Bacterial Foraging Optimization Based Maximum Power Point Tracking for Photovoltaic System under Partially Shaded Condition with Interleaved Resonant Fly-back Converter

Abstract

Due to the non-uniform temperature and irradiance level of PV array, Maximum Power Point Tracking (MPPT) techniques are becoming more common to boost the system efficiency even under varying and unpredictable weather condition. Selection of small value of step size consequence in more convergence for MPPT and large value produces more power oscillations. Therefore, we propose Bacterial Foraging Optimization (BFO-MPPT) algorithm to optimally choose the value of duty cycle that helps to operate the converter at MPP. Moreover, the interleaved converter helps to attain large output power with less ripples and high efficiency. The results prove that the BFO-MPPT can achieve less burden during computation and low computational time with global convergence.