Electric Vehicle Charging Scheduling Strategy for Supporting Load Flattening Under Uncertain Electric Vehicle Departures

The scheduled electric vehicle (EV) charging flexibility has great potential in supporting the operation of power systems, yet achieving such benefits is challenged by uncertain and user-dependent nature EV behavior. Existing research primarily focuses on modeling arrival battery status rarely discusses uncertainty departure. In this paper, we investigate scheduling strategy to support load flattening at distribution level utility grid under departures. A holistic methodology proposed formulate unexpected trip mitigate its negative impacts. To ensure computational efficiency when large fleets are involved, a distributed solution framework developed based alternating direction method multipliers (ADMM) algorithm. numerical results reveal that trips can severely damage user convenience terms energy content. It further confirmed applying methodology, resultant critical sub-critical losses due reduced significantly 83.5% 70.5%, respectively, whereas performance merely sacrificed 17%.