Uncertainty based Electric Vehicle Charging Scheduling with V2G feature considering Photovoltaic and Battery Energy Storage

This paper proposes a charging scheduling algorithm for Electric Vehicles (EV) considering various bidirectional charging/discharging mode of operations with and without considering Renewable Energy Sources (RES) and Battery Energy Storage system (BES). A simultaneous charging scheduling algorithm is proposed to minimize the total daily cost of charging in different scenarios and a cost benefit analysis is performed to find out the optimal combinations among these. Battery degradation is also integrated to extract more benefits in optimal charging scheduling. The algorithm is developed in such a way that both Charging Station Operators (CSO) and EV Owners (EVO), can be in win-win situation. The uncertainty related to EV driving cycles, and Photovoltaic (PV) power output is handled by integrating 2m-Point Estimation Method (2m-PEM). Later, the robustness and consistency of the proposed algorithm is verified by applying statistical non-parametric analysis.