Open AccessImproved Efficiency of photovoltaic Module Based on Fuzzy Logic MPPT Technique
Author(s) -
Hayder Moayad Abd Alhussain,
Naseer M. Yasin
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/745/1/012006
Subject(s) - maximum power point tracking , duty cycle , photovoltaic system , maximum power principle , boost converter , control theory (sociology) , buck converter , controller (irrigation) , computer science , power (physics) , power optimizer , engineering , voltage , electrical engineering , inverter , physics , control (management) , agronomy , quantum mechanics , artificial intelligence , biology
In photovoltaic (PV) systems, the maximum power point trackers are very important for increasing their efficiency. Maximum power can be achieved by using different methods such as P&O, INC so that the PV module can operate under different weather conditions and still produces maximum output power. In this paper, a smart method is presented for a maximum power point tracking (MPPT) based on a fuzzy logic control (FLC). The photovoltaic system consists of a solar panel type MXS 60W, DC-DC boost converter, FLC (MPP) tracker and resistive load are analyzed and simulated in MATLAB program. The output voltage of the solar panel is increased by the boost converter and it depends upon the duty cycle (D) of the MOSFET of the boost converter. Any change in the duty cycle is performed through sensing the output power of the solar panel. The controller tracks the maximum power of a solar panel by adjusting the duty cycle of the DC-DC converter switch. The simulation results show that the FLC controller can track the Maximum Power Point in a shorter time with less power oscillation around the MPP as compared to the most widely conventional method known as perturb and observe (P&O). Both techniques have been modeled and simulated in (MATLAB/Simulink).