| Issue |
EPJ Web Conf.
Volume 344, 2025
AI-Integrated Physics, Technology, and Engineering Conference (AIPTEC 2025)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 9 | |
| Section | AI-Integrated Physics, Technology, and Engineering | |
| DOI | https://doi.org/10.1051/epjconf/202534401002 | |
| Published online | 22 December 2025 | |
https://doi.org/10.1051/epjconf/202534401002
Design and development of an energy monitoring and SDCard– based data logging system for on-grid solar power plants
Department of Electrical Engineering, Faculty of Vocational Studies, Universitas Negeri Surabaya, Surabaya, East Java, Indonesia
* Corresponding author: asadaziz@unesa.ac.id
Published online: 22 December 2025
This research aims to design and build a real-time energy monitoring and data logger tool using an ESP-32 microcontroller and displayed in home assistant software. Real-time monitoring of solar power plant performance is crucial for analyzing daily performance and making technical adjustments to optimize energy production, even under variable environmental condition. To overcome the problems in accuracy and real-time data recording, a system is needed that continuously monitors data based on a data logger. This system consists of several components including the PZEM-004T sensor, a real-time clock module, and an SD card module that are integrated into one system. Data retrieval in the system that has been created is done automatically in real-time and then saved in CSV format. Testing in this study has been successfully carried out with the lowest error value obtained in the R phase test of 0.13% and an accuracy value of 99.87%. While the lowest error value in the current test was obtained in the T phase test of 0.41% and an accuracy value of 99.59%. Meanwhile, the lowest error value in the power test was obtained in the T phase test of 0.10% and an accuracy value of 99.9%.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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