Integration of Electric Vehicles and Renewable Energy Distributed Generators into the Smart Grid using Optimization Method

Due to fossil fuel shortages, environmental concerns, and smart network challenges, Renewable Energy Distributed Generators (REDGs) and electric vehicles (EVs) are being advocated. Electric vehicle (EV) development and marketing have grown in recent decades. Electric vehicles are expected to dominate road transportation in the future. Electric vehicles should help power networks balance load and store energy. This article examines electric vehicles' secondary function and power system effects, particularly in the case of considerable integration. The work introduces an optimization technique for electric vehicle capacity prediction, objective function optimization, station locations and sizes, and system costs. The study found that this technique to electric vehicle capacity forecasting accurately depicts electric vehicle charging and discharging. This study introduces hybrid genetic algorithm improved particle swarm optimization (HGAIPSO) to strategically locate electric vehicle charging stations with regulated charging and renewable energy distribution generators. This method addresses the issues above. By minimizing voltage violation, energy loss, and cost, the suggested charging method improves power quality and lowers system expenses. Simulation of the IEEE-118 bus system in MATLAB to evaluate the existing technology.