Maximum Power Point Tracking Control using Neural Network for Photovoltaic Systems

Actually, renewable energy resources play a significant role in replacing conventional fossil fuel energy resources. Photovoltaic energy is one of the very promising renewable energy resources which quickly grew in the past few years. The Photovoltaic has one main problem which is with the variation of the operating conditions of the array, the voltage at which maximum power can be obtained from it likewise changes. In this paper, a Photovoltaic model is used for simulating actual Photovoltaic arrays behavior, and then a Maximum Power Point tracking technique using neural networks is proposed in order to control the DC-DC converter. Moreover, the proposed artificial neural network technique is compared to the conventional maximum power point tracking technique named perturb and observe. Simulation results shows that the proposed artificial neural network maximum power point tracking technique gives faster response than the conventional Perturb and Observe technique under rapid variations of operating conditions.