Design and Evaluation of an Arduino-Based Data Logger for Applications of Renewable Energy Systems
نویسندگان
1 Smart Power Generation Research Centre, College of Engineering, Universiti Tenaga Nasional (UNITEN), P.O. Box: 43000, Kajang, Malaysia.
2 Faculty of Engineering, University of Sohar, P.O. Box: 44, Sohar, PCI 311, Oman.
3 Smart Power Generation Research Centre, College of Engineering, Universiti Tenaga Nasional (UNITEN), P.O. Box: 43000, Kajang, Malaysia.
4 Department of Mechanical Engineering, College of Engineering, Universiti Tenaga Nasional, P. O. Box: 43000, Kajang, Selangor, Malaysia.
5 Department of Renewable Energy Engineering, Faculty of Engineering and Design, Middle East University (MEU), P. O. Box: 11831, Amman, Jordan.
6 College of Engineering, University of Al-Bayan, Baghdad, Iraq.
7 Faculty of Engineering, University of Sohar, P.O. Box: 44, Sohar, PCI 311, Oman.
doi
10.30501/jree.2025.518618.2365چکیده
This paper introduces a novel Arduino-based data logger designed for hybrid photovoltaic–thermoelectric generator (PV-TEG) systems, enhancing the monitoring of solar irradiance, ambient temperature, wind speed, and electrical outputs with precision and affordability. The data logger integrates real-time data acquisition and efficient documentation through an SD card, with results displayed on an LCD for immediate analysis. The error margin of the system ranges from 1% to 2.92% across different parameters, based on extensive validation against reference data recorded at the Mutah University Weather Station and MATLAB simulations. In particular, the measurement of solar irradiance exhibited an error range of 1–2.6%, ambient temperature 1.2–1.8%, and wind speed 2.43–2.92%. The PV glass temperature recorded an error of 1.2–1.9%, PV power output 1.5–2.5%, and TEG power 1.9–2.75%, respectively. These results confirm the accuracy of the sensors in measuring the dynamic operational conditions of the PV and TEG elements. The capabilities of the data logger can assist researchers in capturing crucial parameters, analyzing readings, and making informed decisions during experimental stages. The performance and optimization of hybrid renewable energy systems are enhanced through the system’s real-time monitoring and reliable data documentation, offering valuable insights into the behavior of PV-TEG systems. This work provides a foundation for future developments in sustainable energy technologies by demonstrating the potential of data loggers in system management and promoting sustainability within the field of renewable energy.
