Cost Minimization of Microgrid Using PSO Algorithm with Renewable Energy Sources and Electric Vehicles

In light of technological advancements and natural calamities, contemporary businesses are exhibiting a heightened inclination toward investigating energy efficiency, reliable power sources, and superior electricity quality for alternative energy sources, particularly renewable energy sources. Consequently, microgrids with distributed generation lay the groundwork for properly distributing power to consumers in an economical, safe, and successful manner. While meeting the system's demand and limitations, it is necessary to decrease the operating costs of a low-voltage microgrid that includes Plug-in Hybrid Electric Vehicles (PHEVs) and renewable energy sources (RESs) like photovoltaics, wind turbines, microturbines, or fuel cells. The proposed scheduling system describes the unknown PHEV and RES characteristics using the Monte Carlo simulation (MCS). The consequences of different PHEV behaviors on MGs are modeled by studying three different charging procedures. A hybrid metaheuristic method based on particle swarm optimization is described in this article. Optimizing distributed generation in microgrids is the goal of the price optimization issue, which is expressed as a nonlinearly limited mathematical problem. Results show that the hybrid method performs optimally when tested with low-voltage microgrids.