The Design and Analysis of Energy Management for the Optimal Charging of Electric Vehicles Based on Estimated Power Flow and Load Conditions at Electric Vehicle Stations Using Fuzzy Logic Controllers

Electric vehicles have become one of the alternatives for managing energy crises in the transportation sector. An increase in the number of these vehicles without being accompanied by a good charging station management system will have negative impacts on the network distribution system, such as voltage fluctuations, drops, stress, low power continuity, and even cause blackouts. Hence, designing an energy management system for electric vehicles at charging stations is necessary to obtain an optimal power flow model between the charging station and the grid. In this project, the optimal charging design and analysis were designed by considering the estimated power flow between the charging station and the grid, alongside the load conditions on the grid (off-peak/peak), using a fuzzy logic controller. This charging management uses the vehicle to vehicle (V2V), vehicle to grid (V2G), and grid to vehicle (G2V) concepts, which are regulated by the filling index and rating of the fuzzy rule scores. Through the two inputs above, the simulation results showed that the fuzzy-based system can flatten the peak load curve of electric vehicles, reduce the impact of peak loads on the grid, and provide cost-saving benefits.