Renewable Energy Resources are viable and dependable solutions for achieving universal electricity access rapidly. Among these, Solar Photovoltaic (PV) stands out, despite its variable output power caused by fluctuations in solar radiation, cell performance, and ambient temperatures. Additionally, the modules utilized often exhibit lower conversion efficiency. Consequently, the implementation of maximum power point tracking becomes imperative to optimize energy harvesting from the sun and enhance the overall efficiency of photovoltaic systems. A microgrid has been designed with a Solar PV Cell and battery system in MATLAB, and a comparative study of maximum power point tracking using Particle Swarm Optimization (PSO), Flying Squirrel Search Optimization (FSSO), and Horse Herd Optimization (HHO) techniques is presented in this work. The Comparison of output power with different changing input parameters like irradiation and temperature has been carried out in this work. The comparative study of the said algorithm is also depicted by figures and tables.