Optimal Energy Transactions for Bidirectional Charging Stations Enabling Grid Ancillary Services

This paper proposes a novel control algorithm to use bidirectional charging of electric vehicles (EVs) in the framework of vehicle-to-grid (V2G) technology for optimal energy transaction and investment. The energy storage components of an electric charging station, including the buffers of energy, provide the opportunity to sell energy to or buy energy from a smart grid that not only improves the stability and power quality of the grid but also offers the possibility to the charging station owner and the EV drivers to benefit from the trades in the energy market financially. Therefore, a model predictive controller (MPC) is developed to maximize the profit of the charging station and satisfy the EVs minimum state of charge (SOC) requirement while participating in incentive-based ancillary programs of the grid. The proposed algorithm changes the energy investment in the components when the price of energy changes with time, especially the price of the grid's energy, to keep the optimality of the energy shares. The simulation results confirm the effectiveness of the proposed control strategy.