Qiao Yi Wang We study the statistical consistency of distributionally robust optimization (DRO) with metric-based ambiguity sets. While convergence of optimal values is well understood, a unified set-valued analysis of feasible regions and solution sets remains largely missing, especially for constrained DRO. We develop a general variational framework based on a collapse principle, which requires that all probability … Read more
Abstract—Renewable-driven direct-current optimal load shedding (DC-OLS) requires a model that is interpretable to operators, data driven under continuous forecast errors, sensitive to severe security failures, and computationally tractable. This paper develops a budgeted KDE-Ï•-HMCR-RS-OLS framework for that purpose. Robust satisficing (RS) replaces ambiguity-radius tuning with an admissible shedding budget. A one-dimensional KDE reference family with … Read more
This paper proposes a context-aware multi-uncertainty-set distributionally robust chance-constrained DC optimal power flow model. Meteorological features are projected to partition the non-convex error support into a context-dependent decomposition of conditional local ambiguity sets, with conditional weights inferred via kernel regression. The minimax problem is reformulated into a finite-dimensional second-order cone program with proven asymptotic consistency. … Read more