GW optimization based MPPT for solar photovoltaic system

Abstract

The most efficient and cleanest form of renewable energy source for effective power generation is the solar photovoltaic (PV) system. In recent years, solar energy generation has become an essential part of electric power applications. The power produced by the solar PV system is unstable, as it depends upon illumination and global climatic change. So as to get the uttermost efficacy the solar PV system must be guided at the maximum point. An efficient MPP tracking method has a vital function to play in upgrading the efficacy of a solar PV system. The operational point of the perturb and observe (P&O) approach swings about MPP at a steady state, resulting in power output variations. In this work, the Grey Wolf (GW) optimization-based MPPT is proposed. The GW is a Metaheuristic optimization technique that extracts the highest amount of energy from a solar PV system. The PV module’s voltage and current are utilized as inputs and the duty ratio is the indeed output that has been obtained and it is been tested under different operating conditions. Depending on the fluctuations in input power, a DC/DC boost converter is utilized to increase the wattage of the output. To estimate the usefulness of this MPPT, the outcomes of GW are correlated with the P&O approach and outcomes demonstrate the GW MPPT gives better power output and its convergence time is faster than the P&O method for change in irradiation levels.