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