Perbandingan Efisiensi Daya Pada Solar Charge Controller Menggunakan Maximum Power Point Tracking (MPPT) dengan Metode Algoritma Adaptive Neuro-Fuzzy Interence System (ANFIS) dan Incremental Conductance Berbasis IoT

Hafizh Prasetio Utomo (Universitas DIponegoro)
Arkhan Subari (Universitas DIponegoro)

GEMA TEKNOLOGI
Vol 22, No 1 (2022): April 2022 - Oktober 2022

Solar panels are a type of renewable energy technology that can convert energy from sunlight into electrical energy. Solar panels consist of an array of solar cells arranged in such a way as to effectively absorb sunlight. Solar panels provide a readily available and free source of renewable energy; however, their efficiency remains relatively low. MPPT (Maximum Power Point Tracking) solar charge controllers are designed to maximize the power output from solar panels and regulate battery conditions to prevent overcharging. This study aims to compare the Adaptive Neuro-Fuzzy Inference System (ANFIS) method and the Incremental Control method using a boost converter to achieve maximum output in terms of voltage, current, and power using an MPPT module. Simulations were conducted using both sunlight and artificial light. Additionally, this MPPT system is integrated with IoT control using an ESP32 microcontroller for remote control.