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Improved peak shaving and valley filling using V2G technology in grid connected Microgrid

During the last decades, the development of electric vehicles has undergone rapid evolution, mainly due to critical environmental issues and the high integration of sustainable energy sources. The large-scale integration of these vehicles will impact the operations and planning of the power grid. In this paper, we focused on an electric vehicle charging/discharging (V2G) (Vehicle to grid) energy management system based on a Tree-based decision algorithm for peak shaving, load balancing, and valley filling in a grid-connected microgrid. The main objective is to provide an optimal clipping strategy based on the use of EV as mobile storage means to reduce critical customer demand, fill off-peak periods by considering vehicle requirements, load demand, and electricity price variation. The study developed in MATLAB/Simulink is applied on a grid-connected microgrid that includes a grid-connected photovoltaic array, a variable hybrid load (industrial and residential), and an EV charging station that receives 10 vehicles during the day depending on the users' lifestyle. Two load peaks are expected during the day (one due to the start-up of industrial areas and another due to high consumption in the evening) are tested to see the behavior of the management system in peak reduction. The simulation results demonstrated the performance of the V2G technology in peak management applications. The analysis of the results proved the robustness of this solution in peak shaving during high demand periods and valley filling during off-peak hours by allowing a smoothing of the load curve and better exploitation of the micro grids.