Harnessing The Sun's Potential: An Arduino-Based System for Optimized Energy Management in PV Systems
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Keywords

Photovoltaic systems
Arduino
Energy management
Renewable energy
Sustainability

How to Cite

Akhinbohun, S., Alli, F. K., & Omosigho, M. (2025). Harnessing The Sun’s Potential: An Arduino-Based System for Optimized Energy Management in PV Systems. ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY AND ENVIRONMENT, 21(1), 64-71. Retrieved from https://azojete.com.ng/index.php/azojete/article/view/1009

Abstract

The global shift towards renewable energy sources has placed photovoltaic (PV) systems at the forefront of sustainable energy solutions. Traditional PV systems often suffer from inefficiencies due to fixed load thresholds that do not adapt to changing environmental conditions, leading to energy waste. It proposes an innovative Arduino-based system for optimizing energy management in PV systems. The Arduino platform was selected for its ease of programming, affordability, and compatibility with various sensors. By continuously monitoring real-time data such as solar irradiance, battery status, and local energy consumption, the proposed system dynamically adjusts load thresholds to prevent energy waste and grid overload. The system architecture includes high-efficiency PV panels, a solar charge controller, deep-cycle batteries, and various sensors to monitor voltage, current, and temperature. The system employs deep-cycle batteries with capacities based on the energy requirements and expected usage patterns, and voltage regulators such as the LM7805 to ensure safe operation of the Arduino microcontroller at 5V, converted from the standard 12V input. This setup shows the comprehensive integration of components to ensure optimal performance. Simulation results demonstrate the system’s ability to manage power effectively, preventing overload and promoting energy efficiency. By maintaining precise control over energy distribution and utilizing a user-friendly interface for real-time monitoring, this research highlights the potential of an intelligent, cost-effective solution for enhanced energy management in PV systems, paving the way for more sustainable energy consumption.

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