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Research Article Open access CC BY 4.0

Development of a Solar Power Generating System with Auto-Tracking and Data Logging Devices

A. S. Onawumi, N. A. Akinrinade, M. A. Olojede, A. O. Ajayeoba

Journal of Engineering Research and Reports · pp. 212–222 · Published 20 Dec 2022

10.9734/jerr/2022/v23i12779

Abstract

Solar power systems have become a viable wellspring of sustainable energy over the years and are commonly used for a variety of industrial and domestic applications. Capturing and storing the maximum amount of available energy for prediction and future analysis have been the major problems. This study aimed at developing a solar power generating system with solar tracking and data logging devices. The Dual Axes Solar Power Generating System (DASPGS) was developed using a combination of hardware and software systems consisting of three major subsystems: mechanical, electro-mechanical, and electrical tracker parts. C-language programme was used in conjunction with the Arduino Uno board for logging the power generated from the DASPGS and already fabricated Fixed Axis Solar Power Generating System (FASPGS). The power generated was stored on the created web page and the Secure Digital (SD) card. Data were harvested and the performance evaluations of the DASPGS over FASPGS were determined for 28 days. DASPGS gave average power of 22.88, 22.25, 24.49, and 25.92 Watts per week while FASPGS gave 5.16, 15.00, 16.23, and 15.74 Watts per week. A significant difference between DASPGS and FASPGS gave a P value of .004. This study showed that the DASPGS performed better than FASPGS. The system developed finds its application in the area of solar power prediction.

Data analysis data logging solar power system solar tracking system

Cited by 2

Modelling and Simulation of Solar Generator Battery Hybrid Systems to Improve Energy Reliability

N. A. Akinrinade, E. T. Oladele, M. O. Ajayi · International Journal of Electrical Engineering and Applied Sciences (IJEEAS) · 2026

Application of Machine Learning Models for the Prediction of Solar Panel Wattage for Rotating and Static Panel Systems

N. A. Akinrinade, A. Onawumi, A. Ajayeoba · Advances in Artificial Intelligence and Machine Learning · 2026

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