Scenario-based robust coordination and flexibility evaluation of transmission–distribution systems under high renewable penetration

High renewable penetration intensifies uncertainty propagation and makes reliable coordination between transmission and distribution systems increasingly challenging. To address this issue, this paper proposes a data-driven robust coordinated scheduling and flexibility assessment framework for integrated transmission–distribution systems (TDS). First, a WGAN-GP-based scenario-to-uncertainty-set calibration method is developed to characterize wind/PV uncertainty. Candidate renewable scenarios are screened by temporal smoothness and WT-PV dependence conditions, and the retained scenarios are used to construct baseline trajectories and quantile-based deviation bounds for budgeted uncertainty sets. Based on this uncertainty representation, a two-stage robust optimization (TSRO) model is formulated for coordinated TDS scheduling under worst-case renewable deviations. A nested ADMM-C&CG solution strategy is further designed, where ADMM enforces first-stage boundary-power consistency between the TN and DN, while C&CG solves regional robust subproblems. In addition, a scheduling-result-based flexibility adequacy assessment framework is established to quantify the upward and downward regulation margins of the DN after robust dispatch. Case studies show that the proposed coordinated strategy reduces the total operating cost by 2.5% compared with independent scheduling, while ADMM converges within 40 iterations. The results further reveal a clear economy–robustness trade-off and demonstrate that TDS coordination support plays a key role in covering the increased flexibility demand caused by renewable uncertainty.