DocumentCode :
3647668
Title :
ANN-based maximum power point tracking of photovoltaic system using fuzzy controller
Author :
Ahmet Afşin Kulaksiz;Ömer Aydoğdu
Author_Institution :
Department of Electrical and Electronics Engineering, Selcuk University, Konya, Turkey
fYear :
2012
fDate :
7/1/2012 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional perturbation & observation based method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.
Keywords :
"Fuzzy logic","Photovoltaic systems","Niobium","Artificial neural networks","Photovoltaic cells","Voltage control","Batteries"
Publisher :
ieee
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on
Print_ISBN :
978-1-4673-1446-6
Type :
conf
DOI :
10.1109/INISTA.2012.6246936
Filename :
6246936
Link To Document :
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