Volume 6, Number 4 (1-2017)                   JEM 2017, 6(4): 26-31 | Back to browse issues page


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khademi R, mohammadi M A. Maximum Power Point Tracking of the Photovoltaic System Based on Adaptive Fuzzy-Neural Method. JEM. 2017; 6 (4) :26-31
URL: http://energy.kashanu.ac.ir/article-1-396-en.html

M.Sc. Student
Abstract:  

The aim of this paper was to present an optimized method in order to use maximum capacity of the photovoltaic panels. In this regard, we presented a method for the maximum power point tracking in the photovoltaic systems by using the neural networks and adaptive controller. In the proposed system, we estimated an error by using neural network. If this error is lower than the allowable systems error, the system works at the maximum power point, and if the error value is greater than the allowable error, the output power can be adjusted by using the adaptive controller. The adaptive part of the proposed system consisted of two fuzzy controllers with two different rule bases. The first controller designed to produce the duty cycle of the boost converter and the second controller designed to adjust online the outputs scaling factor of the first controller. We simulated the proposed system in the MATLAB software and then compared the output power of this system with the output power of the conventional fuzzy and the P&O methods. The comparison results indicated that the proposed system had better performance compared to the two above-mentioned methods.

Type of Study: Research | Subject: Electrical Engineering

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