DocumentCode :
3253118
Title :
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
Link To Document :
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