Design of Artificial Neural Network Controller for Photovoltaic System

The increasing use of non-renewable sources to produce power energy is raising major environmental concerns. To meet this challenge, the use of alternative sources of energy has being developed, such as solar energy which is widely used for power generation due to the abundant availability of solar radiation and its minimal pollution impact. However, reducing the cost and improving the harnessing efficiency of natural sources use is very important in boosting power plant performance. Therefore, many solutions have emerged and, the maximum power point tracking (MPPT) system is most frequently employed for solar energy. It is used to maximize the production of electrical energy from photovoltaic panels. The aim of this paper is to evaluate the performance of MPPT using an artificial neural network (ANN) method that is used with a DC-DC boost converter to provide constant output to a load in a photovoltaic system. The duty cycle is generated by the ANN algorithm, based on irradiation conditions and temperature changes.