AbstracT
Solar energy is a clean and renewable energy. The cost of electricity from the solar array system is more expensive than the electricity from the utility grid. The amount of power generated from a photovoltaic system mainly depends on the following factors, such as temperatures and solar irradiances. Due to the high cost and low efficiency of a PV system, it is necessary to operate the PV system at maximum efficiency by tracking maximum power point at any environmental condition.
This proposed system improves the maximum power point tracking algorithm of a PV system under real climatic conditions. This proposed MPPT is based on the hill climbing method with neural network controller that control the load voltage to ensure optimal operating points of a PV system. The proposed MPPT algorithm has been implemented by a neural network controller and it eliminates the drawbacks of hill climbing algorithm. The simulation result shows that the PV power system, using the proposed MPPT algorithm, is able to accurately track the maximum power points under rapid irradiance variations.
