Fuzzy logic assisted P&O based improved MPPT for photovoltaic systems

Abstract

To make full utilization of PV array, maximum power point tracking (MPPT) techniques are employed, which controls the power converter between the PV panel and the load to keep the system power operating point at its maximum. Perturbation and observation (P&O) method is the most frequently used method for MPPT, however, with smaller step size system taking long time to track MPP, with larger step size operating point oscillation is more in steady state. These obstacles are minimized by using variable step size with fuzzy based MPPT controller. In this research work, a Fuzzy Logic Controller (FLC) based P&O MPPT has been designed for optimal performance. The proposed method adjusts the step size in P&O method to provide faster and accurate convergence at peak power point. The input reference voltage is perturbed adaptively with optimal steps until the maximum power is reached. For evaluation, FLC based MPPT technique is simulated on MATLAB/ Simulink environment and compared with the conventional P&O technique. Results clearly show that proposed technique is able to track maximum output power with less settling time, reduced oscillations at steady state and enhance the operating point convergence speed.