Model-Confidentiality-Preserving Distributionally Robust Chance-Constrained Scheduling of Active Distribution Network–Microgrid Systems

The increasing penetration of renewable energy sources and microgrids (MGs) provides additional flexibility for active distribution networks (ADNs), but it also introduces two coupled operational challenges: renewable uncertainty management and Model-Confidentiality-Preserving coordination between the ADN and MGs. This paper aims to improve the ADN-side cost effectiveness and reserve adequacy of ADN–MG systems by enabling MGs to actively support renewable uncertainty balancing while preserving the confidentiality of their internal operation models. To this end, a Model-Confidentiality-Preserving distributionally robust chance-constrained scheduling method is proposed for ADN–MG systems. In the proposed framework, affine recourse strategies are used to coordinate the uncertainty responses of ADN-side dispatchable generators and MGs, while renewable forecast errors are handled through a tractable Wasserstein-based distributionally robust chance constraint (DRCC) reformulation. Meanwhile, each MG provides an aggregated flexibility box to the ADN operator, so that coordinated scheduling can be performed without accessing detailed MG resource parameters and constraints. Case studies on modified IEEE test systems show that the proposed method can maintain out-of-sample reserve adequacy, reduce online computational time, and achieve near-centralized ADN-side operating-cost performance.