Grid Connected Renewable Energy Source with Multi Objective Grey Wolf Optimization

Abstract

Renewable energy sources like wind and solar will continue to grow in smart power systems through 2050, according to energy predictions. Due to the intermittent nature of these energy sources, using a grid entirely made of renewable resources is extremely unreliable and may result in certain operational problems. It is significantly important in applications and industry since the fundamental purpose of optimization is to find the best practical solution to a particular problem of interest. In this study, we suggest using the multi-objective Grey Wolf Optimizer (MOGWO), a more recent meta-heuristic that draws inspiration from the hunting habits and social structure of grey wolves, to optimize fuzzy controllers for mobile autonomous robots. The integration of storage facilities contributes to the upkeep of system balance Integration of storage facilities contributes to the preservation of system equilibrium. To analyze and discuss the proposed technique based on MOGWO and give simulation results for a two-wheeled autonomous mobile robot.