Implementation of Fuzzy Logic for Controlling the Recharge Rate Electric Vehicles and Minimizing Losses in the Electric Power System

The concerns about the environment have also grown considerably, raising serious questions about the harmful effects of pollutants emitted by automobiles. Allied to these reasons, there is also an increase in concerns about energy security and fossil energy reserves, which have been promoting a considerable dissemination of the use of plug-in electric vehicles (PEVs) in comparison to combustion-powered ones. The integration of EVs into the power grid introduces various challenges, including Dynamic Charging Demand, Grid Congestion, and Balancing Grid Load. Recent techniques to address these challenges include Machine Learning Approaches. This work develops a system based on fuzzy logic to control the recharge rate of plug-in hybrid electric vehicles (HEVs) in order to minimize losses in the electric power system (EPS). This work investigate the optimization strategy to minimize system losses. Also check the influence of the priority entered by the consumer in recharging a plug-in hybrid EV (PHEV). Also the importance of the optimization strategy in the system operation is investigated.