A maximum power point tracking of the photovoltaic system based on adaptive fuzzy-neural method

The aim of this paper is present an optimizing method to use of maximum capacity of the photovoltaic panels. Here, we are presenting a method for the maximum power point tracking in the photovoltaic systems by using of the neural networks and the adaptive controller. In the proposed system, we estimate an error by using of neural network. If this error was less than of the allowable systems error, the system is working at the maximum power point, and if the error value was greater than of the allowable error, the output power can be adjusted by using of the adaptive controller. The adaptive part of the proposed system, is consists of two fuzzy controllers with two different rule base. The first controller designed to produce the duty cycle of the boost converter and the second controller designed to adjusting online the outputs scaling factor of the first controller. We simulate the proposed system in the MATLAB software and then compare the output power of this system with the output power of the conventional fuzzy and the P&O methods. The comparison's results show that the proposed system has better performance with comparison of the two mentioned above methods.