Design of an IoT-Based Control System for Energy Storage Efficiency and Monitoring

The increasing demand for efficient, transparent, and adaptive energy storage systems presents a significant challenge in supporting the global transition to renewable energy. This study presents the development of an Internet of Things (IoT)-based control system designed to optimize intelligent energy storage management. The system is built around an ESP32 microcontroller and integrates voltage, current, and temperature sensors, alongside wireless communication modules, all connected to a web-based dashboard for real-time monitoring. A dynamic control algorithm is employed to enhance the efficiency of the charging and discharging processes. Experimental results show a charging efficiency of 95% and a discharging efficiency of 94.74%, accompanied by a low data latency of 120 ms. The monitoring sensors demonstrate exceptional accuracy, with deviations within ±1% for voltage and current, and ±2°C for temperature, surpassing conventional systems. Compared to traditional approaches, the IoT-based system offers significant improvements in operational efficiency, data accuracy, and transparency in energy management. These findings highlight the potential of IoT integration in electronic control systems as an innovative solution for smart, efficient, and reliable energy storage. Future research should focus on scaling the system for industrial applications and incorporating artificial intelligence to predict performance and adapt system conditions in real-time

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Publication Details

Journal
JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGY
Published
2025-06-02
DOI
https://doi.org/10.31289/jmemme.v9i1.13342
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Design of an IoT-Based Control System for Energy Storage Efficiency and Monitoring

Muhammad Ferdiansyah, Siti Kholifah Kamino, Agus Salim Wardana
JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGY
Power Systems and Renewable Energy
article

Design of an IoT-Based Control System for Energy Storage Efficiency and Monitoring

Muhammad Ferdiansyah, Siti Kholifah Kamino, Agus Salim Wardana
article en

Abstract

The increasing demand for efficient, transparent, and adaptive energy storage systems presents a significant challenge in supporting the global transition to renewable energy. This study presents the development of an Internet of Things (IoT)-based control system designed to optimize intelligent energy storage management. The system is built around an ESP32 microcontroller and integrates voltage, current, and temperature sensors, alongside wireless communication modules, all connected to a web-based dashboard for real-time monitoring. A dynamic control algorithm is employed to enhance the efficiency of the charging and discharging processes. Experimental results show a charging efficiency of 95% and a discharging efficiency of 94.74%, accompanied by a low data latency of 120 ms. The monitoring sensors demonstrate exceptional accuracy, with deviations within ±1% for voltage and current, and ±2°C for temperature, surpassing conventional systems. Compared to traditional approaches, the IoT-based system offers significant improvements in operational efficiency, data accuracy, and transparency in energy management. These findings highlight the potential of IoT integration in electronic control systems as an innovative solution for smart, efficient, and reliable energy storage. Future research should focus on scaling the system for industrial applications and incorporating artificial intelligence to predict performance and adapt system conditions in real-time

JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGYVol. 9(1)
Universitas Teknologi Nusantara (ID)
Openalex Percentile: Top 72%
Power Systems and Renewable Energy
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Design of an IoT-Based Control System for Energy Storage Efficiency and Monitoring — Muhammad Ferdiansyah, Siti Kholifah Kamino, et al. · JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGY (2025) | TGRS Research Map | TGRS