Abstract
The photovoltaic (PV) panel can produce electrical energy that is very environmentally friendly and easy to use. The use of PV panels is suitable for supplying peak loads or at night using batteries as energy storage. However, the battery needs to manage for control, and the battery can last long. The solution to battery management problems is through research about the battery charging system. The DC-DC converter used is the Single Ended Primary Inductance Converter (SEPIC) type. Voltage Control of the battery charging using Adaptive Neuro-Fuzzy Inference System (ANFIS). In the simulation of bright conditions, ANFIS controls can track the charging point set point and obtain a voltage response with a rise time of 0.0028 s, a maximum overshoot of 0.027 %, a peak time of 0.008 s, and a settling time of 0.0193 s. When charging a solar tracker, PV battery gets a 0.25 % increase compared to a fixed PV panel. PV solar tracker can follow the direction of the sun’s position. The irradiation value and maximum temperature affect the input voltage and input current that enters the converter.
Highlights
Electrical energy is the energy needed in supporting human life, especially in meeting primary needs
The brown line is a set point, which is a constant voltage of 14.55 V, while the red line is the result of a stress control response from the Adaptive Neuro-Fuzzy Inference System (ANFIS) control design using PV fixed
The blue line is the result of the stress control response from the ANFIS control design using a photovoltaic solar tracker
Summary
Electrical energy is the energy needed in supporting human life, especially in meeting primary needs. In the process of energy conversion in the solar cell, this is influenced by many factors that can reduce the maximum work of energy conversion [2] These factors include orientation factors towards the position of the ever-changing sun. This research focused on the charging system for batteries Their aim to regulate the consumption of the results of the conversion of electrical energy in PV [5]. Adaptive Neuro-Fuzzy Inference System (ANFIS) is a combination of a fuzzy inference system mechanism It described in neural network architecture so that battery charging is more optimal and makes battery life a long life. The research will be conducted on the Design of Battery Charging Controls Using Adaptive Neuro-Fuzzy Inference System (ANFIS) in Solar-Based One Tracker PV using MATLAB / SIMULINK software
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