Distributionally Robust Chance-Constrained Optimal Transmission Switching for Renewable Integration

Increasing integration of renewable generation poses significant challenges to ensure robustness guarantees in real-time energy system decision-making. This work aims develop a robust optimal transmission switching (OTS) framework that can effectively relieve grid congestion and mitigate curtailment. We formulate two-stage distributionally chance-constrained (DRCC) problem assures limited constraint violations for any uncertainty distribution within an ambiguity set. Here, the second-stage recourse variables are represented as linear functions uncertainty, yielding equivalent reformulation involving constraints only. utilize moment-based (mean-mean absolute deviation) distance-based ( $\infty$ -Wasserstein distance) sets lead scalable mixed-integer program (MILP) formulations. Numerical experiments on IEEE 14-bus 118-bus systems have demonstrated performance improvements proposed DRCC-OTS approaches terms guaranteed reduced In particular, computational efficiency MILP approach, which is scenario-free with fixed dimensions, has been confirmed, making it suitable operations.