Performance Comparison of the Single Axis and Two-Axis Solar System using Adaptive Neuro-Fuzzy Inference System Controls

Abstract

Solar energy is one of the renewable energy that gets more attention from many countries. Solar photo voltaic (PV) takes the right position to get the maximum energy yield. The study was conducted by comparison of performance with two methods of tracking the sun with one axis and two axes by using ANFIS control (Adaptive Neuro-Fuzzy Inference System). The solar tracking system is a system that operates on the sun by using a light sensor and controls the photovoltaic to always perpendicular to the sun by changing the pitch and yaw axis of the sun tracing properties. LDR (Light Dependent Resistor) is one of the light sensors whose resistance changes depending on the intensity of incoming light. Direct current (DC )motor is used as a PV drive panel in a solar tracking system. A two-axis solar tracking system has a greater power output than a tracking system with a single photovoltaic panel that does not use a tracking system (fixed).

Design of Bacterial Foraging Interval Fuzzy Logic Controller on Hybrid Solar Tracker-Ocean Wave Energy Converter

“…This research can improve the deficiencies of previous research, namely a one-axis solar tracker system. Some artificial intelligent control methods have applied to the solar tracker system such as fuzzy, fuzzy PSO, fuzzy type-2, etc [4], [5], [14], [15], [6]- [13]. In 2015, Abadi et al could increase efficiency by 50-60% using fuzzy control based PSO (Particle Swarm Optimization) optimization methods on a two-axis solar tracker system [16].…”