Dynamic Bi-Level Coordination of Heterogeneous EV Charging Demands and System Operations Under Uncertainties

The rapid adoption of electric vehicles (EVs) and electric vehicle charging stations (EVCSs) has introduced significant opportunities and challenges for modern power grids. While EVs and EVCSs offer high operational flexibility, enabling ancillary services and voltage regulation, their inherent behavioral randomness and dynamic interactions with continually evolving market rules pose critical challenges. Notably, the fluctuations in electricity prices driven by multi-layered uncertainties—stemming from EV demand variability, charging behaviors, and distribution system operator (DSO) regulations—exacerbate grid management complexities. To address these issues, this paper proposes a dynamic bi-level control framework that integrates real-time optimization and adaptive decision-making to mitigate the adverse impacts of these uncertainties. The framework incorporates a flexible and adjustable strategy that harmonizes the interests of key stakeholders, including DSOs, EV charging stations, and individual EV users. The proposed methodology is designed to alleviate negative market and grid effects by optimizing pricing mechanisms, bidding strategies, and grid resource allocation in real-time. The efficacy and robustness of the proposed framework are validated and evaluated through comprehensive simulations conducted on various realistic scenarios.