NDLI: ANN-based maximum power point tracking of photovoltaic system using fuzzy controller

Content Provider	IEEE Xplore Digital Library
Author	Kulaksiz, A.A. Aydogdu, O.
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Electronics Engineering, Selcuk University, Konya, Turkey (Kulaksiz, A.A.; Aydogdu, O.)
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.
Starting Page	1
Ending Page	5
File Size	758596
Page Count	5
File Format	PDF
ISBN	9781467314466
e-ISBN	9781467314480
DOI	10.1109/INISTA.2012.6246936
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-02
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Photovoltaic systems PV system Photovoltaic cells Maximum power point tracking Artificial neural networks Batteries Fuzzy controller Voltage control Dc-dc converter Niobium
Content Type	Text
Resource Type	Article

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