MPPT for a Solar PV Array: ANN and P&O Comparison

In this study, an intelligent system that quickly and accurately determines a PV array’s maximum power point by using an artificial neural network is discussed. Maximum Power Point Tracking (MPPT) algorithms for solar photovoltaic (PV) systems are being developed so that we can capture maximum power from varying irradiance (sunlight) and temperature to ensure maximum output power. In this work, two methods of such MPPT techniques are discussed and compared using the same standalone PV system. Two algorithms, the perturb and observe (P&O) and artificial neural network (ANN), are explored and contrasted. Both these methods are used to extract the maximum output power from the PV array and then are compared to determine the better and more efficient option in terms of time consumed to execute the algorithm and the efficiency at which the power is extracted. The simulations required for this project are designed, coded, and executed in MATLAB environment. The ANN has a noticeably better responsiveness when compared to P&O.