Neural network Incremental conductance MPPT algorithm for photovoltaic water pumping system

In this paper, an intelligent Incremental conductance based neural network (ICNN) algorithm is proposed for the maximum power point tracking control of a photovoltaic water pumping system. The objective of this work is to improve the accuracy of the standard IC command in term of rapidity. The proposed strategy combines the neural network (NN) off line learning technique with the standard IC. The NN is used for initializing the system near the optimal maximum point and the IC is used for fast reaching to the MPPT. By comparison with the standard IC algorithm under rapidly changing Atmospheric conditions, the simulation results show the best performance for the proposed ICNN algorithm in term of convergence rapidity.