Quantum-Secure Artificial Intelligence: A Degradation-Free V2G Strategy for Frequency Stability in Multi-Microgrids
TL;DR
A quantum-empowered degradation-aware V2G coordination framework for smart-city MMGs considering communication security and user travel demands that completely immunizes the system against FDIAs, effectively suppresses frequency fluctuations, and significantly reduces battery degradation costs while preserving user mobility.
Abstract
Background: With the deepening coupling of multi-microgrids (MMGs) and transportation systems in smart cities, maintaining frequency stability under extreme conditions increasingly relies on vehicle-to-grid (V2G) flexibility. However, existing V2G dispatch strategies often overlook the noticeable battery degradation caused by high-frequency regulation and the vulnerability of extensive communication networks to false data injection attacks (FDIAs), while the high-dimensional coordination of EV routing and discharging makes classical algorithms struggle to converge. Methods: To address these challenges, this study proposes a quantum-empowered degradation-aware V2G coordination framework for smart-city MMGs considering communication security and user travel demands. At the physical layer, an equivalent RC circuit-based battery degradation model and a traffic flow model are established to quantify capacity loss and travel delays. At the cyber layer, quantum key distribution (QKD) ensures unconditionally secure communication, while a quantum reinforcement learning (QRL) algorithm is developed to achieve fast convergence in high-dimensional multi-objective optimization. Results: Simulation results demonstrate that the proposed framework completely immunizes the system against FDIAs, effectively suppresses frequency fluctuations, and significantly reduces battery degradation costs while preserving user mobility. Conclusions: This framework provides a highly secure and user-friendly pathway for resilient smart-city frequency regulation.