AI based MPPT methods for grid connected PV systems under non linear changing solar irradiation

Author

Arora, Ankita ; Gaur, Prerna

fYear

2015

fDate

19-20 March 2015

Firstpage

542

Lastpage

547

Abstract

This paper presents the artificial neural network (ANN), fuzzy logic controller (FLC) maximum power point tracking (MPPT) methods in grid connected photovoltaic (PV) systems for optimizing the solar energy efficiency. All the methods are simulated in MATLAB-Simulink, respectively together with SunPower-SPR305 PV module connected to single-ended primary inductor converter (SEPIC). Performance assessment covers efficiency, overshoot, settling time response, oscillations and stability.

Keywords

fuzzy control; maximum power point trackers; neural nets; photovoltaic power systems; power engineering computing; power generation control; sunlight; AI based MPPT methods; ANN; FLC; MATLAB; SEPIC; Simulink; SunPower-SPR305 PV module; artificial neural network; fuzzy logic controller; grid connected PV systems; grid connected photovoltaic systems; maximum power point tracking; nonlinear changing solar irradiation; oscillations; settling time response; single-ended primary inductor converter; Artificial neural networks; Computers; Fuzzy logic; Mathematical model; Maximum power point trackers; Niobium; Radiation effects; Artificial Neural Network; Fuzzy Logic Controller; Maximum power point tracking; Photovoltaic; Single-ended primary inductor converter;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in

Conference_Location

Ghaziabad

Type

conf

DOI

10.1109/ICACEA.2015.7164752

Filename

7164752