Maximum power point tracking control of photovoltaic system using neural network

This paper presents an application of a Neural Network for maximum power point tracking(MPPT) of PV supplied DC motor. A variation of solar radiation is most important factor in the MPPT of PV system. That is nonlinear, aperiodic and complicated. NN was widely used due to easily solving a complex math problem. The paper consists of solar radiation source, DC-DC converter, DC motor and load. NN algorithm applies to DC-DC converter through an adaptive control of neural network and calculates converter-chopping ratio using an adaptive control of NN. The results of an adaptive control of NN compared with the results of converter-chopping ratio which are calculated mathematical modeling and evaluate the proposed algorithm. The experimental data show that an adequacy of the algorithm was established through the compared data.