Maximum Power Point Tracking of Single-Phase Grid Connected PV based DC Microgrid System using Modified BBO Algorithm with PR Controller

The depletion of fossil fuels has made the world move toward distributed energy resources for power generation. Due to their simplicity of installation, photovoltaic (PV) systems are widely used for power generation. In order to serve the world of the ever-growing population with the increasing energy demand, it is important to extract the maximum power from PV solar systems to use them either in stand-alone or grid-connected mode. In the literature, various algorithms for the extraction of maximum power are explored. In this work, the Adaptive Quasi-Oppositional Differential Migrated Biogeography Based Optimization (AQDMBBO) algorithm is used for the novel application of maximum power point tracking (MPPT) of a solar PV system, which is integrated with a single-phase grid. This algorithm exhibits simplified implementation with rapid convergence and maximum power extraction from solar panels. The efficacy of AQDMBBO is analysed by comparing its performance with the conventional BBO and Grey Wolf Optimization algorithms for MPPT of the given PV system. From the results, it is concluded that AQDMBBO exhibits higher accuracy, faster settling time and less duty variation for tracking the PV maximum power.