A survey of the maximum power point tracking method and artificial neural networks for photovoltaic cell

چکیده مقاله

In recent years, the solar energy has been considered as one of principal renewable energy sources for electric power generation. In a PV system, the PV modules generate D.C  electricity which is used to charge batteries through a charge controller. Meanwhile, inverters convert the D.C current to A.C current. However, the main drawbacks of PV systems are the capital cost and the dependence on climate conditions such as solar radiation and ambient temperature. However, the maximization of extracted power from PV system is a matter of concern as its conversion efficiency is low. Therefore, a maximum power point tracking (MPPT) controller is necessary in a PV system for maximum power extraction. This paper presents a new model of a PV module and a maximum power point tracking (MPPT) system for solar cell. The proposed technique is based on Artificial Neural Network. The equivalent circuit model of the solar cell includes the parameters of each sub-cell. The simulation results of the proposed MPPT technique are compared with Perturb and Observe MPPT technique. The output power of the proposed technique is higher than that of the Perturb and Observe (P&O) MPPT technique. 

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