Hierarchical Coordination of Smart Inertia-Damping Control and Artificial Bee Colony Scheduling for Resilient Grid-Forming PV-Hybrid Storage Systems

Extreme meteorological events pose critical threats to the operational reliability of contemporary distribution networks. This study develops a comprehensive disaster mitigation framework for grid-forming photovoltaic (PV) systems integrated with multi-source hybrid energy storage. To enhance regulation across heterogeneous timescales, a high-fidelity model is formulated, incorporating PV units, electric vehicle swapping stations (EVSS), and supercapacitors. A multi-dimensional resilience evaluation architecture is established, synthesizing device-level dynamics—inertia, damping, and fault response—with system-level frequency and voltage restoration metrics.The methodology features hierarchical coordination of Smart Inertia-Damping Control (SIDC) and Bee Colony Synergy (BCS) scheduling. The SIDC layer employs reinforcement learning for autonomous calibration of virtual inertia and damping coefficients during disturbances. Concurrently, the BCS layer utilizes swarm intelligence to optimize the spatiotemporal allocation of energy resources. A bidirectional feedback mechanism ensures seamless integration between millisecond-level dynamic control and second-level energy management. Hardware-in-the-loop simulations substantiate that the proposed strategy increases equivalent inertia and damping by 15% and 25%, respectively, while accelerating voltage recovery by 30%. Under extreme contingencies, frequency deviations remain within 0.3%.