Laboratory-Scale Design and Implementation of A Low-Cost IoT-Based Data Logger for A Remote DC Microgrid in Ghana

Abstract

The deployment of renewable and decentralized energy systems in remote locations is on the rise. As a result, the need for supervisory and data-logging frameworks to monitor distributed energy resources efficiently has increased. Robust logging of data forms the core of such systems, as it supports the continuous data acquisition, storage, data management, and analysis of the most critical operational parameters that define the system's operation, stability, and performance. Traditional data logging systems are typically expensive, complicated, and unsuitable for small-scale or remote microgrids. To address this challenge, this paper presents the design and implementation of a low-cost IoT-based data logger for monitoring and analyzing the performance of a remote DC microgrid in Ghana. The proposed system consists of a photovoltaic (PV) system, a wind turbine, a battery energy storage system, and a diesel generator, all connected to a DC bus. An Arduino UNO R4 Wi-Fi microcontroller serves as the RTU that collects voltage and current signals from sensors in the field and transmits them via an MQTT communication protocol to a cloud-based platform for monitoring and further analysis. ThingSpeak and MATLAB App Designer are used to provide real-time display, analysis, and supervision of the system's performance. Tests were conducted on a FESTO LabVolt hybrid power training system, and the results indicated that the data logger effectively captured the system's dynamic electrical parameters. It also enabled cloud-integrated real-time supervision.