Title :
Anfis based a two-phase interleaved boost converter for photovoltaic system
Author :
Radianto, Donny ; Shoyama, Masahito
Author_Institution :
Dept. of Electr. Eng., Kyushu Univ., Fukuoka, Japan
Abstract :
In this paper, A two-phase interleaved boost converter (IBC), which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for photovoltaic (PV) system is proposed. The proposed system has two inputs and 1 output. Two inputs of the proposed system consist of solar irradiation and temperature. Meanwhile, the output of the proposed system is aduty cycle. The duty cycle is used to generate Pulsed Width Modulation (PWM), which serves to activate MOSFET. Furthermore, the proposed ANFIS features 20 epochs and utilizes hybrid mechanism to train data. Some simulations of IBC combined with PV system have been performed using Matlab/SIMULINK. Furthermore, some comparisons of two different methods have been carried out to validate the results. The comparison analysis results indicate that the system using ANFIS can obtain higher voltage than the system using FLC. In addition, the proposed system is also able to reduce overshoot and be able to increase the output power.
Keywords :
electrical engineering computing; fuzzy neural nets; inference mechanisms; photovoltaic power systems; power convertors; ANFIS; MOSFET; PWM; adaptive neuro-fuzzy inference system; photovoltaic system; pulsed width modulation; solar irradiation; temperature; two-phase interleaved boost converter; Inductors; MOSFET; Maximum power point trackers; Observers; Pulse width modulation; Radiation effects; Steady-state; A Two-Phase Interleaved Boost Converter; Adaptive Neuro Fuzzy Inference System; Fuzzy Logic Controller;
Conference_Titel :
Innovative Computing Technology (INTECH), 2014 Fourth International Conference on
Conference_Location :
Luton
DOI :
10.1109/INTECH.2014.6927754