261 ISSN: 2088-8708, DOI: 10.11591/ijece.v15i2.pp1251-1261  1251 Journal homepage: http://ijece.iaescore.com Computer vision-based sun tracking control for optimizing photovoltaic power generation Nopadol Uchaipichat, Chotiwat Wibunsin, Kewalin Chokjulanon, Nutthaphong Tanthanuch Department of Electrical and Computer Engineering, Thammasat School of Engineering, Faculty of Engineering, Thammasat University, Pathumthani, Thailand Article Info ABSTRACT Article history: Received Jul 15, 2024 Revised Oct 4, 2024 Accepted Oct 23, 2024 As global energy consumption rises and fossil fuel reserves dwindle, the transition to renewable energy sources becomes imperative. Solar photovoltaic (PV) technology, crucial in this shift, faces challenges in efficiency and cost. This study explores a motorized sun-tracking system employing image processing techniques to optimize solar panel orientation and maximize energy capture. Using an Arduino Mega 2560 microcontroller, L298N motor driver, Raspberry Pi 3 Model B, and webcam integration, the system dynamically adjusts solar panels based on real-time sun position detection. Experiments compare the performance of fixed and sun-tracking solar panels, revealing that sun-tracking panels consistently outperform fixed ones, particularly during low sun angles, resulting in up to 84.9% higher power output. These findings underscore the potential of sun-tracking technology to significantly enhance solar energy efficiency and support sustainable energy goals. Future research should focus on refining tracking algorithms and optimizing system design to further boost energy capture and reliability. Keywords: Energy efficiency Image processing Photovoltaic Renewable energy Solar tracking systems This is an open access article under the CC BY-SA license. Corresponding Author: Nutthaphong Tanthanuch Department of Electrical and Computer Engineering, Thammasat School of Engineering, Faculty of Engineering, Thammasat University 99 Moo 18 Paholyothin Road, Klong Nueng, Klong Luang, Pathumthani 12120, Thailand Email: tanthanuch1@engr.tu.ac.th 1. INTRODUCTION In today's global scenario, energy consumption has been steadily on the rise, spanning both residential and industrial sectors, while fossil fuel reserves, including oil, natural gas, and coal, are dwindling. The extraction and utilization of these limited resources not only add to environmental pollution, particularly air pollution, but also worsen the effects of climate change. As countries worldwide grapple with these challenges, many have implemented energy sector policies aimed at transitioning towards cleaner energy sources and achieving net zero greenhouse gas emissions [1]. The remarkable expansion of global photovoltaic (PV) capacity, surging to 591 GW in 2019, owes much to advancements in solar cell efficiency and cost reduction, rendering PV technology increasingly competitive in terms of levelized costs of electricity [2]. As PV systems approach cost parity with traditional energy sources, there is an urgent requirement for a detailed plan outlining essential paths for development to enable installations on a terawatt scale [1]. This roadmap must address key technical hurdles and highlight breakthroughs essential for steering future research endeavors and guiding industry investments [2]. Solar PV technology, a vital renewable energy source, faces challenges such as high costs, low efficiency, and intermittency in current systems compared to fossil fuels. Achieving optimal energy capture from the sun with PV systems is complex, influenced by factors like PV material, geographic location,