Executive Summary : | The proposed research focuses on managing uncontrolled charging strategies in vehicle-to-grid (V2G) operation using a large number of EV data sets. The proposed models propose a load power estimation to effectively manage potential charging or discharging patterns. The proposed stochastic charging approach can reduce overall charging costs due to unpredicted charging patterns. The power consumption of vehicles is directly dependent on charging and discharging behavior, and an increase in charging stations can change the load profile in the electric network. The research investigates the impact of EV fleets on power system networks, establishing a flexible charging model based on historical datasets and driving behavior. The flexible dis(charging) algorithm addresses scheduled power requirements efficiently during peak times. The growing installations of EVs have led to challenges for distribution grids in maintaining active power flow and reducing peak power demand. The increasing distributed energy resources (DERs) make power consumers more reliable, but optimal control systems are necessary. The research investigates grid reliability and protection for GC hybrid power subsystems in different operating modes. |