Variational Consistency of Robust Integral Functionals Induced by Empirical Measures

We study the variational convergence of robust integral functionals induced by empirical probability measures. We establish a generalized consistency framework where the ambiguity set is constructed using a probability metric. By replacing traditional uniform equicontinuity assumptions with inherent convexity and general probability metric domination, we prove the almost sure pointwise and uniform convergence of the … Read more

KDE Robust Satisficing for Optimal Load Shedding Under Renewable Uncertainty

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

Context-Aware Cluster-Based Multi-Uncertainty-Set Distributionally Robust Chance-Constrained DC Optimal Power Flow

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