Sistem IoT Monitoring dan Manajemen Energi Surya pada Remote Station dengan Protokol MQTT

Abstract

Sistem tenaga surya pada stasiun terpencil (remote station) sering menghadapi kendala ketidakseimbangan daya dan keterbatasan pemantauan manual. Penelitian ini bertujuan mengembangkan sistem monitoring dan manajemen energi surya berbasis Internet of Things (IoT) menggunakan protokol MQTT. Sistem dirancang menggunakan mikrokontroler utama Arduino Nano, mikrokontroler komunikasi data Arduino Mega, sensor arus ACS712, pyranometer, dan sensor cahaya BPW21. Data telemetri dikirim secara real-time ke server Azure Virtual Machine dan divisualisasikan melalui dashboard interaktif Grafana. Hasil pengujian menunjukkan sistem sukses mengakuisisi 6.370 titik data selama 16 hari pengujian aktif. Penerapan pra-pemrosesan kalibrasi zero-offset dinamis terbukti mampu secara analitis mengeliminasi galat pembacaan arus fiktif pada sensor saat kondisi tanpa cahaya. Kinerja Maximum Power Point Tracking (MPPT) terbukti andal dengan mencatatkan efisiensi penyimpanan baterai mencapai 61,9% hingga 87,5%. Sistem ini efektif memfasilitasi pemantauan efisiensi energi jarak jauh secara akurat.

Solar power systems in remote stations often face power imbalances and manual monitoring limitations. This study aims to develop an Internet of Things (IoT)-based solar energy monitoring and management system using the MQTT protocol. The system is designed with an Arduino Nano microcontroller, Arduino Mega as a data communication microcontroller, ACS712 current sensors, a pyranometer, and a BPW21 light sensor. Telemetry data is transmitted in real-time to a cloud server (Azure Virtual Machine) and visualized via an interactive Grafana dashboard. Test results show the system successfully acquired 6,370 data points over 16 active testing days. The implementation of dynamic zero-offset calibration effectively eliminated fictitious current reading errors during dark conditions. The Maximum Power Point Tracking (MPPT) performance proved highly reliable, achieving battery storage efficiency between 61.9% and 87.5%. This system facilitates accurate remote monitoring of energy efficiency.