Intelligent Charging Scheduling of Plug-In Electric Vehicles and Priority Premium Determination for Users in Parking Station

The electrification of transport is seen as one of the main pathways to achieve significant reductions in CO₂ emissions. However, there are some issues related to it like, a sudden increase in electricity demand, high charging cost in dynamic price market, attending user's priority in charging his/her vehicle and the premium to be levied for such priority. In this paper, an intelligent charging strategy for Plug-in Electric Vehicle(PEV) incorporating a unified grid-to-vehicle(G2V) and vehicle-to-grid(V2G) framework with users' priority is proposed for optimal integration of PEVs in the existing distribution system. The intelligent strategy with objective function considering minimization of total charging cost, with users' priority as well as without priority is developed to study the impact of PEV integration from economic and technical perspective. The proposed strategy is implemented on test bench case consisting of 5 similar PEVs in a parking station. The uncertain parameters like PEV availability at charging station are handled using Monte-Carlo simulation. The bi-linear constraints are modified to pose the problem as a linear optimization problem. A comparative analysis is done on the charging cost with priority and without priority to investigate the economic impact of introducing users' priority. Finally, an investigative study is conducted to assign economic value to priority so the premium can be charged to users for assigning priority to their vehicles. The simulation results present a comprehensive evaluation of the proposed strategy.