Scenario-Driven Deduction and Dual-Timescale Optimization Approach for Digital Twin of Hybrid AC/DC Microgrid

Hybrid AC/DC microgrids (MGs) are compatible with legacy AC grids and enable the integration of renewable distributed energy resources (DERs). However, emergencies such as unscheduled islanding expose a mismatch between day-ahead scheduling and sub-second dynamics. A digital-twin (DT) enabled dual-timescale framework is proposed that unifies upper-level optimal power flow (OPF) scheduling and lower-level model predictive control (MPC) via scenario-driven deduction in a bilevel formulation. Validated on an oil-and-gas well-station MG, the strategy issues consistent pre- and post-event process commands and preserves steady-state optimality. Relative to a second-order cone programming (SOCP) based OPF baseline, average AC frequency deviation and DC bus voltage deviation during islanding are reduced by 74.1% and 49.6%, respectively. Against two state-of-the-art methods, the tracking consistency between dispatched commands and measured transients improves by 23.8% and 31%. Computation for transient sequences completes within 6–10 s across scenarios, supporting real-time deduction on commodity hardware.