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Khofifah Zhiya Ulhaq
Universitas Diponegoro

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Prototype Sistem Proteksi Terhadap Undervoltage dan Overvoltage pada Panel Distribusi Tegangan Rendah Berbasis Internet Of Things (IoT) Khofifah Zhiya Ulhaq; Yuniarto Yuniarto
Gema Teknologi Vol 22, No 1 (2022): April 2022 - Oktober 2022
Publisher : Vocational School Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/gt.v22i1.90230

Abstract

In this modern era, the stability of electrical systems plays a crucial role in sustaining various aspects of human life. Particularly in households and industry, a reliable and high-quality electricity supply is essential. However, electrical systems often face disruptions. Among these disruptions, overvoltage and undervoltage are serious concerns due to their significant impact. In this final project, the author designed a prototype system to protect against overvoltage and undervoltage in low-voltage distribution panels based on the Internet of Things (IoT). The goal is to minimize damage to electrical equipment caused by overvoltage or undervoltage. This prototype utilizes an Arduino Mega 2560 as the control center, collects data from a PZEM-004T sensor to measure electrical parameters, and displays the information on an LCD screen and via the Blynk app on a smartphone. The protection system in this thesis is designed to operate automatically upon detection of undervoltage or overvoltage. Based on the results of the experiments conducted, the IoT-based overvoltage and undervoltage protection system for low-voltage distribution panels is capable of cutting off the power supply to the load when overvoltage or undervoltage occurs. Alerts are provided via a buzzer and notifications on the Blynk app. In addition, the real-time monitoring system for voltage, current, and power per phase also functions as intended, with consistent and accurate data displayed on both the LCD and the Blynk app. Voltage measurements using the PZEM-004T sensor demonstrate excellent accuracy, with an error of 0.26% and an accuracy rate of 99.74%.