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Journal : Jurnal Teliska

 1 
IMPLEMENTASI PLTS OFF-GRID 200 WP DENGAN SISTEM MONITORING BEBAN BERBASIS ARDUINO UNO Anggoro, Muhammad Aji; Amperawan
JURNAL TELISKA Vol 17 No III (2024): Teliska November 2024
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14004912

Abstract

Electrical energy is energy that is very much needed for modern human life today. One of them electrical energy can be generated from solar energy or solar heat. Solar energy is a renewable energy for solar power generation systems that aim to provide renewable energy supplies to households by implementing using an off-grid PLTS system with a capacity of 200 Wp that can function effectively. The implementation of the off-grid PLTS system is carried out by several methods by means of literature, consultation, and observation. Based on the implementation of the 200 WP off-grid PLTS system with arduino uno-based load monitoring for solar panel test results show that solar panels are able to produce voltage and current in accordance with the expected specifications and it is known that energy conversion reaches high efficiency when the weather is in optimal conditions. The PZEM-004T sensor shows accurate and real-time voltage, current, and power measurements. The test results prove that the integration of the PZEM-004T sensor in the Arduino Uno-based load monitoring system for off-grid solar power plants provides significant benefits in terms of measurement accuracy and energy efficiency.
PERANCANGAN SISTEM KERJA PENERANGAN JALAN UMUM MENGGUNAKAN TENAGA SOLAR CELL BERBASIS INTERNET OF THINGS Oktavia, Bela; Amperawan
JURNAL TELISKA Vol 17 No III (2024): Teliska November 2024
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14347618

Abstract

This research discusses the design of a public street lighting system utilizing a 50 Wp solar cell, an 18 Ah battery at 12V, an ESP32 microcontroller, an LDR sensor, an INA219 sensor, and the Blynk platform for monitoring. The system is designed to provide an efficient and eco-friendly lighting solution by harnessing renewable energy from solar panels. The main components of the system include a solar panel that converts solar energy into electricity and stores it in the battery for nighttime use. An LDR (Light Dependent Resistor) sensor is used to detect ambient light intensity, allowing the system to automatically turn on the lights at night and turn them off during the day. The INA219 sensor functions to measure the voltage and current flowing from the solar panel to the battery and from the battery to the light, ensuring efficient energy management. The ESP32 microcontroller serves as the brain of the system, integrating data from the LDR and INA219 sensors to control light operations and send data to the Blynk platform. Blynk is used as a remote monitoring system.
ANALISA KETEPATAN ENCODER PADA SISTEM STEERING AUTONOMOUS ELECTRIC CAR METODE PULSE COUNTER: Teknik Elektro Romadhon, M. Rizki; Amperawan; Nawawi, Muhammad
JURNAL TELISKA Vol 16 No II Juli (2023): TELISKA Juli 2023
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.8167144

Abstract

The encoder in the steering system of an Autonomous electric car is a component used to determine the direction andposition of the racksteer displacement in the Autonomous electric car itself. The advantage of the encoder in this steeringsystem is its ability to read the number of rotations and direction of rotation of the car's steering wheel through pulsereadings from both channels of the encoder, without the need for additional specialized sensors. The data generated by theencoder is then used as a reference to ensure that the racksteer position is in the correct position during automatic controlin autonomous driving mode. Automatic control in an Autonomous electric car is achieved by reading the car's positionrelative to the road using lane detection methods through digital image processing on Raspberry Pi 4. The results of imageprocessing provide data such as direction and speed required by the car to accelerate when approaching or exiting a turn.The data from Raspberry Pi 4 is then received by the microcontroller to command the motor on the racksteer, taking intoconsideration the previous position of the racksteer obtained through the encoder.
ANALISA SISTEM KENDALI KECEPATAN MOTOR BLDC PADA MOBIL AUTONOMOUS MENGGUNAKAN PWM (PULSE WIDTH MODULATION) BERBASIS ARDUINO Amran, Fajar; Amperawan; Annisah, Masayu
JURNAL TELISKA Vol 16 No III November (2023): TELISKA November 2023
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.8375870

Abstract

Bldc motor is an alternative component for autonomous electric car because it has several advantages over conventional DC motors which still use brushes and commutators, while bldc motors do not use brushes and commutators but use electronic circuits to control the bldc motor with high efficiency, high operating life, high maintenance. low and low noise. By using a universal mosfet driver that has a hall effect sensor, hall effect can help calculate the pwm of a bldc motor controlled by arduino. The arduino controlling the universal mosfet driver will calculate using the pwm system of the bldc motor. This system will help the autonomous electric car transportation industry in controlling speed.
MONITORING ARUS DAN TEGANGAN PENERANGAN LAMPU JALAN BERBASIS INTERNET OF THINGS Hidayah, Arini Alfa; Amperawan
JURNAL TELISKA Vol 18 No I (2025): TELISKA Maret 2025
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15052833

Abstract

The purpose of this research is to develop an Internet of Things (IoT) based system capable of monitoring the current and voltage of street lighting. This system utilizes the INA219 sensor to measure the voltage and current generated by the solar panel, which is then sent in real-time through the NodeMCU module using WiFi to the Blynk application. Test results show that the INA219 sensor has good accuracy, with an average error of 0.73% for voltage and 0.75% for current. This monitoring system enables effective remote monitoring of solar cell performance, with data displayed on the Blynk app in real-time and accurately.
Co-Authors A Rahman Abraham Horisanto Amran, Fajar andi Dahlan Anggoro, Muhammad Aji Anisah, Masayu Annisah, Masayu Arsy Ananta, Mohammad Hidayah, Arini Alfa Ilham Wahyu Pamungkas Latifah Husni , Nyayu Muhammad Nawawi Nur Aziz, Arman Oktavia, Bela Romadhon, M. Rizki Venny Agustin Willy Wijayanti