MPPT controller based on the neural network model of the photovoltaic panel

In this paper, we propose the MPPT algorithm that is based on the single-layer neural network model of the photovoltaic panel. It has been shown that the neural network can be employed to accurately model the relationship between the photovoltaic panel current, voltage, solar irradiance, and temperature. Unlike the equivalent circuit model, the neural network model can be used to calculate the gradient of the P-V curve, thus enabling the design of the simple MPPT technique that relies on the steepest ascent method. Simulation results show that the proposed algorithm exhibits a faster convergence speed and a smaller steady-state error than the conventional P&O algorithm.